Transmission-selective muscle pathology induced by the active propagation of mutant huntingtin across the human neuromuscular synapse.

Neuron-to-neuron transmission of aggregation-prone, misfolded proteins may potentially explain the spatiotemporal accumulation of pathological lesions in the brains of patients with neurodegenerative protein-misfolding diseases (PMDs). However, little is known about protein transmission from the central nervous system to the periphery, or how this propagation contributes to PMD pathology. To deepen our understanding of these processes, we established two functional neuromuscular systems derived from human iPSCs.

Molecular characterization of chronic cutaneous wounds reveals subregion- and wound type-specific differential gene expression.

A limited understanding of the pathology underlying chronic wounds has hindered the development of effective diagnostic markers and pharmaceutical interventions. This study aimed to elucidate the molecular composition of various common chronic ulcer types to facilitate drug discovery strategies. We conducted a comprehensive analysis of leg ulcers (LUs), encompassing venous and arterial ulcers, foot ulcers (FUs), pressure ulcers (PUs), and compared them with surgical wound healing complications (WHCs).

Microplastic contamination in commercial fish feeds: A major concern for sustainable aquaculture from a developing country.

Plastic pollution has become a global issue nowadays. Due to the increased population in developing countries, we largely depend on fish from our aquaculture industry to meet the required protein demand. Though several studies documented plastic ingestion in freshwater and marine organisms, very limited studies have been conducted to elucidate microplastic (MP) contamination in commercial fish feed.

Potential antiviral peptides against the nucleoprotein of SARS-CoV-2.

Unlabelled: Nucleoprotein is a conserved structural protein of SARS-CoV-2, which is involved in several functions, including replication, packaging, and transcription. In this research, 21 antiviral peptides that are known to have inhibitory function against nucleoprotein in several other viruses, were screened computationally against the nucleoprotein of SARS-CoV-2. The complexes of five best performing peptides (AVP1142, AVP1145, AVP1148, AVP1150, AVP1155) with nucleoprotein were selected for subsequent screening via 5 ns molecular dynamics (MD) simulation.

HistoNet: A Deep Learning-Based Model of Normal Histology.

We introduce HistoNet, a deep neural network trained on normal tissue. On 1690 slides with rat tissue samples from 6 preclinical toxicology studies, tissue regions were outlined and annotated by pathologists into 46 different tissue classes. From these annotated regions, we sampled small 224 × 224 pixels images (patches) at 6 different levels of magnification.

Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology-A Machine Learning Approach to Histopathology.

Several deep learning approaches have been proposed to address the challenges in computational pathology by learning structural details in an unbiased way. Transfer learning allows starting from a learned representation of a pretrained model to be directly used or fine-tuned for a new domain. However, in histopathology, the problem domain is tissue-specific and putting together a labelled data set is challenging.

Morphological Deconvolution of Beta-Lactam Polyspecificity in E. coli.

Beta-lactams comprise one of the earliest classes of antibiotic therapies. These molecules covalently inhibit enzymes from the family of penicillin-binding proteins (PBPs), which are essential in construction of the bacterial cell wall. As a result, beta-lactams cause striking changes to cellular morphology, the nature of which varies by the range of PBPs simultaneously engaged in the cell.

A multi-scale convolutional neural network for phenotyping high-content cellular images.

Motivation: Identifying phenotypes based on high-content cellular images is challenging. Conventional image analysis pipelines for phenotype identification comprise multiple independent steps, with each step requiring method customization and adjustment of multiple parameters.

Results: Here, we present an approach based on a multi-scale convolutional neural network (M-CNN) that classifies, in a single cohesive step, cellular images into phenotypes by using directly and solely the images' pixel intensity values.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices.

The structure of the cornified claw sheath in the domesticated cat (Felis catus): implications for the claw-shedding mechanism and the evolution of cornified digital end organs.

The morphology of cornified structures is notoriously difficult to analyse because of the extreme range of hardness of their component tissues. Hence, a correlative approach using light microscopy, scanning electron microscopy, three-dimensional reconstructions based on x-ray computed tomography data, and graphic modeling was applied to study the morphology of the cornified claw sheath of the domesticated cat as a model for cornified digital end organs. The highly complex architecture of the cornified claw sheath is generated by the living epidermis that is supported by the dermis and distal phalanx.