RU2782384C2 - Nanoparticles for use in increasing brain working capacity or in stress treatment - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: use of a nanoparticle or an aggregate of nanoparticles and a composition based on them for improvement of training, memorizing, and attention in a subject is disclosed, where material of the nanoparticle or the aggregate of nanoparticles is selected from conductive material selected from Tl, Po, Ag, Pd, Ir, Pt, and/or Au, and organic material having adjacent sp2-hybridized carbon centers in its structure, and insulation material selected from La₂O₃, SiO₂, SnO₂, Ta₂O₅, ReO₂, ZrO₂, HfO₂, Y₂O₃, and diamond-like carbon, where i) a median size of a core of the nanoparticle or the aggregate of nanoparticles of a population is at least 30 nm, when material is conductive material, where ii) the core of the nanoparticle or the aggregate of nanoparticles is covered with biocompatible coating providing a negative surface charge, where iii) nanoparticles or aggregates of nanoparticles are not used as a carrier of a therapeutic compound or a drug, and where iv) biocompatible coating providing the negative surface charge is selected from phosphate, dicarboxylic acid, succinic acid, or sulphate. The use of the above-described nanoparticles or the aggregate of nanoparticles and the composition based on them for the treatment of at least one symptom of pathological stress is also disclosed.

EFFECT: group of inventions provides treatment of diseases and improvement of conditions without impact on a nanoparticle or an aggregate of nanoparticles of an electric field or any other external activation source.

7 cl, 5 dwg, 3 tbl, 12 ex

Description

The present invention relates to the field of medicine, in particular to improving the performance of the brain and to the treatment of pathological stress. More specifically, the present invention relates to a nanoparticle or aggregate of nanoparticles for use in enhancing brain performance or in preventing or treating pathological stress in a subject without exposing the nanoparticle or aggregate of nanoparticles to an electric field, and preferably without exposing them to any other external source of activation, such as a source of light, magnetic field or ultrasound source, where the material of the nanoparticle or aggregate of nanoparticles is selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or higher than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100. In addition furthermore, it relates to compositions and kits comprising such nanoparticles and/or aggregates of nanoparticles, as well as their uses without exposing them to an electric field and preferably without exposing them to any other external source of activation, such as sources to light, magnetic field or ultrasound source.

BACKGROUND OF THE INVENTION

With advances in understanding of neuroscience, the brain can be thought of as an electrical network that encodes and transmits information along its electrical wires, the neurons. Communication between neurons is simple and complex at the same time: simple because it is based on the inflow/outflow of ions within neurons that lead to action potentials (or "spike" of electrical activity); complex because the brain network consists of hundreds of billions of neurons that form nodes, hubs, and modules that demonstrate coordinated interactions across different spatial and temporal scales ( Fornito et al ., Nature Reviews Neuroscience, 2015, 16, 159-172: The connectomics of brain disorders ). Neural communication depends on the anatomical components that connect individual neurons (structure) and on the process of information transfer (function). Both aspects affect the overall functioning of the nervous system. Neuronal interactions are transmitted by fluctuations in the pattern of electrical activity in the brain, which are usually measured using an electroencephalogram (EEG). Different bands of oscillation frequencies are observed: delta, theta, alpha, beta, gamma ( Ward et al., Trends in Cognitive Sciences, 2003, 7(12), 553-559: Synchronous neural oscillations and cognitive processes ). Structurally, the most striking neuroanatomical feature of the brain is the abundant connectivity between neurons, reflecting the importance of neural communication. Synchronization of oscillations (“synchronism”) between one area of the brain and another, apparently, constitutes the last level of information encoding [the first level (neuron): action potentials; second layer (neural network(s)): neural oscillations] by providing spatiotemporal coordination ( Engel et al., Nature Reviews Neuroscience, 2001, 2, 704-716: Dynamic predictions: oscillations and synchronization in top-down processing ). Importantly, evidence is emerging that a delicately balanced pattern of synchronization and desynchronization in space and time is fundamental to the functional performance of the nervous system ( Schnitzler et al., Nature Reviews Neuroscience, 2005, 6, 285-296: Normal and pathological oscillatory communication in the brain ).

The development of certain skills, creativity or idea generation in certain people and not in others is something very mysterious, and it has not yet been explained. However, the study of certain diseases and their symptoms can help to understand the functioning of the “normal” and “abnormal” brain. For example, people with a neurodegenerative disease such as frontotemporal dementia have been noted to develop drawing and painting skills as their disease progresses ( Miller et al., Neurology, 1998, 978-982: Emergence of artistic talent in frontotemporal dementia ) . Several publications show that the propensity to develop a neurological disease, such as bipolar syndrome, schizophrenia, or autism, is higher in people (and their first-degree relatives) working in a creative field (engineering, writing, painting) than in "non-creative people" ( Andreasen NC, American Journal of Psychiatry, 1987, 144(10), 1288-1292: Creativity and mental illness: prevalence rates in writers and their first-degree relatives; Baron-Cohen et al., Autism, 1997, 101-109 : Is there a link between engineering and autism; Sussman et al., Stanford Journal of Neuroscience, 2007, 1(1), 21-24: Mental illness and creativity: a neurological view of the “tortured artist” ). Several models have been developed to describe the process of creating and generating ideas: the hemispheric model, which suggests that the non-dominant hemisphere specializes in creative activity, or the more recently developed frontotemporal model, which suggests that changes in the temporal lobe can increase idea generation, while changes in frontal lobe can reduce it ( Flaherty et al., J Comp Neurol, 2005, 493(1), 147-153: Frontotemporal and dopaminergic control of idea generation and creative drive ). Indeed, some scientists can perform esoteric numerical calculations while having little knowledge of elementary arithmetic ( Snyder et al. , Proceedings of the Royal Society of London B, 1999, 266, 587-592: Is integer arithmetic fundamental to mental processing? : the mind's secret arithmetic ). Interestingly, there is evidence that this unusual ability is associated with inhibition in the left (dominant) hemisphere along with facilitation in the right (non-dominant) hemisphere ( Treffert DA, Philosophical Transactions of the Royal Society B, 2009, 364, 1351-1357: The savant syndrome: an extraordinary condition. A synopsis: past, present, future ).

Thus, the brain is a dynamic system in which specific states of cerebral functioning result from complex excitatory and inhibitory interactions between populations of neurons. Thus, the “abnormal” state reflects an imbalance between complex excitatory and inhibitory interactions between populations of neurons ( Kapur et al., Brain, 1996, 119, 1775-1790: Paradoxical functional facilitation in brain-behavior research, a review critical ).

The present invention relates to nanoparticles and/or nanoparticle aggregates (nanoparticle aggregates) for use in increasing, increasing or improving brain performance/performance, or for preventing or treating/for use in preventing or treating pathological stress or at least one symptom thereof.

The nanoparticles and aggregates of nanoparticles described by the authors in this application do not require the application/induction of an electric current or field/stimulus and preferably do not require exposure to any other external source of activation, such as a light source, a magnetic field or an ultrasound source, in order to manifest their function (i.e., .e. to be effective). The nanoparticles and nanoparticle aggregates described herein do not require an electrical current or field/stimulus, and preferably do not require any other external source of activation, such as a light source, a magnetic field, or an ultrasound source, to be functional in the context of the described in this Application Application. The inventors have found that these nanoparticles or aggregates of nanoparticles can be advantageously and unexpectedly effectively used without exposing the subject to which they are administered to an electric current or field/stimulus, usually an electric current or field/stimulus, affecting said subject, for example, by transcranial electrical stimulation (TES) , by transcranial magnetic stimulation (TMS), and preferably without any other external activation source such as a light source, magnetic field or ultrasound source. This means that the treated subject will not experience the negative side effects of exposure to an electric current or field/stimulus or any other external source of activation such as a light source, a magnetic field or an ultrasound source due to the present invention.

As is well known to one skilled in the art, a nanoparticle has an increased/high surface/volume ratio, typically about 35-40% of the atoms are localized on the surface of a 10 nm nanoparticle compared to less than 20% for a nanoparticle larger than 30 nm. This high surface/volume ratio is associated with high surface reactivity, which is size dependent. As a result, nanoparticles (especially those smaller than 20 nm) can exhibit new properties compared to bulk materials. For example, gold particles are known to be chemically inert and resistant to oxidation on a macroscopic scale, while gold particles smaller than 10 nm have a reactive surface. The toxic mechanisms associated with the chemical destabilization of metal nanoparticles can be (i) direct release of metals in solutions (dissolution process), (ii) catalytic properties of metal nanoparticles, and (iii) redox evolution of the surface of nanoparticles that can oxidize proteins, generate active oxygen species (ROS) and cause oxidative stress (see M. Auffan et al., Environmental Pollution 157 (2009) 1127-1133: Chemical Stability of metallic nanoparticles: a parameter controlling their potential cellular toxicity in vitro ).

In addition to the gold nanoparticles described above, which have catalytic properties, nanoparticles of cerium oxide (7 nm CeO ₂ particle) or iron oxide (20 nm Fe ₃ O ₄ particle) showed redox modification of their surface, which leads to cytotoxic effects associated with oxidative stress in vitro (see M. Auffan et al., Environmental Pollution 157 (2009) 1127-1133: Chemical Stability of metallic nanoparticles: a parameter controlling their potential cellular toxicity in vitro ). In addition, the 11 nm silica nanostructure is degraded by biological media (see SA Yang et al., Scientific Reports 2018 8:185: Silica nanoparticle stability in biological media revisited ).

As explained by the inventors below, nanoparticles having a size of less than 30 nm must be carefully selected when considering their use in vivo in a subject, usually a mammal, in particular a human.

SUMMARY OF THE INVENTION

Provides the advantage that the present application describes for the first time a nanoparticle or an aggregate of nanoparticles for use in increasing, increasing or improving brain performance/performance or for preventing or treating/for use in preventing or treating pathological stress or at least one symptom thereof in a subject without exposing the nanoparticle or aggregate of nanoparticles to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, a magnetic field, or an ultrasound source. The material of the nanoparticle or nanoparticle aggregate is typically selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or greater than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100.

In the present application, the inventors describe, in a specific aspect, a nanoparticle or aggregate of nanoparticles for use in improving brain performance or for use in the prevention or treatment of pathological stress in a subject without exposing the nanoparticle or aggregate of nanoparticles to an electric field or any other external source of activation, where the material nanoparticles or aggregate of nanoparticles is selected from a conductive material, a semiconductor material, an insulating material with a permittivity ε _ijk equal to or greater than 200, and an insulating material with a permittivity ε _ijk equal to or lower than 100, where i) the largest median size of the nanoparticle core or aggregate of nanoparticles population is at least 30 nm when the material is a conductive material, a semiconductor material, or an insulating material with a dielectric constant ε _ijk equal to or greater than 200, and where ii) the core of the nanoparticle or nanoparticle aggregate is coated o a biocompatible coating providing a neutral or negative surface charge when measured in a water solution having an electrolyte concentration of 0.001 to 0.2 M, a concentration of nanoparticle material or nanoparticle aggregates of 0.01 to 10 g/l, and a pH between 6 and 8.

The present application also describes the use of a nanoparticle or an aggregate of nanoparticles to obtain a composition for increasing, increasing or improving the performance/performance of the brain or for the prevention or treatment of pathological stress or at least one symptom thereof in a subject in need without exposing the nanoparticle or aggregate of nanoparticles to an electrical fields and preferably without being exposed to any other external source of activation, such as a light source, a magnetic field or an ultrasound source.

The present application also describes a composition for use in improving brain performance or for prevention or treatment/for use in the prevention or treatment of pathological stress or at least one of its symptoms in a subject, where the composition includes or consists of nanoparticles and/or aggregates of nanoparticles and pharmaceutically acceptable carrier, where the material of the nanoparticle or aggregate of nanoparticles is usually selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or higher than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100, and where the increase in brain performance or the prevention or treatment of pathological stress is carried out without exposing the nanoparticles or aggregates of nanoparticles administered to the subject by means of the composition to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, magic filament field or ultrasound source.

In addition, the present application describes a set comprising or consisting of at least two separate nanoparticles and/or nanoparticle aggregates, with each nanoparticle or nanoparticle aggregate consisting of a separate material, usually selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or higher than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100, and its use is typically in improving brain performance or in a method for improving brain performance, or in the prevention or treatment of pathological stress, or at least at least one of its symptoms in the subject without exposing the nanoparticles or aggregates of nanoparticles to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, a magnetic field or an ultrasound source.

DETAILED DESCRIPTION OF THE INVENTION

The human nervous system is estimated to be composed of approximately 80-120 billion nerve cells ( Herculano-Houzel S. Frontier in Human Neuroscience (2009), 3(31): 1-11, The human brain in numbers: a linearly scaled-up primate brain ). The defining characteristic of a neuron (or nerve cell) is its ability to transmit electrical signals in the form of action potentials.

A neuron/nerve cell makes up the elementary node of the brain. The structure of a neuron/nerve cell consists of: a "soma" or "cell body" which contains a nucleus and can be elongated by dendrites, an "axon" which transmits an electrical signal, and an axon terminal which consists of synaptic endings.

A neuron/nerve cell makes up the elementary node of the brain. Nerve cells can communicate with each other in a highly structured way, forming neural networks. A neuron transmits signals through synaptic connections. Inside the neuron, nanocircuits form the main biochemical mechanism that mediates key neuronal properties such as learning and memory, as well as the genesis of neuronal rhythmicity.

A microcircuit can be formed with only a few interconnected neurons and can perform complex tasks such as mediating reflexes, processing sensory information, initiating motor activity, and mediating learning and memory. A microcircuit is a more complex network consisting of several embedded microcircuits. Macrocircuits mediate higher brain functions such as object recognition and cognition. Thus, several levels of networks are located in the nervous system.

Neural network excitability

Neurons send messages electrochemically (that is, chemicals/ions cause an electrical signal). Important ions in the nervous system are sodium and potassium, calcium and chloride. When a neuron is not sending a signal, it is "at rest". When the neuron is at rest, the inside of the neuron is negative with respect to the outside. Although the concentrations of the various ions try to find a balance on both sides of the membrane, they cannot do so because the cell membrane only allows some of the ions to pass through the channels (ion channels). In addition to these selective ion channels, there is a pump that uses energy to move three sodium ions out of the neuron for every two potassium ions it injects. Finally, when all these forces are balanced and the difference in voltage between the inside and outside of the neuron is measured, the resting membrane potential (also called “resting potential”) of the neuron is about -70 mV. This means that inside the neuron is 70 mV less than outside. At rest, there are relatively more sodium ions outside the neuron, and there are more potassium ions inside this neuron. An action potential (also referred to as a “spike” or “pulse”) occurs when a neuron sends information down its axon, away from the cell body. This means that some event (stimulus) causes the resting potential to move towards 0 mV. When depolarization reaches about -55 mV, the neuron fires an action potential. If the depolarization does not reach this critical threshold level, then the action potential (on/off mechanism) does not fire. In addition, when the threshold level is reached, an action potential with a fixed amplitude is always fired. Therefore, either the depolarization does not reach the threshold or a full action potential is generated.

Greater variability was found in the rate of propagation of action potentials. In fact, the propagation speed of action potentials in nerves can vary from 100 meters per second to less than one-tenth of a meter per second. While the time constant is a measure of how quickly the membrane will respond to a stimulus over time, the space constant (also the length constant) is a measure of how well the electrical potential will propagate along the axon as a function of distance.

Structure of the cerebral cortex

There are two broad classes of cortical neurons: "inhibitory neurons" or "intermediate neurons" that make only near local connections; and "excitatory neurons" or "projection neurons" or "pyramidal neurons" in which axons extend to distant intracortical, subcortical, and subcerebral targets. “Inhibitory neurons” or “interneurons” make up a minority (20%) of cortical neurons; most are “pyramidal neurons” ( Shipp S., Current Biology, 2007, 17(12), R443-449: Structure and function of the cerebral cortex ). Projection neurons are glutamatergic neurons that relay information between different areas of the neocortex and other areas of the brain ( Bikson et al., J Physiol, 2004, 557(1), 175-190: Effects of uniform extracellular DC electric fields on excitability in rat hippocampal slices in vitro ). Projection neurons or pyramidal neurons are named for their prominent apical dendrite, which usually protrudes at the surface, giving them a pyramidal morphology. As a rule, a neuron “belongs” to the layer in which its cell body (or “soma”) is located - even if the apical and basal dendrites between them cover several more layers, capturing a wider range of signals ( Shipp S., Current Biology, 2007, 17(12), R443-449: Structure and function of the cerebral cortex ).

The gray matter of the cerebral cortex is a tortuous, layered sheet of tissue, 2-3 mm thick in humans, but with a surface area of several hundred square centimeters ( Shipp S., Current Biology, 2007, 17(12), R443-449: Structure and function of the cerebral cortex ). There are six main layers in the cerebral cortex:

- Layer I, the molecular layer, contains few scattered neurons and consists mainly of extensions of the apical dendritic bundles of pyramidal neurons and horizontally oriented axons, as well as glial cells;

- Layer II, the outer granular layer, contains predominantly small and medium pyramidal neurons and numerous stellate neurons;

- Layer III, the outer pyramidal layer, contains predominantly small and medium pyramidal neurons, as well as non-pyramidal neurons with vertically oriented intracortical axons;

- Layer IV, the inner granular layer, contains various types of stellate and pyramidal neurons;

- Layer V, contains large pyramidal neurons that give rise to axons that leave the cortex and descend into subcortical structures (such as the basal ganglia). In the primary motor cortex of the frontal lobe, layer V contains cells whose axons pass through the internal capsule, brainstem, and spinal cord to form the corticospinal tract, which is the main pathway for voluntary motor control; and

- Layer VI, polymorphic or multiform layer, contains few large pyramidal neurons and many small spindle-shaped pyramidal and multiform neurons; layer VI directs efferent fibers to the thalamus, establishing a very precise interconnection between the cortex and the thalamus.

These layers develop differently in different areas of the cerebral cortex, for example, the pyramidal layers are more developed in the motor centers, and the granular layers in the sensory centers of the cerebral cortex.

Communication within and between neural networks

There are three types of communication networks that are used to study the transmission of signals within the brain and throughout the brain. Structural connectivity is based on the discovery of pathways that physically connect brain regions. These are anatomical network maps that indicate the possible pathways for signals in the brain. Functional connectivity identifies activity in areas of the brain that have a similar frequency, phase, and/or amplitude of correlated activity. Effective connectivity uses information about functional connectivity and goes one step further in determining the direct or indirect influence that one neural system can have on another, more specifically the direction of dynamic information flow in the brain ( Bowyer et al., Neuropsychiatric Electrophysiology, 2016, 2( 1), 1-12: Coherence a measure of the brain networks: past and present ).

Synchronized activity in the neural network can be detected using magnetoencephalogram (MEG), electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), or positron emission tomography (PET), then imaging using network connectivity analysis. MEG (Magnetoencephalogram) or EEG (Electroencephalogram) are preferred because they have high temporal resolution for dynamic information flow analysis. Brain connectivity analysis is performed to establish communication networks necessary for brain function. Certain areas of the brain are specialized for processing certain types of information. Imaging techniques have shown that these areas are connected and interact with other specialized areas through networks in the brain. “Coherence” ( Bowyer et al., Neuropsychiatric Electrophysiology, 2016, 2(1), 1-12: Coherence a measure of the brain networks: past and present. ) is a mathematical method that quantifies the frequency and amplitude of synchronicity (states synchrony or synchronization) neural patterns of oscillatory activity of the brain. The detection of synchronous neuronal activation can be used to determine the well-being or integrity of functional connections in the human brain. Overlaying functional connectivity maps on images of structural connectivity, as well as using the direction of information flow derived from effective connectivity, provides a comprehensive understanding of how the brain functions.

The intact (i.e. “normal” or “healthy”) brain expresses complex patterns of (“normal” or “healthy”) synchronous activity associated with various body 'states', ranging from a slow delta rhythm (0.5-4 Hz ), to theta (4-8 Hz), alpha (8-12 Hz), beta (15-30 Hz) and gamma (30-70 Hz) vibrations. It is interesting to note that the dissociated culture of cortical structures offers a convenient system for studying the rules that govern the emergence, generation, and propagation of network impulses (spikes) and impulse 'bursts' (spike clusters) in densely connected populations of neurons. Network activity can be recorded over long periods of time in a non-invasive manner and with finite time resolution using multielectrode arrays. A two-dimensional dissociated culture can be used as a viable test system to study the rules that govern the formation and maintenance of network activity in the brain, allowing a hypothesis to be tested that cannot be tested in an intact brain ( Cohen E. et al. , Brain Research, 2008, 1235 , 21-30: Determinants of spontaneous activity in networks of cultured hippocampus).

Human mental capacity or brain performance, such as intelligence, is particularly complex. Understanding these abilities in a mechanistic way can help improve them. Studies using encephalograms and event-related potentials show that the speed and reliability of neural transmission is associated with higher performance, generally higher intelligence. Early neuroimaging studies using PET showed that intelligence is negatively correlated with brain glucose metabolism during mental activity, leading to the formulation of the 'neuron efficiency' hypothesis. According to this hypothesis, smarter people expend less neural resources to perform actions at a given level. Intelligence in the sense of reasoning and new problem-solving abilities is constantly associated with the integrity, structure and function of the lateral prefrontal cortex and possibly other areas. Unresolved questions about the neural basis of intelligence include, among others, the relationships between psychometric intelligence (i.e. intelligence as measured by an IQ-type test, usually assessing response accuracy (rather than speed)), and (i) functional connectivity between components of working memory networks , as shown in electroencephalogram-based studies, and (ii) neuronal plasticity (i.e., used to refer to those processes that capture most of the changes in the connectivity of the nervous system in response to experience and which, according to observations, cease to operate in adulthood in a person). The development of neural connections has been reported to be consistent with the development of intelligence (Gray JR et al. , Nature Review Neuroscience, 2004, 5, 471-482: Neurobiology of intelligence: science and ethics; Garlick D., Psychological Review, 2002, 109(1) , 116-136: Understanding the nature of general factor of intelligence: the role of individual difference in neural plasticity as an explanatory mechanism.).

Communication between neurons is indeed important for higher brain functions such as perception, memory, and movement ( Massobrio P et al. Neural Plasticity, 2015, Article ID 196195, In vitro studies of neuronal networks and synaptic plasticity in invertebrates and in mammals using multi electrode arrays ). Although it is assumed that the formation and development of connections are crucial in the learning process, their maintenance seems to be necessary for memory. Synaptic plasticity has long been observed in cognitive processes such as learning and memory. Synaptic plasticity at the network level provides a distributed mechanism for transforming and storing temporal information in spatially distributed patterns of synaptic modifications. Every time something is learned, the network develops new interoperability and incorporates the newly learned facts.

Effective connections between neurons can be detected using typical imaging techniques well known to those skilled in the art, such as electronic imaging techniques that provide structural information about synaptic connectivity, typically electron microscopy (EM), such as serial block surface electron microscopy (SBFEM), scanning electron microscopy of serial sections (SSSEM), automated transmission electron microscopy (ATEM), etc.; photon-based imaging techniques such as Brainbow (Lichtman JW et al., Curr Opin Neurobiol, 2008, 22, 144-153: Ome sweet ome: what can the genome tell us about the connectome?; Cai D., et al ., Nat Methods, 2013, 10(6), 540-547: Improved tools for the Brainbow toolbox) , “matrix tomography” (AT) (Micheva KD., et al., 2007, Neuron, 55, 25-36: Array tomography: a new tool for imaging the molecular architecture and ultrastructure of neural circuits Micheva KD., et al., 2010, Neuron, 68, 639-653: Single-synapse analysis of a diverse synapse population: proteomic imaging methods and markers ) , reproduction of GFP by synaptic partners (“GRASP”) (“GRASP”), in particular mammalian GRASP “mGRASP” (Kim J, et al., 2012, Nat Methods, 9(1), 96-102: mGRASP enables mapping mammalian synaptic connectivity with light microscopy; Feng L, et al., 2012, Bioinformatics, 28, i25-i31: Improved synapse detection for mGRASP-assisted brain connectivity.) , transsynaptic virus labeling rabies virus variants for monitoring and manipulating activity and gene expression in defined neural circuits; Neuron, 71, 617-631; Wickersham IR, et al., 2007, Nat Methods, 4(1), 47-49: Retrograde neuronal tracing with a deletion-mitant rabies virus; Wickersham IR, et al., 2007, Neuron, 53(5), 639-647: Monosynaptic restriction of transsynaptic tracing from single, genetically targeted neurons) , fluorescence selective planar illumination microscopy (fSPIM) (Tomer R, et al., 2012 York AG, et al., 2012, Nat Methods, 9(7), 749-754: Resolution doubling in live, multicellular organisms via multifocal structured illumination microscopy.), preferably in combination with an explanatory method such as “CLARITY” (Chung K, et al., 2013, Nature, 497 (7449), 332-337: Structural and molecular interrogation of intact biological systems.) ; as well as optogenetic methods, such as rhodopsin channel imaging and/or two-photon microscopic calcium imaging methods, which map the spatial distribution of synaptic connections along with measurements of synaptic strength (Petreanu L, et al ., 2007, Nat Neurosci, 10, 663-668 : Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections Wang H, et al ., 2007, Proc Natl Acad Sci USA, 104, 8143-8148: High-speed mapping of synaptic connectivity using photostimulation in channelrhodopsin-2 transgenic mice), as well as detection of active synapses innervated by different inputs (Little JP, et al., 2012, J Neurosci: Off J Soc Neurosci, 32(37), 12808-12819: Subcellular synaptic connectivity of layer 2 pyramidal neurons in the medial prefrontal cortex; MacAskill AF, et al., 2012, Nat Neurosci, 15(12), 1624-1626: Subcellular connectivity underlies pathway-specific signaling in the nucleus accumbens) ; or any combination of these various methods (Yook C. et al., Cellular and Molecular Life Sciences, 2013, 70, 4747-4757: Mapping mammalian synaptic connectivity).

Provides the advantage that the present application describes for the first time a nanoparticle or an aggregate of nanoparticles for use in increasing, increasing or improving brain performance/performance or for preventing or treating/for use in preventing or treating pathological stress or at least one symptom thereof without exposing the nanoparticle or aggregate of nanoparticles to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, a magnetic field, or an ultrasound source. Such exposure (therapeutic or diagnostic) to an electric field or any other (therapeutic or diagnostic) external source of activation, such as a light source, magnetic field or ultrasound source, in this application should be understood, as a rule, as a therapeutic or diagnostic intervention, usually carried out by a medical staff, such as a doctor or nurse.

The material of the nanoparticle or nanoparticle aggregate is typically selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or greater than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100.

In a typical aspect, the nanoparticle or aggregate of nanoparticles described herein is for use in improving physical performance or in improving cognitive performance, i. learning, memorization, sensory perception, attention and/or decision making by the subject, without exposing the nanoparticle or aggregate of nanoparticles to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, a magnetic field, or an ultrasound source.

NANOPARTICLES

This application describes a nanoparticle or aggregate of nanoparticles for use in accordance with the present invention to improve brain performance or in the treatment of pathological stress or at least one symptom thereof in a subject without exposing the nanoparticle or aggregate of nanoparticles to an electric field and preferably without exposing said nanoparticle or an aggregate of nanoparticles of any other external source of activation, such as a light source, a magnetic field, or an ultrasound source, where the material of the nanoparticle or aggregate of nanoparticles is usually selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or greater than 200, and an insulating material with a permittivity ε _ijk equal to or less than 100.

Size or size of nanoparticles or aggregate of nanoparticles

In accordance with the present invention, the terms "nanoparticle" or "aggregate of nanoparticles" refers to a product, in particular a synthetic product, with a size in the nanometer range, usually from 1 nm to 1000 nm or from 1 nm to 500 nm, for example from at least at least 10 nm to about 500 nm or up to about 1000 nm, from at least 30 nm to about 500 nm or up to about 1000 nm, from at least 40 nm to about 500 nm or up to about 1000 nm, from at least 45 nm up to about 500 nm or up to about 1000 nm, preferably below 500 nm.

The term "aggregate of nanoparticles" or "aggregate consisting of nanoparticles" refers to a collection of nanoparticles that are strongly, usually covalently, linked to each other.

Electron microscopy, such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), or cryo-TEM, can be used to measure the size of a nanoparticle or nanoparticle aggregate and, in particular, the size of the nanoparticle core or nanoparticle aggregate, i.e., nanoparticles or an aggregate of nanoparticles without their biocompatible coating. In fact, a biocompatible coating usually consists of compounds that consist primarily of light elements (polymeric or organic compounds) whose elastic interactions with high energy electrons are relatively weak, resulting in poor image contrast. TEM measures the projected images of particles deposited on an electronically transparent substrate. A recorded image of more than about 50, preferably more than about 100, 150, or 200 nanoparticles or nanoparticle aggregates per sample will typically need to be processed for size estimation. Thus, a recorded image of more than about 50, or preferably more than about 100, 150, or 200 nanoparticles or nanoparticle aggregates allows the largest median core size of the nanoparticles or nanoparticle aggregates of the population to be established, as well as the core size of the nanoparticles or nanoparticle aggregates representing 30%-70% percentile of the population of nanoparticles and aggregates of nanoparticles. A typical assay protocol can be found in “NIST - NCL Joint Assay Protocol, PCC-7; Measuring the size of using transmission electron microscopy (TEM); version 1.1 December 2009”.

In addition, dynamic light scattering (DLS) can be used to measure the hydrodynamic diameter of nanoparticles or nanoparticle aggregates (ie, the diameter of nanoparticles or a nanoparticle aggregate including both their core and their biocompatible coating) in solution. The hydrodynamic diameter is the diameter of an equivalent hard sphere that diffuses at the same rate as the analyte. A typical assay protocol can be found in “NIST - NCL Joint Assay Protocol, PCC-1; Measuring the size of nanoparticles in aqueous media using batch-mode dynamic light scattering; version 1,1 February 2010”. DLS particle size measurement results may not match other methods (eg electron microscopy). This is partly due to differences in the physical properties that are actually measured (eg hydrodynamic diffusion versus projected area). In addition, DLS is sensitive to the presence of small amounts of large particles or clusters of smaller particles, while electron microscopy usually reflects the size of primary particles (i.e., the size of the core of nanoparticles or aggregates of nanoparticles) (see NIST - NCL Joint Assay Protocol, PCC- 1; Measuring the size of nanoparticles in aqueous media using batch-mode dynamic light scattering; version 1.1 February 2010).

These two methods, DLS and electron microscopy, can then be used one after the other to compare sizes and confirm the indicated size. The preferred method for measuring the size of nanoparticles and nanoparticle aggregates is DLS (see International Standard ISO22412 Particle Size Analysis - Dynamic Light Scattering, International Organization for Standardization (ISO) 2008 ). The average hydrodynamic diameter of a nanoparticle or an aggregate of nanoparticles, measured by DLS in solution, is presented as particle size distribution by intensity (light scattering intensity is proportional to particle size) and measured at room temperature (about 25°C).

Typically, the largest value or size is the diameter of a round or spherical nanoparticle or the largest length of an ovoid or oval nanoparticle.

The largest size of a nanoparticle or aggregate as defined herein is typically about 2 nm to about 250 nm or up to about 500 nm, preferably about 4 nm or 10 nm to about 100 nm or up to about 200 nm, even more preferably from about (preferably at least) 10 nm to about 150 nm, from about (preferably at least) 30 nm to about 150 nm, from about (preferably at least) 40 nm to about 500 nm, from about (preferably at least) 45 nm to about 500 nm, preferably below 500 nm.

When measuring the average hydrodynamic diameter of a nanoparticle or an aggregate of nanoparticles in solution, the DLS method is usually used. Determined using DLS, the mean hydrodynamic diameter of a nanoparticle or nanoparticle aggregate in solution is typically from about 10 nm to about 500 nm, preferably from about 10 nm or about 30 nm to about 100 nm or up to about 500 nm, even more preferably from about 10 nm or about 30 nm to about 100 nm, about 150 nm, about 200 nm, about 250 nm, about 300 nm, about 350 nm, about 400 nm, about 450 nm or about 500 nm.

When measuring the core of a nanoparticle or an aggregate of nanoparticles, the method of electron microscopy is usually used. When using electron microscopy, the median value of the largest size (also referred to below as "largest median size") of the core of a nanoparticle or aggregate of nanoparticles of a population is usually from about 5 nm to about 250 nm or up to about 500 nm, preferably from about 5 nm, about 6 nm , about 7 nm, about 8 nm, about 9 nm, about 10 nm, about 11 nm, about 12 nm, about 13 nm, about 14 nm, about 15 nm, about 16 nm, about 17 nm, about 18 nm, about 19 nm, about 20 nm, about 21 nm, about 22 nm, about 23 nm, about 24 nm, about 25 nm, about 26 nm, about 27 nm, about 28 nm, about 29 nm, about 30 nm, about 31 nm , about 32 nm, about 33 nm, about 34 nm, about 35 nm, about 36 nm, about 37 nm, about 38 nm, about 39 nm, about 40 nm, about 41 nm, about 42 nm, about 43 nm, about 44 nm or about 45 nm to about 75 nm, about 76 nm, about 77 nm, about 78 nm, about 79 nm, about 80 nm, about 81 nm, about 82 nm, about 83 nm, about 84 nm, about 85 nm , about 86 nm, about 87 nm, about 88 nm, about 89 nm, about 90 nm, about 91 nm, about 92 nm, about 93 nm, about 94 nm, about 95 nm, about 96 nm, about 97 nm, about 98 nm, about 99 nm, about 100 nm, about 101 nm, approx. 102 nm, approx. 103 nm, approx. 104 nm, approx. 105 nm, approx. 106 nm, approx. 107 nm, approx. 108 nm, approx. 109 nm, approx. 110 nm, approx. nm, about 115 nm, about 116 nm, about 117 nm, about 118 nm, about 119 nm, about 120 nm, about 121 nm, about 122 nm, about 123 nm, about 124 nm, about 125 nm, about 130 nm, about 140 nm, about 150 nm, about 200 nm, about 250 nm, about 300 nm, about 350 nm, about 400 nm, about 450 nm or about 500 nm.

Typically, when measuring the size of a nanoparticle core or nanoparticle aggregate using electron microscopy instruments, the size of the nanoparticle core or nanoparticle aggregate representing the 30%-70% percentile of the population of nanoparticles and nanoparticle aggregates is between about 5 nm, about 6 nm, about 7 nm, about 8 nm, about 9 nm, about 10 nm, about 11 nm, about 12 nm, about 13 nm, about 14 nm, about 15 nm, about 16 nm, about 17 nm, about 18 nm, about 19 nm, about 20 nm, about 21 nm, about 22 nm, about 23 nm, about 24 nm, about 25 nm, about 26 nm, about 27 nm, about 28 nm, about 29 nm, about 30 nm, about 31 nm, about 32 nm, about 33 nm, about 34 nm, about 35 nm, about 36 nm, about 37 nm, about 38 nm, about 39 nm, about 40 nm, about 41 nm, about 42 nm, about 43 nm, about 44 nm or about 45 nm to about 75 nm, about 76 nm, about 77 nm, about 78 nm, about 79 nm, about 80 nm, about 81 nm, about 82 nm, about 83 nm, about 84 nm, about 85 nm, about 86 nm, about 87 nm, about 88 nm, about 89 nm, about 90 n m, about 91 nm, about 92 nm, about 93 nm, about 94 nm, about 95 nm, about 96 nm, about 97 nm, about 98 nm, about 99 nm, about 100 nm, about 101 nm, about 102 nm, approx. 103 nm, approx. 104 nm, approx. 105 nm, approx. 106 nm, approx. 107 nm, approx. 108 nm, approx. 109 nm, approx. 110 nm, approx. 111 nm, approx. nm, about 116 nm, about 117 nm, about 118 nm, about 119 nm, about 120 nm, about 121 nm, about 122 nm, about 123 nm, about 124 nm, about 125 nm, about 130 nm, about 140 nm, about 150 nm, about 200 nm, about 250 nm, about 300 nm, about 350 nm, about 400 nm, about 450 nm, about 500 nm, or about 520 nm.

Composition of nanoparticles

Nanoparticle obtained from a conductive material

The nanoparticle obtained from the conductive material is an organic nanoparticle or an inorganic nanoparticle.

An inorganic nanoparticle of conductive material is typically prepared from a metal element having a standard reduction potential E° equal to or greater than about 0.01, typically measured at 25°C and 1 atm pressure relative to a standard hydrogen electrode ( see Table 2 “reduction reactions having E° values more positive than that of the standard hydrogen electrode”, 8-25, Handbook of chemistry and physics; David R. Lide; 88 ^th Edition ), more preferably equal to or higher than about 0.1, 0.2, 0 .3, 0.4 or 0.5. Typical metallic elements used to produce the nanoparticle can be selected from Tl, Po, Ag, Pd, Ir, Pt, Au, and mixtures thereof. Preferably, the metal element used as the conductor material for producing the nanoparticle is selected from Ir, Pd, Pt, Au and mixtures thereof, even more preferably selected from Au, Pt, Pd and any mixture thereof. Particularly preferred materials are Au and Pt.

Typically, gold nanoparticles exhibit catalytic activity when their size is reduced to a few nm (see M. Auffan et al., Nature Nanotechnology 2009, 4(10), 634-641: Towards a definition of inorganic nanoparticles from an environmental, health and safety perspective) . In order to reduce the surface/volume ratio and thus minimize the contribution of the surface of the inorganic nanoparticle to catalytic activity, it is preferred that the largest median size of the nanoparticle core or population aggregate of at least 30 nm, typically at least 40 nm or more at least 45 nm.

An organic conductive material nanoparticle is typically prepared from an organic material having adjacent sp2 hybridized carbon centers in its structure (i.e. carbon double bond or aromatic rings containing heteroatoms, usually N or S, in or out of the aromatic ring). Preferred organic materials are selected from polyaniline, polypyrrole, polyacetylene, polythiophene, polycarbazole, polypyrene, poly(3,4-ethylenedioxythiophene) and/or poly(3,4-ethylenedioxythiophene)polystyrenesulfonate.

In a particular aspect, the largest median core size of a nanoparticle or population nanoparticle aggregate is at least 30 nm, or at least 40 nm, and preferably below 500 nm, as described above, such as 45 nm when the material is a conductive material, as described above, in in particular a metallic material, typically a metal having a standard E° reduction potential greater than 0.2, or an organic material, typically an organic material having adjacent sp2 hybridized carbon centers in its structure, preferably a metallic material as described above, in particular any one from Au, Pt, Pd and any mixture thereof.

Nanoparticle obtained from a semiconductor material

A nanoparticle obtained from a semiconductor material is usually an inorganic nanoparticle.

Inorganic nanoparticles are typically made using a semiconductor material having a relatively small band gap (Eg) between its valence and conduction bands. Typically, a semiconductor material has a band gap Eg below 3.0 eV, typically when measured at room temperature (about 25°C) ( see, for example, table 12-77, Table 3; Handbook of chemistry and physics; David R. Lide; 88th ^Edition ) . In a particular aspect, the material is a pure semiconductor material or a doped semiconductor material, as further described below.

Pure semiconductor materials usually consist of an element from group IV A of the periodic table, such as silicon (Si) or germanium (Ge), in a mixed composition of elements from groups III and V of the periodic table, such as AlSb, AlN, GaP, GaN, InP, InN, etc., or in a mixed composition of elements from groups II and VI of the periodic table, such as ZnSe, ZnTe, CdTe, etc.

Doped semiconductor materials typically include or consist of a pure semiconductor obtained with a high degree of chemical purity, and the pure semiconductor material contains a dopant. In a specific aspect, when the semiconductor dopant material of the nanoparticles or nanoparticle aggregate consists of an element from group IVA of the periodic table, it is doped with a charge carrier selected from Al, B, Ga, In, and P. Such semiconductor dopant materials can be either n-type, in which negative charge carriers predominate, or p-type, in which positive charge carriers predominate. A typical p-type semiconductor dopant material consists of silicon (Si) or germanium (Ge) doped with a charged carrier selected from aluminum (Al), boron (B), gallium (Ga), and indium (In); A typical p-type doped semiconductor material consists of silicon (Si) or germanium (Ge), usually doped with phosphorus (P).

Generally, it has been shown that the band gap energy of semiconductor nanoparticles increases when the nanoparticle size decreases below 10 nm (see M. Auffan et al., Nature Nanotechnology 2009, 4(10), 634-641: Towards a definition of inorganic nanoparticles from an environmental, health and safety perspective) . In order to provide a low surface/volume ratio and to keep the volume energy gap of the nanoparticles or nanoparticle aggregates below 3.0 eV, the largest median core size of the nanoparticle or population nanoparticle aggregate is preferably at least 30 nm, preferably at least 40 nm.

Thus, in a specific aspect, the largest median core size of a nanoparticle or aggregate of nanoparticles in a population is at least 30 nm, or at least 40 nm, and preferably below 500 nm, when the material is a semiconductor material as described above, in particular a semiconductor material with energy gap Eg below 3.0 eV, typically a material consisting of an element from group IVA of the periodic table, in particular an element from group IVA of the periodic table, doped with a charge carrier selected from Al, B, Ga, In and P, or a mixed composition of elements from groups III and V of the periodic table of Mendeleev or a mixed composition of elements from groups II and VI of the periodic table of Mendeleev.

A nanoparticle obtained from an insulating material having a high relative permittivity (permittivity), i.e. equal to or higher than 200

Nanoparticles made from, or consisting of, an insulating material having a high relative permittivity ε _ijk (also referred to as permittivity) are typically made from a material having an energy gap Eg equal to or greater than 3.0 eV, typically when measured at room temperature. temperature (about 25°C), and a relative permittivity ε _ijk equal to or greater than 200, which is usually measured between 20°C and 30°C and from 10 ² Hz to infrared frequency ( see, for example, table 12-45 “Permittivity (dielectric constant) of inorganic solid”, Handbook of chemistry and physics, David R. Lide, 88th ^Edition , Compilation of the static dielectric constant of inorganic solid, KF Young and HPR Frederikse, J. Phys. Chem. Ref. Data, Vol. 2, No. 2, 1973 ).

Such nanoparticles are usually prepared from a dielectric material which is a mixed metal oxide, preferably selected from BaTiO ₃ , PbTiO ₃ , KTaNbO ₃ , KTaO ₃ , SrTiO ₃ , BaSrTiO ₃ , etc.

As a rule, the structure of the perovskite type of PbTiO ₃ nanoparticles showed a change in the temperature of their transition from the paraelectric to the ferroelectric phase for nanoparticles smaller than 20 nm - 30 nm (see M. Auffan et al., Nature Nanotechnology 2009, 4(10), 634-641 : Towards a definition of inorganic nanoparticles from an environmental, health and safety perspective) . To provide a low surface/volume ratio and maintain the dielectric properties of the nanoparticles or nanoparticle aggregates, the largest median core size of the nanoparticle or population aggregate of at least 30 nm, typically at least 40 nm, is preferred.

Thus, in a particular aspect, the largest median size of a nanoparticle core or population nanoparticle aggregate is at least 30 nm or at least 40 nm and preferably below 500 nm when the material is an insulating material as described above having a high relative permittivity ε _ijk equal to or higher than 200, in particular an insulating material with an energy gap Eg equal to or higher than 3.0 eV, preferably a mixed metal oxide selected from BaTiO ₃ , KTaNbO ₃ , KTaO ₃ , SrTiO ₃ and BaSrTiO ₃ .

A nanoparticle obtained from an insulating material having a low relative permittivity (permittivity), i.e. equal to or below 100

Nanoparticles made from, or consisting of, an insulating material having a low relative dielectric constant are usually made from a material having an energy gap Eg equal to or greater than 3.0 eV, usually when measured at room temperature (about 25°C), and a relative permittivity ε _ijk equal to or less than 100, preferably less than 50 or less than 20, which is usually measured between 20°C and 30°C and from 10 ² Hz to infrared frequency, ( see, for example, table 12-45 "Permittivity (dielectric constant) of inorganic solid"; Handbook of chemistry and physics; David R. Lide; 88th Edition; Compilation of the static dielectric constant of inorganic solid. KF Young and HPR Frederikse. J. Phys. Chem. Ref. Data , Vol. 2, No. 2, 1973 ).

Such nanoparticles are usually made from a dielectric material which is selected from a metal oxide, a mixed metal oxide whose metal element is selected from period 3, 5 or 6 of the periodic table or a lanthanide, and a carbon material. The dielectric material is preferably selected from Al ₂ O ₃ , LaAlO ₃ , La ₂ O ₃ , SiO ₂ , SnO ₂ , Ta ₂ O ₅ , ReO ₂ , ZrO ₂ , HfO _{2 ,} Y ₂ O ₃ and diamond-like carbon. More preferably, the dielectric material is a metal oxide selected from ReO ₂ , ZrO ₂ , HfO ₂ and any mixture thereof. Particularly preferred is a dielectric material selected from ZrO ₂ and HfO ₂ . In a specific and preferred aspect, the dielectric material or metal oxide is not CeO ₂ (cerium oxide), Fe ₃ O ₄ (iron oxide), SiO ₂ (silicon dioxide) or any mixture thereof.

Zirconium (Zr) and hafnium (Hf) are both elements in the ⁴⁺ oxidation state, and the elements Zr ⁴⁺ and Hf ⁴⁺ are almost identical in size and chemical properties; that is why these two ions are considered together when establishing the chemistry of their aqueous solutions (see chapter 8, section 8.2 Zr4+ and Hf4+, p. 147 “The hydrolysis of cations”, Baes CF & Mesmer RE; John Wiley and Sons, Inc. reprint Edition 1986 ).

In a specific aspect, the largest median core size of a nanoparticle or population nanoparticle aggregate is at least 10 nm, and preferably below 500 nm, as described above, when the material is selected from ReO ₂ , ZrO ₂ , HfO ₂ , preferably from ZrO ₂ and HfO ₂ , and any mixture thereof, as described above.

Shape of nanoparticles or aggregate of nanoparticles

Since the shape of a particle or aggregate can affect its "biocompatibility", a particle or aggregate having a fairly uniform shape is preferred. For pharmacokinetic reasons, nanoparticles or aggregates that are substantially spherical, round or egg-shaped are preferred. This shape also promotes the interaction of the nanoparticle or aggregate with cells or absorption by cells. A spherical or round shape is particularly preferred.

The shape of a nanoparticle or an aggregate of nanoparticles is usually assessed using electron microscopy, such as transmission electron microscopy (TEM).

Biocompatible coating of nanoparticles or aggregates of nanoparticles

In a preferred embodiment, the core of the nanoparticle or aggregate of nanoparticles used in the context of the present invention to obtain a composition of interest may be coated with a biocompatible material selected from an agent exhibiting subtle properties. The agent exhibiting subtle properties may be an agent exhibiting a steric group. Such a group may be selected from, for example, polyacrylate; polyacrylamide (poly(N-isopropylacrylamide)); polyurea; biopolymer; a polysaccharide such as dextran or xylan; and collagen. In another preferred embodiment, the core of the nanoparticles or aggregates of nanoparticles may be coated with a biocompatible material selected from a biological target interaction agent. Such an agent can typically impart a positive or negative charge to the surface of the nanoparticles or nanoparticle aggregate. The agent that forms a positive charge on the surface of a nanoparticle or an aggregate of nanoparticles may be, for example, aminopropyltriethoxysilane or polylysine. The agent that forms a negative charge on the surface of a nanoparticle or an aggregate of nanoparticles can be, for example, a phosphate (eg polyphosphate, metaphosphate, pyrophosphate, etc.), a carboxylate (eg citrate or a dicarboxylic acid, in particular succinic acid) or sulfate.

In a preferred embodiment, the core of the nanoparticle or aggregate of nanoparticles used in the context of the present invention is a hydrophilic surface charge neutral or coated with a biocompatible material (i.e. coating agent) selected from a hydrophilic agent imparting a neutral surface charge to the nanoparticle. Indeed, when the nanoparticles of the present invention are administered to a subject, nanoparticles presenting a hydrophilic neutral surface charge or a core of nanoparticles coated with a biocompatible agent selected from a hydrophilic agent imparting a neutral surface charge to the nanoparticles are particularly advantageous for optimizing the use of the nanoparticles described herein.

The hydrophilic agent imparting a neutral surface charge to the core of a nanoparticle or an aggregate of nanoparticles may be an agent containing a functional group selected from alcohol (R-OH), aldehyde (R-COH), ketone (R-CO-R), ester ( R-COOR), acid (R-COOH), thiol (R-SH), saccharide (eg glucose, fructose, ribose), anhydride (RCOOOC-R), and pyrrole. The hydrophilic agent imparting a neutral surface charge to the core of a nanoparticle or aggregate of nanoparticles may be a monomer, dimer, oligomer, polymer, or copolymer. When the agent is an oligomer, it may be an oligosaccharide such as cyclodextrin. When the agent is a polymer, it may be a polyester (such as poly(lactic acid) or polyhydroxyalkanoic acid), polyether, polyethylene oxide, polyethylene glycol, polyvinyl alcohol, polycaprolactone, polyvinylpyrrolidone, a polysaccharide such as cellulose, polypyrrole, etc.

In addition, the hydrophilic agent imparting a neutral surface charge to the core of the nanoparticle or nanoparticle aggregate may be an agent containing specific groups (R-) capable of interacting with the surface of the nanoparticle or nanoparticle aggregate. R is usually selected from a thiol, silane, carboxyl and phosphate group.

When the core of the nanoparticle or aggregate of nanoparticles is a conductor or semiconductor and a metal nanoparticle, R is preferably a thiol, thioether, thioether, dithiolane, or carboxyl group. Preferably, the hydrophilic neutral coating agent is selected from thioglucose, 2-mercaptoethanol, 1-thioglycerol, thiodiglycol and hydroxybutyric acid.

When the core of the nanoparticle or aggregate of nanoparticles is a dielectric and an oxide or mixed oxide nanoparticle, R is preferably a silane or phosphate group. Preferably, the hydrophilic neutral coating agent is hydroxymethyltriethoxysilane, a fructose-6-phosphate or glucose-6-phosphate compound.

The hydrophilic agent imparting a neutral surface charge to the core of a nanoparticle or an aggregate of nanoparticles may be a zwitterionic compound such as an amino acid, peptide, polypeptide, vitamin, or phospholipid.

The surface charge of a nanoparticle or nanoparticle aggregate is usually determined, as is well known to the skilled person, by measuring the zeta potential, typically in (solution) in water, having a concentration of nanoparticle or nanoparticle aggregate material between 0.01 and 10 g/l, pH between 6 and 8 and typically an electrolyte concentration (in water) of 0.001 to 0.2 M, such as 0.01 M or 0.15 M. Under the conditions defined above, the surface charge of a nanoparticle or aggregate of nanoparticles is typically -10 mV to +10 mV ( corresponds to neutral surface charge), -20 mV to +20 mV or -35 mV to +35 mV. In the neutral state, the surface charge of nanoparticles or nanoparticle aggregates is typically in the range of -10 mV, -9 mV, -8 mV, -7 mV, -6 mV, -5 mV, -4 mV, -3 mV, -2 mV, or -1mV to 1mV, 2mV, 3mV, 4mV, 5mV, 6mV, 7mV, 8mV, 9mV or 10mV. With a negative value, the surface charge of the nanoparticles or nanoparticle aggregate is usually below -11 mV, -12 mV, -13 mV, -14 mV -15 mV, -16 mV, -17 mV, -18 mV, -19 mV, -20 mV, -21mV, -22mV, -23mV, -24mV, -25mV, -26mV, -27mV, -28mV, -29mV, -30mV, -31mV, -32mV, -33 mV, -34 mV or -35 mV.

A complete biocompatible coating of a nanoparticle or aggregate may be advantageous in the context of the present invention to avoid any electrical charge on the surface of the nanoparticle when the nanoparticle presents a hydrophilic neutral surface charge. "Full coverage" implies the presence of a very high density/compactness of biocompatible molecules capable of creating at least a complete monolayer on the surface of the particle.

The biocompatible coating provides, in particular, the stability of the nanoparticles in a liquid, such as a physiological fluid (blood, plasma, serum, etc.) or any isotonic medium or physiological medium necessary for pharmaceutical administration.

Stability can be confirmed by quantitative determination of the dry extract using a drying oven and by measurement on a suspension of nanoparticles before and after filtration, usually on a 0.45 µm filter.

Advantageously, the coating maintains the integrity of the particle in vivo , provides or improves its biocompatibility, and facilitates its optional functionalization (eg, with spacer molecules, biocompatible polymers, targeting agents, proteins, etc.).

The biocompatible nanoparticle or nanoparticle aggregate of the invention must neither dissolve nor release toxic substances after administration in vivo (i.e. at physiological pH) nor exhibit redox behavior, typically in order for said nanoparticle or nanoparticle aggregate to be considered biocompatible, that is, for safe use in a subject, in particular a mammal, preferably a human.

Another specific object described in this application relates to a composition, in particular a pharmaceutical composition comprising nanoparticles and/or aggregates of nanoparticles as defined above, preferably together with a pharmaceutically acceptable carrier or diluent.

In particular, this application describes a composition for use in improving brain performance or for prevention or treatment / for use in the prevention or treatment of pathological stress or at least one of its symptoms, as described in this application, in a subject without exposure to nanoparticles or aggregates nanoparticles of an electric field, and preferably without exposure to any other external source of activation, such as a light source, a magnetic field or an ultrasound source, where the composition includes or consists of nanoparticles and/or aggregates of nanoparticles and a pharmaceutically acceptable carrier, and where the material of the nanoparticle or aggregate The nanoparticles are typically selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or greater than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100 as described and explained above.

In a preferred aspect, the composition comprises or consists of at least two separate nanoparticles and/or aggregates of nanoparticles, with each nanoparticle or aggregate of nanoparticles consisting of a separate material, usually selected from a conductive material, a semiconductor material, an insulating material with a dielectric constant ε _ijk , equal to or higher than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100.

In a typical aspect of the invention, the nanoparticle(s) or aggregate(s) of nanoparticles described herein are not used as carrier(s) (active) therapeutic compound(s) or drug(s).

The composition may be in the form of a solid, liquid (particles in suspension), aerosol, gel, paste, and the like. Preferred compositions are in the form of a liquid or gel. Particularly preferred compositions are in liquid form.

The pharmaceutically acceptable carrier or carrier used may be any conventional carrier known to those skilled in the art, such as, for example, saline, isotonic, sterile, buffered, non-aqueous carrier solutions, and the like.

The composition may also include stabilizers, sweeteners, surfactants, polymers, and the like.

It may be formulated, for example, as an ampoule, aerosol, vial, tablet, capsule, using pharmaceutical formulation methods known to those skilled in the art.

The nanoparticles or aggregates of nanoparticles of the invention can be administered to a subject using various possible routes such as intracranial, intravenous (IV), respiratory (inhalation), intrathecal, intraocular or oral (per os), intracerebroventricular (ICV), preferably using intracranial or intrathecal route.

If necessary, repeated injections or injections of nanoparticles can be used. Preferably, nanoparticles or aggregates of nanoparticles should be introduced once.

After administration, nanoparticles and/or aggregates of nanoparticles typically interact with neurons. In a preferred aspect, this interaction is a long-term interaction, that is, an interaction over several hours, days, weeks or months. In a particular aspect, the nanoparticles or aggregates of nanoparticles remain in the subject's body.

The present application describes nanoparticles, nanoparticle aggregates and compositions comprising such nanoparticles or nanoparticle aggregates for use in a subject, usually for use in an animal, preferably a mammal, even more preferably a human, regardless of age and sex.

The typical amount(s) of nanoparticles or nanoparticle aggregates administered to the cerebral cortex, hippocampus, or amygdala of a subject is(are) from 10⁵ to 10¹⁷, from 10⁵ to 10¹⁶or from 10⁵ to 10^fifteen, preferably from 10⁷ to 10^fourteen, more preferably from 10⁹ to 10¹². In addition, the typical amount(s) of nanoparticles or nanoparticle aggregates administered to the cerebral cortex, hippocampus, or amygdala of a subject is(are) from 10² to 10¹² nanoparticles or aggregates of nanoparticles per cm³.

The typical amount(s) ^of nanoparticles or nanoparticle aggregate injected deep into the subject's brain is(are) ¹⁰⁴ to ¹⁰¹⁷ , 104 to ¹⁰¹⁶ , 104 to ¹⁰¹⁵ , or ¹⁰⁴ to ¹⁰¹⁴ , ^preferably 10 ⁶ to 10 ¹² , more preferably 10 ⁸ to 10 ¹¹ . In addition, the typical amount(s) of nanoparticles or nanoparticle aggregates injected deep into the brain of a subject is(are) from 10 ¹ to 10 ¹¹ nanoparticles or nanoparticle aggregates per cm ³ .

In addition, the present application describes a method for improving brain performance in a subject and a method for treating pathological stress or at least one symptom thereof in a subject, where each method includes the step of introducing any of the nanoparticles or aggregates of nanoparticles described in this application to the subject. This method generally does not include any step of exposing the subject, and more specifically the nanoparticles or aggregates of nanoparticles that have been administered to said subject, to an electric field, and preferably also does not include any step of exposing the subject, and more specifically the nanoparticles or aggregates of nanoparticles that have been introduced to the specified subject, any other external source of activation, such as a light source, a magnetic field or an ultrasound source.

The following object, described in this application, refers to a set including at least two separate nanoparticles and/or aggregates of nanoparticles, as described in this application, with each nanoparticle or aggregate of nanoparticles consists of a separate material, usually selected from a conductive material, semiconductor material, an insulating material with a dielectric constant ε _ijk equal to or higher than 200, and an insulating material with a dielectric constant ε _ijk equal to or lower than 100, as described in this application.

In a specific embodiment, the kit includes, in separate containers, individual nanoparticles and/or aggregates of nanoparticles as described herein (which are intended to be contacted, usually in a mixed form, either in situ , i.e. at the target site, or in vitro or ex vivo until the mixture is deposited on the target site).

The present application also describes the use, in vivo , in vitro or ex vivo , of such a kit in the method described in this application to improve brain performance/performance, usually to increase synaptic plasticity, synaptic connectivity and/or memory capacity of a neural network in a subject , or in a method for preventing or treating pathological stress or at least one symptom thereof in a subject in need thereof, without exposing the nanoparticles or aggregates of nanoparticles administered to the subject to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, magnetic field or ultrasound source. In addition, the present application discloses the kit described above for use in the prevention or treatment of pathological stress or at least one symptom thereof in a subject without exposing the nanoparticles or aggregates of nanoparticles administered to the subject to an electric field, and preferably without exposing them to any another external source of activation, such as a light source, a magnetic field, or an ultrasound source.

In a specific aspect, the nanoparticle or aggregate of nanoparticles described herein is for use in, or for use in a method of treatment for, improving physical performance, or improving learning, memory, sensory perception, attention, and/or decision making by a subject in need of such treatment, without exposing said nanoparticle or aggregate of nanoparticles to an electric field, and preferably without exposing them to any other external source of activation, such as a light source, a magnetic field, or an ultrasound source.

In rodents, usually mice, reliable evidence of psychometric intelligence can be obtained from battery tests involving various tasks. These tests usually include learning tasks such as smell recognition or spatial navigation. The learning test is related to the sensory, motor or motivational requirements placed on the animal. For example, a test based on the concept of "quick mapping" ( Carey S, et al., Proceedings of the Standford Child Language Conference., 1978, 15, 17-29: Acquiring a single new word) can be used to assess thinking in mice. the “Mouse Stroop test” can be used to assess the attention task in mice, and the “radial eight-arm maze” analysis can be used to evaluate working memory performance or working memory capacity in mice (Matzel LD et al. Current Directions in Psychological Science, 2013 , 22(5), 342-348: The architecture of intelligence Converging evidence from studies of humans and animals).

An IQ test can be used to assess a person's memory capacity. IQ tests such as the Raven Matrix or the Wechsler Adult Intelligence Rating Scale are well known in the art and are commonly used to assess a person's working memory capacity. The Stroop test of word-color interference (Stroop JR, Journal of Experimental Psychology, 1935, 18, 643-652: Studies of interference in serial verbal reactions) can also be used in humans to predict general intelligence (Huang L, et al., Journal of Experimental Psychology: Human Perception and Performance, 2012, 38, 414-428: Measuring the interrelations among multiple paradigms of visual attention: an individual differences approach) .

In another specific aspect, the nanoparticle or nanoparticle aggregate described herein is for use in enhancing neuronal/neuronal connectivity, functional connectivity, and/or synaptic plasticity in the brain of a subject in need of such treatment, without exposing the nanoparticle or nanoparticle aggregate to electrical fields and preferably without being exposed to any other external source of activation, such as a light source, a magnetic field or an ultrasound source.

In a typical aspect, the nanoparticle or aggregate of nanoparticles described in this application is intended for prevention or treatment/for use in the prevention or treatment of a subject suffering from altered functional activity of the brain, without exposing the nanoparticle or aggregate of nanoparticles to an electric field and preferably without exposing them to any other an external source of activation, such as a light source, a magnetic field, or an ultrasound source.

In another specific aspect, the nanoparticle or aggregate of nanoparticles described in this application is intended for prevention or treatment/for use in the prevention or treatment of a subject suffering from pathological stress or at least one symptom thereof, in particular chronic stress, without affecting nanoparticles or aggregates of nanoparticles of the electric field, and preferably without exposure to any other external source of activation, such as a light source, a magnetic field or an ultrasound source. All living organisms strive for a dynamic balance, which is called homeostasis. This balance is threatened by certain physical and psychological events. The interface between incoming sensory information and the evaluation process is formed by the limbic structures of the brain, which include the hippocampus, amygdala, and prefrontal cortex. Stress can be caused by various situations such as novelty, uncertainty, disappointment, conflict, fear, pain, etc. Constant exposure to an unfavorable environment, including irritants such as noise, pollution, and interpersonal conflict, can also cause stress.

Pathological stress resulting from such cumulative and/or repetitive situations alters the structure (morphology) and/or connections of brain cells and/or functional properties of brain cells. As a result, pathological stress greatly affects health and limits the quality of human life.

Uncontrolled stress can have serious adverse effects and cause symptoms, including learning and memory impairment. Under moderate levels of stress, certain neurochemical systems (eg, catecholamines, glucocorticoids) can influence learning. As the level of stress (in duration and/or intensity) increases, several temporary and permanent changes are observed in the hippocampus, including changes in synaptic plasticity, cellular morphological changes, suppression of adult neurogenesis, and/or neuronal destruction or atrophy (these changes are described in this application as symptoms of pathological stress). These stress-related changes in the brain affect learning and memory. Indeed, the hippocampus, amygdala, and prefrontal cortex undergo stress-induced structural remodeling that alters behavioral and physiological responses. Chronic stress causes neuronal atrophy in the hippocampus and prefrontal cortex, as well as brain regions involved in memory, selective attention, and executive function, and causes neuronal hypertrophy in the amygdala, a brain area associated with fear as well as aggressiveness. The ability to learn, remember and make decisions can be compromised and is usually reduced by chronic stress and may be accompanied by increased aggressiveness.

Extensive observations from in vitro and in vivo electrophysiological studies support that stress and stress hormones attenuate long-term potentiation (LTP) (i.e., long-term facilitation of neurotransmission at the synapse following natural or artificial stimulation of the synapse, which is believed to be cellular mechanism of plasticity in the brain and especially involved in learning and memory).

There are many pharmaceuticals, such as sleeping pills, anxiolytics, and beta-blockers, that counteract some of the problems associated with pathological stress. Similarly, drugs that reduce oxidative stress or inflammation, block cholesterol synthesis or absorption, and treat insulin resistance or chronic pain may help manage the metabolic and neurological consequences of "pathological devastation." All of these drugs are valuable to some extent, but unfortunately each has its own side effects and limitations (Kim JJ et al. Nature Reviews Neuroscience, 2002, 3, 453-462: The stressed hippocampus, synaptic plasticity and lost memories; McEwen BX Physiological Review, 2007, 87, 873-904: Physiology and neurobiology of stress and adaptation: central role of the brain) . The nanoparticles described herein can now advantageously be used to treat a subject suffering from such pathological stress, in particular chronic stress, typically a subject having stress-related changes found in the brain as described above.

The term "treatment" refers to therapeutic treatment or measures capable of preventing, alleviating or curing pathological stress or a symptom thereof, as described above in this application, in particular chronic stress. Such treatment is intended for a mammalian subject, preferably a human subject, in need thereof. As such, subjects are considered to be already identified (diagnosed) as suffering from pathological stress, as described in this application, or individuals who are considered "at risk of developing" such pathological stress, for which treatment is a preventive or prophylactic treatment. Specific subjects suffering from pathological stress are subjects who are prescribed a drug selected from a hypnotic, an anxiolytic, and a beta-blocker.

Pathological stress is different from oxidative stress. According to M. Auffan et al. (see M. Auffan et al., Environmental Pollution 157 (2009) 1127-1133: Chemical Stability of metallic nanoparticles: a parameter controlling their potential cellular toxicity in vitro ), oxidative stress is a state of impaired oxidative - reductive equilibrium, in which the production of ROS (reactive oxygen species) (by the cell or by the nanoparticle itself) exceeds the antioxidant protective capacity of the cell, thereby leading to adverse biological consequences: damage to macromolecules, lipids, DNA or proteins, leading to excessive cell proliferation, apoptosis, lipid peroxidation or mutagenesis. In cells, ROS production can be monitored, for example, using fluorescent dyes such as dichlorofluorescein diacetate.

The following examples and their corresponding drawings illustrate the invention without limiting its scope.

BLUEPRINTS

Fig. 1. Schematic of two simplified flashes showing some of the parameters that can be extracted from electrical activity registration. Parameters are provided that describe the overall activity (spike, burst, burst interval (IBI), and burst period) and burst structure (burst duration, burst plateau, burst amplitude, burst interval (ISI), and burst area). The standard deviations (SD) of these parameters are indicative of the regularity of the overall activity and outbreak structure, respectively. The coefficient of variation over time (CVtime) reflects the temporal regularity of the activity pattern of each unit. CVtime is calculated as the ratio of the standard deviation of the parameter to the mean. The coefficient of variation among a network (CVnet) reflects the synchronization between neurons in a network. CVnet is calculated as the ratio of the standard deviation of the parameter to the network mean. Larger CVnet values suggest a wide range of changes in network activity, which means less synchronization and higher synaptic plasticity and synaptic connectivity.

Fig. 2. Functional effects of the nanoparticles from Example 1 observed in the "Nanoparticles" group, compared with water used in the "Control" group, on the activity of the frontal cortex network. The results indicate higher synaptic plasticity and synaptic connectivity at the cellular level in the presence of nanoparticles.

Fig. Fig. 3. Functional effects of the nanoparticles from Example 2 observed in the "Nanoparticles" group, compared with water used in the "Control" group, on the activity of the frontal cortex network. The results indicate higher synaptic plasticity and synaptic connectivity at the cellular level in the presence of nanoparticles.

Fig. 4. Functional effects of the nanoparticles from Example 3 observed in the "Nanoparticles" group, compared with water used in the "Control" group, on the activity of the frontal cortex network. The results indicate higher synaptic plasticity and synaptic connectivity at the cellular level in the presence of nanoparticles.

Fig. 5. Functional effects of the nanoparticles from Example 5 observed in the "Nanoparticles" group, compared to water used in the "Control" group, on the activity of the frontal cortex network. The results indicate higher synaptic plasticity and synaptic connectivity at the cellular level in the presence of nanoparticles.

EXAMPLES

In vitro studies of neurons

At the level of neurons, the patch clamp method is very useful for determining action potentials, since it allows you to directly measure and control the membrane potential of a neuron at the same time.

This method is used to evaluate the effects of nanoparticles on an individual neuron.

In vitro neuronal network studies

Dissociated neural cultures coupled to multielectrode arrays (MEAs) are widely used to better understand the complexity of brain networks. In addition, the use of dissociated neural aggregates allows manipulation and control of network connectivity (Poli D. et al, Frontiers in Neural Circuits, 2015, 9 (article 57), 1-14: Functional connectivity in in vitro neuronal assemblies) .

The MEA system allows for non-invasive long-term simultaneous extracellular registrations from multiple sites in a neural network in real time, increasing the spatial resolution and thus providing a reliable measurement of network activity. Simultaneous collection of action potential and field potential data over long periods of time allows monitoring of network functions resulting from the interaction of all cellular mechanisms responsible for the formation of spatiotemporal patterns (Johnstone AFM et al., Neurotoxicology (2010), 31: 331 -350, Microelectrode arrays: a physiologically based neurotoxicity testing platform for the 21st ^century ) . Compared to patch clamp and other single electrode recording methods, MEA measures the responses of the entire network by integrating global information about the interaction of all receptors, synapses and neuron types present in the network (Novellino A. et al., Frontiers in Neuroengineering. (2011) , 4(4), 1-14, Development of micro-electrode array based tests for neurotoxicity: assessment of interlaboratory reproducibility with neuroactive chemicals.) . As such, MEA registrations are applied to understanding neural communication, encoding, dissemination, and information processing in neural cultures (Taketani, M., et al., (2006). Advances in Network Electrophysiology. New York, NY: Springer; Obien et al. , Frontiers in Neurosciences, 2015, 8(423): Revealing neuronal functions through microelectrode array recordings) . MEA technology is an advanced phenotypic multiparameter screening method for characterizing functional changes in network activity in electrically active cell cultures that is highly sensitive to neurogenesis as well as neuroregenerative and neurodegenerative aspects. Moreover, neural networks grown on MEA are known to be able to respond to neuroactive or neurotoxic compounds in approximately the same concentration ranges that alter the functions of the intact mammalian nervous system (Xia et al., Alcohol, 2003, 30, 167-174: Histiotypic electrophysiological responses of cultured neuronal networks to ethanol; Gramowski et al., European Journal of Neuroscience, 2006, 24, 455-465: Functional screening of traditional antidepressants with primary cortical neuronal networks grown on multielectrode neurochips; Gramowski et al., Frontiers in Neurology, 2015, 6(158): Enhancement of cortical network activity in vitro and promotion of GABAergic neurogenesis by stimulation with an electromagnetic field with 150MHz carrier wave pulsed with an alternating 10 and 16 Hz modulation) .

This method is used to evaluate the effect of nanoparticles on neural network(s).

In vivo studies of the network of neurons

It is believed that a suitable animal model allows one to evaluate the effect of the nanoparticles of the invention on the neural networks of animals.

For example, mazes are used to study spatial learning and memory in rats or mice. Maze research helps uncover general principles of learning that can be applied to many species, including humans. Today, mazes are commonly used to determine whether different treatments or conditions affect learning and memory in rats.

EXAMPLE 1. Nanoparticles obtained from a conductive material: synthesis of gold nanoparticles coated with a biocompatible coating having a neutral surface charge.

Gold nanoparticles were synthesized by reduction of a gold chloride salt (HAuCl ₄ ) with a protective agent (sodium citrate) (protocol adapted from G. Frens Nature Physical Science 241 (1973) 21). In a typical experiment, a solution of HAuCl ₄ was heated to boiling. Then sodium citrate solution was added. The resulting solution was kept at the boil for an additional 5 minutes.

A 0.22 µm filtration (filter membrane: poly(ethersulfone) (PES)) of the nanoparticle suspension was performed, and the gold concentration in the suspension was determined by UV visible spectroscopy at 530 nm.

The surface was coated with α-methoxy-ω-mercaptopoly(ethylene glycol) 20 kDa (“thiol-PEG20 kDa”). Sufficient "thiol-PEG 20kDa" was added to the nanoparticle suspension to achieve at least half of the monolayer coverage (2.5 molecules/nm ² ) on the surface of the gold nanoparticle. The pH was adjusted between 7 and 7.2 and the nanoparticle suspension was stirred overnight.

The hydrodynamic diameter (intensity measurement) was determined using dynamic light scattering (DLS) at room temperature (about 25°C) using a Nano-Zetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm, by dilution of the suspension of nanoparticles in water (final concentration: [Au] = 0.1 g/l). The hydrodynamic diameter of the thus obtained biocompatible gold nanoparticles in suspension was found to be 118 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) of 0.13.

Zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in a NaCl solution at 1 mM at pH 7 (final concentration: [Au] = 0.1 g/l). The zeta potential at pH 7 was found to be -1mV.

EXAMPLE 2. Nanoparticles obtained from a conductive material: synthesis of gold nanoparticles coated with a biocompatible coating having a negative surface charge.

Gold nanoparticles were prepared as described in Example 1 (same inorganic gold core).

0.22 µm filtration was carried out on a PES membrane filter and the concentration of gold in the suspension was determined by spectroscopy in the visible region of UV radiation at 530 nm.

The biocompatible surface coating was applied using meso-2,3-dimercaptosuccinic acid (DMSA). Sufficient DMSA was added to the nanoparticle suspension to achieve at least half monolayer coverage (2.5 molecules/nm ² ) on the surface. The pH was adjusted between 7 and 7.2 and the nanoparticle slurry was stirred overnight.

The hydrodynamic diameter (intensity measurement) was determined by dynamic light scattering (DLS) at room temperature (about 25°C) using a nanozetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm by diluting a suspension of nanoparticles in water (final concentration: [Au] = 0.1 g/l). The hydrodynamic diameter of the thus obtained nanoparticles in suspension was 76 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) equal to 0.46.

Zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in a NaCl solution at 1 mM at pH 7 (final concentration: [Au] = 0.1 g/l). The zeta potential at pH 7 was found to be -23mV.

EXAMPLE 3 Nanoparticles prepared from an insulating material having a low relative dielectric constant equal to or below 100: Synthesis of zirconium oxide nanoparticles coated with a biocompatible coating having a neutral surface charge.

Zirconium oxide (ZrO ₂ ) nanoparticles were synthesized by precipitation of zirconium chloride (ZrCl ₄ ) with tetramethylammonium hydroxide (TMAOH) at basic pH. The resulting suspension was transferred to an autoclave and heated at a temperature above 110°C. After cooling, the suspension was washed with deionized water and acidified.

The largest median size of the core of nanoparticles or aggregates of nanoparticles of the population and the size of the core of nanoparticles or aggregates of nanoparticles representing 30-70% percentile of the population of nanoparticles and aggregates of nanoparticles were estimated using electron microscopy and found to be 10 nm and 8 nm - 12 nm, respectively. 446 nanoparticles were counted and their largest size was measured.

0.22 μm filtration was carried out on a PES membrane filter and the concentration of nanoparticles (ZrO ₂ ) was determined by drying the aqueous solution to a powder state and weighing the thus obtained mass.

A biocompatible coating was obtained using a 2kDa silane-poly(ethylene)glycol (“Si-PEG 2kDa”). Sufficient "Si-PEG 2kDa" was added to the nanoparticle suspension to achieve at least half of the monolayer coverage (2.5 molecules/nm ² ) on the surface. The nanoparticle suspension was stirred overnight and then the pH was adjusted to 7.

Hydrodynamic diameter (intensity measurement) was determined by dynamic light scattering (DLS) at room temperature (about 25°C) using a nanozetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm by diluting a suspension of nanoparticles in water (final concentration of ZrO ₂ constituting the core of the nanoparticle: [ZrO ₂ ] = 0.1 g/l). The hydrodynamic diameter of the nanoparticles was found to be 55 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) equal to 0.1.

Zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in a NaCl solution at 1 mM at pH 7 (final concentration: [ZrO ₂ ] = 0.1 g/l). The zeta potential at pH 7 was found to be -1mV.

EXAMPLE 4 Nanoparticles prepared from an insulating material having a low relative dielectric constant equal to or below 100: Synthesis of zirconium oxide nanoparticles coated with a biocompatible coating having a negative surface charge.

Zirconium oxide nanoparticles were prepared as described in Example 3 (same inorganic core).

0.22 μm filtration was carried out on a PES membrane filter and the concentration of nanoparticles (ZrO ₂ ) was determined by drying the aqueous solution to a powder and weighing the thus obtained mass.

Surface functionalization was carried out using sodium hexametaphosphate. Sufficient mass of sodium hexametaphosphate was added to the nanoparticle suspension to achieve at least half of the monolayer coverage (2.5 molecules/nm ² ) on the surface. The nanoparticle suspension was stirred overnight and then the pH was adjusted to 7.

Hydrodynamic diameter (intensity measurement) was determined by dynamic light scattering (DLS) at room temperature (about 25°C) using a nanozetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm by diluting a suspension of nanoparticles in water (final concentration of ZrO ₂ constituting the core of the nanoparticle: [ZrO ₂ ] = 0.1 g/l). The hydrodynamic diameter of the nanoparticles was found to be 70 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) of 0.11.

Zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in NaCl solution at 1 mM at pH 7 (final concentration: [ZrO ₂ ] = 0.1 g/l). The zeta potential at pH 7 was found to be -33mV.

EXAMPLE 5 Nanoparticles made from a semiconductor material: silicon nanoparticles coated with a biocompatible coating having a neutral surface charge.

Silicon (Si) nanoparticles (powder) were obtained from US Research Nanomaterials Inc. They were coated with PVP (1 wt%), which is less than 0.1 molecule/nm ² on the surface.

The largest median core size of the population of nanoparticles or aggregates of nanoparticles and the size of the core of nanoparticles or aggregates of nanoparticles representing 30-70% percentile of the population of nanoparticles and aggregates of nanoparticles were estimated using electron microscopy and found to be 53 nm and 45-61 nm, respectively. Seventy-one (71) nanoparticles were counted and their largest size measured.

They were then coated with silane-poly(ethylene glycol) 20kDa (Si-PEG 20kDa) by adding a mass sufficient to obtain at least half of the monolayer (2.5 molecules/nm ² ) and incubating the coated solution overnight at basic pH. Then they were dispersed in water at a concentration of 30 g/l under sonication (using a probe).

0.22 µm filtration was carried out on a PES membrane filter and the concentration of nanoparticles (Si) was determined by drying the suspension to a powder and weighing the thus obtained mass.

The hydrodynamic diameter (intensity measurement) was determined by dynamic light scattering (DLS) at room temperature (about 25°C) using a nanozetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm, by diluting a suspension of nanoparticles in water ( final concentration of Si constituting the core of the nanoparticle: [Si] = 0.1 g/l). The hydrodynamic diameter of the nanoparticles was found to be 195 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) equal to 0.10,

Zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in a NaCl solution at 1 mM at pH 7 (final concentration: [Si] = 0.1 g/l). The zeta potential at pH 7 was found to be -3mV.

EXAMPLE 6. Nanoparticles obtained from a semiconductor material: silicon nanoparticles coated with a biocompatible coating having a negative surface charge.

Silicon (Si) nanoparticles (powder) were obtained from US Research Nanomaterials Inc. They were coated with PVP (1 wt%), which is less than 0.1 molecule/nm ² on the surface.

They were dispersed in water at 30 g/l under sonication (using a probe).

0.22 µm filtration was carried out on a PES membrane filter and the concentration of nanoparticles (Si) was determined by drying the suspension to a powder and weighing the thus obtained mass.

The hydrodynamic diameter (intensity measurement) was determined by dynamic light scattering (DLS) at room temperature (about 25°C) using a nanozetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm by diluting a suspension of nanoparticles in water (final concentration of Si constituting the core of the nanoparticle: [Si] = 0.1 g/l). The hydrodynamic diameter of the nanoparticles was found to be 164 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) of 0.16.

The largest median core size of the population of nanoparticles or aggregates of nanoparticles and the size of the core of nanoparticles or aggregates of nanoparticles representing 30-70% percentile of the population of nanoparticles and aggregates of nanoparticles were estimated using electron microscopy and found to be 53 nm and 45-61 nm, respectively. Seventy-one (71) nanoparticles were counted and their largest size measured.

Zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in a NaCl solution at 1 mM at pH 7 (final concentration: [Si] = 0.1 g/l). The zeta potential at pH 7 was found to be -19mV.

EXAMPLE 7 Nanoparticles prepared from an insulating material having a high relative dielectric constant equal to or greater than 200: barium titanate nanoparticles coated with a biocompatible coating having a negative surface charge.

A suspension of barium titanate (BaTiO ₃ ) nanoparticles (20 wt% in water) was obtained from US Research Materials Inc. (US3835).

The surface was functionalized using silane-poly(ethylene)glycol 10 kDa (“Si-PEG 10 kDa”). Briefly, "Si-PEG 10kDa" was first dissolved in an ethanol/water solution (1/3 v/v) and added to a suspension of BaTiO ₃ (20 wt.% in water) to achieve a complete monolayer coating on the surface of the nanoparticles. The suspension was sonicated and then stirred overnight. After 0.22 µm filtration (filter membrane: poly(ethersulfone)) a washing step was carried out to remove unreacted “Si-PEG 10kDa” polymers.

The hydrodynamic diameter (intensity measurement) was determined by dynamic light scattering (DLS) at room temperature (about 25°C) using a nanozetasizer (Malvern) at a scattering angle of 173° using a laser emitting at 633 nm by diluting a suspension of nanoparticles in water (final concentration of BaTiO₃, constituting the core of the nanoparticle: [BaTiO₃] = 0.1 g/l). The hydrodynamic diameter of the nanoparticles was found to be 164 nm, with a polydispersity index (dispersion of the population of nanoparticles by size) of 0.16.

The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of the nanoparticles in a NaCl solution at 1 mM at pH 7 (final concentration: [BaTiO ₃ ] = 0.1 g/l). Zeta potential at pH 7 was found at -11mV.

The largest median core size of the population of nanoparticles or aggregates of nanoparticles and the size of the core of nanoparticles or aggregates of nanoparticles representing 30-70% percentile of the population of nanoparticles and aggregates of nanoparticles were estimated using electron microscopy and found to be 67 nm and 60-77 nm, respectively. Fifty-one (51) nanoparticles were counted and their largest size was measured.

EXAMPLE 8. Functional evaluation of the nanoparticles of the invention (nanoparticles from examples 1 and 2) on frontal cortex neuron cultures using multielectrode arrays (MEA).

MATERIALS AND METHODS

Neurochips with microelectrode array

Neurochips with a 48-well microelectrode array were purchased from Axion Biosystems Inc. These chips have 16 passive electrodes per well. The surface was covered with polyethyleneimine (PEI, 50% in borate buffer) for 1 hour, washed and air dried.

Primary cell culture, processing conditions

Frontal cortex tissue was harvested from embryos (day 15/16) of chr:NMRI mice (Charles River). Mice were sacrificed by cervical dislocation. The tissue was dissociated by enzymatic digestion (133.3 Kunitz units/ml DNase; 10 units/ml papain) and mechanical trituration, counted, viability monitored and seeded in a 20 µl drop of DMEM containing laminin (10 µg/ml), 10% fetal bovine serum and 10% horse serum, per MEA. Cultures on MEA were incubated at 37°C in an atmosphere of 10% CO ₂ until ready for use. Culture media were replenished twice a week with DMEM containing 10% horse serum. Developing co-cultures were treated with mitosis inhibitors 5-fluoro-2'-deoxyuridine (25 μM) and uridine (63 μM) on day 5 post-seeding to prevent further glial proliferation.

The frontal cortex was cultured for 26 days (culture period, also referred to as "native phase"). The number of active wells was counted, and suspensions of nanoparticles ([Au] = 800 µM) (Nanoparticle groups) or water (Control group) were added to the active wells. After 2 days (48 hours) of incubation, activity was recorded for 2 hours (values obtained from 60-second data sets taken from a 30-minute span).

Multi-channel registration and multi-parameter data analysis

The MAESTRO multichannel registration system from Axion Biosystems (USA) was used for registration. For extracellular recording, 48-well MEAs were placed on a MAESTRO recording station and maintained at 37°C. Registrations were made in DMEM/10% heat-inactivated horse serum. pH was maintained at 7.4 using a continuous stream of filtered humidified air with 10% CO ₂ .

Each unit represents the activity emanating from one neuron, registered on one electrode. Units are separated at the beginning of registration. For each unit, action potentials (ie, spikes) were recorded as sequences of spikes, which are combined into so-called "bursts". Flares were quantified by direct spike sequence analysis using Spike Wrangler and NPWaveX software (both from NeuroProof GmbH, Rostock, Germany). Flares were determined by the beginning and end of short spike events (see Fig. 1).

Using a multi-parameter high-throughput analysis of network activity patterns, 204 spike sequences describing the activity of a parameter were obtained. These parameters provide an accurate description of activity changes in the following four categories: overall activity, burst pattern, oscillation pattern, and synchronicity.

- Changes in “general activity parameters” describe the effects on the frequency of action potentials (speed of spikes), flash rate and flash period as the time between flashes.

- “Flash structure parameters” define not only the internal structure of the spikes in the high-frequency spike phase (“flash”), such as the frequency of the spikes in the bursts, the speed of the spikes in the bursts, and the density of the spikes of the burst, but also the overall structure of the burst, such as duration, area, and plateau.

- “Variation parameters” quantify the regularity of occurrence or structure of outbreaks, which are calculated from the coefficients of variation of primary activity parameters describing the variability of parameters (general activity, outbreak structure) in experimental episodes ( Gramowski A. et al., Eur. J. Neurosci., 2004, 19, 2815-2825: Substance identification by quantitative characterization of oscillator activity in murine spinal cord networks on microelectrode arrays ). Higher values indicate a less regular flash pattern or less regular overall activity (eg ripple, pulse 'burst').

- As a measure of synchronicity in a sequence of spikes, “CVnet parameters” reflect “synchronization” between neurons in a network ( Gramowski A. et al., Eur. J. Neurosci., 2004, 19, 2815-2825: Substance identification by quantitative characterization of oscillator activity in murine spinal cord networks on microelectrode arrays ). CVnet is the coefficient of variation over the network. Larger CVnet values imply a wide range of network activity changes, which means less synchronization. ( Gramowski A. et al., Frontiers in Neurology, 2015, 6(158): Enhancement of cortical network activity in vitro and promotion of GABAergic neurogenesis by stimulation with an electromagnetic field with 150MHz carrier wave pulsed with an alternating 10 and 16 Hz modulation ).

CVtime reflects the periodic behavior, activity pattern, of a single unit (single neuron), while CVnet shows the coordination between different neurons in a certain period of time and is a measure of synchronicity. If the population of neurons (network) is synchronized but fluctuates in its time pattern, a low CVnet value and a high CVtime are observed. Conversely, an unsynchronized network with multiple periodic patterns results in high CVnet and low CVtime. High CVnet is usually achieved in vivo (i.e., under healthy conditions and in the absence of any treatment) when synaptic connectivity (which refers to the ensemble of chemical and electrical connections between neurons) is maximized.

The functional effects induced by the nanoparticles of the invention on the neural network were evaluated by the parameters described above (also summarized for some of them in Table 1 below).

Table 1
Parameters describing activity from multivariate data analysis in the following two categories: general activity and synchronicity General activity Spike speed Number of spikes per second averaged over all recorded spike sequences Flash Speed Number of flashes per minute, averaged over all registered units Synchronicity CVnet Spike Rate Spike rate CVnet, reflecting the network variability of spike rates in experimental episodes. Decreasing this setting indicates an increase in synchronization on the network, while increasing this setting indicates a decrease in synchronization. CVnet flash rate Flash rate CVnet reflecting the change in flash rate over the network during experimental episodes Height and frequency of peaks
flash CVnet Flash duration CVnet, reflecting the change in flash duration over the network during experimental episodes Flash Amplitude CVnet CVnet of flare amplitude, reflecting the change in flare amplitudes in flare intervals in experimental episodes throughout the network. A decrease in this parameter indicates an increase in network synchronization, while an increase in this parameter indicates a decrease in synchronization. CVnet flash period The CVnet of the burst period (distance between the onset of successive bursts), reflecting the variability in flash frequency in experimental episodes across the network. A decrease in this parameter indicates an increase in network synchronization, while an increase in this parameter indicates a decrease in synchronization.

The functional effects on network activity were recorded in the presence or absence of the tested nanoparticles. Absolute activity values (parameter values) were expressed as mean ± SEM of independent networks. For each "Nanoparticles" or "Control" group, at least 8 active wells ("active" means wells with a sufficient number of electrical activity electrodes) were included in the analysis. Distributions of absolute parameters were tested for normality and statistical significance between groups was assessed using one-way analysis of variance.

Fig. 2 (nanoparticles from example 1) and 3 (nanoparticles from example 2) represent some representative parameters (general activity and synchrony) characterizing the functional effects observed in the groups "Nanoparticles" and in the "Control" group. Compared to water (used in the "Control" group), nanoparticles increase the variability of network communication (increased values of CVnet parameters). This may be due to an increase in synaptic plasticity and synaptic connectivity, and thus an increase in network memory capacity.

EXAMPLE 9 Functional evaluation of the nanoparticles of the invention (nanoparticles from Examples 3 and 5) in cultures of frontal cortex neurons using multielectrode arrays (MEA).

MATERIALS AND METHODS

Neurochips with microelectrode array

Neurochips with a 48-well microelectrode array were purchased from Axion Biosystems Inc. These chips have 16 passive electrodes per well. The surface was covered with polyethyleneimine (PEI, 50% in borate buffer) for 1 hour, washed and air dried.

Primary cell culture, processing conditions

Frontal cortex tissue was harvested from embryos (day 15/16) of chr:NMRI mice (Charles River). Mice were sacrificed by cervical dislocation. The tissue was dissociated by enzymatic digestion (133.3 Kunitz units/ml DNase; 10 units/ml papain) and mechanical trituration, counted, viability monitored, and plated in DMEM containing 10% fetal bovine serum and 10% horse serum on coated poly -D-lysine and laminin MEA. Cultures on MEA were incubated at 37°C in an atmosphere of 10% CO ₂ until ready for use. Culture media were replenished twice a week with DMEM containing 10% horse serum. Developing co-cultures were treated with mitosis inhibitors 5-fluoro-2'-deoxyuridine (25 μM) and uridine (63 μM) on day 5 post-seeding to prevent further glial proliferation.

The frontal cortex was cultured for at least 4 weeks (culture period, also referred to as "native phase"). The number of active wells was counted, and suspensions of nanoparticles ([Si] = 800 µM for a suspension of nanoparticles from example 5 and [ZrO ₂ ] = 400 µM for a suspension of nanoparticles from example 3) (groups “Nanoparticles”) or water (“Control group”) were added to the active wells. " Group). After 4 days (96 hours) of incubation, activity was recorded for 2 hours (values obtained from 60 second data sets taken from a 30 minute span).

Multi-channel registration and multi-parameter data analysis

The MAESTRO multichannel registration system from Axion Biosystems (USA) was used for registration. For extracellular recording, 48-well MEAs were placed on a MAESTRO recording station and maintained at 37°C. Registrations were made in DMEM/10% heat-inactivated horse serum. pH was maintained at 7.4 using a continuous stream of filtered humidified air with 10% CO ₂ .

Each unit represents the activity emanating from one neuron, registered on one electrode. Units are separated at the beginning of registration. For each unit, action potentials (ie, spikes) were recorded as sequences of spikes, which are combined into so-called "bursts". Flares were quantified by direct spike sequence analysis using Spike Wrangler and NPWaveX software (both from NeuroProof GmbH, Rostock, Germany). Flares were determined by the beginning and end of short spike events (see Fig. 1).

Using a multi-parameter high-throughput analysis of network activity patterns, 204 spike sequences describing the activity of a parameter were obtained. These parameters provide an accurate description of activity changes in the following four categories: overall activity, burst pattern, oscillation pattern, and synchronicity.

- Changes in “general activity parameters” describe the effects on the frequency of action potentials (speed of spikes), flash rate and flash period as the time between flashes.

- “Flash structure parameters” define not only the internal structure of the spikes in the high-frequency spike phase (“flash”), such as the frequency of the spikes in the bursts, the speed of the spikes in the bursts, and the density of the spikes of the burst, but also the overall structure of the burst, such as duration, area, and plateau.

- “Variation parameters” quantify the regularity of occurrence or structure of outbreaks, which are calculated from the coefficients of variation of primary activity parameters describing the variability of parameters (general activity, outbreak structure) in experimental episodes ( Gramowski A. et al., Eur. J. Neurosci., 2004, 19, 2815-2825: Substance identification by quantitative characterization of oscillator activity in murine spinal cord networks on microelectrode arrays ). Higher values indicate a less regular flash pattern or less regular overall activity (eg ripple, pulse 'burst').

- As a measure of synchronicity in a sequence of spikes, “CVnet parameters” reflect the “synchronization” between neurons in a network ( Gramowski A. et al., Eur. J. Neurosci., 2004, 19, 2815-2825: Substance identification by quantitative characterization of oscillator activity in murine spinal cord networks on microelectrode arrays ). CVnet is the coefficient of variation over the network. Larger CVnet values imply a wide range of network activity changes, which means less synchronization. ( Gramowski A. et al., Frontiers in Neurology, 2015, 6(158): Enhancement of cortical network activity in vitro and promotion of GABAergic neurogenesis by stimulation with an electromagnetic field with 150MHz carrier wave pulsed with an alternating 10 and 16 Hz modulation ).

CVtime reflects the periodic behavior, activity pattern, of a single unit (single neuron), while CVnet shows the coordination between different neurons in a certain period of time and is a measure of synchronicity. If the population of neurons (network) is synchronized but fluctuates in its time pattern, low CVnet and high CVtime are observed. Conversely, an unsynchronized network with multiple periodic patterns results in high CVnet and low CVtime. High CVnet is usually achieved in vivo (i.e., under healthy conditions and in the absence of any treatment) when synaptic connectivity (which refers to the ensemble of chemical and electrical connections between neurons) is maximized.

The functional effects induced by the nanoparticles of the invention on the neural network were evaluated by the parameters described above (also summarized for some of them in Table 2 below).

table 2
Parameters describing activity from multivariate data analysis in the following two categories: general activity and synchronicity General activity Spike speed Number of spikes per second averaged over all recorded spike sequences Flash Speed Number of flashes per minute, averaged over all registered units Synchronicity Spike speed
CVnet Spike rate CVnet, reflecting the network variability of spike rates in experimental episodes. Decreasing this setting indicates an increase in synchronization on the network, while increasing this setting indicates a decrease in synchronization. Flash Speed
CVnet Flash rate CVnet reflecting the change in flash rate over the network during experimental episodes Height and Peak Frequency of CVnet Flash Flash duration CVnet, reflecting the change in flash duration over the network during experimental episodes Flash Amplitude
CVnet CVnet of flare amplitude, reflecting the change in flare amplitudes in flare intervals in experimental episodes throughout the network. A decrease in this parameter indicates an increase in network synchronization, while an increase in this parameter indicates a decrease in synchronization. CVnet flash period The CVnet of the burst period (distance between the onset of successive bursts), reflecting the variability in flash frequency in experimental episodes across the network. A decrease in this parameter indicates an increase in network synchronization, while an increase in this parameter indicates a decrease in synchronization.

The functional effects on network activity were recorded in the presence or absence of the tested nanoparticles. Activity values (parameter values) were normalized to the corresponding native activity set to 100% for each experiment (native activity values were obtained from 60-second data sets taken from a 30-minute window after 30-minute activity stabilization). Relative activity values were expressed as mean ± SEM of independent networks. For each "Nanoparticles" or "Control" group, at least 8 active wells ("active" means wells with a sufficient number of electrical activity electrodes) were included in the analysis. Distributions of absolute parameters were tested for normality and statistical significance between groups was assessed using one-way analysis of variance.

Fig. 4 (nanoparticles from example 3) and 5 (nanoparticles from example 5) represent some representative parameters (total activity and synchrony) characterizing the functional effects observed in the "Nanoparticles" groups of the group and in the "Control" group. Compared to water (used in the "Control" group), nanoparticles increase the variability of network communication (increased values of CVnet parameters). This may be due to an increase in synaptic plasticity and synaptic connectivity, and thus an increase in network memory capacity.

These results highlight the advantageous characteristics of the nanoparticles described herein in enhancing functional effects (synaptic plasticity and synaptic connectivity in a neural network) in a neural network.

EXAMPLE 10: Synthesis and physico-chemical characterization of gold nanoparticles with different sizes, having a neutral surface charge.

Gold nanoparticles are obtained by reducing gold chloride with sodium citrate in an aqueous solution. The protocol has been adapted from G. Frens Nature Physical Science 241 (1973) 21.

In a typical experiment, a solution of HAuCl ₄ was heated to boiling. Then sodium citrate solution was added. The resulting suspension was kept at the boil for an additional 5 minutes.

The nanoparticle size was adjusted from about 15 nm to about 110 nm by carefully modifying the ratio of citrate to gold precursor (see Table 3).

The resulting suspension of gold nanoparticles was then concentrated using an ultrafiltration device (Amicon stirred cell model 8400 from Millipore) with a cellulose membrane having an appropriate molecular weight cut-off of retained components (MWCO) and filtered through a 0.22 μM cut-off membrane filter (membrane PES from Millipore) in a laminar flow hood.

Surface coating was carried out using α-methoxy-ω-mercaptopoly(ethylene glycol) 20 kDa (“thiol-PEG20 kDa”). A sufficient amount of "thiol-PEG 20 kDa" was added to the suspension of nanoparticles to obtain a monolayer coating on the surface of the gold nanoparticles. The pH was adjusted between 6.8 and 7.4 and the nanoparticle suspension was stirred overnight. Excess thiol-PEG 20 kDa was removed using an ultrafiltration centrifuge filter (Vivaspin from Sartorius or Amicon Ultra from Merck Millipore) with an appropriate MWCO membrane in a laminar flow cabinet and the resulting suspension was stored at 4°C.

Particle size was determined by transmission electron microscopy by counting at least 200 nanoparticles, taking the largest nanoparticle size for size determination. The largest median core size of the population of nanoparticles or aggregates of nanoparticles and the core size of nanoparticles or aggregates of nanoparticles, representing the 30% - 70% percentile of the population of nanoparticles and aggregates of nanoparticles, are presented in Table 3 along with the concentration of gold ([Au]) measured using optical emission inductively coupled plasma spectrometry (ICP-OES), and zeta potential determined by measuring the electrophoretic mobility of nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of nanoparticles in a NaCl solution at 1 mM, at a concentration of gold ([Au]) from 0, 01 to 0.05 g/l and at a pH of about 7.

Table 3 Samples Citrate/Au ratio during synthesis (mol/mol) Largest median size of the nanoparticle core (nm) 30%-70% percentile (nm) Zeta potential (mV) [Au] mg/ml (by ICP-OES) GOLD-15 3.5 fifteen 14-16 -3 3.6 GOLD-30 1.96 34 30-37 -3 3.9 GOLD-45
Same core of nanoparticles as the nanoparticles from Examples 1 & 2 1.26 45 42-49 -four 3.6 GOLD-80 0.8 83 77-93 -2 3.4 GOLD-110 0.7 108 91-123 -2 2.9

EXAMPLE 11 Synthesis of nanoparticles derived from conductive material: poly(3,4-ethylenedioxythiophene) nanoparticles (PEDOT nanoparticles) having a negative surface charge.

A dispersion of poly(3,4-ethylenedioxythiophene) nanoparticles (PEDOT nanoparticles) in water (1.1% w/w) was obtained from Sigma (Sigma 675288) and used without further purification.

The zeta potential was determined by measuring the electrophoretic mobility of the nanoparticles (Nanozetasizer, Malvern) by diluting a suspension of the nanoparticles in a 1 mM NaCl solution at pH 7.3 (PEDOT final concentration: 1g/l). The zeta potential at pH 7.3 was found to be -53mV.

The largest median size of the population of nanoparticles or aggregates of nanoparticles and the size of the core of nanoparticles or aggregates of nanoparticles, representing the 30%-70% percentile of the population of nanoparticles and aggregates of nanoparticles, were estimated using scanning electron microscopy (SEM), and they were equal to 408 nm and 311 nm - 518 nm, respectively (56 nanoparticles were counted and their largest size was measured).

EXAMPLE 12 Synthesis of nanoparticles obtained from an insulating material having a low relative dielectric constant equal to or below 100: synthesis of hafnium oxide nanoparticles coated with a biocompatible coating having a negative surface charge.

Hafnium oxide (HfO ₂ ) nanoparticles were synthesized by precipitation of hafnium chloride (HfCl ₄ ) with tetramethylammonium hydroxide (TMAOH) at basic pH. The resulting suspension was transferred to an autoclave and heated at a temperature above 110°C. After cooling, the suspension was washed with deionized water and acidified.

Surface functionalization was carried out using sodium hexametaphosphate. Sufficient mass of sodium hexametaphosphate was added to the nanoparticle suspension to achieve at least half of the monolayer coverage (2.5 molecules/nm ² ) on the surface. The nanoparticle suspension was stirred overnight and then the pH was adjusted to 7.

Claims (7)

1. The use of a nanoparticle or an aggregate of nanoparticles to improve learning, memorization and attention in a subject without exposing the nanoparticle or aggregate of nanoparticles to an electric field or any other external source of activation, where the material of the nanoparticle or aggregate of nanoparticles is selected from a conductive material selected from a metal having a standard potential recovery E° above 0.2 selected from Tl, Po, Ag, Pd, Ir, Pt and/or Au, and an organic material having adjacent sp2-hybridized carbon centers in its structure, and an insulating material with a relative permittivity ε _ijk , equal to or less than 100, selected from La ₂ O ₃ , SiO ₂ , SnO ₂ , Ta ₂ O ₅ , ReO ₂ , ZrO ₂ , HfO ₂ , Y ₂ O ₃ and diamond-like carbon, when measuring the relative permittivity ε _ijk in the range from 20°C to 30°C and from 10 ² Hz to infrared frequency, where i) the median size of the core of the nanoparticle or aggregate of nanoparticles of the population is at least 30 nm when the material is a conductive material, and where ii) the core of the nanoparticle or aggregate of nanoparticles is coated with a biocompatible coating providing a negative surface charge when measured in a water solution having an electrolyte concentration of 0.001 to 0.2 M, the concentration of the nanoparticle material, or nanoparticle aggregates from 0.01 to 10 g/l and a pH between 6 and 8, where iii) nanoparticles or nanoparticle aggregates are not used as a carrier of a therapeutic compound or drug and where iv) a biocompatible coating providing a negative surface charge is selected from phosphate , dicarboxylic acid, succinic acid or sulfate. 2. The use of a nanoparticle or aggregate of nanoparticles for the treatment of at least one symptom of pathological stress in a subject without exposing the nanoparticle or aggregate of nanoparticles to an electric field or any other external source of activation, where the material of the nanoparticle or aggregate of nanoparticles is selected from a conductive material selected from a metal having standard reduction potential E° above 0.2 selected from Tl, Po, Ag, Pd, Ir, Pt and/or Au, and an organic material having adjacent sp2 hybridized carbon centers in its structure, and an insulating material with a relative permittivity ε _ijk equal to or less than 100 selected from La ₂ O ₃ , SiO ₂ , SnO ₂ , Ta ₂ O ₅ , ReO ₂ , ZrO ₂ , HfO ₂ , Y ₂ O ₃ and diamond-like carbon, when measuring the relative permittivity ε _ijk in the range from 20°C to 30°C and from 10 ² Hz to the frequency of the infrared range, where i) the median size of the core of a nanoparticle or aggregate of nanoparticles of the population with is at least 30 nm when the material is a conductive material, and where ii) the core of the nanoparticle or aggregate of nanoparticles is coated with a biocompatible coating providing a negative surface charge, when measured in a water solution having an electrolyte concentration of 0.001 to 0.2 M, a concentration material of nanoparticles or aggregates of nanoparticles from 0.01 to 10 g/l and a pH between 6 and 8, where iii) the nanoparticles or aggregates of nanoparticles are not used as a carrier of a therapeutic compound or drug and where iv) a biocompatible coating that provides a negative surface charge, selected from phosphate, dicarboxylic acid, succinic acid or sulfate. 3. Use according to claim 1 or 2, where the material of the nanoparticle or aggregate of nanoparticles is selected from a metal nanoparticle, where the metal element is Ir, Pd, Pt, Au, or any mixture thereof, and an organic nanoparticle consisting of polyaniline, polypyrrole, polyacetylene, polythiophene, polycarbazole and/or polypyrene. 4. Use according to claim 1 or 2, wherein the insulating material with a relative permittivity ε _ijk equal to or less than 100 is a metal oxide selected from ReO ₂ , ZrO ₂ and HfO ₂ . 5. The use of a composition comprising nanoparticles and/or aggregates of nanoparticles defined in any one of paragraphs. 1-4, and a pharmaceutically acceptable carrier, for improving learning, memory, and attention in a subject without exposing the nanoparticles and/or aggregates of nanoparticles to an electric field or any other external source of activation. 6. The use of a composition comprising nanoparticles and/or aggregates of nanoparticles defined in any one of paragraphs. 1-4, and a pharmaceutically acceptable carrier, for treating at least one symptom of pathological stress in a subject without exposing the nanoparticles and/or aggregates of nanoparticles to an electric field or any other external source of activation. 7. Use according to claim 5 or 6, where the composition includes at least two separate nanoparticles and/or aggregates of nanoparticles defined in any one of paragraphs. 1-4.

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