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). To explore the pathophysiological mechanisms and identify similarities or differences within wounds, we dissected wounds into distinct subregions, including the wound bed, border, and peri-wound areas, and compared them against intact skin. By correlating histopathology, RNA sequencing (RNA-Seq), and immunohistochemistry (IHC), we identified unique genes, pathways, and cell type abundance patterns in each wound type and subregion. These correlations aim to aid clinicians in selecting targeted treatment options and informing the design of future preclinical and clinical studies in wound healing. Notably, specific genes, such as PITX1 and UPP1, exhibited exclusive upregulation in LUs and FUs, potentially offering significant benefits to specialists in limb preservation and clinical treatment decisions. In contrast, comparisons between different wound subregions, regardless of wound type, revealed distinct expression profiles. The pleiotropic chemokine-like ligand GPR15L (C10orf99) and transmembrane serine proteases TMPRSS11A/D were significantly upregulated in wound border subregions. Interestingly, WHCs exhibited a nearly identical transcriptome to PUs, indicating clinical relevance. Histological examination revealed blood vessel occlusions with impaired angiogenesis in chronic wounds, alongside elevated expression of genes and immunoreactive markers related to blood vessel and lymphatic epithelial cells in wound bed subregions. Additionally, inflammatory and epithelial markers indicated heightened inflammatory responses in wound bed and border subregions and reduced wound bed epithelialization. In summary, chronic wounds from diverse anatomical sites share common aspects of wound pathophysiology but also exhibit distinct molecular differences. These unique molecular characteristics present promising opportunities for drug discovery and treatment, particularly for patients suffering from chronic wounds. The identified diagnostic markers hold the potential to enhance preclinical and clinical trials in the field of wound healing.

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. Therefore, this study was designed to identify, quantify, and characterize microplastics (MPs) in commercial fish feeds in Bangladesh and assess possible health risks in fish consuming different commercial fish feeds. All fish feed samples were 100 % contaminated with MPs, where the mean abundance of MPs ranged between 500 and 2200 MPs/kg. No significant differences among different types of feeds (e.g., starter, grower, and finisher) were observed in terms of MPs abundance (F = 0.999, p = 0.385). This study revealed that fiber was the most dominant shape of MPs (90 %), while the most dominant color of MPs was red (34 %), followed by black (31 %) and blue (19 %). The 100-1500 µm size class covers 88 % of the total MPs in the collected fish feed samples. Identified polymers in the samples were polyethylene (PE, 37.71 %), polyvinyl chloride (PVC, 27.14 %), polypropylene (PP, 22.08 %), and polyethylene terephthalate (PET, 13.07 %), respectively, where PE and PVC fall under the risk category IV to V. The Pollution load index (PLI) values of all fish feed samples were <10, indicating the risk category of I (low risk). Therefore, this study highly recommended avoiding plastic materials in the packaging and storing purposes of feed ingredients in the feed mills to ensure contamination-free fish feed for sustainable aquaculture.

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

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. Two peptides, namely AVP1145 and AVP1155, came out as promising candidates and hence were selected for 200 ns MD simulation for further validation, incorporating a DMPC-based membrane environment. In the long MD simulation, both AVP1155 and AVP1145 utilized multiple residues-mainly aromatic, acidic, and nonpolar residues-as interacting points to remain in contact with the nucleoprotein and formed predominantly hydrogen bonds along with hydrophobic and electrostatic interactions. However, AVP1155 proved to be superior to AVP1145 when its complex with nucleoprotein was analyzed in terms of root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent accessible surface area and free energy landscape. In a nutshell, the findings of this research may guide future studies in the development of selective peptide inhibitors of SARS-CoV-2 nucleoprotein. Supplementary Information: The online version contains supplementary material available at 10.1007/s11696-022-02514-4.

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. One was suitable for long-term high-throughput live-cell imaging and the other was adapted to a microfluidic system assuring that connectivity between motor neurons and muscle cells was restricted to the neuromuscular junction. We show that the Huntington's disease (HD)-associated mutant HTT exon 1 protein (mHTTEx1) is transmitted from neurons to muscle cells across the human neuromuscular junction. We found that transmission is an active and dynamic process that starts before aggregate formation and is regulated by synaptic activity. We further found that transmitted mHTTEx1 causes HD-relevant pathology at both molecular and functional levels in human muscle cells, even in the presence of the ubiquitous expression of mHTTEx1. In conclusion, we have uncovered a causal link between mHTTEx1 synaptic transmission and HD pathology, highlighting the therapeutic potential of blocking toxic protein transmission in PMDs.

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. Using 4 studies as training set and 2 studies as test set, we trained VGG-16, ResNet-50, and Inception-v3 networks separately at each magnification level. Among these model architectures, Inception-v3 and ResNet-50 outperformed VGG-16. Inception-v3 identified the tissue from query images, with an accuracy up to 83.4%. Most misclassifications occurred between histologically similar tissues. Investigation of the features learned by the model (embedding layer) using Uniform Manifold Approximation and Projection revealed not only coherent clusters associated with the individual tissues but also subclusters corresponding to histologically meaningful structures that had not been annotated or trained for. This suggests that the histological representation learned by HistoNet could be useful as the basis of other machine learning algorithms and data mining. Finally, we found that models trained on rat tissues can be used on non-human primate and minipig tissues with minimal retraining.

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. On the other hand, whole slide-level annotations, such as biomarker levels, are much easier to obtain. We compare two pretrained models, one histology-specific and one from ImageNet on various computational pathology tasks. We show that a domain-specific model (HistoNet) contains richer information for biomarker classification, localization of biomarker-relevant morphology within a slide, and the prediction of expert-graded features. We use a weakly supervised approach to discriminate slides based on biomarker level and simultaneously predict which regions contribute to that prediction. We employ multitask learning to show that learned representations correlate with morphological features graded by expert pathologists. All of these results are demonstrated in the context of renal toxicity in a mechanistic study of compound toxicity in rat models. Our results emphasize the importance of histology-specific models and their knowledge representations for solving a wide range of computational pathology tasks.

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. The traditional method of exploring beta-lactam polyspecificity is a gel-based binding assay which is low-throughput and typically is run  ex situ in cell extracts. Here, we describe a medium-throughput, image-based assay combined with machine learning methods to automatically profile the activity of beta-lactams in E. coli cells. By testing for morphological change across a panel of strains with perturbations to individual PBP enzymes, our approach automatically and quantifiably relates different beta-lactam antibiotics according to their preferences for individual PBPs in cells. We show the potential of our approach for guiding the design of novel inhibitors toward different PBP-binding profiles by predicting the mechanisms of two recently reported PBP inhibitors.

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. The only parameters in the approach are the weights of the neural network, which are automatically optimized based on training images. The approach requires no a priori knowledge or manual customization, and is applicable to single- or multi-channel images displaying single or multiple cells. We evaluated the classification performance of the approach on eight diverse benchmark datasets. The approach yielded overall a higher classification accuracy compared with state-of-the-art results, including those of other deep CNN architectures. In addition to using the network to simply obtain a yes-or-no prediction for a given phenotype, we use the probability outputs calculated by the network to quantitatively describe the phenotypes. This study shows that these probability values correlate with chemical treatment concentrations. This finding validates further our approach and enables chemical treatment potency estimation via CNNs. AVAILABILITY AND IMPLEMENTATION: The network specifications and solver definitions are provided in Supplementary Software 1. CONTACT: william_jose.godinez_navarro@novartis.com or xian-1.zhang@novartis.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

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. The latter is characterized by an ossified unguicular hood, which overhangs the bony articular base and unguicular process of the distal phalanx and creates an unguicular recess. The dermis covers the complex surface of the bony distal phalanx but also creates special structures, such as a dorsal dermal papilla that points distally and a curved ledge on the medial and lateral sides of the unguicular process. The hard-cornified external coronary horn and proximal cone horn form the root of the cornified claw sheath within the unguicular recess, which is deeper on the dorsal side than on the medial and lateral sides. As a consequence, their rate of horn production is greater dorsally, which contributes to the overall palmo-apical curvature of the cornified claw sheath. The external coronary and proximal cone horn is worn down through normal use as it is pushed apically. The hard-cornified apical cone horn is generated by the living epidermis enveloping the base and free part of the dorsal dermal papilla. It forms nested horn cones that eventually form the core of the hardened tip of the cornified claw. The sides of the cornified claw sheath are formed by the newly described hard-cornified blade horn, which originates from the living epidermis located on the slanted face of the curved ledge. As the blade horn is moved apically, it entrains and integrates the hard-cornified parietal horn on its internal side. It is covered by the external coronary and proximal cone horn on its external side. The soft-cornified terminal horn extends distally from the parietal horn and covers the dermal claw bed at the tip of the uniguicular process, thereby filling the space created by the converging apical cone and blade horn. The soft-cornified sole horn fills the space between the cutting edges of blade horn on the palmar side of the cornified claw sheath. The superficial soft-cornified perioplic horn is produced on the internal side of the unguicular pleat, which surrounds the root of the cornified claw sheath. The shedding of apical horn caps is made possible by the appearance of microcracks in the superficial layers of the external coronary and proximal cone horn in the course of deformations of the cornified claw sheath, which is subjected to tensile forces during climbing or prey catching. These microcracks propagate tangentially through the coronary horn and do not injure the underlying living epidermal and dermal tissues. This built-in shedding mechanism maintains sharp claw tips and ensures the freeing of the claws from the substrate.