Structural basis of transcription: RNA polymerase II substrate binding and metal coordination using a free-electron laser.

Catalysis and translocation of multisubunit DNA-directed RNA polymerases underlie all cellular mRNA synthesis. RNA polymerase II (Pol II) synthesizes eukaryotic pre-mRNAs from a DNA template strand buried in its active site. Structural details of catalysis at near-atomic resolution and precise arrangement of key active site components have been elusive.

Early archaeological evidence of wheat and cotton from medieval Ile-Ife, Nigeria.

This study reports the earliest directly dated occurrence of archaeological wheat and cotton in the humid forests of West Africa. These are the first archaeobotanical results from the medieval urban center of Ile-Ife, southwestern Nigeria, best known for its famous artworks. Both wheat and cotton likely spread through trans-Saharan trade networks that laid the foundation for later European trade systems.

A posture subspace in primary motor cortex.

To generate movements, the brain must combine information about movement goal and body posture. Motor cortex (M1) is a key node for the convergence of these information streams. How are posture and goal information organized within M1's activity to permit the flexible generation of movement commands? To answer this question, we recorded M1 activity while monkeys performed a variety of tasks with the forearm in a range of postures.

COVID-19 vaccine uptake and intention of Black adults: A county-wide analysis of an online survey.

Background: There are demonstrated racial inequities in coronavirus 2019 (COVID-19) disease burden, and the initial vaccine rollout did not equitably address these disparities.

Methods: We conducted analyses of a national Facebook survey restricted to Black adult residents of Allegheny County, Pennsylvania for the period of May 2021 to January 2022. We assessed the associations between demographics, health status, social normative context, perceived racial discrimination, and beliefs about COVID-19 mitigation strategies on vaccine uptake and intention and compared reasons reported for vaccine hesitancy, and vaccine non-intention among the unvaccinated.

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance.

Enhancing Hypotension Prediction in Real-time Patient Monitoring Through Deep Learning: A Novel Application of XResNet with Contrastive Learning and Value Attention Mechanisms.

The precise prediction of hypotension is vital for advancing preemptive patient care strategies. Traditional machine learning approaches, while instrumental in this field, are hampered by their dependence on structured historical data and manual feature extraction techniques. These methods often fall short of recognizing the intricate patterns present in physiological signals.

Derivation and dynamics of discrete population models with distributed delay in reproduction.

We introduce a class of discrete single species models with distributed delay in the reproductive process and a cohort dependent survival function that accounts for survival pressure during that delay period. These delay recurrences track the mature population for species in which individuals reach maturity after at least τ and at most τ+τ breeding cycles. Under realistic model assumptions, we prove the existence of a critical delay threshold, τ˜.

Co-flowering richness has variable effects on pollen quantity and quality limitation in four Clarkia species.

Background And Aims: Pollination failure occurs from insufficient pollen quantity or quality. However, the relative contributions of pollen quantity vs. quality to overall pollen limitation, and how this is affected by the co-flowering context, remain unknown for most plant populations.

Predicting individual differences in preschoolers' numeracy and geometry knowledge: The role of understanding abstract relations between objects and quantities.

Preschoolers' mathematics knowledge develops early and varies substantially. The current study focused on two ontogenetically early emerging cognitive skills that may be important predictors of later math skills (i.e.

How Well Can Quantum Embedding Method Predict the Reaction Profiles for Hydrogenation of Small Li Clusters?

Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits.

popDMS infers mutation effects from deep mutational scanning data.

Summary: Deep mutational scanning (DMS) experiments provide a powerful method to measure the functional effects of genetic mutations at massive scales. However, the data generated from these experiments can be difficult to analyze, with significant variation between experimental replicates. To overcome this challenge, we developed popDMS, a computational method based on population genetics theory, to infer the functional effects of mutations from DMS data.

Towards cross-application model-agnostic federated cohort discovery.

Objectives: To demonstrate that 2 popular cohort discovery tools, Leaf and the Shared Health Research Information Network (SHRINE), are readily interoperable. Specifically, we adapted Leaf to interoperate and function as a node in a federated data network that uses SHRINE and dynamically generate queries for heterogeneous data models.

Materials And Methods: SHRINE queries are designed to run on the Informatics for Integrating Biology & the Bedside (i2b2) data model.

Deep learning-based dose prediction for magnetic resonance-guided prostate radiotherapy.

Background: Daily adaptive radiotherapy, as performed with the Elekta Unity MR-Linac, requires choosing between different adaptation methods, namely ATP (Adapt to Position) and ATS (Adapt to Shape), where the latter requires daily re-contouring to obtain a dose plan tailored to the daily anatomy. These steps are inherently resource-intensive, and quickly predicting the dose distribution and the dosimetric evaluation criteria while the patient is on the table could facilitate a fast selection of adaptation method and decrease the treatment times.

Purpose: In this work, we aimed to develop a deep-learning-based dose-prediction pipeline for prostate MR-Linac treatments.

Application of artificial backbone connectivity in the development of metalloenzyme mimics.

Metal-dependent enzymes are abundant and vital catalytic agents in nature. The functional versatility of metalloenzymes has made them common targets for improvement by protein engineering as well as mimicry by de novo designed sequences. In both strategies, the incorporation of non-canonical cofactors and/or non-canonical side chains has proved a useful tool.

A New Horizon for Understanding the Comparative Effectiveness for Cooling Prospectively Infants with Mild Encephalopathy.

The authors summarize the methodology for a new pragmatic comparative effectiveness research investigation, Cooling Prospectively Infants with Mild Encephalopathy (COOLPRIME), which uses sites' existing mild hypoxic-ischemic encephalopathy (HIE) treatment preference (hypothermia or normothermia) to assess hypothermia effectiveness and safety. COOLPRIME's primary aim is to determine the safety and effectiveness of hypothermia compared to normothermia in mild HIE. Engagement of Families and Community Affected by Hypoxic-Ischemic Encephalopathy strongly favored Effectiveness over Efficacy Trials leading to COOL PRIME design.

Diverse Relationships between Batrachochytrium Infections and Antimicrobial Peptide Defenses Across Leopard Frog Populations.

Antimicrobial peptides (AMPs) play a fundamental role in the innate defense against microbial pathogens, as well as other immune and non-immune functions. Their role in amphibian skin defense against the pathogenic fungus Batrachochytrium dendrobatidis (Bd) is exemplified by experiments in which depletion of host's stored AMPs increases mortality from infection. Yet, the question remains whether there are generalizable patterns of negative or positive correlations between stored AMP defenses and the probability of infection or infection intensity across populations and species.

Resonance-Assisted Self-Doping in Robust Open-Shell Ladder-Type Oligoaniline Analogues.

A novel resonance-assisted self-doping mechanism has been demonstrated in ladder-type oligoaniline-derived organic conductors. The new class of compounds has a unique structure incorporating acidic phenolic hydroxyl groups into the ladder-type cyclohexadiene-1,4-diimine core, enabling efficient resonance-assisted proton transfer and electronic doping without the need for external dopants. Mechanistic and computational studies confirm the open-shell, zwitterionic nature of the self-doped state and the significant role played by the dielectric environment.

Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.

The effective design of combinatorial libraries to balance fitness and diversity facilitates the engineering of useful enzyme functions, particularly those that are poorly characterized or unknown in biology. We introduce MODIFY, a machine learning (ML) algorithm that learns from natural protein sequences to infer evolutionarily plausible mutations and predict enzyme fitness. MODIFY co-optimizes predicted fitness and sequence diversity of starting libraries, prioritizing high-fitness variants while ensuring broad sequence coverage.

Mitigation of Fetal Radiation Injury from Mid-Gestation Total-body Irradiation by Maternal Administration of Mitochondrial-Targeted GS-Nitroxide JP4-039.

Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal radiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal radiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)-nitroxide radiation mitigator JP4-039.

Targeted delivery of bee venom to A549 lung cancer cells by PEGylate liposomal formulation: an apoptotic investigation.

This study focused on developing an optimal formulation of liposomes loaded with bee venom (BV) and coated with PEG (BV-Lipo-PEG). The liposomes were characterized using dynamic light scattering, transmission electron microscopy, and Fourier transform infrared spectroscopy. Among the liposomal formulations, F3 exhibited the narrowest size distribution with a low PDI value of 193.

An Umbrella Review of Body Image Concerns, Disordered Eating, and Eating Disorders in Elite Athletes.

Several systematic reviews and meta-analyses have been conducted to date indicating a high prevalence of disordered eating in elite athletes and associated risk factors. However, the substantial time burden associated with locating and comparing these reviews, which are varied in methodology and sampling focus, may be a barrier for informing policy and best practice as well as directing future research. This umbrella review aimed to provide a summary of evidence across published reviews regarding the prevalence and risk factors for disordered eating (including body image concerns and eating disorders) in elite athletes.