An object detection system compensates for variations in transmission characteristics within an object passageway caused by, for example, dust or dirt. An object detection device includes a plurality of electromagnetic radiation emitters and detectors arranged in rows on opposite sides of a passageway. First lenses focus radiation from the emitters into a semi-columnated beams of radiation that together create a plane of semi-columnated electromagnetic radiation that spans substantially across a width of the passageway. Second lenses focus the received electromagnetic radiation onto corresponding ones of the plurality of radiation detectors. A controller receives a radiation intensity signal from the detectors, determines that its value is outside of a predetermined range, and adjusts an amount of electrical power supplied to the plurality of radiation emitters so that the value of the radiation intensity signal changes to become within the predetermined range.

Methods of monitoring Klotho activity are provided.

To improve a determination accuracy when determining each particle contained in an image of an object. An image analysis apparatus according to an embodiment of the present invention includes: a shape determination unit configured to determine a shape of a particle included in a particle image that is extracted from an image of an object, so that an OK particle image which is a particle image of an OK particle that satisfies a predetermined standard for shape and a provisional NG particle image which is a particle image of a provisional NG particle that does not satisfy the predetermined standard, are obtained; a pseudo image generation unit configured to generate a pseudo image; and a similarity determination unit configured to determine whether the provisional NG image and the pseudo image are similar.

Aspects of the present disclosure include methods for identifying one or more components of a sample in a flow stream using a dynamic algorithm (e.g., a machine learning algorithm). Methods according to certain embodiments include detecting light from a sample having particles in a flow stream, generating a data signal of parameters of the particles from the detected light, generating an image based on the data signal, comparing the image with one or more image classification parameters and classifying one or more components of the image using a dynamic algorithm that updates the image classification parameters based on the classified components in the image. Systems and integrated circuit devices programmed for practicing the subject methods, such as on a flow cytometer, are also provided.

The present invention is directed to a method of identifying, isolating, and enabling downstream analysis of circulating tumor cells comprising contacting a blood or blood serum sample of a subject with a composition comprising a phospholipid ether analog bound to a luminescent molecule or a magnetic bead and subjecting the blood or blood serum sample of the subject to fluorescent microscopy, flow cytometry or magnetic isolation.

A method for evaluating a biological material for unassociated virus-size particles having a particular epitope uses a fluorescent antibody stain specific for binding with the epitope and a fluid sample with the virus-size particles and fluorescent antibody stain is subjected to flow cytometry with identification of fluorescent emission detection events indicative of passage through a flow cell of a flow cytometer of unassociated labeled particles of virus size including such a virus-size particle and fluorescent antibody stain.

Methods of detecting the efficacy and presence of a biologic drug which uses one or more 2A peptide in its manufacture and/or final pharmaceutical formulation.

The present invention includes methods to determine a risk of a cardiovascular disease (CVD) or a subclinical CVD (sCVD) in a subject, by detecting a subset of intermediate monocyte cell populations in the immune cells, wherein a percentage of the subsets as compared to a total intermediate monocyte cell population present in the isolated immune cells is determined; comparing a proportion of the subsets subset of intermediate monocyte cell populations determined with a statistical sample representative of a proportion of equivalent subsets in a total intermediate monocyte cell populations from a subject that does not have a cardiovascular disease; and determining that the subject has an increased risk for cardiovascular disease where the subject has a decrease in the certain subsets, has an increase in another subset, or both, as compared to the statistical sample.

A method of measuring malarial parasitemia includes disposing a sample including red blood cells in liquid form on a sample stage, illuminating the sample with optical radiation, capturing a plurality of images of the sample, and extracting, from the one or more of the plurality of images, a set of red blood cell images. Each red blood cell image is associated with a particular red blood cell. The method also includes for each red blood cell image in the set of red blood cell images, inputting each red blood cell image into a machine learning model and generating, using the machine learning model, a classification related to a malaria parasite lifecycle stage for each of the red blood cells. The method further includes determining the malarial parasitemia for the sample.

A technique, called the Coupling Assay for T-cell Specificity (CATS), to identify antigen-specific cells using cell lines expressing MHC II molecules with tethered peptides. CATS successfully identified antigen-specific T cells with a low-affinity peptide, while tetramer failed to identify cells with this same peptide. Increasing avidity on artificial antigen presenting cells can overcome low affinity TCR-pMHC interactions, can identify more responding endogenous populations, and may be specific for the MHCII.