Automated annotation of disease subtypes.

Background: Distinguishing diseases into distinct subtypes is crucial for study and effective treatment strategies. The Open Targets Platform (OT) integrates biomedical, genetic, and biochemical datasets to empower disease ontologies, classifications, and potential gene targets. Nevertheless, many disease annotations are incomplete, requiring laborious expert medical input.

Detecting anomalous proteins using deep representations.

Many advances in biomedicine can be attributed to identifying unusual proteins and genes. Many of these proteins' unique properties were discovered by manual inspection, which is becoming infeasible at the scale of modern protein datasets. Here, we propose to tackle this challenge using anomaly detection methods that automatically identify unexpected properties.

What's next? Forecasting scientific research trends.

Scientific research trends and interests evolve over time. The ability to identify and forecast these trends is vital for educational institutions, practitioners, investors, and funding organizations. In this study, we predict future trends in scientific publications using heterogeneous sources, including historical publication time series from PubMed, research and review articles, pre-trained language models, and patents.

Optothermal Needle-Free Injection of Vaterite Nanocapsules.

The propulsion and acceleration of nanoparticles with light have both fundamental and applied significance across many disciplines. Needle-free injection of biomedical nano cargoes into living tissues is among the examples. Here a new physical mechanism of laser-induced particle acceleration is explored, based on abnormal optothermal expansion of mesoporous vaterite cargoes.

Gilded vaterite optothermal transport in a bubble.

Laser beams, capable of controlling the mechanical motion of micron-scale objects, can serve as a tool, enabling investigations of numerous interaction scenarios under full control. Beyond pure electromagnetic interactions, giving rise to conventional gradient forces and radiation pressure, environment-induced thermal effects can play a role and, in certain cases, govern the dynamics. Here we explore a thermocapillary Marangoni effect, which is responsible for creating long-range few hundreds of nano-Newton forces, acting on a bubble around a 'gilded vaterite' nanoparticle.

Inferring microRNA regulation: A proteome perspective.

Post-transcriptional regulation in multicellular organisms is mediated by microRNAs. However, the principles that determine if a gene is regulated by miRNAs are poorly understood. Previous works focused mostly on miRNA seed matches and other features of the 3'-UTR of transcripts.

Revisiting the Risk Factors for Endometriosis: A Machine Learning Approach.

Endometriosis is a condition characterized by implants of endometrial tissues into extrauterine sites, mostly within the pelvic peritoneum. The prevalence of endometriosis is under-diagnosed and is estimated to account for 5-10% of all women of reproductive age. The goal of this study was to develop a model for endometriosis based on the UK-biobank (UKB) and re-assess the contribution of known risk factors to endometriosis.

ProteinBERT: a universal deep-learning model of protein sequence and function.

Summary: Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optimized for text analysis. We introduce ProteinBERT, a deep language model specifically designed for proteins.

Amplified spontaneous emission and gain in highly concentrated Rhodamine-doped peptide derivative.

Bioinspired fluorescence, being widely explored for imaging purposes, faces challenges in delivering bright biocompatible sources. While quite a few techniques have been developed to reach this goal, encapsulation of high-quantum yield fluorescent dyes in natural biological forms suggest achieving superior light-emitting characteristics, approaching amplified spontaneous emission and even lasing. Here we compare gain capabilities of highly concentrated Rhodamine B solutions with a newly synthesized biocompatible peptide derivative hybrid polymer/peptide material, RhoB-PEG1300-F6, which contains the fluorescent covalently bound dye.

The language of proteins: NLP, machine learning & protein sequences.

Natural language processing (NLP) is a field of computer science concerned with automated text and language analysis. In recent years, following a series of breakthroughs in deep and machine learning, NLP methods have shown overwhelming progress. Here, we review the success, promise and pitfalls of applying NLP algorithms to the study of proteins.

Strong bonding of corneal incisions using a noncontact fiber-optic laser soldering method.

Suturing of corneal incisions requires significant skill. We demonstrate a noncontact method that will simplify the bonding process. 5-mm-long penetrating vertical and slanted incisions were made in corneas of eyes, extracted from dead piglets.

Overlooked Short Toxin-Like Proteins: A Shortcut to Drug Design.

Short stable peptides have huge potential for novel therapies and biosimilars. Cysteine-rich short proteins are characterized by multiple disulfide bridges in a compact structure. Many of these metazoan proteins are processed, folded, and secreted as soluble stable folds.

ASAP: a machine learning framework for local protein properties.

Determining residue-level protein properties, such as sites of post-translational modifications (PTMs), is vital to understanding protein function. Experimental methods are costly and time-consuming, while traditional rule-based computational methods fail to annotate sites lacking substantial similarity. Machine Learning (ML) methods are becoming fundamental in annotating unknown proteins and their heterogeneous properties.

An expanded evaluation of protein function prediction methods shows an improvement in accuracy.

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.

ProFET: Feature engineering captures high-level protein functions.

Motivation: The amount of sequenced genomes and proteins is growing at an unprecedented pace. Unfortunately, manual curation and functional knowledge lag behind. Homologous inference often fails at labeling proteins with diverse functions and broad classes.

NeuroPID: a classifier of neuropeptide precursors.

Neuropeptides (NPs) are short secreted peptides produced in neurons. NPs act by activating signaling cascades governing broad functions such as metabolism, sensation and behavior throughout the animal kingdom. NPs are the products of multistep processing of longer proteins, the NP precursors (NPPs).

NeuroPID: a predictor for identifying neuropeptide precursors from metazoan proteomes.

Motivation: The evolution of multicellular organisms is associated with increasing variability of molecules governing behavioral and physiological states. This is often achieved by neuropeptides (NPs) that are produced in neurons from a longer protein, named neuropeptide precursor (NPP). The maturation of NPs occurs through a sequence of proteolytic cleavages.

Short toxin-like proteins attack the defense line of innate immunity.

ClanTox (classifier of animal toxins) was developed for identifying toxin-like candidates from complete proteomes. Searching mammalian proteomes for short toxin-like proteins (coined TOLIPs) revealed a number of overlooked secreted short proteins with an abundance of cysteines throughout their sequences. We applied bioinformatics and data-mining methods to infer the function of several top predicted candidates.

A systematic review of CPAP adherence across age groups: clinical and empiric insights for developing CPAP adherence interventions.

Continuous positive airway pressure (CPAP) is a highly efficacious treatment for obstructive sleep apnea (OSA) but adherence to the treatment limits its overall effectiveness across all age groups of patients. Factors that influence adherence to CPAP include disease and patient characteristics, treatment titration procedures, technological device factors and side effects, and psychological and social factors. These influential factors have guided the development of interventions to promote CPAP adherence.

Pediatric polysomnography: the patient and family perspective.

Study Objectives: The gold-standard test used to diagnose childhood obstructive sleep apnea is polysomnography. However, this test requires an overnight stay at a sleep laboratory and the attachment of multiple sensors to the patient. The long-term impact of this testing on the child and family are not known.

Laparoscopic hysterectomy versus total abdominal hysterectomy: a comparative study.

Objective: The objective of this study was to compare the intraoperative and short-term postoperative complications of laparoscopic hysterectomy and total abdominal hysterectomy.

Study Design: Retrospective study of 167 women who had laparoscopic hysterectomy and 119 women who had total abdominal hysterectomy. For assessing the learning curve, the laparoscopic hysterectomies were further subdivided to the first 30 hysterectomies and the later hysterectomies.

A common mode of attraction of larvae and adults of insect predators to the sex pheromone of their prey (Hemiptera: Matsucoccidae).

The attraction of several adult predators, genera Elatophilus, Hemerobius and Sympherobius, to the sex pheromones of pine bast scales, Matsucoccus Cockerell, has already been demonstrated. Here, the hypothesis that the larvae of these predators are similarly attracted to the host prey sex pheromone is tested. The response of predators was tested in field trials using pine tree arenas baited with the sex pheromones of M.

Approaches for introducing high molecular diversity in scaffolds: fast parallel synthesis of highly substituted 1H-quinolin-4-one libraries.

We have developed a two steps strategy for the parallel synthesis of highly diversified quinolin-ones. In the first step we have combined and improved different synthetic methods for generating quinolin-4-ones bearing four different substitutions at specific positions using round bottomed flasks. The synthesis was assessed for a large number of substituted quinolin-4-ones.

Everyday life of Jews under Nazi occupation: methodological issues.

Despite the dire circumstances of Jews under Nazi occupation, individuals continued to persevere in their efforts to maintain patterns of everyday life. An understanding of daily routines may help us comprehend the reality of the Holocaust, but it may also contribute to the trivialization and banalization of the topic. To counter this danger, the methodology proposed in this article asserts that the individual's struggle reveals another perspective on the state of mind and the social order of various strata of Jewish society under Nazi occupation.