Methods and apparatus for detecting, quantifying, enriching, and/or separating bacterial species in fluid sample are provided. The fluid sample is provided as input to a microfluidic passage of a microfluidic device, wherein the microfluidic device comprises at least one electrode disposed adjacent to the microfluidic passage. The at least one electrode is activated to capture bacteria in the sample using dielectrophoresis, wherein the capture efficiency of bacteria is at least 99%.

A method for determining whether obesity is present by using a machine learning model may include a process of analyzing a mixture of a gut-derived substance collected from a subject and a gut environment-like composition, a process of extracting multiple microbial data based on an analysis result of the mixture, a process of selecting microbe-related features to be used in the machine learning model from the multiple microbial data based on a predetermined feature selection algorithm, a process of training the machine learning model with the microbe-related features, and a process of inputting, to the trained machine learning model, the microbial data collected from the subject to be tested and determining whether obesity is present. The microbe-related features may include the amount of one or more microbes selected from families included in orders, Lachnospirales, Lactobacillales, and Erysipelotrichales.

A method for determining whether atopic dermatitis is present by using a machine learning model may include a process of analyzing a mixture of a gut-derived substance collected from a subject and a gut environment-like composition, a process of extracting multiple microbial data based on an analysis result of the mixture, a process of selecting microbe-related features to be used in the machine learning model from the multiple microbial data based on a predetermined feature selection algorithm, a process of training the machine learning model with the microbe-related features, and a process of inputting, to the trained machine learning model, the microbial data collected from the subject to be tested and determining whether atopic dermatitis is present. The microbe-related features may include the amount of one or more microbes selected from genera included in families, Ruminococcaceae, Lactobacillaceae, Prevotellaceae, Barnesiellaceae, Bacteroidaceae, Lachnospiraceae, and UCG.010.

A microwell microelectrode filtration sensor created by using an inert planar surface, which can be a metal pattern dry etched, to generate a filtration membrane with pores, generating a reactive metal surface layer as a working electrode. The electrode is within an area covering a filtration membrane, and makes one or more microwells added by a first layer of inert plastic of an effective working distance height and a second layer of a non-reactive metal of an effective microwell surface area to serve counter and/or reference an electrode. This is followed by at least one layer of inert plastic or metal.

Apparatus for detecting the presence in an enclosed environment of a subject or subjects infected with viral, bacterial and/or parasitic disease or diseases, the apparatus comprising: (a) an air sampling unit (1) able to take an air sample of the atmosphere in the enclosed environment and to divert said sample for sensing; (b) a selected definitive sensor set (9) comprising at least two sensors reactive to the presence of specific odours or Volatile Organic Compounds (VOCs) in the air sample taken from the environment; (c) a processing unit (10) comprising a pattern recognition analyser, wherein the pattern recognition analyser receives output signals of the sensor set, compares them to diseasespecific patterns derived from a database of response patterns of the sensor set exposed to the totality of the bodily emissions of subjects with known disease or diseases, wherein each of the disease-specific patterns is characteristic of a particular disease, selected from bacteriological, viral and parasitic disease, and selects a closest match between the output signals of the sensor set and the disease-specific pattern; and (d) a control system that triggers the sampling of the air space of the environment at pre-determined times or intervals for rendering the apparatus entirely automatic and self-contained in operation, wherein the air sampling unit comprises: a surface (2) for capturing VOCs from the air sample; and a heater (3) for heating the surface to release captured VOCs when diverting the air sample for sensing.

A method of using electrochemical reporters in a micro-filtration sensor which contains multiple analyte detection wells with electrodes and where the electrochemical reporters determine the identity and integrity of the product and sample. Identity and integrity are assessed for suitable use and linkage to additional data or preventing producing erroneous in-vitro diagnostic data. The micro-filtration sensor is additionally used for electrochemical bioassays of analytes in one or more of the analyte detection microwells. Analyte detection microwells may contain an additional affinity agent for capture of affinity agents for analyte detection and electrochemical reporters for identity and integrity detection.

The present invention relates to DNA sequences encoding Vmp-like polypeptides of pathogenic Borrelia, the use of the DNA sequences in recombinant vectors to express polypeptides, the encoded amino acid sequences, application of the DNA and amino acid sequences to the production of polypeptides as antigens for immunoprophylaxis, immunotherapy, and immunodiagnosis. Also disclosed are the use of the nucleic acid sequences as probes or primers for the detection of organisms causing Lyme disease, relapsing fever, or related disorders, and kits designed to facilitate methods of using the described polypeptides, DNA segments and antibodies.

Methods for predicting the development of sepsis in a subject at risk for developing sepsis are provided. In one method, features in a biomarker profile of the subject are evaluated. The subject is likely to develop sepsis if these features satisfy a particular value set. Methods for predicting the development of a stage of sepsis in a subject at risk for developing a stage of sepsis are provided. In one method, a plurality of features in a biomarker profile of the subject is evaluated. The subject is likely to have the stage of sepsis if these feature values satisfy a particular value set. Methods of diagnosing sepsis in a subject are provided. In one such method, a plurality of features in a biomarker profile of the subject is evaluated. The subject is likely to develop sepsis when the plurality of features satisfies a particular value set.

The invention provides compositions (e.g., peptide compositions) useful for the detection of antibodies that bind to Borrelia antigens. The peptide compositions comprise polypeptide sequences comprising variants in the IR6 domain of the Borrelia VlsE protein. The invention also provides devices, methods, and kits comprising such peptide compositions and useful for the detection of antibodies that bind to Borrelia antigens and the diagnosis of Lyme disease.

Provided herein are methods, systems, and devices for detecting and/or identifying one or more specific microorganisms in a culture sample. Indicator particles, such as surface enhanced Raman spectroscopy (SERS)-active nanoparticles, each having associated therewith one or more specific binding members having an affinity for the one or more microorganisms of interest, can form a complex with specific microorganisms in the culture sample. Further, agitating magnetic capture particles also having associated therewith one or more specific binding members having an affinity for the one or more microorganisms of interest can be used to capture the microorganism-indicator particle complex and concentrate the complex in a localized area of an assay vessel for subsequent detection and identification. The complex can be dispersed, pelleted, and redispersed so that the culture sample can be retested a number of times during incubation so as to allow for real-time monitoring of the culture sample.