Exploration of non-coding RNAs related to intramuscular fat deposition Xinjiang Brown cattle and Angus × Wagyu cattle.

Non-coding RNAs (ncRNAs) serve as crucial regulatory elements in the process of adipogenesis in animals; however, the specific roles and interrelationships of ncRNAs in bovine fat deposition remain poorly understood. This study aims to investigate the differentially expressed ncRNAs in the longissimus dorsi muscle of Xinjiang Brown cattle (XB) and Angus Wagyu cattle (AW), to elucidate the regulatory mechanisms underlying lipidogenesis that may involve ncRNAs. Four Xinjiang Brown cattle and four Angus Wagyu cattle were selected, ensuring they are subjected to identical feeding conditions, in order to evaluate the intermuscular fat (IMF) of longissimus dorsi muscles.

Generation of dynamic oxygen vacancies in graphene quantum dots/NaNbO heterojunction for boosting photocatalytic hydrogen evolution.

The design and theoretical study of green, low-cost heterojunction photocatalysts with strong interfacial interactions are crucial for achieving efficient and stable photocatalytic hydrogen evolution (PHE). This study proposes a simple method to synthesizing graphene quantum dots (GQDs)/NaNbO heterojunction with dynamic oxygen vacancies. GQDs promote the formation of oxygen vacancies and increase the surface-active sites of NaNbO, significantly enhancing light absorption efficiency.

Novel Computational Pipeline Enables Reliable Diagnosis of Inverted Urothelial Papilloma and Distinguishes It From Urothelial Carcinoma.

Purpose: With the aid of ever-increasing computing resources, many deep learning algorithms have been proposed to aid in diagnostic workup for clinicians. However, existing studies usually selected informative patches from whole-slide images for the training of the deep learning model, requiring labor-intensive labeling efforts. This work aimed to improve diagnostic accuracy through the statistic features extracted from hematoxylin and eosin-stained slides.

PocketDTA: A pocket-based multimodal deep learning model for drug-target affinity prediction.

Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a substantial challenge. This paper proposes a pocket-based multimodal deep learning model named PocketDTA for drug-target affinity prediction, based on the principle of "structure determines function".

Cascade-Type Microglial Pyroptosis Inhibitors for Enhanced Treatment of Cerebral Ischemia-Reperfusion Injury.

Neuroinflammation is a critical factor in the progression of cerebral ischemia-reperfusion injury (CIRI). Pyroptosis, which is an inflammatory form of programmed cell death, greatly amplifies neuroinflammatory processes. It does so by promoting the release of various inflammatory contents that intensify the overall inflammatory response within the central nervous system.

Origin and Key Enrichment Factors of Helium Resource in the Lower Yangtze Region, Eastern China.

Helium is a critical, scarce, and strategic resource, often found in association with natural gas. This study reports the first discovery of overpressured helium-rich natural gas in the Lower Yangtze Region of Eastern China, with helium concentrations reaching as high as 4.5%, significantly surpassing the commercial extraction threshold of 0.

How responsible leadership affects employees' turnover intention in China: A psychological contract perspective.

Background: The current high rate of employee turnover has become a key factor affecting organizational stability and core competitiveness, which requires organizational leaders to work with a higher sense of responsibility. Although several studies have confirmed that responsible leadership (RL) negatively affects employees' turnover intention, the specific mechanism of this effect has not been fully elucidated.

Objective: On the basis of the discrepancy model of psychological contract violation (PCV) and substitutes for leadership theory, this study aims to examine the indirect impact of RL on employees' turnover intention through employees' PCV and the moderating effect of organizational identification.

Effects of preweaning calf daily gain and feed intake on first-lactation performance: A metaanalysis.

This study aimed to investigate the effects of daily weight gain and feed intake of calves on first-lactation milk yield and composition using a metaanalysis. A total of 57 treatments from 18 studies were included in the study. Univariate and multivariate mixed models were constructed for calf ADG, liquid DMI (LDMI), starter DMI (SDMI), 305-d milk, milk fat, and protein yields data to gain insight into the effects of preweaning calf daily gain and feed intake on first-lactation performance.

Robust whole-body PET image denoising using 3D diffusion models: evaluation across various scanners, tracers, and dose levels.

Purpose: Whole-body PET imaging plays an essential role in cancer diagnosis and treatment but suffers from low image quality. Traditional deep learning-based denoising methods work well for a specific acquisition but are less effective in handling diverse PET protocols. In this study, we proposed and validated a 3D Denoising Diffusion Probabilistic Model (3D DDPM) as a robust and universal solution for whole-body PET image denoising.

Dialing the glenosphere eccentricity posteriorly to optimize range of motion in reverse shoulder arthroplasty.

Background: Friction is the primary cause of notching in reverse shoulder arthroplasty during internal, external rotation (IR/ER), and extension (EXT). To address notching, glenosphere eccentricity (ECC) was introduced. The primary objective of this study was to investigate different positions of glenosphere ECC to determine whether there is an optimal position for impingement-free range of motion.

Effects of feeding different proportions of steam-flaked corn-based starter on growth performance, immunity and serum metabolism of pre-weaned Simmental calves.

Introduction: This study examines the effects of steam-flaked corn starter on pre-weaned Simmental calves' growth, immunity, and metabolism. Despite benefits shown in adult cattle, research on calves is limited. The goal is to optimize calf feeding for better growth, health, and nutrient use.

Prevalent and Drug-Resistant Phenotypes and Genotypes of Isolated from Healthy Cow's Milk of Large-Scale Dairy Farms in China.

is a common cause of mastitis in dairy cows, which results in large economic losses to the livestock industry. The aim of this study was to investigate the prevalence of in raw milk in China, assess antimicrobial drug susceptibility, and identify key antibiotic resistance genes carried by the isolates. In total, 350 raw milk samples were collected from large-scale farms in 16 provinces and cities in six regions of China to assess the resistance of .

Alternative splicing of EZH2 regulated by SNRPB mediates hepatocellular carcinoma progression via BMP2 signaling pathway.

Increasing evidence suggests that aberrant alternative splicing plays crucial roles in tumorigenesis. However, the function of EZH2 splice variants as well as the mechanism by which EZH2 alternative splicing occurs in hepatocellular carcinoma (HCC) remain elusive. Here, we analyzed both our own and published transcriptomic data, obtaining 19 splice variants of EZH2 in addition to canonical full-length EZH2-A in HCC.

Graphene Oxide Foam-Based Floating Actuators Manipulated via Dual-Marangoni-Effect Propulsion and Magnetic-Field-Guided Navigation.

Intelligent stimuli-responsive actuators that can convert environmental energies into mechanical works have garnered significant research interests. Among different actuation principles, Marangoni effect is distinguished due to simplicity, high efficiency, remote manipulation, and water environment adaptability. Nevertheless, both chemical and physical Marangoni actuators face their own challenges with respect to limited chemical loading, precise light illumination, and relatively poor motion controllability.

Silencing of lncRNA Gm26917 Attenuates Alveolar Macrophage-mediated Inflammatory Response in LPS-induced Acute Lung Injury Via Inhibiting NKRF Ubiquitination.

The inflammatory response mediated by alveolar macrophages plays a crucial role in the development of acute lung injury. Numerous studies have reported that lncRNAs are highly expressed in acute lung injury in mouse models and cell lines, and acute lung injury (ALI) can be effectively alleviated by targeting these lncRNAs. The aim of this study was to explore the mechanism by LncRNA Gm26917 regulates the inflammatory response in alveolar macrophages during acute lung injury mouse model.

RetinaRegNet: A zero-shot approach for retinal image registration.

Retinal image registration is essential for monitoring eye diseases and planning treatments, yet it remains challenging due to large deformations, minimal overlap, and varying image quality. To address these challenges, we propose RetinaRegNet, a multi-stage image registration model with zero-shot generalizability across multiple retinal imaging modalities. RetinaRegNet begins by extracting image features using a pretrained latent diffusion model.

Identification of crucial extracellular genes as potential biomarkers in newly diagnosed Type 1 diabetes integrated bioinformatics analysis.

Purpose: In this study, we aimed to study the role of extracellular proteins as biomarkers associated with newly diagnosed Type 1 diabetes (NT1D) diagnosis and prognosis.

Patients And Methods: We retrieved and analyzed the GSE55098 microarray dataset from the Gene Expression Omnibus (GEO) database. Using R software, we screened out the extracellular protein-differentially expressed genes (EP-DEGs) through several protein-related databases.

Boosting Hot Electron Generation in Energy Center Embedded Metal-Organic Frameworks for Photocatalysis.

The ligands in metal-organic framework (MOF) play as light absorption center and transfer photogenerated electrons to metal node through ligand-to-metal charge transfer (LMCT) during photocatalysis, and energy utilization efficiency is strongly restricted by the light inertness of ligands. Herein, a ligand updating strategy is proposed by inserting energy centers to MOFs to activate the inherent ligands, realizing boosting hot electron generation and photocatalytic activities via the cascaded proceeding of energy transfer and charge transfer. By taking PCN-777 (a zeotype mesoporous Zr-containing MOF) as an example, this study shows that the embedded energy center of 1-pyrenecarboxylic acid (PCA) can activate the inherent ligand of PCN-777 through triplet-triplet energy transfer, where triplet excitons would dissociate into photocarriers migrating to the Zr metal cluster via LMCT process.

Investigation of bidirectional causal association between temporomandibular disorders and five mental disorders.

Objective: This study utilized two-sample Mendelian randomization (TSMR) to investigate the bidirectional causal associations between temporomandibular disorders (TMD) and five mental disorders.

Methods: Single-nucleotide polymorphisms (SNPs) linked to TMD were extracted from the Genome-Wide Association Studies (GWAS) database. The SNPs selected as instrumental variables (IVs) were required to have strong associations with the exposure phenotype and to meet the assumptions of Mendelian randomization (MR) analysis.

Enhanced Photothermal/Immunotherapy under NIR Irradiation Based on Hollow Mesoporous Responsive Nanomotor.

In this research, a hollow mesoporous responsive nanomotor was proposed for enhanced photothermal/immunotherapy under near infrared (NIR) irradiation. HA-HMCuS/AS as the nanomotor composed of hollow mesoporous copper sulfide (HMCuS) loaded with artesunate (AS) and hyaluronic acid (HA) was utilized to induce the polarization of tumor-associated macrophages. At the beginning, ResNet18 deep learning model was utilized to predict the Brunauer-Emmett-Teller (BET) surface area of HMCuS based on the morphology data set which was obtained from our conventional research.

iResNetDM: An interpretable deep learning approach for four types of DNA methylation modification prediction.

Motivation: Although several computational methods for predicting DNA methylation modifications have been developed, two main limitations persist: 1) All of the models are currently confined to binary predictors, which merely determine the presence or absence of DNA methylation modifications and thus prevent comprehensive analyses of the interrelations among varied modification types. Multi-class classification models for RNA modifications have been developed, and a comparable approach for DNA is essential. 2) Few previous studies offer adequate explanations of how models make decisions, instead relying on the extraction and visualization of attention matrices, which have identified few motifs and do not provide sufficient insights into the model decision-making process.

Ultrafast self-healing zwitterionic hydrogels reinforced by carboxymethyl chitosan-oxidized hyaluronic acid and graphene oxide toward high-performance strain sensors.

Inspired by the inherent recuperative ability of organisms in nature, researchers have dedicated significant efforts towards developing self-healing hydrogel sensors. Although the works on self-healing hydrogels have made great progress, achieving hydrogel sensors combining with rapid and efficient healing capability, excellent mechanical properties and high sensing sensitivity remains a challenging task. In this study, we proposed a novel approach for fabricating a self-healing conductive zwitterionic hydrogel sensor by adding carboxymethyl chitosan (CMCs) and oxidized hyaluronic acid (OHA) to induce dynamic Schiff base reaction, and graphene oxide (GO) nanosheets as physical crosslinker.

LsKN1 and LsOFP6 synergistically regulate the bolting time by modulating the gibberellin pathway in lettuce.

Bolting time is an important agronomic trait in lettuce (Lactuca sativa) production. Premature bolting significantly reduces crop quality and marketability. Here, we report map-based cloning and characterization of a LsKN1 gene that controls bolting in lettuce.

Peptidomic Analysis of Potential Bioactive Peptides in Mare Milk Under Different Heat Treatment Conditions.

Active peptides in mare milk have unique biological activities, but how the bioactive protein in mare's milk changes under the influence of temperature has not been fully studied. Therefore, in this study, the differential expression of bioactive peptides potentially present in horse milk under different heat treatment conditions was investigated for the first time using peptidomic and bioinformatic techniques. We collected a total of 15 samples.