Effects of heat stress on endocrine, thermoregulatory, and lactation capacity in heat-tolerant and -sensitive dry cows.

Introduction: Increasing global temperatures present a significant challenge to livestock production. The dry period is an important stage in the production cycle of cow, and environmental heat stress (HS) during this period can have adverse effects on the subsequent lactation performance. In this study, we aimed to investigate the effects of HS on endocrine, thermoregulatory, and lactation parameters in heat-tolerant dry cows (HTDC) and heat-sensitive dry cows (HSDC). Methods: We measured the respiratory rate (RR), body temperature (BT), and temperature-humidity index (THI) in 66 dry cows during HS. The slopes of RR and BT to THI were determined through analysis of measurements and dry cows background information using a mixed-effects model. Subsequently, the heat tolerance or sensitivity of dry cows was assessed using clustering method (HTDC = 19 and HSDC = 47). Results: Compared with that of HSDC, the RR of HTDC significantly increased after exposure to HS (p < 0.05). The average reduction in milk yield from new lactation to the previous lactation was significantly lower in HTDC compared to HSDC (p < 0.05). Plasma cortisol and non-esterified fatty acid levels were significantly lower in HTDC compared to HSDC (p < 0.05), while plasma triiodothyronine (p = 0.07) and growth hormone (p = 0.08) levels tended to be higher in HTDC relative to HSDC. Discussion: HTDC can more effectively alleviate the impacts of HS through their superior thermoregulation and metabolism, thereby ensuring optimal postpartum lactation performance.

Inferior Interfacial Superconductivity in 1 UC FeSe/SrVO3/SrTiO3 with Screened Interfacial Electron-Phonon Coupling.

Single-unit cell (1 UC) FeSe interfaced with TiOx or FeOx exhibits significantly enhanced superconductivity compared to that of bulk FeSe, with interfacial electron-phonon coupling (EPC) playing a crucial role. However, the reduced dimensionality in 1 UC FeSe, which may drive superconducting fluctuations, complicates our understanding of the enhancement mechanisms. We construct a new superconducting interface, 1 UC FeSe/SrVO3/SrTiO3. Here, the itinerant electrons of highly metallic SrVO3 films can screen all high-energy Fuchs-Kliewer phonons, including those of SrTiO3, making it the first FeSe/oxide system with screened interfacial EPC while maintaining the 1 UC FeSe thickness. Despite comparable doping levels, the heavily electron-doped 1 UC FeSe/SrVO3 exhibits a pairing temperature (Tg ∼ 48 K) lower than those of FeSe/SrTiO3 and FeSe/LaFeO3. Our findings disentangle the contributions of interfacial EPC from dimensionality in terms of enhancing Tg in FeSe/oxide interfaces, underscoring the critical importance of interfacial EPC. This FeSe/VOx interface also provides a platform for studying interfacial superconductivity.

GP's GP, general practitioner's health and willingness to contract family doctors in China: a national cross-sectional study.

OBJECTIVES: General practitioners are trained to care for patients with a high level of responsibility and professional competency. However, there are few reports on the physical and mental health status of general practitioners (GPs) in China, particularly regarding help seeking and self-treatment. The primary aims of this study were to explore GPs' expectations of their own family doctors and their reflection on role positioning, and to explore the objective factors that hinder the system of family doctors. STUDY DESIGN: Cross-sectional study. METHODS: We conducted an online survey of Chinese GPs. Descriptive statistics were used to summarize the findings. RESULTS: More than half of the participants (57.20%) reported that their health was normal over the past year. A total of 420 participants (23.35%) reported having chronic diseases. For sleep duration, 1205 participants (66.98%) reported sleeping 6-8 h per day; 473 participants (26.29%) reported chronic insomnia. Two hundred thirty-one participants (12.84%) had possible depression. A total of 595 (33.07%) participants reported that they had contracted a fixed family doctor. In terms of preventing themselves from contracting for a family doctor, the following factors were identified: lack of sufficient time (54.81%), could solve obstacles themselves (50.97%), and embarrassment (24.24%). The proportion of the contract group (12.44%) taking personal relationship as a consideration was higher than that of the non-contract group (7.64%) (χ2 = 10.934 P = 0.01). Most participants (79.90%) in the non-signed group reported never having seen a family doctor. In terms of obstacles, more than half of the signed group thought that they could solve obstacles themselves, while the non-signed group (39.20%) was less confident in the ability of family doctors than the signed group (29.75%) (χ2 = 15.436, P < 0.01). CONCLUSIONS: GPs work under great pressure and lack of self-care awareness, resulting in an increased prevalence of health conditions. Most GPs did not have a regular family doctor. Having a family doctor with a fixed contract is more conducive to the scientific management of their health and provides a reasonable solution to health problems. The main factors hindering GPs from choosing a family doctor were time consumption, abilities to solve obstacles themselves, and trust in the abilities of GPs. Therefore, simplifying the process of family doctor visits, Changing the GPs' medical cognition, and strengthening the policy of GP training would be conducive to promoting a family doctor system that enhances hierarchical diagnosis and treatment. International collaboration could integrate GP health support into global healthcare system.

A multi-modality imaging strategy to determine the multiple in vivo fates of human umbilical cord mesenchymal stem cells at different periods of acute liver injury treatment.

Human umbilical cord mesenchymal stem cells (HUCMSCs) are applied for disease therapy as a new type of drug in many countries. Their effects are not only presented by live cells, but also apoptotic bodies or cell fragments of dead cells. Therefore, it is meaningful to determine the multiple fates of HUCMSCs in vivo. Although various probes combining different imaging modalities have been developed to label and trace transplanted HUCMSCs in vivo, the status of the cells (live, dead, or apoptotic) was not distinguished, and a thorough understanding of the multiple fates of HUCMSCs after transplantation in vivo is lacking. Therefore, a magnetic resonance (MR)/near infrared fluorescent (NIRF)/bioluminescence (BI) multi-modality imaging strategy was developed. Iron oxide nanoparticles (IONPs) were assembled into 100 nm nanoparticles using epigallocatechin gallate as a chemical linker to increase the MR signal and reduce the exocytosis of IONPs for direct cell labeling and longitudinal MR imaging tracking. Fluorescent probes for apoptosis (DEVD-Cy-OH) were also loaded in the above assemblies to monitor the cell status. Meanwhile, the cell surface was labeled with the fluorescent dye Cy7 via bioorthogonal reactions to visualize the NIRF signal. Luciferase was lentivirally transfected into live cells to generate bioluminescence. Such labeling did not affect either the viability, proliferation, migration, differentiation characteristics of HUCMSCs or their therapeutic effects on acute liver injury mice in vivo. The in vivo fates of HUCMSCs were monitored via MR/NIRF/BI multi-modality imaging in acute liver injury mice. Although MR and Cy7 signals aggregated in injured liver for 7 days, the BI signals persisted for less than 24 hours. There was an increase in DEVD-Cy-OH signals in the injured liver, but they were almost at the basal level. That means that HUCMSCs survive in mice for a short time, and the dead form of HUCMSCs accumulated in a large quantity and sustained for a long time, which might contribute to their therapeutic effect.

The effect of probiotics supplementation on cancer-treatment complications: a critical umbrella review of interventional meta-analyses.

Cancer-related complications pose significant challenges in the management and treatment of patients with malignancies. Several meta-analyses have indicated improving effects of probiotics on cancer complications, while some studies have reported contentious findings. The purpose of the present study was to evaluate the efficacy of probiotics in addressing cancer complications, including diarrhea, mucositis, and infections, following chemotherapy, radiotherapy, and surgery. Relevant studies were searched in the PubMed, Scopus, Embase and Web of Science databases and Google Scholar up to September 2023. All meta-analyses addressing the effects of probiotics on all cancer treatments-induced complications including infection, diarrhea and oral mucositis were included. The pooled results were calculated using a random-effects model. Analyses of subgroups, sensitivity and publication bias were also conducted. The results revealed that the probiotics supplementation was effective on reduction of total cancer complications (OR:0.53; 95% CI: 0.44, 0.62, p < 0.001; I2=79.0%, p < 0.001), total infection rate (OR:0.47; 95%CI: 0.41, 0.52, p < 0.001; I2= 48.8%, p < 0.001); diarrhea (OR:0.50; 95%CI: 0.44, 0.57, p < 0.001; I2=44.4%, p = 0.023) and severe diarrhea (OR: 0.4; 95%CI: 0.27, 0.56, p < 0.001; I2=31.3%, p = 0.178), oral mucositis (OR: 0.76; 95%CI: 0.58, 0.94, p < 0.001; I2=95.5%, p < 0.001) and severe oral mucositis (OR:0.65, 95%CI: 0.58, 0.72 p < 0.001; I2=22.1%, p = 0.274). Multi strain probiotic (OR:0.49; 95%CI: 0.32, 0.65, p < 0.001; I2=90.7%, p < 0.001) were more efficacious than single strain (OR:0.73; 95%CI: 0.66, 0.81, p < 0.001; I2=0.00%, p = 0.786). The findings of the current umbrella meta-analysis provide strong evidence that probiotic supplementation can reduce cancer complications.

Recurrently gellable and thermochromic inorganic hydrogel thermogalvanic cells.

Thermogalvanic cells (TGCs) draw great attention in the field of heat to electricity conversion, but TGCs were only in the form of liquid or organic gel. Here, we report an all-inorganic hydrogel TGC via simply mixing and stirring two inorganic salt solutions. Benefiting from the hydrogen bonds resultant framework and endogenous Fe2+/3+ redox couple, the TGC can recurrently pulverize-gel with completely holding its initial thermogalvanic performances after even 60 cycles. As the temperature and pH coregulating Fe3+ concentration and reversible transformation between Fe3+ and Fe(OH)3, we boost thermopower and realize thermochromism. This work provides a different perspective for TGCs and offers an avenue for future hydrogel materials research.

A retrospective study on the impact of radiotherapy on the survival outcomes of small cell lung cancer patients based on the SEER database.

Small cell lung cancer (SCLC) patients exhibit significant heterogeneity in tumor burden, physical condition, and responses to initial treatment. This diversity in treatment responses can result in varying treatment outcomes. The primary objective of this study was to explore the patient demographics associated with improved survival outcomes through radiotherapy. Based on the SEER database, we identified 42,824 SCLC patients enrolled between 2004 and 2015. These patients were stratified into radiotherapy (n = 20,360) and non-radiotherapy groups (n = 22,464). We controlled for confounding factors using propensity score matching (PSM) analysis. Subsequently, Kaplan-Meier (KM) analysis was employed to evaluate the impact of radiotherapy on patients' overall survival (OS) and cancer-specific survival (CSS). Cancer-specific mortality was further analyzed using competitive risk models. Cox analysis was also conducted to examine additional variables potentially affecting the survival of SCLC patients. We identified a total of 42,824 eligible patients, and following PSM, 13,329 patients were successfully matched in both the radiotherapy and non-radiotherapy groups. The KM analysis showed that the median OS was 9 months in the radiotherapy group and 6 months in the non-radiotherapy group. The median CSS was 10 months in the radiotherapy group and 7 months in the non-radiotherapy group. The 5-year OS and 10-year OS rates were 6.2% versus 1.6% in the radiotherapy group and 2.6% versus 0.8% in the non-radiotherapy group (P < 0.001). Competitive risk analysis showed that cancer-specific mortality was significantly higher in the non-radiotherapy group than in the radiotherapy group (P < 0.001). Multivariate Cox analysis showed that the radiotherapy group (relative non-radiotherapy group) showed a significant positive effect on survival outcomes (OS: HR 0.658 95% CI [0.642, 0.675] P < 0.001; CSS: HR 0.662 95% CI [0.645, 0.679], P < 0.001). In addition, age, gender, race, primary tumor site, T stage, N stage, M stage, chemotherapy, and surgery were also considered as important predictors of SCLC outcome. The results of the subgroup analysis showed that the radiotherapy group showed a significant survival advantage regardless of age, sex, race, primary tumor site, M stage, chemotherapy, and surgery (P < 0.001). Radiotherapy may improve both OS and CSS in SCLC patients. Patients with SCLC may benefit from radiotherapy regardless of age, sex, race, primary tumor site, M stage, chemotherapy, and surgery.

Do cows with stereotypic tongue-rolling behaviour cope better with their environment?

Introduction: Stereotypic behaviours, especially oral stereotypic behaviours, are frequently expressed in farm animals. Tongue-rolling is the most common oral stereotypic behaviour in dairy cows (Bos taurus). If animals frequently display stereotypic behaviours, this is an indication of poor welfare. It has been suggested that animals express stereotypic behaviours as a way of coping with stress. As a result, animals with stereotypic behaviours may have lower levels of stress hormones than animals without stereotypic behaviours. Methods: In this study, 916 Holstein cows in the first lactation were subjected to scan sampling behavioural observations 200 times for 10 days. All cows were assigned to either a stereotypic behaviours group (SB) or a control group (CON). The SB group was further subdivided into a tongue-rolling group (TR) and an other-stereotypic behaviours group (OS). The TR group was also split into an only tongue-rolling group (OTR) and a mixed tongue-rolling and other stereotypic behaviours group (TROS). Some cows in the TR group belonged to an extreme tongue-rolling group (ETR). Hair and saliva samples were collected from 601 cows to test cortisol concentrations and dairy herd improvement (DHI) data were collected from a total of 762 cows. Results: There were no differences in hair or saliva cortisol concentrations between the groups (p>0.05), and the frequencies of tongue-rolling were not associated with cortisol concentrations (p>0.05). For DHI in cows, the milk protein percentage (p = 0.028), milk true protein percentage (p = 0.021) and milk crude protein percentage (p = 0.023) of cows in the ETR group were significantly lower than those in the CON group. For cows in ETR group, as the frequencies of tongue-rolling increased, the milk protein percentage (p = 0.034, r = 0.365), milk true protein percentage (p = 0.022, r = 0.393) and milk crude protein percentage (p = 0.035, r = 0.363) increased. Discussion: We investigated the relationship between stereotypic behaviours and stress by using a non-invasive sampling method to minimise harm to the cows. We suggest that tongue-rolling may not be a way for cows to cope with stress, at least in terms of cortisol concentrations.

Interface-Suppressed Nematicity and Enhanced Superconducting Pairing Strength of FeSe/NdFeO3 in the Low-Doping Regime.

The discovery of interfacial superconductivity in monolayer FeSe/oxides has spurred intensive research interest. Here we not only extend the FeSe/FeOx superconducting interface to FeSe/NdFeO3 but also establish robust interface-enhanced superconductivity at a very low doping level. Specifically, well-annealed FeSe/NdFeO3 exhibits a low doping level of 0.038-0.046 e-/Fe with a larger superconducting pairing gap without a nematic gap, indicating an enhancement of the enhanced superconducting pairing strength and suppression of nematicity by the FeSe/FeOx interface compared with those of thick FeSe films. These results improve our understanding of the roles of the oxide interface in the low-electron-doped regime.

Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus.

Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen's genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.

Clinical improvement effect of regulating gut microbiota on metabolic dysfunction-associated steatotic liver disease: Systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is constantly rising globally. There are barely any effective medications or supplements for the management of MASLD. We aim to systematically evaluate the most current evidence for gut microbiota-regulating supplements in patients with MASLD. METHODS: We searched multiple electronic data for randomized controlled trials (RCTs) published from January 1, 2012, to July 15, 2023. The intervention measures included probiotics, prebiotics, synbiotics, antibiotics, and fecal microbiota transplantation (FMT). The control group was treated with a placebo or usual care. The intervention duration was divided into two periods (>12 weeks and ≤12 weeks). Adequate evaluation data for antibiotics and FMT have not been obtained. Therefore, the other three microbiota regulators are the primary evaluation measures in this study. RESULTS: We found that probiotics alone could not improve clinical indicators in MASLD patients. However, synbiotics exhibited an improvement in reducing liver steatosis, TNF-ɑ levels, and increasing HDL-c levels, and the inflammatory markers of liver cells (ALT and AST) were also improved. For the effective intervention duration, this systematic review suggested that around 12 weeks is an ideal intervention cycle for MASLD patients. CONCLUSIONS: This meta-analysis supported the modulation of gut microbiota with synbiotics in the management of MASLD.

Cross-linked K0.5MnO2 nanoflower composites for high rate and low overpotential Li-CO2 batteries.

Rechargeable Li-CO2 batteries are deemed to be attractive energy storage systems, as they can effectively inhale and fix carbon dioxide and possess an extremely high energy density. Unfortunately, the irreversible decomposition of the insoluble and insulating Li2CO3 results in awful electrochemical performance and inferior energy efficiency of Li-CO2 batteries. Furthermore, the low energy efficiency will exacerbate the extra waste of resources. Therefore, it is vital to design novel and efficient catalysts to enhance the battery performance. Herein, a facile, one-step strategy is introduced to design cross-linked, ultrathin K0.5MnO2 nanoflowers combined with CNTs (K0.5MnO2/CNT) as a highly efficient cathode for Li-CO2 batteries. Impressively, the Li-CO2 battery based on the K0.5MnO2/CNT cathode achieves a low overpotential (1.05 V) and a high average energy efficiency (87.95%) at a current density of 100 mA g-1. Additionally, the K0.5MnO2/CNT cathode can steadily run for over 100 cycles (overpotential < 1.20 V). Moreover, a low overpotential of 1.47 V can be obtained even at a higher current density of 1000 mA g-1, indicating the superior rate performance of K0.5MnO2/CNT. This strategy offers new insight and guidance for the development of low-cost and high-performance Li-CO2 batteries.

Discrete latent embedding of single-cell chromatin accessibility sequencing data for uncovering cell heterogeneity.

Single-cell epigenomic data has been growing continuously at an unprecedented pace, but their characteristics such as high dimensionality and sparsity pose substantial challenges to downstream analysis. Although deep learning models-especially variational autoencoders-have been widely used to capture low-dimensional feature embeddings, the prevalent Gaussian assumption somewhat disagrees with real data, and these models tend to struggle to incorporate reference information from abundant cell atlases. Here we propose CASTLE, a deep generative model based on the vector-quantized variational autoencoder framework to extract discrete latent embeddings that interpretably characterize single-cell chromatin accessibility sequencing data. We validate the performance and robustness of CASTLE for accurate cell-type identification and reasonable visualization compared with state-of-the-art methods. We demonstrate the advantages of CASTLE for effective incorporation of existing massive reference datasets in a weakly supervised or supervised manner. We further demonstrate CASTLE's capacity for intuitively distilling cell-type-specific feature spectra that unveil cell heterogeneity and biological implications quantitatively.

pNet: A toolbox for personalized functional networks modeling.

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

Dietary supplementation with Neolamarckia cadamba leaf extract improves broiler meat quality by enhancing antioxidant capacity and regulating metabolites.

This study was to evaluate the effect of supplementing the diet of broilers with Neolamarckia cadamba leaf extract (NCLE) on meat quality by evaluating antioxidant parameters and the expression of genes in the p38 mitogen-activated protein kinase/nuclear factor-erythroid 2-related factor 2/antioxidant responsive element (p38 MAPK/Nrf2/ARE) signaling pathway, coupled with LC-MS-based metabolomic analysis. A total of 480 one-day-old male broilers were randomly allocated to four treatment groups-a control (CON) group, which was fed a basal diet, and three NCLE treatment groups, which were fed the basal diet supplemented with 100, 200, or 400 mg/kg NCLE (N1, N2, and N3 groups, respectively) for 42 d. Compared with the CON group, meat quality was improved in the N2 and N3 groups, as evidenced by the higher pH45min (P < 0.05) and lower shear force (P < 0.05) in breast muscle (BM) and lower drip loss at 48 h (P < 0.05) in leg muscle (LM). Moreover, BM antioxidant capacity was significantly enhanced in the N3 group, characterized by an increase in the total antioxidant capacity (T-AOC), the concentrations of glutathione peroxidase (GSH-Px) and catalase (CAT), and the relative mRNA expression of p38 MAPK, extracellular-signal regulated kinase (ERK1/2), c-Jun N-terminal kinase (JNK), Nrf2, CAT, and GSH-Px (P < 0.05). Similarly, LM in the N3 group displayed higher T-AOC, increased GSH-Px and CAT concentrations, reduced malonaldehyde contents (P < 0.05), and upregulation of the relative mRNA levels of JNK, Nrf2, heme oxygenase, CAT, and superoxide dismutase (SOD) (P < 0.05). Metabolomics analysis revealed that D-arabinono-1,4-lactone and lyso-PAF C-16-d4 were negatively correlated with shear force and cooking loss (P < 0.05) and displayed increased abundance in BM of the N3 group. L-Serine levels were upregulated while D-fructose 1,6-diphosphate contents were downregulated in the three NCLE groups. Finally, the differential metabolites in both BM and LM were involved in amino acid metabolism pathways. Our results indicated that NCLE supplementation improved meat quality by enhancing antioxidant enzyme activities, promoting the expression of genes in the p38 MAPK/Nrf2/ARE signaling pathway, and regulating amino acid metabolism. The optimal NCLE concentration was found to be 400 mg/kg.

Thin Film Resistance Gating by Redox Charge Exchange: Evidence for a Quantum Transition State.

Field effect transistors (FETs) and related devices have enabled tremendous advances in electronics, as well as studies of fundamental phenomena. FETs are classically actuated as fields charge/discharge materials, thereby modifying their resistance. Here, we develop charge exchange transistors (CETs) that comprise thin films whose resistance is modified by quantum charge exchange processes, e.g., redox and bonding. We first use CETs to probe the metallocene-thin film interaction during cyclic voltammetry. Remarkably, CETs reveal transient resistance peaks associated with charge transfer during both oxidation and reduction. Our data combined with kinetics and density functional theory modeling are consistent with a multistep redox pathway, including the formation/destruction of a quantum transition state that overlaps molecule + thin film band states. As a further proof-of-principle demonstration, we also use CETs to monitor n-alkanethiol self-assembly on thin Au films in real-time. CETs exhibit monotonic resistance increase consistent with previously reported fast-then-slow kinetics attributed to thiol-thin film bond formation (charge localization) and etching and/or molecule reorganization.

Naringin as a natural candidate for anti-autoimmune hepatitis: Inhibitory potency and hepatoprotective mechanism.

BACKGROUND: Autoimmune hepatitis (AIH), primarily mediated by T cells, is characterized by liver inflammation. Despite the advancements in understanding its pathogenesis, effective therapeutic options are limited. Naringin, a flavonoid abundant in citrus fruits, is recognized for its anti-inflammatory properties and ability to protect against various inflammatory diseases, including drug-induced liver injury. However, the exact effects of naringin on AIH and the mechanisms involved remain poorly understood. PURPOSE: We aim to determine the role of naringin in AIH, exploring its targets and actions in this disease. METHODS: Network pharmacology, molecular docking, and molecular dynamics simulations were utilized to predict the HUB targets connecting naringin, T cell-mediated autoimmune disorders, and AIH. Cellular thermal shift assays were used to determine the binding abilities of naringin with the HUB targets. An in vivo experiment confirmed the impact of naringin treatment on AIH development and underlying mechanisms. RESULTS: Naringin demonstrated therapeutic effects on ConA-induced AIH. There were 455 shared targets between naringin, T cell-mediated autoimmune diseases, and AIH. Ten HUB genes (AKT1, ALB, IL-6, IL-1ß, CTNNB1, TNF, TP53, MAPK3, VEGFA, and JUN) were identified through the PPI network. Gene ontology analysis revealed involvement in gene expression regulation, lipopolysaccharide-mediated signaling, and I-kappa kinase/NFκB signaling. Pathway analysis suggested TNF, Th1/Th2 cell differentiation, and Toll-like receptor pathways, with favorable naringin-HUB gene binding. Molecular docking confirmed albumin (ALB), IL-1ß, IL-6, and TNF as primary targets for naringin. Molecular dynamics simulations showed stable binding in ALB-naringin, TNF-naringin, and IL-1ß-naringin complexes. Naringin's hepatoprotective effect on AIH was supported by increased serum ALB and decreased hepatic inflammatory cytokines including IL-1ß, IL-6, and TNF-α. CONCLUSION: Our data underscore the potential of naringin as a preventive or therapeutical agent in T cell-mediated autoimmune diseases including AIH.

scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism.

MOTIVATION: With the rapid advancement of single-cell sequencing technology, it becomes gradually possible to delve into the cellular responses to various external perturbations at the gene expression level. However, obtaining perturbed samples in certain scenarios may be considerably challenging, and the substantial costs associated with sequencing also curtail the feasibility of large-scale experimentation. A repertoire of methodologies has been employed for forecasting perturbative responses in single-cell gene expression. However, existing methods primarily focus on the average response of a specific cell type to perturbation, overlooking the single-cell specificity of perturbation responses and a more comprehensive prediction of the entire perturbation response distribution. RESULTS: Here, we present scPRAM, a method for predicting perturbation responses in single-cell gene expression based on attention mechanisms. Leveraging variational autoencoders and optimal transport, scPRAM aligns cell states before and after perturbation, followed by accurate prediction of gene expression responses to perturbations for unseen cell types through attention mechanisms. Experiments on multiple real perturbation datasets involving drug treatments and bacterial infections demonstrate that scPRAM attains heightened accuracy in perturbation prediction across cell types, species, and individuals, surpassing existing methodologies. Furthermore, scPRAM demonstrates outstanding capability in identifying differentially expressed genes under perturbation, capturing heterogeneity in perturbation responses across species, and maintaining stability in the presence of data noise and sample size variations. AVAILABILITY AND IMPLEMENTATION: https://github.com/jiang-q19/scPRAM and https://doi.org/10.5281/zenodo.10935038.

Improving Image Segmentation with Contextual and Structural Similarity.

Deep learning models for medical image segmentation are usually trained with voxel-wise losses, e.g., cross-entropy loss, focusing on unary supervision without considering inter-voxel relationships. This oversight potentially leads to semantically inconsistent predictions. Here, we propose a contextual similarity loss (CSL) and a structural similarity loss (SSL) to explicitly and efficiently incorporate inter-voxel relationships for improved performance. The CSL promotes consistency in predicted object categories for each image sub-region compared to ground truth. The SSL enforces compatibility between the predictions of voxel pairs by computing pair-wise distances between them, ensuring that voxels of the same class are close together whereas those from different classes are separated by a wide margin in the distribution space. The effectiveness of the CSL and SSL is evaluated using a clinical cone-beam computed tomography (CBCT) dataset of patients with various craniomaxillofacial (CMF) deformities and a public pancreas dataset. Experimental results show that the CSL and SSL outperform state-of-the-art regional loss functions in preserving segmentation semantics.

EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data.

SUMMARY: Recent technical advancements in single-cell chromatin accessibility sequencing (scCAS) have brought new insights to the characterization of epigenetic heterogeneity. As single-cell genomics experiments scale up to hundreds of thousands of cells, the demand for computational resources for downstream analysis grows intractably large and exceeds the capabilities of most researchers. Here, we propose EpiCarousel, a tailored Python package based on lazy loading, parallel processing, and community detection for memory- and time-efficient identification of metacells, i.e. the emergence of homogenous cells, in large-scale scCAS data. Through comprehensive experiments on five datasets of various protocols, sample sizes, dimensions, number of cell types, and degrees of cell-type imbalance, EpiCarousel outperformed baseline methods in systematic evaluation of memory usage, computational time, and multiple downstream analyses including cell type identification. Moreover, EpiCarousel executes preprocessing and downstream cell clustering on the atlas-level dataset with 707 043 cells and 1 154 611 peaks within 2 h consuming <75 GB of RAM and provides superior performance for characterizing cell heterogeneity than state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION: The EpiCarousel software is well-documented and freely available at https://github.com/biox-nku/epicarousel. It can be seamlessly interoperated with extensive scCAS analysis toolkits.