Exposures to hazardous airborne particles can pose a significant health risk to those routinely exposed in ambient air and industrial work environments. Measuring chemical composition and concentration of aerosol particles is important to preventing worker exposures and protecting health.
Tailoring the best treatments to cancer patients remains a highly important endeavor in the oncology field. However, personalized treatment courses are challenging to determine, and technologies or methods that can successfully be employed for precision oncology are lacking.
There is growing awareness that a wide variety of synthetic and natural compounds that may be present in water sources, such as streams, wells, and ground water, may lead to adverse health effects, including increased cancer risk. Even low concentrations of these compounds are of concern, as they may have biological effects at concentrations of parts per billion or less.
Computer and imaging technologies led to the development of digital pathology and the capture and storage of pathological specimens as digitally formatted images. The use of artificial intelligence (AI) in digital pathology, such as in three-dimensional (3D) reconstruction, requires analyses of high volumes of data. This results in increased demands for processing and acquisition of digital images of pathology samples. Increased usage cannot be met by the time-consuming, manual, and laborious methods currently used.
Vaccines have become one of the most important tools in the fight against cancers and infectious diseases. However, some vaccines have shown limitations due to their high cost and low immune responses. To overcome these limitations, bacteriophages were proposed for the development of more cost-effective, immunogenic vaccines. Phages have shown a strong ability to activate induced and adaptive immune systems. The genome of these viral particles can be engineered, and their surface proteins can be exploited for antigen display.
Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that are released from cells. EVs may contain proteins derived from their cells of origin with the potential as diagnostic biomarkers indicating the state of the cells when released. However, due to their small size (50-1000nm), the methods currently used to phenotype EVs have limited sensitivity and scale. A need exists for development of novel technologies improving EV detection and phenotyping.
Multi-parameter flow cytometry has been extensively used in multiple disciplines of biological discoveries, including immunology and cancer research. However, the disadvantage of traditional flow cytometry platforms using excitation lasers and fluorescence detectors is spectral overlap when using multiple dyes on the same biological sample. Metaethical compensation of spectral overlap could only be effective to a certain degree. Mass cytometry is advantageous compared to flow cytometry but is pricey and requires highly skilled operators.
The development of precision medicine approaches for DLBCL (Diffuse Large B Cell Lymphoma) is complicated by its genetic, phenotypic and clinical heterogeneity. Current classification methods do not fully explain the observed differences in clinical outcomes to current chemotherapy and targeted therapy. Therefore, better analytical methods to classify and predict DLBCL patients’ treatment response are needed.
Computer and imaging technologies led to the development of digital pathology and the capture and storage of pathological specimens as digitally formatted images. The use of artificial intelligence (AI) in digital pathology, such as in three-dimensional (3D) reconstruction, requires analyses of high volumes of data. This resulted in increased demands for processing and acquisition of digital images of pathology samples. Increased usage cannot be met by the time-consuming, manual, and laborious methods currently used.
Three-dimensional (3D) cell cultures systems are important for studying cell biology because they provide in vivo-like microenvironments more physiologically relevant than two-dimensional (2D) culture systems. In 3D culture systems, cells are grown in culture matrixes and turn into spheroids and organoids later processed for downstream analysis by microscopy and histology techniques. The processing of 3D cultures for analysis by microscopy or histology is laborious and time-consuming due to incompatibility of the 3D culture vessels and the microscopy and pathology blocks.