WO2021252850A1

WO2021252850A1 - Imaging system and process

Info

Publication number: WO2021252850A1
Application number: PCT/US2021/036945
Authority: WO
Inventors: Ryan Senaratne; Galan MOODY; Weerasinghe PRIYANTHA
Original assignee: Weedetect Llc
Priority date: 2020-06-12
Filing date: 2021-06-11
Publication date: 2021-12-16

Abstract

An imaging system and process is provided for rapid screening and detection of particles, such as for example viruses. More specifically, the imaging system includes a microscope in combination with a photonic chip or spatial light modulator. The process is not a molecular or serological (antibody) test, but instead utilizes one or more viral properties such as size, shape, and isoelectric point for identification of a virus in a sample.

Description

IMAGING SYSTEM AND PROCESS

[0001] This application claims the benefit of U.S. Provisional Application Nos. 63/038,179, filed June 12, 2020, 63/057,529, filed July 28, 2020, 63/075,292, filed September 7, 2020, and 63/083,880 filed September 26, 2020, which are each incorporated in their entirety herein by reference.

[0002] An imaging system and process is provided for rapid screening and detection of particles, such as for example viruses. More specifically, the imaging system includes a microscope in combination with a photonic chip or spatial light modulator. The process for viral detection includes utilizing one or more viral properties such as size, shape, and isoelectric point for identification of a virus in a sample.

BACKGROUND

[0003] Pandemics such as the COVID-19 have emphasized the need for rapid viral screening and detections systems. The COVID-19 pandemic started in Wuhan city in China. The first case was detected in November 2019. It took another two months for it to start to spread in other parts of the world. Although there was a window of opportunity, the world authorities failed to stop the spread of this virus throughout the world. One of the key reasons behind this failure was the lack of high throughput technology to detect a virus in human body within minutes in the field or at a point of care (outside a laboratory). There are two types of tests commonly used to detect viral infections in humans: molecular and serological (antibody) tests. In respiratory infections, caused by viruses, molecular tests are routinely used to detect the presence of viral genetic material in a sample. The specific technique that is used to detect RNA viruses is called reverse transcription polymerase chain reaction, or RT-PCR, where presence of specific viral genetic material can be detected using the above amplification reaction. This type of molecular tests typically involves inserting a 6-inch long swab into the back of the nasal passage through one nostril and rotating the swab several times for 15 seconds. This process is then repeated through the other nostril. The swab is then inserted into a container and sent to a lab for testing. A RT-PCR test can confirm a diagnosis of COVID-19 if it identifies two specific SARS-CoV-2 genes. If it identifies only one of these genes, it will produce an inconclusive result Loop mediated isothermal amplification (LAMP) is another molecular method of nucleic acid amplification. This method can yield results within an hour of testing, compared to 4-8 hours taken with RT- PCR methods. This method is not necessarily a quantitative measure of infection, but rather a simple positive/negative assay for relatively rapid detection of genetic material of the virus of interest in infected people. (Junaid Kashir and Ahmed Yaqinuddin 20201. Price of a commercially available molecular test is around $40 (James B. Mahonv et al 2004). For example people with Medicare the prices of these tests vary from $35-52, depending on the state (https://www.medicalnewstodav.com/articles/coronavirus- testing#how-does-it-work.)

[0004] Unlike molecular tests, serological tests can identify people who were infected and have recovered (or in the late stages of the infection). Serological tests rely on detecting antibodies in a blood sample, usually obtained through a simple finger prick. Therefore, serological tests are not useful as a diagnostic tool to stop the spread of a viral infection from person to person. Especially when it comes to viruses like SARS-CoV-2 (causative agent of COVID-19) which makes the host infectious about two days before the manifestation of symptoms. ( https://www.nature.com/articles/s41591 -020-0869-5)

[0005] The price of a test, the requirement of trained professionals to extract viral material from people, the time required for RT-PCR test, and time required for analysis of results do not qualify above methods as practical methods to screen large number of people within a short period of time. To put things into perspective, during the COVID- 19 pandemic the U.S. was slower than other countries to take up COVID-19 testing. The U.S. was administering far fewer tests than many European and some Asian countries.

As a result, the U.S experienced a large number of deaths and big set backs to the country’s economy. However, countries that implemented more testing and maintained much higher ratio of negative to positive COVID-19 tests results achieved some success in containing the virus. Further to this point Nguyen et. al. through analysis of current and passed data has shown that a point-of-care (PoC) device is required to contain an outbreak like COVID-19. Additionally, they argued that such a device should be, a rapid, robust, and cost-efficient, and does not necessarily require a framed technician to operate the device. In addition to the above features of rapid, robust, cost-efficient, and no need of trained technicians, such a devise should also be a high throughput devise to screen a large number of people in short time. Also, the cost per test should be in cents rather than in dollars.

[0006] Out of the six pandemics in the last 102 years, five of them are respiratory illnesses: Spanish Flu; 1918-1920 (H1N1 virus), Asian Flu; 1957-1958 (H2-N2 virus), 1968 Pandemic (H3-N2 virus), H1N1 Swine Flu pandemic: 2009-2010

(https://www.cdc.gov/flu/pandemic-resources/1918-pandemic-h1n1.html) and the COVID-19 pandemic. Also, there have been two respiratory illnesses epidemics: Middle East respiratory syndrome coronavirus (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS) in the last two decades. The respiratory illness causing viruses are present in saliva when people are infected with those viruses. Several studies have shown that saliva samples are a source to detect respiratory illness causing viruses in humans (Y asuo Suda et al. Biotechnol Rep 2015, Robinson et.al., Clinical Infectious Diseases, 2008). Recently, the FDA authorized the first molecular test that uses saliva (instead of deep nose or throat swabs) to detect COVID-19, developed by Rutgers’ RUCDR Infinite Biologies. These at-home saliva collection tests are as accurate as the swab-based tests and patients just need to spit into a collection device. However, this new saliva-based test through Rutgers can only deliver results in 24 to 48 hours

(https://www.goodrx.com/blog/coronavirus-covid-19-testing-updates-methods-cost- availability/) (https://www.rutgers.edu/news/fda-approves-first-home-saliva-collection- test-coronaviruest).

SUMMARY

[0007] An imaging system and process are provided for rapid screening and detection of particles, including for example, viruses and bacteria. The process may be utilized as a high through put screening to very rapidly identify the presence of viruses in large numbers of samples. Samples which are identified to include viruses can be further analyzed quickly to identify specific virus types which are present. The process is not a molecular or serological (antibody) test, but instead utilizes one or more viral properties such as size, shape, and isoelectric point for identification of a virus in a sample.

[0008] In one aspect, an imaging system includes a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip. The photonic chip or spatial light modulator is provided with a beam of light having a wavelength of less than 1000 nm. The spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 1000 nm onto a field of observation containing objects of interest to obtain an image of that object at a resolution of one fourth or lower than one fourth the size of the wavelength of the input light beam. The wavelength of light is the same throughout the entire apparatus. An image acquisition speed of greater than 1 kHz is possible.

[0009] In another aspect, a detection process comprising analyzing a solution with an imaging system, the imaging system comprising a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip. The photonic chip or spatial light modulator is provided with a beam of light having a wavelength of less than 1000 nm. The spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 1000 nm onto a field of observation containing objects of interest to obtain an image of that object at a resolution of one fourth or lower than one fourth the size of the wavelength of the input light beam. The wavelength of light is the same throughout the entire apparatus.

[0010] In another aspect, a viral detection process comprising analyzing a sample in an imaging system, the imaging system comprising a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip. The photonic chip or spatial light modulator is provided with a beam of light having a wavelength of less than 1000 nm. The spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 1000 nm onto a field of observation containing objects of interest to obtain an image of that object at a resolution of one fourth or lower than one fourth the size of the wavelength of the input light beam. The wavelength of light is the same throughout the entire apparatus.

[0011] In this aspect, a viral detection process includes analyzing a sample in a detection system effective for determining virus shapes and sizes. In some aspects of the detection system in addition to shapes and sizes also use variation of surface structures and variation of morphology in its population (PASS value). In another aspect, a viral detection process includes filtering an aqueous sample to remove particles outside of a target size range to provide a virus containing solution; and analyzing the virus containing solution in a detection system effective for determining virus shapes and sizes.

[0012] In another aspect, a viral detection process includes selecting one or more viruses from a sample based on an isoelectric point to provide a virus containing solution with a pH in a range of an isoelectric point of a targeted virus; and analyzing the virus containing solution in a detection system effective for determining virus shapes and sizes.

[0013] In another aspect, a viral detection process includes filtering an aqueous sample to remove particles outside of a target size range; selecting one or more viruses from the filtered aqueous sample, wherein the virus has an isoelectric point in a target isoelectric point range to provide a virus containing solution; and analyzing the virus containing solution in a detection system effective for determining virus shapes and sizes.

[0014] In another aspect, a viral detection system includes analyzing a sample in a detection system effective for determining virus shapes and sizes. If analyzing the sample indicates that virus is present in the sample the process further includes at least one of the steps of: filtering to remove particles outside of a target size range, and selecting one or more viruses from a sample based on an isoelectric point to provide a virus containing solution with a pH in a range of an isoelectric point of a targeted virus. The virus containing solution that has been filtered and/or selected by isoelectric point is analyzed in a detection system effective for determining virus shapes and sizes and PASS value. BRIEF DESCRIPTION OF FIGURES

[0015] So that the maimer in which the above recited features of the present disclosure can be understood in detail, a more particular description of the disclosure, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this disclosure and are therefore not to be considered limiting of its scope, for the disclosure may admit to other equally effective embodiments.

[0016] Figures 1a,1b and 1c illustrate an integrated photonic coherent scattering microscope.

[0017] Figure 2 provides a general overview of various aspects of the viral detection system.

[0018] Figure 3 illustrates different viral sizes and shapes. Adapted from: https://bio.libretexts,org/ Bookshelves/Microbiology/Book%3A Microbiology (Kalser)/Unit 4%3

A Eukaryotic Microorganisms and Viruses/10%3A Viruses/10.02%3A Size and Shapes of Vi ruses

[0019] Figures 4A-K depict various types of viruses (see below examples of size and shape section for source references) .

[0020] Figure 5 shows various types of membranes which can be utilized. (Adopted from https://www.membracon.co.uk/biog/whats-the-difference-between -microfiltration- uitrafiltration-and-nanofiltration/)

[0021] Figure 6 describes an isoelectric point focusing system. [0022] Figure 7 illustrates a more detailed example of detection of a virus in saliva.

[0023] Figure 8 illustrates a nanoparticle imaging system and slide.

[0024] Figure 9 shows an aspect of a slide and imaging device.

DETAILED DESCRIPTION

[0025] The following description is not to be taken in a limiting sense, but is made merely for the purpose of describing the general principles of exemplary embodiments. The scope of the disclosure should be determined with reference to the claims.

Imaging System

[0026] In one aspect, an imaging system includes a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip. The photonic chip is configured to provide a beam of light having a wavelength of less than 1000 nm to the spatial light modulator or photonic chip. The spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 250 nm into the microscope. In this aspect, the wavelength of light to the microscope is the same as what the photonic chip or spatial light modulator is providing. The wavelength of light is the same throughout the entire apparatus.

[0027] The imaging system may further incudes an image acquisition device, such as for example a camera. The imaging system may also include and image analysis system configured for analyzing images provided by the image acquisition device.

[0028] Figures 1a, 1b and 1c illustrate one aspect of an integrated photonic coherent scattering microscope. An aluminum nitride (AIN) integrated photonic chip 110 splits a 300 to 400 nm continuous-wave pump laser 120 into an array of 2N coherent beams using a series of multimode interference beam splitters, GHz electro-optical amplitude- modulators, and grating output couplers (N- 4 shown for simplicity). The beams from combination of outputs B_N- to B_N+ can modulated with high on/off ratios. The output beams from the chip are sent through a dark-field optical microscope to coherently excite the sample. Scattered light is imaged with high suppression of the laser light with dark- field imaging. A high-speed CCD camera enables > 1 MHz frame rate. FP: Focal plane; CP: Collimated plane.

[0029] A super resolution imaging system as described can resolve two or more objects that are separated by a less than the Abbe diffraction limit of d < λ/2.8 using oblique illumination where λ is the illumination wavelength. As shown in Figure la, a collimated laser beam illuminates a sample on a microscope slide at an oblique incident angle. In this aspect, the system utilizes a single-wavelength laser beam that can be tuned throughout the ultraviolet (UV) and visible wavelength regimes. The laser beam is collimated and incident on the slide after passing through a beam splitter. Due to total internal reflection of the laser at the top surface of the slide, the coherent laser field does not propagate to the objects residing on the top surface of the slide. The slide may be made of material transparent to the UV and visible wavelengths. Some examples of suitable material include sapphire, fused silica, and BK7.

[0030] As further illustrated in Figure 1 a, the reflected laser beam propagates back through the microscope assembly and is blocked from reaching a CCD camera by a dark- field diaphragm. However, at the top surface of the slide, the evanescent field from the laser propagates to the sample residing on the surface of the slide. Light from the evanescent field is scattered by the sample (Figure 1b) and takes a slightly different path through the imaging optics such that it is not blocked by the dark-field diaphragm and can be imaged by the CCD camera. In this way, the sample can be imaged while suppressing the illumination laser light. A single CCD image frame is acquired while the laser beam azimuthal angle is scanned a full 2π radians about the normal axis of the microscope slide. Super-resolution is achieved through interference between the optical fields scattered at different laser beam azimuthal angles, resulting in a high-resolution image. Two such angles are shown in Figure 1a. The ~100 nm propagation depth of the evanescent field also suppresses any background scattered light from other parts of the sample or microscope slide along the direction normal to the slide, enabling a sub-100 nm depth of field for imaging.

[0031] Traditionally, super-resolution microscopy techniques require either fluorescent labeling of the samples to suppress the illumination light using optical filters, or they use coherent scattering techniques with physical raster scanning of the illumination laser or the sample microscope slide to achieve multiple angles, which limits the acquisition speed to < 100 Hz. The system described herein provides a method for high-speed > 1 kHz super-resolution microscopy using the combination of a coherent dark-field optical microscope system and may include a spatial light modulator (SLM) instead of a photonic chip. The herein SLM operate to rapidly sweep the direction and angle of the input optical beam into the microscope, as shown in Figure lc. In this embodiment, the output from a single 400 nm wavelength continuous-wave laser is incidence on the SLM in reflection geometry. The SLM is full programmable to efficiently diffract the laser beam into different azimuthal directions with up to a 1 kHz clock speed. Using a high- speed CCD that is synchronized to SLM laser beam sweep rate, images can be acquired at > 1 kHz clock rate. All components are commercially available.

[0032] The photonic chip is fabricated with the following procedure. A single-crystalline AIN thin film of ~500 nm thickness is grown on a c-axis sapphire or silicon dioxide on silicon substrate by metal-organic chemical vapor deposition. The photonic waveguides, grating output coupler, and electro-optical modulator sections are defined using 100 kV electron-beam lithography (EBL) and negative EBL resist plus a thin charge-dissipation layer. The EBL resist is developed and the photonic layer pattern is transferred to the AIN layer by chlorine-based inductively coupled plasma dry etching. Next is the deposition of a thin SiO₂ film by plasma-enhanced chemical vapor deposition to serve as the AIN photonic waveguide cladding layer. The final step is photolithography followed by metal deposition and lift-off to create the electrodes for the modulator sections. [0033] The system described herein is capable of distinguishing between various objects on the glass slide through their unique fingerprints related to their spatial size. Moreover, the system is capable of examining the distinguishing features through optical polarization and the object fluorescence spectrum by adding in modular optical polarizers and a spectrometer before the CCD camera. For spatial imaging of the scattered light, the population density of the various objects on the glass slide can be determined by analyzing and correlating the CCD camera image intensity to the spatial size. Such a system can be applied to sub-diffraction imaging of various nanoscale systems provided they can be isolated and confined to within ~100 nm on the surface of the glass slide.

Detection Process

[0034] The present process is not a molecular or serological method. Instead, this process uses physical properties of a virus for its detection. Physical properties utilized may include size, shape and the iso-electric point of a given virus. The sizes of viruses vary from 10 nm to 400 nm (Hans R. Gelderblom 1996). Different families of viruses have different shapes (see below). Iso-electric point of a virus depend on the amino acid composition of the outer layer of the given virus (see below). Any one of the above or two of the above or all them in combination can be employed to detect the virus of interest or at least the presence or absence of any virus in saliva, blood, urine, feces, phlegm, mucous, spinal fluid, gastric fluids, surface swabs, and municipal sewage effluent

[0035] A general overview of the process is provided in Figure 2. In this aspect, a sample or multiple samples may be rapidly screened with a light/laser detection system to determine if that sample contains any type virus. If no virus is present in the sample, nothing further needs to be done. If the initial screening identifies that a virus is present in the sample, then further analysis can be conducted. The sample may be subjected to known molecular or serological tests or may be further analyzed as shown in Figure 2.

[0036] As further illustrated in Figure 2, samples that test positive for the presence of virus may be subjected to optional dilution and filtration, followed by viral detection; isoelectric focusing, followed by viral detection; or a combination of optional dilution and filtration and isoelectric focusing, followed by viral detection. In this aspect, and depending on sample properties, the sample may be diluted and/or filtered to remove particles outside of a target size range for a virus of interest. The filtered sample may then be subjected to isoelectric focusing to select one or more viruses from the sample having an isoelectric point in a target isoelectric point range to provide a virus containing solution. The virus containing solution may be further analyzed using known molecular or serological tests or further analyzed using a light/laser detection system effective for determining virus shapes and sizes.

Virus Types

[0037] In one aspect, the current process is effective for detecting viruses that cause respiratory viral infections. Respiratory viral infections commonly affect the upper or lower respiratory tract. Although respiratory infections can be classified by the causative virus (eg, influenza), they are generally classified clinically according to syndrome (eg, the common cold, bronchiolitis, croup, pneumonia). Although specific pathogens commonly cause characteristic clinical manifestations (eg, rhinovirus typically causes the common cold, respiratory syncytial virus [RSV] typically causes bronchiolitis), each can cause many of the viral respiratory syndromes (see Table herein). As the respiratory viral infections are causing all but one pandemic in last 102 years and viruses are present in saliva during the respiratory infections the process focuses more on detection of respiratory viruses. However, this process can also be employed to detect other viruses that causes non-respiratory infections, such as for example HIV (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7167023/).

[0038] Adopted from: https://www.merckmanuals.com/professional/infectious- diseases/respiratory-viruses/overview-of-viral-respiratory-infections *In humans, Coronavirus can cause mild infection in the upper respiratory tract, like the common cold, but also more serious lower respiratory tract infections. These infections can manifest as bronchitis, pneumonia, or a severe respiratory illness, such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), or coronavirus disease 19 (COVID-19). https://www.medicalnewstoday.com/articles/how- do-sars-and-mers-compare-with-covid-19

Virus Sizes and Shapes

[0039] Viruses have distinctive size ranges and shapes. In one aspect, the current process utilizes differences of size and shape in identifying a virus present in a biological fluid. Viruses are usually much smaller than bacteria with the vast majority being submicroscopic. Most viruses range in size from 10 to 300 nanometers (nm). Different viral sizes and shapes are illustrated in Figure 3.

[0040] Examples of size and shapes (morphology) of respiratory viruses is as follows:

Sample Collection

[0041] The process primarily focuses on screening a large number of people in short period of time with a cost of less than a US $1 per test Utilization of the process does not require extensive training or a science graduate to operate this high throughput screening process. This process will at least function as a first line of screening of people harboring viruses causing respiratory diseases. As a first line of screening device it will have 90% or more accuracy in detecting a virus in human biological samples. Particularly this will be a device that countries can employ to prevent a spread of a virus into the country from another country. For example, when the country A is experiencing an epidemic or something suspected to be an epidemic country B can employ this instrument to screen all the passengers coming into country B from Country A or from selected countries or from rest of the world. This device will screen the passengers at the site of the embarkation before they embark on the journey to Country B. For example, if the passengers are flying into the country B they can be screened at the gate to the air plane by collecting a saliva sample. A vial pre-labeled with a number is delivered to the passenger with the boarding pass, the passenger spit into the vial, close the cap and place it into a carousel. Once the number of vials in the carousel reached a certain number (for example 100) the carousal is placed into the device, then the device will detect the presence or absence of the virus of interest or any virus in saliva. Also, the devise will scan the vial number of each vial. Once the detection of viruses in all the vials are completed the device will generate a report showing the individuals who are infected with the virus of interest or any virus. The devise will be able to corelate the number of each vial with its owner by accessing airline database of passenger’s name vs the given vial number. At this point passengers can be denied entry into the airplane and direct them to medical authorities.

[0042] For a mass scale high throughput screening to be effective the sample collections from individuals must be non-invasive and should not require trained personnel to extract samples. Additionally, if sample collectors are exposed to the risk of contracting the diseases, the whole process of screening or the detection time can become too long to be employed as a mass scale high throughput screening method. Also, the number of tests that can be done per a unit time will depend on the number of trained personnel available for sample extraction. Therefore, self-extraction of samples is a preferred method for a mass scale high throughput screening system.

[0043] Examples of samples include samples selected from the group consisting of saliva, blood, urine, feces, phlegm, mucous, spinal fluid, gastric fluids, surface swabs, and municipal sewage effluent.

Filtering of Biological Fluid

[0044] Once the aqueous biological fluid sample is collected, sample may be diluted if necessary. (Necessity of dilution depend on the noise to signal ratio and the clarity of the signal. For example, if there are too many contaminating particles, viruses or even the virus of interest (too concentrated to measure) are present to impede the clarity of the final detection-signal a dilution step before the filtration is desirable. Diluted or undiluted sample are filtered to remove particles through for example using a 0.45 um (450 nm) pore size filter. This filtration will remove large percentage of particles which are bigger than 450 nm (length, diameter, width, or height) in size. Filtrate of the above filtration is then filtered through a filter which has pore size smaller than 0.05 um (50 nm) and pore size bigger than 0.01 um (10 nm), the retentate of which is recovered using a saline solution or water.

[0045] In another aspect, the filtration steps above can be customized to suite the virus and the situation. For example, if the average size of the virus of interest is 120 nm (diameter/length) the filter with average pore size of 150 nm can be chosen for the first filtration and the filter with the pore size of 90 nm can be chosen for the second filtration. By using a narrow range of 60 nm between the two filtration steps, other non-viral particles or contaminating viral particles can be excluded before the measurement of size or the shape or both. Figure 5 illustrates types of membranes that may be used for filtration.

Selection Using Isoelectric Points

[0046] In one aspect, the process includes selecting one or more viruses from the filtered aqueous biological sample having an isoelectric point in a target isoelectric point range to provide a virus containing solution.

[0047] Viruses as well as other (bio-)colloids possess a pH-dependent surface charge in polar media such as water. This electrostatic charge determines the mobility of these particle in an electric field. The pH value at which the net surface charge switches its sign is referred to as the isoelectric point (IEP) and is a characteristic parameter of the virion in equilibrium with its environmental water chemistry. A review by Michen and Graule 2009 has shown that IEP of viruses are in the pH range of 1.9 to 8.4; most frequently, they are measured in a band of 3.5 < IEP < 7. Most notably the same review has shown the variability of IEP’s of different strains of the same species of a virus (see table below) (Michen and Graule 2009). Also Kang and Cannon 2015 demonstrated the ability to separate virus particles based on their IEP using an electric field. Additionally, Mi et.al., 2019 has used chemical force microscopy to measure the IEP of single virus particles. This method will facilitate the comparison of IEPs of different viruses or even among the subpopulation of the same virus. Because the fact that different strains of the same virus species have different IEPs, using IEP to distinguish viruses will increase the specificity of the diagnosis.

[0048] One aspect of the IEP selection process is illustrated in Figure 6. Virus particles that are in a pH region below its isoelectric point (IEP) will be positively charged and so will migrate toward the cathode (negatively charged electrode), similarly virus particles with IEPs below the pH region it is in will be negatively charged and so will migrate towards the anode. Therefore, this property of viruses can be used to separate viruses of known IEP.

[0049] In one example illustrated in Figure 6, if the IEP of the virus of interest is pH 5 the virus suspension is injected into the chamber C1 containing a buffer of pH 4.5 and then open the valve V1. All the virus particles with IEP below 4,5, which are negatively charged, will migrate towards the anode while all the virus particles with IEP above pH 4.5, which are positively charged, will migrate towards the cathode. Once the first step of IEP based virus particles separation is completed, valve V1 is closed and valve V2 is opened connecting the chambers C2 and C3. Then tile pH of the buffer in chamber C1+C3 is adjusted to pH 5.5 and the electric field switches so that the cathode of the C1+C2 becomes the anode of the chambers C1+C3. All the virus particles with IEP above 5.5 will migrate towards the cathode. Once the second step of IEP based virus particles separation is completed, valve V2 closes, the electrical field is switched off and the virus suspension in the chamber C1 is recovered. The recovered virus suspension contains only the virus(es)) with IEP/s in the range of 4.5 to 5.5. Depending on the situations, this IEP range can be narrowed to smaller range and increase the specificity of the virus selection. The whole above procedure can be automated using an algorithm (computer software), pH sensors, standard cleaning in place (CIP) methods (between tests) and various other components/methods use in robotic machines handling fluids and electric fields.

Viral Texture and Diversity

[0050] As shown in the figure 4 and described herein (Examples of size and shapes of respiratory viruses) morphology of virus particles in a given population is not always uniform. Pleomorphism (term used in histology and cytopathology to describe variability in the size, shape) do exist in a viral population. Also, some viruses have distinctive surface structure variations. For example, a corona virus with a diameter of 120 nm can have a 20nm long protein spike on its outer surface.

(https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7152864/#:~:text⁼As%20known%2C% 20coronavirus%20virions%20are,crown%20or%20the%20solar%20corona.). Obviously light/laser scattering or absorption by virus particles is affected by the surface structure of a virus. Also, through the measurement of size and shape the degree of pleomorphism of a given viral population can also be measured. The degree of pleomorphism in a viral population is different from virus to virus. Also, the surface structure is different from virus to virus. Therefor the degree of pleomorphism of a virus in its population and the surface structure variations measured by the light/laser detection system will be used to develop a unique signature value for each virus. For example, viruses with a smooth surface structure and no pleomorphism will have a zero or close to zero (positive) value while viruses with higher degree of pleomorphism and distinctive surface structures will have a higher value. Measurement of the above Pleomorphic And Surface Structure (PASS) value in addition to the size and shape measurements increases the detection specificity of a virus. Through research and development, a database will be developed to assign a PASS value for each virus of clinical importance.

[0051] In one aspect, a viral suspension is transferred to a cuvette or vial that allow light or laser to travel through it. The cuvette/vial containing the viral suspension is place in the path of either light or laser. Light beam or the laser beam traveling through the cuvette or the vial containing the viral suspension is received by a light or a laser detector. Based on the absorption/scattering/reflection of light or laser the detector will generate a signal.

[0052] The imaging system may include an artificial intelligence based imaging analysis system that includes machine learning algorithms commonly known as convolutional neural networks configured to analyze images provided by the image acquisition device. The signal will be analyzed and interpreted by computer software to identify the signature of the virus. As shown above each virus has unique appearance based on its size, shape, surface structures, and the degree of variation of its morphology in the population. Computer programs are used to develop unique signature for each virus strains based on the above properties of a virus. In one aspect, size, shape variation of surface structures and variation of morphology in its population is measured by a particle detector.

[0053] Additionally, computer programs can be employed to ignore the contaminating particles. For example, a control sample carrying the particulate materials of a typical human saliva is subjected to the same procedures as of the sample containing the saliva of a person being tested. The measurements (i.e size and shape) of the particulate materials in the test sample can be subtracted from the measurements of the particulate materials in the control sample. Also, a data base of particulate material in saliva of people who are not infected with a virus can be generated. These computer programs can select the information of particles in each size range from these data bases. For example, number of particles and their shapes in the size range of 90 to 150 nm. This information of particles, if present, will be subtracted from the information of particles, if present, in the test sample. Using above filtration methods, particle detection methods and computer programs, the viral particles can be identified in a test sample. The presence or absence of such particles can be used as a positive or negative test for a viral infection. Additionally, depending on the situation for example if mouth can be washed before sample collection oar computer programs are developed to ignore particles smaller than viruses (less than 10 nm) or detectors are developed so that the detection of virus particles are not interfered by the particles smaller than virus particles the above second filtration step to exclude particles smaller than viruses can be excluded from the detection procedure. Similarly, that once the computer programs and detectors are further developed virus in saliva can be detected without any filtration steps.

[0054] Similarly, the specificity of virus detections can be further improved by adding another selection step before the size or shape or both are measured. For example, as described above depending on the composition of the outer protein-envelope of a virus, it can have different iso-electric points (IEP). Different strains of viruses even within the same species can have different lEPs. This physical property can be employed to differentiate viruses from other contaminating viruses or interfering particles in the saliva samples. Far example, viruses or other particles with IEP’s outside the range of the IEP of the virus of the interest can be removed from the test sample. Therefore by employing two filtration steps, selection based on IEP of a given virus, particle detection using laser or light sources combined with light/laser detectors (particle detectors), computer programs to refine and interpret the detector signal, a virus of interest can be identified. Depending on the virus and the situation all the above steps or only some of the above steps can be used. Also, all the above steps can be automated starting from the sample injection into the first filtration step to the generation of the presence or absence of a virus or the virus of interest report. Additionally, many test units can be installed into one instrument so that it can be automated to test many saliva samples at the same time. For example, if one instrument can measure 100 samples at a time, it will be able to test more than 25,000 individuals per day (at 5 minutes per test). Therefore, 10 of these instruments can scan the whole population of a city like San Francisco within 4 days and identify all the people infected with the virus of interest or at least with a virus to take measures to isolate those individuals from the general population.

[0055] A more detailed example of detection of a virus is illustrated in Figure 7.

EXAMPLES

[0056] Commercial solutions to detect viruses: using a nano particle imaging device and separation methods (based on physicochemical properties of virus particles)

[0057] Number of viruses in different solutions with commercial application

[0058] Physicochemical methods to separate and concentrate virus particles from complex solutions

[0059] Filtration to concentrate and separate based on size range of virus particles: Example 1

[0060] Virus particles will be separated/concentrated from particles which are smaller than virus particles by filtering out the smaller particles by using (retentive) filters of pore size 10 nm or smaller or 20 nm or smaller.

Example 2 [0061] Virus particles will be separated/concentrated from particles which are bigger than virus particles by filtering out and collecting virus particles by using filters of pore size 400 nm or bigger or 500 nm or bigger.

Example 3

[0062] Virus particle of interest will be separated/concentrated from particles which are bigger and smaller than the virus particle of interest by filtering with filters having pore sizes bigger and smaller than the virus particle of interest

Example 4

[0063] Virus particle of interest will be separated/concentrated from particles which have different surface hydrophobicity by using membranes with appropriate surface hydrophobicity. Affinity (binding) or repulsion (elution) of virus particles from a given membrane depends on the hydrophobicity/hydrophilicity of the membrane. Optionally the virus particle of interest will be separated/concentrated from other particles using specific affinity ligands/markers.

Example 5

[0064] Virus particle of interest will be separated/ concentrated from particles which have different isoelectric point by using buffers with different pH values and an electric potential with an anode/cathode system. Above methods individually or in combination can be used to separate virus particles. Above methods individually or in combination can be used to concentrate virus particles from 10 fold to 10,000 fold.

Example 6: Nano particle imaging devise to detect viruses [0065] Optionally the surface of the well of the slide in Figure 8 can be coated with a molecule or a material or a protein that can specifically bind a virus of interest: for example, the well can be coated with antibodies to capture/bind a virus of interest.

[0066] Optionally the slide in Figure 8 can have 1 to 10⁷ wells with the dimensions (diameter or length/width) in micrometer scale (shown in Figure 9A). The slide can be flooded with a solution containing virus particles so that virus particles will fall into wells or wells in the slide can be loaded with a robotic microfluidics pipette.

[0067] Optionally the virus can be attached with an excitable chromophore with a specific wavelength. This can be done by flooding the slide with the above chromophore or individually loading the chromophore to each well using a robotic/automated pipette. In this scenario the virus can be either bound to an antibody coated to the surface of the well or free floating. Once the chromophore is attached above mentioned nano particle imaging/detecting device can be utilized to detect/image the virus by exciting the attached chromophore using the specific wavelength.

[0068] Optionally the slide in Figure 8 can be disposable under all the above combinations. Optionally instead of a slide microfluidics channel can be used to detect/image viruses using the above nano particle imaging/detection device. In this scenario sample can be pumped through a nano/micro tube/channel as shown in the below diagram. In some instances, this system can be used to separate virus particles into a different zone/area using this system of microfluidic channel/tube system This may be achieved by directing the fluid to an alternative path or coating the walls of the flow path to adsorb virus particles. All of the method used to separate virus particles (filtration, hydrophobicity, isoelectric point) may be used to steer virus particles into a specific flow path.

[0069] As further illustrated in Figure 9, by having a moving slide with n number of wells and having n number of detection devices (as shown in the below figure) can increases the level of detection of viruses per unit time in a given sample.

[0070] For example, if the detection device comprises of 100 detection units and a slide with 100,000 to 200,000 wells (slide per each detection unit), with the aid of virus concentration using physicochemical methods (mentioned above) this device is capable of detecting a virus particle per 100 ml within 1 to 3 seconds. [0071] Example 7: Nano particle Imaging devise to identify bacteria: Nano particle imaging device is used to visualize morphological features such as inclusion bodies, vesicles, flagella, appendages, cell envelop pigmentation, cell envelop imperfections and etc that are non-visible as well as visible under a light microscope with magnification up to 1500 times to identify bacteria.

[0001] Example 8: Nano particle Imaging devise to identify eucaryotic cells: Nano particle imaging device is used to visualize morphological features such as inclusion bodies, vesicles, flagella, appendages, cell envelop pigmentation, cell envelop imperfections and etc that are non- visible as well as visible under a light microscope with magnification up to 1500 times to identify eucaryotic cells such as yeast

[0002] While the disclosure herein disclosed has been described by means of specific embodiments, examples and applications thereof numerous modifications and variations could be made thereto by those skilled in the art without departing from the scope of the disclosure set forth in the claims.

Claims

What is claimed is:

1. An imaging system comprising: a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip, wherein the photonic chip or spatial light modulator is provided with a beam of light having a wavelength of less than 1000, wherein the spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 1000 nm onto a field of observation containing objects of interest to obtain an image of that object at a resolution of one fourth or lower than one fourth the size of the wavelength of the input light beam.

2. The imaging system of claim 1 wherein the photonic chip is an integrated photonic directional beam array chip.

3. The imaging system of claim 1 further comprising an image acquisition device.

4. The imaging system of claim 3 wherein the image acquisition device is a camera.

5. The imaging system of claim 1 wherein the system can acquire images at a speed greater than about 1kHz.

6. The imaging system of claim 3 further comprises an artificial intelligence based imaging analysis system that includes machine learning algorithms (convolutional neural networks) configured to analyze images provided by the image acquisition device.

7. A detection process comprising analyzing a solution with an imaging system, the imaging system comprising a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip, wherein the photonic chip or spatial light modulator is provided with a beam of light having a wavelength of less than 1000, wherein the spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 1000 nm onto a field of observation containing objects of interest to obtain an image of that object at a resolution of one fourth or lower than one fourth the size of the wavelength of the input light beam.

8. The detection process of claim 7 wherein the solution includes particles selected from the group consisting of microbes, viruses, solid particles and mixtures thereof.

9. The detection process of claim 7 wherein the solution is an aqueous solution and the aqueous solution is filtered prior to analysis to remove particles outside of a target size range

10. The detection process of claim 7 wherein the solution is an aqueous solution and the aqueous solution is subjected to isoelectric focusing prior to analysis to provide a solution having particles in a target isoelectric point range.

11. The detection process of claim 7 wherein images from the imaging system are acquired by an image acquisition device.

12. The detection process of claim 10 wherein images acquired by the image acquisition device are analyzed by an artificial intelligence based imaging analysis system that includes machine learning algorithms (convolutional neural networks) configured to analyze images provided by the image acquisition device.

13. A viral detection process comprising analyzing a sample in an imaging system, the imaging system comprising a coherent dark-field optical microscope; and a spatial light modulator, or a photonic chip, wherein the photonic chip or spatial light modulator is provided with a beam of light having a wavelength of less than 1000, wherein the spatial light modulator or photonic chip is configured to input an optical beam of light having a wavelength of less than 1000 nm onto a field of observation containing objects of interest to obtain an image of that object at a resolution of one fourth or lower than one fourth the size of the wavelength of the input light beam.

14. The viral detection process of claim 13 wherein the photonic chip is an integrated photonic directional beam array chip.

15. The viral detection process of claim 13 further comprising an image acquisition device.

16. The viral detection process of claim 15 wherein the image acquisition device is a camera.

17. The viral detection process of claim 15 wherein images acquired by the image acquisition device are analyzed by an artificial intelligence based imaging analysis system that includes machine learning algorithms (convolutional neural networks) configured to analyze images provided by the image acquisition device.

18. The viral detection process of claim 13 wherein the sample is selected from the group consisting of saliva, blood, urine, feces, phlegm, mucous, spinal fluid, gastric fluids, surface swabs, and municipal sewage effluent.

19. The viral detection process of claim 18 wherein the sample is an aqueous solution and the aqueous solution is filtered prior to analysis to remove particles outside of a target size range

20. The detection process of claim 18 wherein the sample is an aqueous solution and the aqueous solution is subjected to isoelectric focusing prior to analysis to provide a virus containing solution having a target isoelectric point range.