Pan-Ret: a semi-supervised framework for scalable detection of pan-retinal diseases.

It has been shown in recent years that a range of optical diseases have early manifestation in retinal fundus images. It is becoming increasingly important to separate the regions of interest (RoI) upfront in the automated classification pipeline in order to ensure the alignment of the disease diagnosis with clinically relevant visual features. In this work, we introduce Pan-Ret, a semi-supervised framework which starts with locating the abnormalities in the biomedically relevant RoIs of a retinal image in an "annotation-agnostic" fashion.

Averrhoa carambola Leaf Extract Induces Apoptosis-Like Death with Increased ROS Generation in Leishmania donovani.

Purpose: The parasitic disease leishmaniasis is responsible for high mortality and morbidity rates worldwide. The visceral form is the most severe form of leishmaniasis (or leishmaniosis), which is caused predominantly by Leishmania donovani. Currently, clinically recommended antileishmanial drugs are not convenient because of several medical complications and resistance issues.

Computational analysis of pathogen-host interactome for fast and low-risk in-silico drug repurposing in emerging viral threats like Mpox.

Monkeypox (Mpox), a zoonotic illness triggered by the monkeypox virus (MPXV), poses a significant threat since it may be transmitted and has no cure. This work introduces a computational method to predict Protein-Protein Interactions (PPIs) during MPXV infection. The objective is to discover prospective drug targets and repurpose current potential Food and Drug Administration (FDA) drugs for therapeutic purposes.

MSO-GP: 3-D segmentation of large and complex conjoined tree structures.

Robust segmentation of large and complex conjoined tree structures in 3-D is a major challenge in computer vision. This is particularly true in computational biology, where we often encounter large data structures in size, but few in number, which poses a hard problem for learning algorithms. We show that merging multiscale opening with geodesic path propagation, can shed new light on this classic machine vision challenge, while circumventing the learning issue by developing an unsupervised visual geometry approach (digital topology/morphometry).

Computational drug repurposing for viral infectious diseases: a case study on monkeypox.

The traditional method of drug reuse or repurposing has significantly contributed to the identification of new antiviral compounds and therapeutic targets, enabling rapid response to developing infectious illnesses. This article presents an overview of how modern computational methods are used in drug repurposing for the treatment of viral infectious diseases. These methods utilize data sets that include reviewed information on the host's response to pathogens and drugs, as well as various connections such as gene expression patterns and protein-protein interaction networks.

Correction: Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

[This corrects the article DOI: 10.1371/journal.pone.

RUBic: rapid unsupervised biclustering.

Biclustering of biologically meaningful binary information is essential in many applications related to drug discovery, like protein-protein interactions and gene expressions. However, for robust performance in recently emerging large health datasets, it is important for new biclustering algorithms to be scalable and fast. We present a rapid unsupervised biclustering (RUBic) algorithm that achieves this objective with a novel encoding and search strategy.

Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

Robust semantic segmentation of tumour micro-environment is one of the major open challenges in machine learning enabled computational pathology. Though deep learning based systems have made significant progress, their task agnostic data driven approach often lacks the contextual grounding necessary in biomedical applications. We present a novel fuzzy water flow scheme that takes the coarse segmentation output of a base deep learning framework to then provide a more fine-grained and instance level robust segmentation output.

Learning Cellular Phenotypes through Supervision.

Image-based cell phenotyping is an important and open problem in computational pathology. The two principal challenges are: 1) making the cell cluster properties insensitive to experimental settings (like seed point and feature selection) and 2) ensuring that the phenotypes emerging are biologically relevant and support clinical reporting. To gauge robustness, we first compare the consistency of the phenotypes using self-supervised and supervised features.

Automated Annotator: Capturing Expert Knowledge for Free.

Deep learning enabled medical image analysis is heavily reliant on expert annotations which is costly. We present a simple yet effective automated annotation pipeline that uses autoencoder based heatmaps to exploit high level information that can be extracted from a histology viewer in an unobtrusive fashion. By predicting heatmaps on unseen images the model effectively acts like a robot annotator.

Epigallocatechin Gallate with Potent Anti- Activity Binds Efficiently to Its Histone-like DNA Binding Protein.

()-a human gastric pathogen-forms a major risk factor for the development of various gastric pathologies such as chronic inflammatory gastritis, peptic ulcer, lymphomas of mucosa-associated lymphoid tissues, and gastric carcinoma. The complete eradication of infection is the primary objective of treating any -associated gastric condition. However, declining eradication efficiencies, off-target effects, and patient noncompliance to prolong and broad-spectrum antibiotic treatments has spurred the clinical interest to search for alternative effective and safer therapeutic options.

Bioassay-based Corchorus capsularis L. leaf-derived β-sitosterol exerts antileishmanial effects against Leishmania donovani by targeting trypanothione reductase.

Leishmaniasis, a major neglected tropical disease, affects millions of individuals worldwide. Among the various clinical forms, visceral leishmaniasis (VL) is the deadliest. Current antileishmanial drugs exhibit toxicity- and resistance-related issues.

Prevalence and antibiogram of coagulase negative Staphylococci in bioaerosols from different indoors of a university in India.

Background: Staphylococci species are the major constituents of infectious bioaerosols, particularly methicillin-resistant Staphylococci (MRS) have serious health impacts. Here, the bacterial burden was quantified, especially prevalence of MRS in bioaerosols collected from indoors of Dr. B.

Exquisite binding interaction of 18β-Glycyrrhetinic acid with histone like DNA binding protein of Helicobacter pylori: A computational and experimental study.

The Histone-like DNA binding protein is one of the most abundant nucleoid associated protein expressed by human gastric-pathogen, Helicobacter pylori (H. pylori). The protein -referred here as Hup- has been recognized as a potential drug target for developing therapeutic strategies against H.

Curative efficacy of purified serine protease inhibitor PTF3 from potato tuber in experimental visceral leishmaniasis.

To overcome the drug toxicity and frequent resistance of parasites against the conventional drugs for the healing of human visceral leishmaniasis, innovative plant derived antileishmanial components are very imperative. Fuelled by the complications of clinically available antileishmanial drugs, a novel potato serine protease inhibitor was identified with its efficacy on experimental visceral leishmaniasis (VL). The serine protease inhibitors from potato tuber extract (PTEx) bearing molecular mass of 39 kDa (PTF1), 23 kDa (PTF2) and 17 kDa (PTF3) were purified and identified.

Prediction of Thermodynamic Properties of Levulinic Acid via Molecular Simulation Techniques.

Second-generation biofuels are a complex mixture of organic compounds that can be further processed to hydrocarbon fuels and other valuable chemicals. One such chemical is levulinic acid (IUPAC name: 4-oxo pentanoic acid), which is a highly versatile ketoacid obtained from cellulose present in agricultural byproducts. For oxygen-containing compounds that decompose at elevated temperatures and pressures, determining the vapor-liquid equilibria data at high temperatures via the experimental route may be challenging.

White jute (Corchorus capsularis L.) leaf extract has potent leishmanicidal activity against Leishmania donovani.

In pursuit of effective, safe and affordable antileishmanial drugs, the current study was designed to explore Corchorus capsularis L. leaf extract (CCEx) as an effective leishmanicidal substitute against Leishmania donovani. The leaf extract displays potent antileishmanial activity against L.

Drug Resistance in Protozoan Parasites: An Incessant Wrestle for Survival.

Nowadays, drug resistance in parasites is considered to be one of the foremost concerns in health and disease management. It is interconnected worldwide and undermines the health of millions of people, threatening to grow worse. Unfortunately, it does not receive serious attention from every corner of society.