Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
  • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
  • G01N33/483—Physical analysis of biological material
  • G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/08—Measuring devices for evaluating the respiratory organs
  • A61B5/082—Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
  • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
  • G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
  • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
  • G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
  • G01N27/12—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body in dependence upon absorption of a fluid; of a solid body in dependence upon reaction with a fluid, for detecting components in the fluid
  • G01N27/125—Composition of the body, e.g. the composition of its sensitive layer
  • G01N27/127—Composition of the body, e.g. the composition of its sensitive layer comprising nanoparticles
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
  • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
  • G01N27/22—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
  • G01N27/26—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
  • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
  • G01N33/483—Physical analysis of biological material
  • G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
  • G01N33/4975—Physical analysis of biological material of gaseous biological material, e.g. breath other than oxygen, carbon dioxide or alcohol, e.g. organic vapours
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
  • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
  • G01N27/22—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance
  • G01N27/221—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance by investigating the dielectric properties
  • G01N2027/222—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance by investigating the dielectric properties for analysing gases
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
  • G01N2333/195—Assays involving biological materials from specific organisms or of a specific nature from bacteria
  • G01N2333/35—Assays involving biological materials from specific organisms or of a specific nature from bacteria from Mycobacteriaceae (F)
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N2800/00—Detection or diagnosis of diseases
  • G01N2800/12—Pulmonary diseases
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
  • G01N2800/00—Detection or diagnosis of diseases
  • G01N2800/26—Infectious diseases, e.g. generalised sepsis

Definitions

• the present invention relates to sensor technology for diagnosing tuberculosis caused by M. tuberculosis bacteria. BACKGROUND OF THE INVENTION
• Tuberculosis is a common infectious disease caused by mycobacterium, mainly M. tuberculosis. It usually attacks the lungs (as pulmonary TB) but can also affect the central nervous system, the lymphatic system, the circulatory system, the genitourinary system, the gastrointestinal system, bones, joints, and even the skin. TB is easily spread by airborne transmission of small droplets. Over 90% of the annual new TB cases and deaths occur in resource -poor and developing countries.
• Sputum smear microscopy is the standard diagnostic method used for diagnosing TB. This method is more than 100 years old and fails to detect more than half of all active cases (Lalvani et al., Br. Med. Bull. 93, 69-84 (2010)).
• the interpretation of the tuberculin skin test relies on individual epidemiological risk factors of infection. This test therefore tends to be inaccurate under certain biological conditions and is incapable of distinguishing between latent TB and active TB infection. Additionally, it is labor-intensive for the patient as well as the health-care provider.
• Another diagnostic test for TB includes acid-fast bacilli staining of sputum sample. However, this test does not distinguish M. tuberculosis from non-tuberculosis mycobacteria and it requires an additional positive smear culture after 8 weeks for definitive diagnosis of pulmonary TB.
• NAATs Nucleic acid amplification tests
• M. tuberculosis in respiratory system within 2-7 hours
• interferon ⁇ release assay are two of the more recently developed methods for TB diagnosis. These methods are considered to be more rapid, accurate and sensitive.
• the equipment used in these methods is expensive and it requires technical expertise and/or the testing requires the use of radioactive materials and their disposals.
• the current diagnostic techniques are either inaccurate and time consuming, or are expensive and demand highly sophisticated laboratories which are not available in resource-poor and developing countries.
• VOCs Volatile Organic Compounds
• the diagnosis of infectious diseases by detecting VOCs that are emitted from infected cells and/or the surrounding microenvironment has been performed.
• the diagnosis is based on the following principles of cell biology.
• the cell membrane of bacteria consists primarily of amphipathic phospholipids, carbohydrates and many integral membrane proteins that are distinct for different cell types.
• oxidative stress i.e. a peroxidation of the cell membrane that induces VOCs emission.
• oxidative stress i.e. a peroxidation of the cell membrane that induces VOCs emission. It has been shown that each type of infectious disease is characterized by a unique composition of VOCs (Dummer et al., Trends Anal. Chem., 30, 960-967 (2011)).
• VOCs can be detected from samples of bodily fluids or the headspace of a container containing infected cells and/or tissues or directly from exhaled breath in which disease-related changes are reflected through exchange via the blood or directly via the lung airways (Zhu et al, J. Clic. Microbiol, 48, 4426-4431 (2010); and Naraghi et al, Sens. Actual. B, 146, 521-526 (2010); Abaffy et al, PLOS ONE, 5(11), el3813, doi:10.1371/journal.pone.0013813 (2010); Sahgal et al, Br. J. Dermatol, 155, 1209- 1216 (2006); Turner, Exp. Rev. Mol.
• VOCs identified unique VOCs or a VOC profile in the breath of cattle infected with M. bovis (bovine tuberculosis) using GC-MS analysis.
• the unique profile of VOCs was used to design a nano technology-based array of sensors for detection of M. bovis- infected cattle via breath (Sens. Actuat. B, 171-172, 588-594 (2012); Fig. 11).
• U.S. 2010/0291617 and U.S. 2009/0239252 disclose methods and devices for identifying M. tuberculosis bacteria in a sample comprising the detection of one or more volatile organic compounds indicative of a presence of or response to treatment or resistance of the M. tuberculosis bacteria in the sample.
• U.S. 2010/0137733 discloses a method for detecting whether a subject has tuberculosis or monitoring a tuberculosis subject, said method comprising: contacting breath from said subject with an apparatus, said apparatus having a gas chromatograph, wherein said gas chromatograph is fluidly coupled to a detector array to produce a signal; and analyzing said signal from the detector array to determine whether said subject has tuberculosis.
• U.S. 2007/0062255 discloses an apparatus for collecting and detecting compounds in a human breath sample comprising: a handheld sample collector comprising a sorbent phase; a breath analyzer comprising a thermal desorption column; two or more sensors for detection of breath compounds; and a flow controller for controlling the transfer of breath compounds from the sample collector into the breath analyzer, wherein the handheld sample collector and breath analyzer are configured for fluid communication with each other so that breath compounds from the sample collector can pass into the breath analyzer for detection.
• U.S. 2007/0062255 discloses an apparatus for collecting and detecting compounds in a human breath sample comprising: a handheld sample collector comprising a sorbent phase; a breath analyzer comprising a thermal desorption column; two or more sensors for detection of breath compounds; and a flow controller for controlling the transfer of breath compounds from the sample collector into the breath analyzer, wherein the handheld sample collector and breath analyzer are configured for fluid communication with each other so that breath compounds from the sample collector can pass into the breath analyzer for detection.
• 2004/0127808 discloses a method for assessing a disease in a subject, said method comprising: collecting condensate from a subject's breath, said condensate having an acetic acid or acetate concentration or both an acetic acid and acetate concentration; testing said condensate to determine said acetic acid or acetate concentration or both said acetic acid and acetate concentrations; and evaluating said acetic acid or acetate concentration or both said acetic acid and acetate concentrations to determine the presence, absence or status of a disease in the subject.
• the present invention is directed to a sensor for diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject, the sensor comprising at least one of gold nanoparticles coated with dodecanethiol and single walled carbon nanotubes coated with 2-methyl-2- butene.
• the present invention is further directed to a system comprising a plurality of sensors, a detection means and a pattern recognition analyzer and use thereof for diagnosing tuberculosis caused by M. tuberculosis bacteria in a non-invasive manner.
• the present invention is based in part on the unexpected finding that a single sensor comprising gold nanoparticles coated with dodecanethiol or a single sensor comprising single walled carbon nanotubes coated with 2-methyl-2-butene provide enhanced sensitivity and selectivity for volatile biomarkers which are indicative of the presence of active tuberculosis caused by M. tuberculosis bacteria in a subject.
• the use of a plurality of sensors in conjunction with a pattern recognition algorithm provides the discrimination between TB positive and control populations with sensitivity, specificity and accuracy of over 90% thus offering significant advantages over the hitherto used diagnostic tests.
• the sensitivity, specificity and accuracy are not affected by confounding factors including smoking habits, HIV infection, drug consumption and/or combinations thereof.
• the present invention thus provides a fast and reliable diagnosis of tuberculosis, suitable for population screening.
• the present invention provides a sensor for diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject, the sensor comprising gold nanoparticles coated with dodecanethiol.
• the sensor consists essentially of gold nanoparticles coated with dodecanethiol.
• the gold nanoparticles coated with dodecanethiol are in a configuration selected from ID wires, 2D films, and 3D assemblies. Each possibility represents a separate embodiment of the present invention.
• the gold nanoparticles have a morphology selected from a cubic, a spherical, and a spheroidal morphology. Each possibility represents a separate embodiment of the present invention.
• the gold nanoparticles have diameters ranging from about 3 nanometer to about 5 nanometers.
• the present invention provides a sensor for diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject, the sensor comprising single walled carbon nanotubes coated with 2-methyl-2-butene. In one embodiment, the sensor consists essentially of single walled carbon nanotubes coated with 2-methyl-2-butene.
• the single walled carbon nanotubes coated with 2-methyl-2-butene are organized in a random network configuration.
• the single walled carbon nanotubes have diameters ranging from about 0.9 nanometer to about 5 nanometers, and lengths ranging from about 1 micrometer to about 50 micrometers.
• the senor of the present invention further comprises a substrate and a plurality of electrodes on said substrate.
• the gold nanoparticles coated with dodecanethiol or the single walled carbon nanotubes coated with 2- methyl-2-butene form a conductive path between the electrodes.
• the electrical conductivity between the electrodes changes thereby providing a measurable signal indicative of tuberculosis.
• the senor of the present invention is configured in a form selected from the group consisting of a capacitive sensor, a resistive sensor, a chemiresistive sensor, an impedance sensor, and a field effect transistor sensor. Each possibility represents a separate embodiment of the present invention.
• the sensor is configured as a chemiresistor.
• the senor further comprises a detection means comprising a device for measuring changes in resistance, conductance, alternating current (AC), frequency, capacitance, impedance, inductance, mobility, electrical potential, optical property or voltage threshold.
• a detection means comprising a device for measuring changes in resistance, conductance, alternating current (AC), frequency, capacitance, impedance, inductance, mobility, electrical potential, optical property or voltage threshold.
• AC alternating current
• the present invention provides a sensor for diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject, the sensor consisting essentially of at least one of gold nanoparticles coated with dodecanethiol and single walled carbon nanotubes coated with 2-methyl-2-butene, a substrate, a plurality of electrodes on said substrate, and a detection means.
• the sensor of the present invention is used in conjunction with either one of a breath concentrator and a dehumidifying unit. Each possibility represents a separate embodiment of the present invention
• the senor of the present invention is used in conjunction with either one of a chemiresistor, a chemicapacitor, a quartz crystal microbalance, a bulk acoustic wave (BAW) and a surface acoustic wave (SAW) resonator, an electrochemical cell, a surface plasmon resonance (SPR), and an optical spectroscope.
• a chemiresistor a chemicapacitor
• a quartz crystal microbalance a bulk acoustic wave (BAW) and a surface acoustic wave (SAW) resonator
• BAW bulk acoustic wave
• SAW surface acoustic wave
• electrochemical cell a surface plasmon resonance
• SPR surface plasmon resonance
• optical spectroscope optical spectroscope
• the present invention provides a method of diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject, the method comprising the steps of: (a) providing a sensor comprising gold nanoparticles coated with dodecanethiol; (b) exposing the sensor to a test sample selected from exhaled breath and at least one bodily fluid or secretion of the subject; (c) measuring an electrical signal upon exposure of the sensor to the test sample using a detection means; and (d) diagnosing tuberculosis caused by M. tuberculosis bacteria if the electrical signal is greater than a reference.
• the present invention provides a method of diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject, the method comprising the steps of: (a) providing a sensor comprising single walled carbon nanotubes coated with 2-methy-2-butene; (b) exposing the sensor to a test sample selected from exhaled breath and at least one bodily fluid or secretion of the subject; (c) measuring an electrical signal upon exposure of the sensor to the test sample using a detection means; and (d) diagnosing tuberculosis caused by M. tuberculosis bacteria if the electrical signal is greater than a reference.
• the electrical signal measured upon exposure of the sensor to the test sample is selected from the group consisting of resistance, conductance, alternating current (AC), frequency, capacitance, impedance, inductance, mobility, electrical potential, and voltage threshold.
• AC alternating current
• the electrical signal measured upon exposure of the sensor to the test sample is selected from the group consisting of resistance, conductance, alternating current (AC), frequency, capacitance, impedance, inductance, mobility, electrical potential, and voltage threshold.
• the present invention provides a system comprising a plurality of sensors, for example between 2 and 6 sensors, selected from the group consisting of gold nanoparticles coated with dodecanethiol, single walled carbon nanotubes coated with 2-methy-2-butene, and a combination thereof, and further comprising a detection means and a processing unit comprising a learning and pattern recognition analyzer wherein the learning and pattern recognition analyzer receives sensor signal outputs and compares them to stored data.
• the system comprises two sensors wherein each sensor comprises gold nanoparticles coated with dodecanethiol.
• the system comprises a plurality of sensors comprising at least one sensor comprising gold nanoparticles coated with dodecanethiol and at least one sensor comprising single walled carbon nanotubes coated with 2-methy-2-butene.
• the present invention provides a method of diagnosing tuberculosis caused by M.
• tuberculosis bacteria in a subject comprising the steps of: (a) providing a system comprising a plurality of sensors selected from the group consisting of gold nanoparticles coated with dodecanethiol, single walled carbon nanotubes coated with 2-methy-2-butene, and a combination thereof, and further comprising a detection means and a processing unit comprising a learning and pattern recognition analyzer wherein the learning and pattern recognition analyzer receives sensor signal outputs and compares them to stored data; (b) exposing the sensors to a test sample selected from exhaled breath and at least one bodily fluid or secretion of the subject; (c) measuring a response induced parameter from the sensors upon exposure to the test sample using a detection means to generate a response pattern; and (d) using a pattern recognition algorithm to analyze the response pattern by comparing it to stored data obtained from a control sample whereby significantly different response pattern of the test sample as compared the control sample is indicative of tuberculosis caused by M.
• step (c) comprises measuring a plurality of response induced parameters from the sensors upon exposure to the test sample to generate a plurality of response patterns.
• the step of measuring a plurality of response induced parameters comprises measuring a plurality of electrical signals from the sensors upon exposure to a test sample.
• the step of measuring a plurality of response induced parameters comprises measuring an electrical signal from the sensors upon exposure to a test sample and fitting the electrical signal to a function or a plurality of functions whereby the response induced parameters are selected from function constants, function coefficients, and a combination thereof.
• the step of measuring a plurality of response induced parameters comprises measuring an electrical signal from the sensors upon exposure to a test sample and processing the measured electrical signal followed by the extraction of the plurality of response induced parameters.
• the step of processing the measured electrical signal comprises normalization of the measured electrical signal, calibration of the measured electrical signal or a combination thereof.
• the response induced parameter is selected from the group consisting of steady state normalized response, the time interval for obtaining steady state normalized response, and the time interval for reaching baseline after removal of the test sample. Each possibility represents a separate embodiment of the present invention.
• the response induced parameter is selected from the group consisting of the normalized change of sensor signal at the peak of the exposure, the normalized change of sensor signal at the middle of the exposure, the normalized change of sensor signal at the end of the exposure, and the area under the curve of the sensor signal.
• the response induced parameter is selected from the group consisting of full non steady state response at the beginning of the signal, full non steady state response at the beginning of the signal normalized to baseline, full non steady state response at the middle of the signal, full non steady state response at the middle of the signal normalized to baseline, full steady state response, full steady state response normalized to baseline, area under non steady state response, area under steady state response, the gradient of the response upon exposure to the test sample, the gradient of the response upon removal of the test sample, the time required to reach a certain percentage of the response, such as the time required to reach 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or 100% of the response upon exposure to the test sample, and the time required to reach a certain percentage of the response, such as the time required to reach 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20% or 10% of the response upon removal of the test sample.
• the response induced parameter is selected from the group consisting of full non steady state response at the beginning of the signal, full non steady state response at
• the learning and pattern recognition analyzer comprises at least one algorithm selected from the group consisting of artificial neural network algorithms, principal component analysis (PCA), support vector machine (SVM), multi-layer perception (MLP), generalized regression neural network (GRNN), fuzzy inference systems (FIS), self-organizing map (SOM), radial bias function (RBF), genetic algorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory (ART), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor.
• PCA principal component analysis
• SVM support vector machine
• MLP multi-layer perception
• GRNN generalized regression neural network
• FIS fuzzy inference systems
• SOM self-organizing map
• RBF radial bias function
• GAS genetic algorithms
• NFS neuro-fuzzy systems
• ART adaptive resonance theory
• PLS multiple linear regression
• PCR principal component regression
• DFA discriminant function analysis
• LDA linear discrimin
• Figure 1 A photograph of the manual thermal desorption system.
• Figures 2A-2C ( Figures 2A-2C.
• Figure 2A Schematic representation of the gold nanoparticle-based sensors of the present invention.
• Figure 2B Schematic representation of the carbon nanotube-based sensors of the present invention.
• Figure 2C Resistance recording of multiple sensors, prior to (left), during (middle), and after (recovery; right) exposure to breath samples.
• FIGS. 4A-4E Receiver operating characteristic (ROC) curves of sensors of ( Figure 4A) gold nanoparticles coated with tert-dodecanethiol; ( Figure 4B) gold nanoparticles coated with 2-ethylhexanethiol; ( Figure 4C) single walled carbon nanotubes coated with PAH1 ; ( Figure 4D) single walled carbon nanotubes coated with PAH2; and ( Figure 4E) single walled carbon nanotubes coated with PAH3.
• ROC Receiver operating characteristic
• Figures 5A-5F ROC curves ( Figures 5A, 5C, 5E) and normalized sensing features ( Figures 5B, 5D, 5F) of sensor 1 (SI ; Figures 5A, 5B), sensor 2 (S2; Figures 5C, 5D) and sensor 3 (S3; Figures 5E, 5F).
• Each circle represents one training sample and each star represents one blind sample where samples from the validation set with responses lower than the threshold were classified as TB positive and are marked as open stars.
• the dashed lines in Figures 5D, 5F and the middle dashed line in Figure 5B represent Youden' s cut-point.
• the top and bottom lines in Figure 5B represent rule-in and rule-out cut-points, respectively.
• Figures 6A-6F Figures 6A-6F.
• ROC curves ( Figures 6A, 6C, 6E) and normalized sensing features (Figures 6B, 6D, 6F) of sensor 1 (SI), where ( Figures 6A, 6B) refer to smoking habits of the study population, ( Figures 6C, 6D) refer to HIV status among TB positive derivation set samples, and ( Figures 6E, 6F) refer to medication status among the same group.
• Figure 7. Normalized resistance of a sensor of the present invention when exposed to breath samples. TB samples (T), control samples (*), and blind samples ( ⁇ ). Blind samples below the cut-off (dashed line) were classified as TB positive.
• Figure 8 Normalized resistance of two sensors (S33 and S02), when exposed to breath samples. TB samples (T), control samples (*), and blind samples ( ⁇ ). Blind samples below the cut-off (dashed line) were classified as TB positive.
• Figure 9 Principal component analysis of the combined sensing signals from S02, S26 and S33, when exposed to breath samples. TB samples ( A), control samples (*), and blind samples ( ⁇ ). Blind samples below the cut-off (dashed line) were classified as TB positive.
• FIG. 10 Illustration of a TB breath testing device according to the present invention with USB port for fast analysis.
• DFA Discriminant Factor Analysis
• the present invention is directed to the diagnosis of tuberculosis caused by M. tuberculosis bacteria using a single sensor comprising gold nanoparticles coated with dodecanethiol or single walled carbon nanotubes coated with 2-methyl-2-butene.
• An Artificial Olfactory System usually contains an array of chemically modified, cross-reactive nanomaterial-based sensors in conjunction with pattern recognition algorithms. The system can be trained to recognize repeatable compositions which characterize a specific disease to afford its diagnosis. The system provides a different and unique response to a mixture of VOCs indicative of a disease in a subject (Tisch et al., MRS Bull., 35, 797-803 (2012)).
• AOS systems have already been trained to successfully diagnose various diseases by analyzing individual VOCs in complex multi-component media, for example in human exhaled breath samples (Hakim et al., Chem. Rev., 112(11), 5949-5966 (2012); Barash et al, Small, 5(22), 2618-2624 (2009); Barash et al, NanoMed., 8(5), 580- 589 (2012); Peng et al, J. Cancer, 103(4), 542-551 (2012); Peng et al, Nature Nanotech., 4, 669-673 (2009); Ionescu et al., ACS Chem. Neurosc, DOI: 10.1021/cn2000603 (2011); Peng et al., Br. J.
• the present invention provides for the first time a highly sensitive and specific sensor comprising gold nanoparticles coated with dodecanethiol or single walled carbon nanotubes coated with 2-methyl-2-butene which can be used for the diagnosis of tuberculosis caused by M. tuberculosis bacteria in a subject.
• the sensor of the present invention provides a simple and accurate YES answer when detecting minute amounts (less than 1 ppm) of at least one VOC indicative of tuberculosis caused by M. tuberculosis bacteria in breath samples or samples of bodily fluids, without the need for post-measurement analysis.
• the sensor can thus be used as a non-invasive, portable, and cost-effective diagnostic tool for population screening and early detection of tuberculosis caused by M.
• tuberculosis bacteria When used in a system comprising an array of sensors in conjunction with a pattern recognition algorithm, an identification of TB positive subjects and their differentiation form TB negative and healthy controls with sensitivity, specificity and accuracy of over 90% could be achieved.
• the sensing signals of the sensors of the present invention are not affected by confounding factors, including smoking habits, the use of several TB medications, and HIV co-infection of the TB patients.
• the sensors of the present invention are thus suitable for use as a point-of- care screening tool for early detection of active TB.
• the sensors do not require sophisticated laboratory equipment or experienced operators, thus being particularly advantages for use in resource -poor and developing countries.
• VOC Upon adsorption of a VOC on an organic coating (dodecanethiol or 2-methyl-2- butene) of a conductive or semi-conductive material (gold nanoparticles or single walled carbon nanotubes), a change in structural configuration occurs. This change can be translated into an electrical signal which is caused by the formation of a conductive path or plurality of conductive paths between at least two conducting elements (e.g. electrodes).
• the electrical signal upon VOC exposure is determined by the nature of the interaction between the VOC and the molecular organic coating. Experimental results have shown 16 statistically different VOCs (derivatives of alkenes, dienes, ethers, methylated alkanes, ketones, and alcohols) in culture positive and culture negative TB samples.
• the sensors of the present invention are designed to be particularly sensitive and selective to at least one VOC indicative of tuberculosis caused by . tuberculosis bacteria.
• the present invention provides a sensor for diagnosing tuberculosis caused by . tuberculosis bacteria in a subject, the sensor comprising at least one of gold nanoparticles coated with dodecanethiol and single walled carbon nanotubes coated with 2-methyl-2-butene, wherein the sensor is configured to detect the presence of at least one volatile organic compound indicative of tuberculosis caused by M. tuberculosis bacteria in a sample thereby affording TB diagnosis.
• the sensors of the present invention comprise a plurality of conducting elements which are coupled to each sensor, thereby enabling the measurement of the electrical signals generated by the sensors.
• the conducting elements may include a source and a drain electrode separated from one another by a source-drain gap.
• the conducting elements may further comprise a gate electrode wherein the electrical signal may be indicative of the change in structural configuration under the influence of a gate voltage.
• the conducing elements may comprise metals such as Au, Ag, Ti/Pd or Pt electrodes and may further be connected by interconnecting wiring.
• the distance between adjacent electrodes defines the sensing area. Accordingly, different configurations of the electrodes in the sensors of the present invention may be fabricated as is known in the art. Typically, the distance between adjacent electrodes in each sensor ranges between about 0.01-5mm.
• the gold nanoparticles coated with dodecanethiol or the single walled carbon nanotubes coated with 2-methyl-2-butene are casted on a plurality of interdigitated electrodes on a suitable substrate.
• the substrate according to the principles of the present invention may be a substantially flexible or substantially rigid substrate. Each possibility represents a separate embodiment of the present invention.
• the substantially flexible substrate comprises a polymer selected from the group consisting of polyimide, polyamide, polyimine, polyethylene, polyester, polydimethylsiloxane, polyvinyl chloride, and polystyrene.
• the substantially flexible or rigid substrate comprises silicon dioxide.
• the substantially flexible substrate comprises a silicon rubber.
• the substantially rigid substrate is selected from the group consisting of metals, insulators, semiconductors, semimetals, and combinations thereof. Each possibility represents a separate embodiment of the present invention.
• the substantially rigid substrate comprises silicon dioxide on a silicon wafer.
• the substantially rigid substrate comprises a substantially rigid polymer.
• the substantially rigid substrate comprises indium tin oxide.
• Exemplary substrates within the scope of the present invention include, but are not limited to, silicon, glass, ceramic material, PVC 200, Kapton ® 50, Kapton ® 127, Kapton ® b. 131, PET 125, Mylar ® 36, Mylar ® 50 and the like. Each possibility represents a separate embodiment of the present invention.
• the sensor signal can be detected by a detection means.
• Suitable detection means include devices which are susceptible to a change in any one or more of resistance, conductance, alternating current (AC), frequency, capacitance, impedance, inductance, mobility, electrical potential, optical property and voltage threshold. Each possibility represents a separate embodiment of the present invention.
• the detection means includes devices which are susceptible to a change in any one or more of optical signal (detected by e.g. spectroscopic ellipsometry), florescence, chemiluminsence, photophorescence, bending, surface acoustic wave, piezoelectricity and the like. Each possibility represents a separate embodiment of the present invention.
• the sensors of the present invention can be configured as any one of the various types of electronic devices, including, but not limited to, capacitive sensors, resistive sensors, chemiresistive sensors, impedance sensors, field effect transistor sensors, and the like, or combinations thereof. Each possibility represents a separate embodiment of the present invention.
• the sensors of the present invention are configured as chemiresistive sensors (i.e. chemiresistors).
• Sensors can be formed on suitable substrates using a variety of techniques well known in the art. Exemplary techniques include, but are not limited to,
• the sensors of the present invention may be used in conjunction with a breath concentrator and/or a dehumidifying unit.
• Breath concentrators that are within the scope of the present invention include, but are not limited to, I. Solid Phase Microextraction (SPME) -
• SPME Solid Phase Microextraction
• the SPME technique is based on a fiber coated with a liquid (polymer), a solid (sorbent), or combination thereof.
• the fiber coating extracts the compounds from the sample either by absorption (where the coating is liquid) or by adsorption (where the coating is solid).
• the SPME fiber is then inserted directly into the sensing apparatus for desorption and subsequent analysis (Ouyang, et al., Anal. Bioanal. Chem., 386, 1059-1073 (2006); Coelho et al, J. Chromatography B, 853, 1-9 (2007)).
• Sorbent Tubes - Sorbent tubes are typically composed of glass and contain various types of solid adsorbent material (sorbents). Commonly used sorbents include activated charcoal, silica gel, and organic porous polymers such as Tenax and
• Cryogenic Condensates - Cryogenic condensation is a process that allows recovery of volatile compounds for reuse. The condensation process requires very low temperatures so that the volatile compounds can be condensed.
• chlorofluorocarbon (CFC) refrigerants have been used to induce condensation.
• liquid nitrogen is used in the cryogenic (less than -160°C) condensation process.
• a dehumidifier that is within the scope of the present invention includes, but is not limited to,
• Silica Gel - is an amorphous form of silicon dioxide, which is synthetically produced in the form of hard irregular granules or beads.
• a microporous structure of interlocking cavities provides a very high surface area (800 square meters per gram). This unique structure renders the silica gel as a high capacity desiccant. Water molecules adhere to the surface of the silica gel due to its low vapor pressure as compared to the surrounding air. When pressure equilibrium is reached, the adsorption ceases. Thus, the higher the humidity of the surrounding air, the larger the amount of water that is adsorbed before equilibrium is reached. Silica gel is advantageous as a drying substance since the process of drying does not require any chemical reaction and it does not produce any by products or side effects.
• Activated carbon - is formed by processing charcoal to an extremely porous carbon substance. Due to its high degree of microporosity, the activated carbon possesses a very large surface area available for chemical reactions. Sufficient activation may be obtained solely from the high surface area, though further chemical treatments often enhance the adsorbing properties of the material.
• Desiccant Molecular Sieves are synthetically produced, highly porous crystalline metal-alumino silicates. They are classified by the many internal cavities of precise diameters, namely, 3 A, 4A, 5 A, and 10A. Adsorption occurs only when molecules to be adsorbed have smaller diameters than the cavity openings. Molecules of high polarity are better adsorbed onto the molecular sieves. Molecular sieves adsorb water molecules and other contaminants from liquids and gases down to very low levels of concentrations, often to 1 ppm.
• the sensors may be used in conjunction with either one of a chemiresistor, a chemicapacitor, a quartz crystal microbalance, a bulk acoustic wave (BAW) and a surface acoustic wave (SAW) resonator, an electrochemical cell, a surface plasmon resonance (SPR), and an optical spectroscope.
• a chemiresistor a chemicapacitor
• a quartz crystal microbalance a bulk acoustic wave (BAW) and a surface acoustic wave (SAW) resonator
• an electrochemical cell a surface plasmon resonance (SPR), and an optical spectroscope.
• SPR surface plasmon resonance
• optical spectroscope optical spectroscope
• the single- walled carbon nanotubes (SWCNTs) coated with 2-methyl-2-butene of the present invention are arranged in a random network configuration.
• the network of SWCNTs can be fabricated by a physical manipulation or in a self-assembly process.
• self-assembly refers to a process of the organization of molecules without intervening from an outside source. The self-assembly process occurs in a solution/solvent or directly on a solid-state substrate.
• Main approaches for the synthesis of carbon nanotubes in accordance with the present invention include, but are not limited to, laser ablation of carbon, electric arc discharge of graphite rod, and chemical vapor deposition (CVD) of hydrocarbons. Each possibility represents a separate embodiment of the present invention.
• CVD coupled with photolithography has been found to be the most versatile in the preparation of various carbon nanotube devices.
• a transition metal catalyst is deposited on a substrate (e.g. silicon wafer) in the desired pattern, which may be fashioned using photolithography followed by etching.
• the substrate having the catalyst deposits is then placed in a furnace in the presence of a vapor-phase mixture of, for example, xylene and ferrocene.
• Carbon nanotubes typically grow on the catalyst deposits in a direction normal to the substrate surface.
• Various carbon nanotube materials and devices are now available from commercial sources.
• CVD methods include, but are not limited to, the preparation of carbon nanotubes on silica (S1O 2 ) and silicon surfaces without using a transition metal catalyst. Accordingly, areas of silica are patterned on a silicon wafer, by photolithography and etching. Carbon nanotubes are then grown on the silica surfaces in a CVD or a plasma-enhanced CVD (PECVD) process. These methods provide the production of carbon nanotube bundles in various shapes.
• PECVD plasma-enhanced CVD
• single walled carbon nanotubes refers to a cylindrically shaped thin sheet of carbon atoms having a wall which is essentially composed of a single layer of carbon atoms which are organized in a hexagonal crystalline structure with a graphitic type of bonding.
• a nanotube is characterized by the length-to-diameter ratio. It is to be understood that the term “nanotubes” as used herein refers to structures in the nanometer as well as micrometer range.
• the single-walled carbon nanotubes of the present invention have diameters ranging from about 0.6 nanometers (nm) to about 100 nm and lengths ranging from about 50 nm to about 10 millimeters (mm). More preferably, the single- walled carbon nanotubes have diameters ranging from about 0.7 nm to about 50 nm and lengths ranging from about ranging from about 250 nm to about 1 mm. Even more preferably, the single- walled carbon nanotubes have diameters ranging from about 0.8 nm to about 10 nm and lengths ranging from about 0.5 micrometer ( ⁇ ) to about 100 ⁇ . Most preferably, the single-walled carbon nanotubes of the present invention have diameters ranging from about 0.9 nm to about 5 nm and lengths ranging from about 1 ⁇ to about 50 ⁇ .
• Sensors comprising metal nanoparticles coated with dodecanethiol can be synthesized as is known in the art, for example using the two-phase method (Brust et al., J. Chem. Soc. Chem. Commun, 801, 2 (1994)) with some modifications (Hostetler et al., Langmuir, 14, 24 (1998)).
• Coated gold nanoparticles can be synthesized by transferring AuCL t from aqueous HAuC '-xifeO solution to a toluene solution by the phase-transfer reagent TOAB. After isolating the organic phase, excess thiols are added to the solution.
• the mole ratio of thiol: HAuC '-xifeO can vary between 1 : 1 and 10:1, depending on the thiol used. This is performed in order to prepare mono-disperse solution of gold nanoparticles in average size of about 3-5 nm.
• a thiol:Au mole ratio of 10:1 is used for nanoparticles with an average diameter of 5 nm.
• aqueous solution of reducing agent NaBtU in large excess is added. The reaction is constantly stirred at room temperature for at least 3 hours to produce a dark brown solution of the thiol-coated Au nanoparticles.
• the resulting solution is further subjected to solvent removal in a rotary evaporator followed by multiple washings using ethanol and toluene.
• the gold nanoparticles may have any desirable morphology including, but not limited to, a cubic, a spherical, and a spheroidal morphology. Each possibility represents a separate embodiment of the present invention.
• the synthesized coated nanoparticles can then be assembled (e.g. by a self-assembly process) to produce a ID wire, 2D film or 3D assembly of coated nanoparticles.
• a self-assembly process e.g. by a self-assembly process
• the present invention further provides a method of diagnosing tuberculosis caused by M. tuberculosis bacteria in a subject.
• the method comprises the step of exposing a single sensor of the present invention to a test sample and measuring an electrical signal upon exposure of the sensor to the test sample using a detection means, whereby if the electrical signal is greater than a reference, a YES answer is obtained to afford the diagnosis of tuberculosis caused by M. tuberculosis bacteria.
• the YES/NO answer can be displayed on a display in conjunct to the sensor without further manipulation or processing.
• the term "reference" refers to a threshold criterion/value to which measured electrical signals are compared in order to obtain an identification of the presence of tuberculosis caused by M. tuberculosis bacteria.
• the reference can be derived in any one of a number of manners. For example, the reference may be based on a collection of data of samples from subjects known to be afflicted with tuberculosis caused by M. tuberculosis bacteria or known to be TB negative. According to certain aspects and embodiments, the reference is determined from statistical analysis of studies that compared VOC profiles of subjects with known clinical outcomes and correlated them with the corresponding electrical signals of the sensors of the present invention.
• the reference may be obtained from data collected from a sample population of subjects, which acts as a pool of data from which normalized expected differences in electrical responses for TB positive and TB negative subjects can be determined.
• the reference is then generated by selecting the value of electrical signal that is determined as the cut-off for classifying TB positive and TB negative samples.
• the reference may be varied according to subject parameters such as age, sex, height, weight, race, interventions, or the like.
• the present invention provides a system comprising a plurality of sensors (sensor array) of the present invention.
• the system may comprise between 2 and 6 sensors.
• the system comprises a sensor of single walled carbon nanotubes coated with 2-methyl-2-butene and a sensor of gold nanoparticles coated with dodecanethiol.
• the system comprises two sensors of gold nanoparticles coated with dodecanethiol.
• the system further comprises a detection means as described herein and a processing unit comprising a learning and pattern recognition analyzer which utilizes at least one algorithm.
• Algorithms for sample analysis include, but are not limited to, principal component analysis, Fischer linear analysis, neural network algorithms, genetic algorithms, fuzzy logic pattern recognition, and the like. Each possibility represents a separate embodiment of the present invention.
• Many of the algorithms are neural network based algorithms.
• a neural network has an input layer, processing layers and an output layer. The information in a neural network is distributed throughout the processing layers. The processing layers are composed of nodes that simulate the neurons by the interconnection to their nodes.
• VOCs unknown analytes
• the neural network is trained by correcting the false or undesired outputs from a given input. Similar to statistical analysis revealing underlying patterns in a collection of data, neural networks locate consistent patterns in a collection of data, based on predetermined criteria.
• Suitable pattern recognition algorithms include, but are not limited to, principal component analysis (PCA), support vector machine (SVM), Fisher linear discriminant analysis (FLDA), soft independent modeling of class analogy (SIMCA), K-nearest neighbors (KNN), neural networks, genetic algorithms, fuzzy logic, and the like.
• PCA principal component analysis
• SVM support vector machine
• FLDA Fisher linear discriminant analysis
• SIMCA soft independent modeling of class analogy
• KNN K-nearest neighbors
• neural networks genetic algorithms, fuzzy logic, and the like.
• PCA is an effective method to reduce multidimensional data space to its main components by determining the linear combinations of the sensor values such that the maximum variance between all data points can be obtained in mutually orthogonal dimensions.
• the first principle component provides the largest variance between sensor values.
• the second, third, fourth etc. principal components provide decreasing magnitudes of variance between all data points.
• PCA is a mathematical technique that transforms a number of correlated variables into a smaller number of uncorrected variables.
• the smaller number of uncorrected variables is known as principal components.
• the first principal component or eigenvector accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible.
• the main objective of PCA is to reduce the dimensionality of the data set and to identify new underlying variables.
• PCA compares the structure of two or more covariance matrices in a hierarchical fashion. For instance, one matrix might be identical to another except that each element of the matrix is multiplied by a single constant. The matrices are thus proportional to one another.
• the matrices share identical eigenvectors (or principal components), but their eigenvalues differ by a constant. Another relationship between matrices is that they share principal components in common but their eigenvalues differ.
• the mathematical technique used in principal component analysis is called eigenanalysis.
• the eigenvector associated with the largest eigenvalue has the same direction as the first principal component.
• the eigenvector associated with the second largest eigenvalue determines the direction of the second principal component.
• the sum of the eigenvalues equals the trace of the square matrix and the maximum number of eigenvectors equals the number of rows in this matrix.
• SVM support vector machine
• SVM models are closely related to neural networks.
• SVM models are alternative training methods for polynomial, radial basis function and multi-layer perceptron classifiers in which the weights of the network are found by solving a quadratic programming problem with linear constraints, rather than by solving a nonconvex, unconstrained minimization problem as in standard neural network training.
• Using an SVM model with a sigmoid kernel function is equivalent to a two-layer, perceptron neural network.
• a predictor variable is called an attribute
• a transformed attribute that is used to define the hyperplane is called a feature.
• the task of choosing the most suitable representation is known as feature selection.
• a set of features that describes one case i.e., a row of predictor values
• the output of SVM modeling provides the optimal hyperplane that separates clusters of vectors in a manner that affords cases with one category of the target variable on one side of the plane and cases with the other category on the other size of the plane.
• the vectors near the hyperplane are the support vectors.
• the present invention further provides a method for diagnosing tuberculosis caused by M. tuberculosis bacteria comprising exposing the plurality of sensors to a test sample, measuring a response induced parameter from the sensors upon exposure to the test sample using a detection means to generate a response pattern and analyzing the response pattern by comparing it to stored data obtained from a control sample whereby significantly different response pattern of the test sample as compared the control sample is indicative of tuberculosis caused by M. tuberculosis bacteria.
• the analysis is performed using a learning and pattern recognition algorithm.
• the term "significantly different” as used herein refers to a statistically significant quantitative difference between the pattern of the test sample and the pattern of a control sample.
• a statistically significant difference can be determined by any test known to the person skilled in the art. Common tests for statistical significance include, among others, t- test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann- Whitney and odds ratio. Individual samples (of unknown status) can be compared with data from the reference group (negative control), and/or compared with data obtained from a positive control group known to have tuberculosis caused by M. tuberculosis bacteria. A statistically significant elevation or reduction in the particular response parameter being measured between the test and control sample qualifies as significant difference.
• a set of control samples or response patterns can be stored as a reference collection of data for multiple analyses. It will be recognized by one of skill in the art that the determination of whether a test subject has active TB caused by M. tuberculosis bacteria is performed when comparing a response pattern to the appropriate control. For example, if the control is a negative control then significantly different response pattern of the test sample as compared the control sample are indicative of TB caused by M. tuberculosis bacteria. Conversely, if the control is a positive control then significantly different response pattern of the test sample as compared the control sample are indicative of lack of active TB caused by M. tuberculosis bacteria. According to certain aspects and embodiments, a plurality of response induced parameters are measured. In accordance with these embodiments, the plurality of response induced parameters generate a plurality of patterns which are then conveyed to a learning and pattern recognition analyzer which utilizes an algorithm in order to analyze the signal patterns by comparing them to stored data.
• the step of measuring a plurality of response induced parameters comprises measuring a change in any electrical property such as, but not limited to the resistance, impedance, capacitance, inductance, conductivity, or optical properties of the sensors upon exposure to a test sample using a detection means and extracting a plurality of response induced parameters from said response.
• a response induced parameter includes, but is not limited to, steady state normalized response, the time interval for obtaining steady state normalized response, the time required to reach baseline after removal of the test sample, the normalized change of sensor signal at the peak of the exposure, the normalized change of sensor signal at the middle of the exposure, the normalized change of sensor signal at the end of the exposure, and the area under the curve of the sensor signal.
• the response induced parameter includes, but is not limited to, full non steady state response at the beginning of the signal, full non steady state response at the beginning of the signal normalized to baseline, full non steady state response at the middle of the signal, full non steady state response at the middle of the signal normalized to baseline, full steady state response, full steady state response normalized to baseline, area under non steady state response, area under steady state response, the gradient of the response upon exposure to the test sample, the gradient of the response upon removal of the test sample, the time required to reach a certain percentage of the response, such as the time required to reach 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or 100% of the response upon exposure to the test sample, and the time required to reach a certain percentage of the response, such as the time required to reach 100%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20% or 10% of the response upon removal of the test sample.
• the response induced parameter includes, but is not limited to, full non steady state response at the beginning of the signal, full non steady state response at
• the step of measuring a plurality of response induced parameters comprises measuring a plurality of responses selected from resistance, impedance, capacitance, inductance, conductivity, and optical properties of the sensors upon exposure to a test sample.
• a plurality of responses selected from resistance, impedance, capacitance, inductance, conductivity, and optical properties of the sensors upon exposure to a test sample.
• the step of measuring a plurality of response induced parameters comprises measuring a change in the resistance, impedance, capacitance, inductance, conductivity, or optical properties of the sensors upon exposure to a test sample and fitting the response to a function or a plurality of functions whereby the response induced parameters are selected from function constants, function coefficients, and a combination thereof.
• the step of measuring a plurality of response induced parameters comprises measuring a change in the resistance, impedance, capacitance, inductance, conductivity, or optical properties of the sensors upon exposure to a test sample and processing the signal (e.g. by normalization, calibration etc.) followed by the extraction of the plurality of response induced parameters.
• the methods of diagnosis of the present invention can be performed even in the presence of confounding factors selected from smoking, HIV infection, consumption of medication and combinations thereof. Each possibility represents a separate embodiment of the present invention.
• the test sample is selected from a breath sample and a bodily fluid or secretion of a subject.
• the sensor or system of the present invention can be directly exposed to a breath sample or sample of bodily fluid or secretion.
• the sensor or system of the present invention can be exposed to the headspace of a container wherein breath samples, bodily fluids or secretions have been deposited.
• the sensor or system of the present invention can be exposed to breath directly exhaled by the subject through a mouthpiece, without a need for pre-concentrating or dehumidifying the sample.
• Other possibilities include exhaling into an inert bag and then exposing the collected breath to the sensor or system of the present invention.
• Bodily fluids or secretions within the scope of the present invention include, but are not limited to, serum, urine, feces, sweat, vaginal discharge, saliva and sperm. Each possibility represents a separate embodiment of the present invention.
• the present invention provides sensor technology for diagnosing TB caused by M. tuberculosis bacteria.
• the sensor technology of the present invention could be easily adapted as a disposable home- or office-kit for fast TB testing.
• Fig. 10 illustrates an exemplary device for simple and reliable TB diagnosis in accordance with the present invention.
• the devise comprises a sensor according to the present invention mounted on an electronic chip for signal readout and data storage.
• the device is designed to include an opening at one end adapted to capture the breath of a subject after the removal of a sterile seal.
• the sensors' readout and software for subsequent data analysis is loaded onto a computer via the USB port at the opposite end of the device.
• the data could be analyzed within less than a minute, either on-site or via data-link to the doctor' s office or to a central server.
• Exhaled breath is a mixture of alveolar air and respiratory dead space air.
• the dead space air was automatically filled into a separate bag, and 750 ml of end tidal expirium was sampled into an inert Mylar bag.
• VOCs in the breath samples were trapped and pre-concentrated in two-bed ORBOTM 420
• Tenax® TA sorption tubes for gas and vapor sampling (specially treated; 35/60 mesh; 100/50 mg; purchased from Sigma-Aldrich, China) by pumping the content of each collection bag through a sorbent tube (flow rate: 150-200 ml/min).
• TD thermal desorption
• An Agilent Multifunction switch 34980 was used to measure the resistance of all sensors simultaneously as a function of time.
• the sensors' baseline responses were recorded for 5 minutes in vacuum, followed by 5 minutes under breath sample exposure, followed by another 5 minutes in vacuum.
• the sensors were daily calibrated by exposing the sensors to known concentrations of three calibration compounds and recording their change in resistance.
• the test chamber was evacuated for 5 minutes in order to eliminate possible contaminations, followed by exposure of the sensors to a fixed mixture of three VOCs including 23.8 ppm isopropyl alcohol, 6.3 ppm trimethylbenzene and 1.2 ppm 2-ethylhexanol for a duration of 5 minutes, and then concluded by evacuation of the test chamber for 5 minutes in order to eliminate the calibration compounds from the test chamber.
• the exposure of the sensors to the breath samples or the calibration compounds resulted in rapid and fully reversible changes of the electrical resistance (Fig. 2C).
• sensing features response induced parameters
• Fl the normalized change of sensor resistance at the peak of the exposure
• F2 the normalized change of sensor resistance at the middle of the exposure
• F3 the normalized change of sensor resistance at the end of the exposure
• F4 the area under the curve of the entire measured resistance signal.
• the net sensing features that were extracted for the breath samples were then divided by the corresponding values that were obtained for the reference calibration compound.
• Fig. 2A shows the optical microscopy image of the electrodes circles of organically coated spherical gold nanoparticles of the present invention.
• the inset shows a schematic representation (not drawn to scale) of films of organically capped spherical gold nanoparticles, which connect the electrodes and form multiple pathways between them.
• Fig. 2B shows a schematic representation (not drawn to scale) of CNT-based sensors of the present invention.
• the left inset shows a scanning electron micrograph of SWCNTs which were functionalized with PAH molecules.
• Chemiresistive layers were formed by drop-casting the solution onto semicircular microelectronic transducers, until a resistance of several ⁇ was reached. The devices were dried for 2 hours at ambient temperatures and then baked overnight at 50 °C in a vacuum oven.
• the microelectronic transducers consisted of ten pairs of circular interdigitated (ID) gold electrodes on silicon with 300 nm thermal oxide (Silicon Quest International, Nevada, US). The outer diameter of the circular electrode area was 3 mm, and the gap between two adjacent electrodes and the width of each electrode, was 20 ⁇ each.
• ID circular interdigitated
• the sensors were based on an electrically continuous random network of SWCNTs (U.S. 8,366,630; U.S. 8,481 ,324; the contents of each of which are hereby incorporated in their entirety). After the deposition, the device was slowly dried overnight under ambient conditions to enhance the self-assembly of the SWCNTs and to afford the evaporation of the solvent.
• the microelectronic transducer for the SWCNT sensor consisted of ten pairs of 4.5 mm wide, interdigitated Ti/Pd electrodes on silicon with two microns of thermal oxide (Silicon Quest International, Nevada, US). The gap between two adjacent electrodes was 100 ⁇ .
• the SWCNT sensor was organically functionalized with 2-methyl-2-butene or with a Polycyclic Aromatic Hydrocarbon (PAH) derivative.
• PAH Polycyclic Aromatic Hydrocarbon
• the GNP and SWCNT sensors used in this study responded rapidly and reversibly when exposed to typical VOCs in the breath with a very low responsivity to water vapors (Zilberman et al, Adv. Mater. 22, 4317-4320 (2010); Zilberman et al, Langmuir, 25, 5411- 5416 (2009); Zilberman et al, ACS Nano, 5, 6743-6753 (2011); Peng et al, Nat. Nanotech., 4, 669-673 (2009); Peng et al, Nano Lett., 8, 3631-3635 (2008); and Konvalina et al., ACS Appl. Mater.
• PCA Principal Component Analysis
• Example 1 Identification of TB patients using a single nano material-based sensor
• the feasibility of three sensors of the present invention to diagnose TB was tested by comparing breath samples of 44 TB positive patients to breath samples of 94 TB negative patients and healthy controls. Each sensor responded to all (or to a certain subset) of VOCs that were present in the exhaled breath samples.
• the sensing features were selected according to the accuracy of the training sets' differentiation between TB positive patients and control group (including both TB negative patients and healthy controls) using leave-one-out cross validation to determine the cut-off value between TB positive and healthy controls.
• the discriminative ability of all 12 normalized sensing features that were read from three sensors designated S02, S26 and S33 (four features per sensor) were compared. All the features discriminated well between the groups.
• Table 5 lists as an example, the classification test results for a training set that was used and a blind test using a single feature (i.e. F3) of sensor S26, which provided the best result.
• the blind test validation yielded values of over 90% for sensitivity, specificity and accuracy.
• Fig. 5B shows the well separated clusters of TB positive and control populations that were obtained using a single feature (F3) of a single sensor of dodecanethiol-coated gold nanoparticles (S26).
• the cut-off value was set as 0.49. This was the cut-off value that was used for classifying the blind samples.
• the Area Under Curve (AUC) of ROC was 94.8%.
• the first sensor scored 90%, 93%, and 92% for sensitivity, specificity and accuracy, respectively. Moreover, when changing the threshold to higher sensitivity (95%), the NPV calculated by blind experiment was 94%. When lowering the rates of false negatives by increasing specificity of training set classification to 95%, a PPV of 93% was achieved (Table 6; Figs. 5A-5B).
• the second sensor which was fabricated under very similar conditions was able to sharply distinguish between TB samples and control samples, with accuracy of 83% and 90% AUC of ROC.
• the third sensor which comprises SWCNTs modified with 2-methyl-2-butene sensing layer (CNT1) scored a total accuracy of 86% in the blind experiment, with sensitivity of 80% and specificity of 90%. The results of the blind test were very close to the training set, where the accuracy was 84% and the AUC was 87.6% when ROC analysis was applied (Table 6, Figs. 5E-5F).
• a single sensing feature and a single sensor of the present invention can be used to provide well separated clusters of TB positive and control populations and can therefore afford the differentiation of TB positive breath samples from controls. It is noteworthy that no significant difference between the sensors' response to healthy controls and TB negative samples were observed, even though the samples were collected at different locations due to safety regulations.
• the sensors of the present invention are essentially unaffected by the sampling surrounding, while being very sensitive to comprehensive alteration in exhaled breath composition, due to acute TB inflammatory process.
• a single sensor of the present invention provides the diagnosis of TB via breath analysis without the need for post-measurement analysis. Table 6. Statistical analysis results
• TP True Positive
• FN False Negative
• TN True Negative
• FP False Positive
• Example 2 The responses of the sensors to main confounding factors
• Figs. 6A-6B show that the dodecanethiol coated GNP sensor of the present invention was not sensitive to tobacco smoking, even though smoking is known to cause significant changes to the chemical composition of human breath samples (Buszewski et al., Biomed. Chromatogr., 21, 553-566 (2007); Amann et al, Euro. Resp. Soc.
• the sensor of the present invention correctly recognized 92% of the blind samples with no more than random detection ability regarding subjects' smoking habits, HIV status or medication treatment with ROC AUC of 56%, 55% and 54%, respectively. It is therefore concluded that the sensing signals of the sensors of the present invention are not affected by several important confounding factors, including smoking habits, TB medication and HIV co-infection.
• Example 3 Identification of TB patients using a sensor array comprising GNP- and SWCNT- based sensors
• the ability of an array of sensors of the present invention to identify TB patients was assessed using a combination of two different sensing features from three different sensors.
• one feature of the GNP-based sensors (S02, S26) and one feature of SWCNT- based sensor (S33) were used.
• the combination of two-features from three sensors yielded better classification results.
• the values for sensitivity, specificity and accuracy ranged from 80% to 93%.
• the maximal classification success did not exceed that of the best single sensing feature (F3 of sensor S26; see Table 5).
• Figs. 7 and 8 show the two-dimensional plots of the combination of two different sensing features as representative examples.
• the dashed line represents the cut-off between the clusters of TB positive and control samples.
• the 2D clusters are well separated with little overlap between them.
• Table 5 lists the corresponding classification success.
• the values for the sensitivities, specificities and accuracies of the blind experiments were typically above 90%.
• the ability of an array of sensors of the present invention to identify TB patients was assessed using a combination of twelve sensing features from three different sensors. Principal component analysis of the combined signals showed that the cluster of TB samples is well separated from the cluster of control samples (Fig. 9).
• PCA Principle Component Analysis
• the GNP and SWCNT sensors of the present invention are capable of identifying TB positive subjects and differentiate them from TB negative and healthy subjects in a blind experiment. Very high classification success with sensitivity, specificity and accuracy of more than 90% was achieved. The results were shown to be very reliable and reproducible. Increasing the number of readout signals did not improve the classification success.
• a single readout signal from a sensor of the present invention provides the diagnosis of TB caused by M. tuberculosis bacteria and can be used for breath testing of TB that could easily be adapted as a disposable home- or office-kit for fast TB testing, suitable for population screening.

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