Reversible Hydration Composite Films for Evaporative Perspiration Control and Heat Stress Management.

Donning of personal protective equipment (PPE) in the healthcare sector has been intensified by the on-going COVID-19 pandemic around the globe. While extensive PPE provides protection, it typically limits moisture permeability and severely hinders the sweat evaporation process, resulting in greater heat stress on the personnel. Herein, a zinc-poly(vinyl alcohol) (Zn-PVA) composite film is fabricated by embedding a super-hygroscopic zinc-ethanolamine complex (Zn-complex) in the PVA matrix. By attaching the Zn-PVA composite film, the relative humidity (RH) inside the protective suit decreases from 91.0% to 48.2%. The reduced RH level, in turn, enhances evaporative cooling, hence bringing down the heat index from 64.6 to 40.0 °C at an air temperature of 35 °C, remarkably lowering the likelihood of heat stroke. The American Society for Testing and Materials tests conducted on a sweating manikin have also proven that the Zn-PVA composite films can significantly reduce the evaporative resistance of the protective suit by 90%. The low material cost, facile fabrication process, and reusability allow the Zn-PVA composition films to be readily available for healthcare workers worldwide. This application can be further extended to other occupations that are facing severe thermal discomfort and heat stress.

Multivariate profiling of neurodegeneration-associated changes in a subcellular compartment of neurons via image processing.

BACKGROUND: Dysfunction in the endolysosome, a late endosomal to lysosomal degradative intracellular compartment, is an early hallmark of some neurodegenerative diseases, in particular Alzheimer's disease. However, the subtle morphological changes in compartments of affected neurons are difficult to quantify quickly and reliably, making this phenotype inaccessible as either an early diagnostic marker, or as a read-out for drug screening. METHODS: We present a method for automatic detection of fluorescently labeled endolysosomes in degenerative neurons in situ. The Drosophila blue cheese (bchs) mutant was taken as a genetic neurodegenerative model for direct in situ visualization and quantification of endolysosomal compartments in affected neurons. Endolysosomal compartments were first detected automatically from 2-D image sections using a combination of point-wise multi-scale correlation and normalized correlation operations. This detection algorithm performed well at recognizing fluorescent endolysosomes, unlike conventional convolution methods, which are confounded by variable intensity levels and background noise. Morphological feature differences between endolysosomes from wild type vs. degenerative neurons were then quantified by multivariate profiling and support vector machine (SVM) classification based on compartment density, size and contrast distribution. Finally, we ranked these distributions according to their profiling accuracy, based on the backward elimination method. RESULTS: This analysis revealed a statistically significant difference between the neurodegenerative phenotype and the wild type up to a 99.9% confidence interval. Differences between the wild type and phenotypes resulting from overexpression of the Bchs protein are detectable by contrast variations, whereas both size and contrast variations distinguish the wild type from either of the loss of function alleles bchs1 or bchs58. In contrast, the density measurement differentiates all three bchs phenotypes (loss of function as well as overexpression) from the wild type. CONCLUSION: Our model demonstrates that neurodegeneration-associated endolysosomal defects can be detected, analyzed, and classified rapidly and accurately as a diagnostic imaging-based screening tool.