Trophic niche variation driven by water level fluctuations facilitates the co-occurrence of invasive tilapia species in a subtropical reservoir in China.

Investigating how multiple invasive fish species with similar ecological traits respond to different environmental conditions is crucial to understanding their successful invasion and coexistence. Here, we used stomach content analysis and stable isotope analysis to analyse the effects of water level fluctuation on the trophic niche plasticity of three dominant co-occurring invasive tilapia species (Coptodon zillii, Sarotherodon galilaeus, and Oreochromis niloticus) in the Shanmei Reservoir, southern China. We found that the tilapia species exhibited an iliophagous habit with dietary variations between the high-water (HW) and low-water (LW) level periods.

Evaluation of genomic mating approach based on genetic algorithms for long-term selection in Huaxi cattle.

Background: Genomic mating (GM) can effectively control the growth rate of inbreeding in population and achieve long-term sustainable genetic progress. However, the design of GM method and assessment of its effects during long-term selection have not been fully explored in beef cattle breeding.

Results: In this study, we constructed a simulated population based on the real genotypes of Huaxi cattle, where five generations of simulated breeding were carried out using the genomic optimal contribution selection (GOCS), genetic algorithms strategy and three traditional mating strategies.

Design and biological evaluation of candidate drugs against zoonotic porcine deltacoronavirus (PDCoV).

Porcine deltacoronavirus (PDCoV) is an emerging swine enteric coronavirus with zoonotic potential. PDCoV spillovers were recently detected in Haitian children with acute undifferentiated febrile illness, underscoring the urgent need to develop anti-PDCoV therapeutics. Coronavirus 3C-like protease (CoV 3CL) is essential for viral replication, and therefore provides an attractive target for drugs directed against CoV.

Route-level carbon dioxide emissions in intercity multimodal passenger transport: analytical framework and characteristics.

Understanding the CO emission characteristics and key mitigation pathways of intercity passenger transport is crucial for achieving sustainable development in the transport system. Using origin-destination data on travel between city pairs by various transportation modes, we employ the life cycle assessment (LCA) method to estimate route-level CO emissions from intercity multimodal passenger transport corridors, considering infrastructure construction and vehicle operation phases. Subsequently, a sensitivity analysis is conducted to assess the impact of 39 parameters associated with the construction phase, operation phase, and transportation modes on CO emissions from corridors.

Erythromycin disrupts Acinetobacter baumannii biofilms through destruction of the quorum sensing system.

Background: This study was conducted to explore the effects of erythromycin on biofilms comprising Acinetobacter baumannii (A baumannii).

Methods: To clarify the effect of erythromycin on the biofilms of A baumannii, we collected pure Ab strains isolated and identified from a variety of sample types extracted from patients in the microbiological laboratory of our hospital from April to August 2023, and divided them into an experimental group (treated with erythromycin) and a control group (without erythromycin). The morphology and quantity of A baumannii biofilm were observed at 24h, 48h, 72h, and 5d post-treatment, respectively, and the expression of quorum sensing (QS) system gene (abaI, abaR) mRNA was detected by fluorescence quantitative PCR.

Investigating the impact of temporal instability in smart roadway retrofitting on terrain-related crash injury severity.

The advancement of intelligent road systems in developing countries poses unique challenges in identifying risk factors and implementing safety strategies. The variability of factors affecting crash injury severity leads to different risks across levels of roadway smartness, especially in hazardous terrains, complicating the adaptation of smart technologies. Therefore, this study investigates the temporal instability of factors affecting injury severities in crashes across various terrains, with a focus on the evolution of road smartness.

Machine-learned molecular mechanics force fields from large-scale quantum chemical data.

The development of reliable and extensible molecular mechanics (MM) force fields-fast, empirical models characterizing the potential energy surface of molecular systems-is indispensable for biomolecular simulation and computer-aided drug design. Here, we introduce a generalized and extensible machine-learned MM force field, espaloma-0.3, and an end-to-end differentiable framework using graph neural networks to overcome the limitations of traditional rule-based methods.

Spatial-aware contrastive learning for cross-domain medical image registration.

Background: With the rapid advancement of medical imaging technologies, precise image analysis and diagnosis play a crucial role in enhancing treatment outcomes and patient care. Computed tomography (CT) and magnetic resonance imaging (MRI), as pivotal technologies in medical imaging, exhibit unique advantages in bone imaging and soft tissue contrast, respectively. However, cross-domain medical image registration confronts significant challenges due to the substantial differences in contrast, texture, and noise levels between different imaging modalities.

The Open Force Field Initiative: Open Software and Open Science for Molecular Modeling.

Force fields are a key component of physics-based molecular modeling, describing the energies and forces in a molecular system as a function of the positions of the atoms and molecules involved. Here, we provide a review and scientific status report on the work of the Open Force Field (OpenFF) Initiative, which focuses on the science, infrastructure and data required to build the next generation of biomolecular force fields. We introduce the OpenFF Initiative and the related OpenFF Consortium, describe its approach to force field development and software, and discuss accomplishments to date as well as future plans.

Rb-Doped Perovskite Oxides: Surface Enrichment and Structural Reconstruction During the Oxygen Evolution Reaction.

Alkali-metal doped perovskite oxides have emerged as promising materials due to their unique properties and broad applications in various fields, including photovoltaics and catalysis. Understanding the complex interplay between alkali metal doping, structural modifications, and their impact on performance remains a crucial challenge. In this study, this challenge is addressed by investigating the synthesis and properties of Rb-doped perovskite oxides.

An in-depth analysis of postoperative insomnia in elderly patients and its implications on rehabilitation.

Objectives: (1) Assess the prevalence of postoperative insomnia; (2) identify the risk factors for postoperative insomnia before exposure to surgery; (3) explore the impact of postoperative insomnia on rehabilitation.

Methods: A study was conducted with 132 participants aged ≥ 65 undergoing spine interbody fusion. We collected the basic demographic data, Numeric Rating Scales (NRS), Pittsburgh Sleep Quality Index (PSQI), Geriatric Depression Scale (GDS), and Beck Anxiety Inventory (BAI).

DrugGym: A testbed for the economics of autonomous drug discovery.

Drug discovery is stochastic. The effectiveness of candidate compounds in satisfying design objectives is unknown ahead of time, and the tools used for prioritization-predictive models and assays-are inaccurate and noisy. In a typical discovery campaign, thousands of compounds may be synthesized and tested before design objectives are achieved, with many others ideated but deprioritized.

EspalomaCharge: Machine Learning-Enabled Ultrafast Partial Charge Assignment.

Atomic partial charges are crucial parameters in molecular dynamics simulation, dictating the electrostatic contributions to intermolecular energies and thereby the potential energy landscape. Traditionally, the assignment of partial charges has relied on surrogates of ab initio semiempirical quantum chemical methods such as AM1-BCC and is expensive for large systems or large numbers of molecules. We propose a hybrid physical/graph neural network-based approximation to the widely popular AM1-BCC charge model that is orders of magnitude faster while maintaining accuracy comparable to differences in AM1-BCC implementations.

A review of social-ecological system vulnerability in desertified regions: Assessment, simulation, and sustainable management.

Desertified regions face considerable vulnerability due to the combined effects of climate change and human activities, which threaten regional ecological security and societal development. It is therefore necessary to assess, simulate, and manage the vulnerability of desertified regions from the perspective of the social-ecological system, to support desertification control and sustainable development. This study is a systematic review of the vulnerability of the social-ecological system in desertified regions (SESDR) based on a bibliometric analysis, and a summary of the research progresses in vulnerability assessment, simulation, and sustainable management is provided.

Deep profiling of potential substrate atlas of porcine epidemic diarrhea virus 3C-like protease.

Coronavirus (CoV) 3C-like protease (3CL) is essential for viral replication and is involved in immune escape by proteolyzing host proteins. Deep profiling the 3CL substrates in the host proteome extends our understanding of viral pathogenesis and facilitates antiviral drug discovery. Here, 3CL from porcine epidemic diarrhea virus (PEDV), an enteropathogenic CoV, was used as a model which to identify the potential 3CL cleavage motifs in all porcine proteins.

Modeling and optimizing through plenoptic function for the dual lenticular lens-based directional autostereoscopic display system.

We propose an autostereoscopic display system that ensures full resolution for multiple users by directional backlight and eye tracking technology. The steerable beam formed by directional backlight can be regarded as the result of sparsely sampling the light field in space. Therefore, we intuitively propose an optimization algorithm based on the characterization for the state of the steerable beams, which is computed in matrix form using the plenoptic function.

LEIFR-Net: light estimation for implicit face relight network.

Relighting facial images based on estimated lighting distribution and intensity from image backgrounds and environments can lead to more natural and convincing effects across diverse settings. In this paper, we introduce the Light Estimation for Implicit Face Relight Network (LEIFR-Net), which we believe to be a novel approach that significantly improves upon current methodologies. Initially, we present a method to estimate global illumination from a single image.

In-Situ Derived Defective Ru Particles Anchored on Ru-Ni Layered Double Hydroxides for Enhanced Alkaline Hydrogen Evolution.

Developing active, stable, and cost-efficient electrocatalysts to replace platinum for the alkaline hydrogen evolution reaction (HER) is highly desirable yet represents a great challenge. Here, it is reported on a facile one-pot synthesis of RuNi layered double hydroxides (RuNi-LDHs) that exhibit remarkable HER activity and stability after an in-situ activation treatment, surpassing most state-of-the-art Ru-based catalysts as well as commercial Ru/C and Pt/C catalysts. The structural and chemical changes triggered by in-situ activation are systematically investigated, and the results clearly show that the pristine, less-active RuNi-LDHs are transformed into a highly active catalyst characterized by raft-like, defect-rich Ru° particles decorated on the surface of RuNi-LDHs.

Targeting LRRC41 as a potential therapeutic approach for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, characterized by high mortality rate. In clinical practice, several makers of liver cancer, such as VEGFR1, FGFR1 and PDGFRα, were identified and their potentials as a therapeutic target were explored. However, the unsatisfied treatment results emphasized the needs of new therapeutic targets.

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy.

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials.

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy.

Middle ear innovation in Early Cretaceous eutherian mammals.

The middle ear ossicles in modern mammals are repurposed from postdentary bones in non-mammalian cynodonts. Recent discoveries by palaeontological and embryonic studies have developed different models for the middle ear evolution in mammaliaforms. However, little is known about the evolutionary scenario of the middle ear in early therians.

Nonlinear connection between remnant cholesterol and stroke risk: evidence from the China health and retirement longitudinal study.

Objective: The evidence on the relationship between remnant cholesterol (RC) and stroke remains controversial. Therefore, this study aimed to explore the relationship between RC and stroke risk in a Chinese population of middle-aged and elderly individuals.

Methods: The present study included 10067 Chinese subjects of middle-aged and elderly individuals.