The disclosure features systems and methods for measuring and diagnosing target constituents bound to labeling particles in a sample. The systems include a radiation source, a sample holder, a detector configured to obtain one or more diffraction patterns of the sample each including information corresponding to optical properties of sample constituents, and an electronic processor configured to, for each of the one or more diffraction patterns: (a) analyze the diffraction pattern to obtain amplitude information and phase information corresponding to the sample constituents; (b) identify one or more particle-bound target sample constituents based on at least one of the amplitude information and the phase information; and (c) determine an amount of at least one of the particle-bound target sample constituents in the sample based on at least one of the amplitude information and the phase information.

Biosensing platform for simultaneous, multiplexed, high throughput and ultra-sensitive optical detection of biomarkers labelled with plasmonic nanoparticles, the platform being provided with a biosensor, a broadband and continuous spectrum illumination source, an optical detector for simultaneously capturing spatially resolved and spectrally resolved the scattering signal of each individual nanoparticle, an autofocus system and an optical system adapted to collect the scattered signal of the biosensor's surface onto the optical detector, the platform being provided with translation means for the optical system and/or the biosensor, such that the optical system and the biosensor can be displaced relative to each other in the three dimensions, and wherein the processing means are adapted to: i) simultaneously capture spatially and spectrally resolved scattering signals from each nanoparticle individually, and ii) to analyze these signals simultaneously with the capture process.

The disclosed subject matter compensates or corrects for errors that otherwise would be present when a measurement is made on a condensation particle counting system with the only difference causing the errors being absolute pressure. The difference in absolute pressure may be due to, for example, a change in altitude in which the condensation particle counting system is located. Techniques and mechanisms are disclosed to compensate for changes in particle count, at a given particle diameter, for changes in sampled absolute pressure at which measurements are taken. Other methods and apparatuses are disclosed.

Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

Apparatus and methods are described including placing at least a portion of a blood sample within a sample chamber (52), and acquiring microscopic images of the portion of the blood sample. Candidates of a given entity within the blood sample are identified, within the microscopic image. At least some of the candidates as being the given entity are validated, by performing further analysis of the candidates. A count of the candidates of the given entity is compared to a count of the validated candidates of the given entity, and at least the portion of the sample is invalidated from being used for performing at least some measurements upon the sample, at least partially based upon a relationship between the count of candidates and the count of validated candidates. Other applications are also described.

Techniques for label-free determination of a value of at least one blood property are presented. The techniques may utilize a device that includes an optical objective including at least one lens, at least a first light source situated so as to provide light to a body part at a location that is off-center from a central axis of the objective, at least a first electronic detector situated to receive light gathered by the optical objective and generate image data, at least one electronic processor communicatively coupled to the first electronic detector, the at least one electronic processor configured to determine the value of the at least one blood property based at least in part on the image data, and an output interface communicatively coupled to the at least one electronic processor and configured to provide the value of the at least one blood property.

An air-quality detection apparatus is disclosed. The air-quality detection apparatus includes a casing body including a bottom and a side wall extending upwards from the circumference of the bottom, a first printed circuit board (PCB) disposed horizontally above the bottom, a temperature/humidity sensor mounted on the bottom surface of the first PCB, a second PCB disposed horizontally above the first PCB, and a CO.sub.2 sensor mounted on the second PCB.

The present invention relates to a method for subjecting a plurality of microwells containing cells to a high-content assay, said method comprising: a) Acquiring at least one image of said plurality of microwells; b) In said image, detecting a plurality of areas of interest, each area of interest corresponding to a single cell; c) Measuring at least one derived property, and, optionally, at least one direct property of said areas of interest, where said one or more properties is a selection property; d) Selecting a subset of said plurality of microwells, where said microwells belonging to the subset contain areas of interest selected based on said at least one selection property; e) Extrapolating an output parameter from a property measured in the set of areas of interest selected, where said property is defined as output property, said output property being distinct from said selection properties where said output parameter is the processing of an output property measured in said set of areas of interest. In a further aspect, there are claimed a system for subjecting a plurality of microwells containing cells to a high-content assay and a computer program which comprises instructions for subjecting a plurality of microwells containing cells to a high-content assay.

A system structured to monitor particle contamination of different equipment or machinery categories including power pressure systems having a monitoring module. The monitoring module includes an intake structure and an exhaust structure, wherein the intake structure is connected in fluid communication with an air intake or air supply the power pressure systems being monitored. The monitoring module further includes alarm capabilities structured to communicate alarm signals to local and remote operating personnel. In addition, a particle sensor module is structured to determine predetermined particle characteristics of an air sample received from the power pressure systems. An electronic control module (ECM) is connected in on-off activating relation to the intake and exhaust structures and the particle sensor. As such, the ECM is operative to capture and analyze an air sample from the power pressure systems within said particle sensor and categorize the particle characteristics within the captured air sample as normal or abnormal dependent on levels of contamination.

A portable air quality monitoring device is disclosed that can identify the type of particles in the air. This device takes images of particles in the air and compares them with a library of particles in its memory to identify the type of particles. The device has a housing that draws ambient air into the system and takes microscopic images of the flowing particles and droplets using flash photography. The device can be stand alone or can connect to the back of a mobile phone and use the mobile phone camera and light. People can upload their local air quality data online for all to see the local air quality.