Reinforcing Cd-S bonds through morphology engineering for enhanced intrinsic photocatalytic stability of CdS.

Effectively mitigating photocorrosion is paramount for achieving high-efficiency and sustainable hydrogen production through photocatalytic water splitting over CdS. In this work, we develop a morphology engineering strategy with adjustable Cd-S bond energy through a simple chemical bath deposition method to synthesize novel hollow hemispherical CdS (H-CdS). The morphologic structure CdS can be precisely controlled by adjusting the reaction temperature, time and pH. Compared with common morphologies of CdS, H-CdS, with its reinforced Cd-S bonding, exhibits not only improved photocatalytic hydrogen evolution activity (20.04 mmol/g/h) but also exceptional resistance to photocorrosion, resulting in outstanding cyclic stability even without the aid of cocatalysts or the introduction of other semiconductors. Comprehensive characterizations reveal that the photocorrosion resistance of H-CdS stems from the high Cd-S bond strength. Moreover, in-situ infrared spectroscopy confirms alterations in the properties and activities of the various CdS morphologies after photocatalytic reaction due to photocorrosion. We thoroughly describe the relationship among morphology, surface energy, bond energy and photocorrosion resistance. Our findings present a novel strategy for mitigating the photocorrosion of CdS and offer valuable insights for future research on CdS photocatalysts aimed at stable water splitting.

Orbital torque switching in perpendicularly magnetized materials.

The orbital Hall effect in light materials has attracted considerable attention for developing orbitronic devices. Here we investigate the orbital torque efficiency and demonstrate the switching of the perpendicularly magnetized materials through the orbital Hall material, i.e., Zr. The orbital torque efficiency of approximately 0.78 is achieved in the Zr orbital Hall material with the perpendicularly magnetized [Co/Pt]3 sample, which significantly surpasses that of the perpendicularly magnetized CoFeB/Gd/CoFeB sample (approximately 0.04). Such a notable difference is attributed to the different spin-orbit correlation strength between the [Co/Pt]3 sample and the CoFeB/Gd/CoFeB sample, confirmed through theoretical calculations. Furthermore, the full magnetization switching of the [Co/Pt]3 samples with a switching current density of approximately 2.6×106 A/cm2 has been realized through Zr, which even outperforms that of the W spin Hall material. Our finding provides a guideline to understand orbital torque efficiency and paves the way for developing energy-efficient orbitronic devices.

Unveiling the crucial role of ferroptosis in host resistance to streptococcus agalactiae infection.

IL-1ß represents an important inflammatory factor involved in the host response against GBS infection. Prior research has suggested a potential involvement of IL-1ß in the process of ferroptosis. However, the relationship between IL-1ß and ferroptosis in the context of anti-GBS infection remains uncertain. This research demonstrates that the occurrence of ferroptosis is essential for the host's defense against GBS infection in a mouse model of abdominal infection, with peritoneal macrophages identified as the primary cells undergoing ferroptosis. Further research indicates that IL-1ß induces lipid oxidation in macrophages through the upregulation of pathways related to lipid oxidation. Concurrently, IL-1ß is not only involved in the initiation of ferroptosis in macrophages, but its production is intricately linked to the onset of ferroptosis. Ultimately, we posit that ferroptosis acts as a crucial initiating factor in the host response to GBS infection, with IL-1ß playing a significant role in the resistance to infection by serving as a key inducer of ferroptosis.

CXCL13: a common target for immune-mediated inflammatory diseases.

CXCL13 is a chemokine that plays an important role in the regulation and development of secondary lymphoid organs. CXCL13 is also involved in the regulation of pathological processes, particularly inflammatory responses, of many diseases. The function of CXCL13 varies depending on the condition of the host. In a healthy condition, CXCL13 is mainly secreted by mouse stromal cells or human follicular helper T cells, whereas in diseases conditions, they are produced by human peripheral helper T cells and macrophages in non-lymphoid tissues; this is termed ectopic expression of CXCL13. Ectopic CXCL13 expression is involved in the pathogenesis of various immune-mediated inflammatory diseases as it regulates the migration of B lymphocytes, T lymphocytes, and other immune cells in inflammatory sites as well as influences the expression of inflammatory factors. Additionally, ectopic expression of CXCL13 plays a key role in ectopic lymphoid organ formation. In this review, we focused on the sources of CXCL13 in different conditions and its regulatory mechanisms in immune-mediated inflammatory diseases, providing novel ideas for further research on targeting CXCL13 for the treatment of immune-mediated inflammatory diseases.

Preoperative Prediction of Occult Level V Lymph Node Metastasis in Papillary Thyroid Carcinoma: Development and Validation of a Radiomics-Driven Nomogram Model.

RATIONALE AND OBJECTIVES: The study aimed to analyze the patterns and frequency of Level V lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC), identify its risk factors, and construct predictive models for assessment. METHODS: We conducted a retrospective analysis of 325 PTC patients who underwent thyroidectomy and therapeutic unilateral bilateral modified radical neck dissection from October 2020 to January 2023. Patients were randomly allocated into a training cohort (70%) and a validation cohort (30%). The radiomics signature model was developed using ultrasound images, applying the minimum Redundancy-Maximum Relevance and Least Absolute Shrinkage and Selection Operator regression to extract high-throughput quantitative features. Concurrently, the clinic signature model was formulated based on significant clinical factors associated with Level V LNM. Both models were independently translated into nomograms for ease of clinical use. RESULTS: The radiomics signature model, without the inclusion of clinical factors, showed high discriminative power with an area under the curve (AUC) of 0.933 in the training cohort and 0.912 in the validation cohort. Conversely, the clinic signature model, composed of tumor margin, simultaneous metastasis, and high-volume lateral LNM, achieved an AUC of 0.749 in the training cohort. The radiomics signature model exhibited superior performance in sensitivity, specificity, positive predictive value, negative predictive value across both cohorts. Decision curve analysis demonstrated the clinical utility of the radiomics signature model, indicating its potential to guide more precise treatment decisions. CONCLUSION: The radiomics signature model outperformed the clinic signature model in predicting Level V LNM in PTC patients. The radiomics signature model, available as a nomogram, offers a promising tool for preoperative assessment, with the potential to refine clinical decision-making and individualize treatment strategies for PTC patients with potential Level V LNM.

Eucommiae cortex extract alleviates renal fibrosis in CKD mice induced by adenine through the TGF-ß1/Smad signaling pathway.

Research into the potential therapeutic benefits of herbal remedies for treating chronic kidney disease (CKD), a condition marked by renal fibrosis and persistent inflammation, has become popular. Eucommiae cortex (EC) is a vital herb for strengthening bones and muscles and tonifying the kidneys and liver. In the study, C57 BL/6 mice were given a diet containing 0.2% adenine to create a CKD model. The findings demonstrated that exogenous EC supplementation successfully decreased the levels of creatinine and urea nitrogen, down-regulated the TGF-ß1/Smad signaling pathway's expression levels of TGF-ß1, α-SMA, Smad3, and phospho-Smad3, and prevented renal fibrosis. Consequently, it was determined that EC might have a nephroprotective impact.

Stroke Prognosis: The Impact of Combined Thrombotic, Lipid, and Inflammatory Markers.

AIM: D-dimer, lipoprotein (a) (Lp(a)), and high-sensitivity C-reactive protein (hs-CRP) are known predictors of vascular events; however, their impact on the stroke prognosis is unclear. This study used data from the Third China National Stroke Registry (CNSR-III) to assess their combined effect on functional disability and mortality after acute ischemic stroke (AIS). METHODS: In total, 9,450 adult patients with AIS were enrolled between August 2015 and March 2018. Patients were categorized based on a cutoff value for D-dimer, Lp(a), and hs-CRP in the plasma. Adverse outcomes included poor functional outcomes (modified Rankin Scale (mRS score ≥ 3)) and one- year all-cause mortality. Logistic and multivariate Cox regression analyses were performed to investigate the relationship between individual and combined biomarkers and adverse outcomes. RESULTS: Patients with elevated levels of all three biomarkers had the highest odds of functional disability (OR adjusted: 2.01; 95% CI (1.47-2.74); P＜0.001) and mortality (HR adjusted: 2.93; 95% CI (1.55-5.33); P＜0.001). The combined biomarkers improved the predictive accuracy for disability (C-statistic 0.80 vs.0.79, P＜0.001) and mortality (C-statistic 0.79 vs.0.78, P=0.01). CONCLUSION: Elevated D-dimer, Lp(a), and hs-CRP levels together increase the risk of functional disability and mortality one-year post-AIS more than any single biomarker.

[Study on the clinical effect of meridian massage in the treatment of lumbar disc herniation].

OBJECTIVE: To observe the clinical efficacy of meridian massage in the treatment of lumbar disc herniation(LDH). METHODS: Between July 2020 and April 2023, 82 patients with lumbar disc herniation were selected, including 58 males and 24 females, aged from 23 to 55 years old with an average of (43.76±6.64) years old. According to the different treatment methods, they were divided into observation group and control group with 41 cases in each group. The control group was treated with routine treatment, and the observation group was treated with meridian massage on the basis of routine treatment. In the control group, there were 30 males and 11 females;aged from 22 to 52 years old with an average of (42.27±9.34) years old;the Body mass index (BMI) ranged from 19 to 28 kg·m-2 with an average of(23.82±1.08) kg·m-2;the course of disease ranged from 0.5 to 3.0 years (2.40±0.48) years. There were 28 cases in L4,5 segment and 13 cases in L5S1 segment. In the observation group, there were 28 males and 13 females;the age ranged from 19 to 54 years old (42.19±9.26) years old;the BMI ranged from 18 to 29 kg·m-2 with an average of(23.73±1.15) kg·m-2;the course of disease ranged from 0.6 to 2.8 with an average of(2.56±0.45) years;there were 26 cases in L4,5 segment and 15 cases in L5S1 segment. Visual analogue scale(VAS), Oswestry disability index(ODI), M-JOA score and TCM syndrome score were measured before and after 3 courses of treatment, and the clinical efficacy was evaluated by the standard of curative effect evaluation. RESULTS: After treatment, VAS [(3.24±1.45) vs(4.46±0.64)], ODI [(11.45±1.98)% vs (17.21±2.74)%] and TCM symptom score [(2.03±0.27) vs (3.99± 0.54)] of the observation group were lower than those of the control group. The score of M-JOA [(23.43±2.61) vs (19.37±1.62)] increased (P<0.05). The scores of VAS, ODI and TCM symptoms in the observation group were lower than those in the control group, while the scores of M-JOA were higher than those in the control group (P<0.05). CONCLUSION: Meridian massage is effective in the treatment of LDH, which can effectivelyrelieve low back pain, improve clinical symptoms and increaselumbar function, which is worthy of clinical promotion.

Trait-customized sampling of core collections from a winter wheat genebank collection supports association studies.

Subsampling a reduced number of accessions from ex situ genebank collections, known as core collections, is a widely applied method for the investigation of stored genetic diversity and for an exploitation by breeding and research. Optimizing core collections for genome-wide association studies could potentially maximize opportunities to discover relevant and rare variation. In the present study, eight strategies to sample core collections were implemented separately for two traits, namely susceptibility to yellow rust and stem lodging, on about 6,300 accessions of winter wheat (Triticum aestivum L.). Each strategy maximized different parameters or emphasized another aspect of the collection; the strategies relied on genomic data, phenotypic data or a combination thereof. The resulting trait-customized core collections of eight different sizes, covering the range between 100 and 800 accession samples, were analyzed based on characteristics such as population stratification, number of duplicate genotypes and genetic diversity. Furthermore, the statistical power for an association study was investigated as a key criterion for comparisons. While sampling extreme phenotypes boosts the power especially for smaller core collections of up to 500 accession samples, maximization of genetic diversity within the core collection minimizes population stratification and avoids the accumulation of less informative duplicate genotypes when increasing the size of a core collection. Advantages and limitations of different strategies to create trait-customized core collections are discussed for different scenarios of the availability of resources and data.

Predicting 3-month poor functional outcomes of acute ischemic stroke in young patients using machine learning.

BACKGROUND: Prediction of short-term outcomes in young patients with acute ischemic stroke (AIS) may assist in making therapy decisions. Machine learning (ML) is increasingly used in healthcare due to its high accuracy. This study aims to use a ML-based predictive model for poor 3-month functional outcomes in young AIS patients and to compare the predictive performance of ML models with the logistic regression model. METHODS: We enrolled AIS patients aged between 18 and 50 years from the Third Chinese National Stroke Registry (CNSR-III), collected between 2015 and 2018. A modified Rankin Scale (mRS) ≥ 3 was a poor functional outcome at 3 months. Four ML tree models were developed: The extreme Gradient Boosting (XGBoost), Light Gradient Boosted Machine (lightGBM), Random Forest (RF), and The Gradient Boosting Decision Trees (GBDT), compared with logistic regression. We assess the model performance based on both discrimination and calibration. RESULTS: A total of 2268 young patients with a mean age of 44.3 ± 5.5 years were included. Among them, (9%) had poor functional outcomes. The mRS at admission, living alone conditions, and high National Institutes of Health Stroke Scale (NIHSS) at discharge remained independent predictors of poor 3-month outcomes. The best AUC in the test group was XGBoost (AUC = 0.801), followed by GBDT, RF, and lightGBM (AUCs of 0.795, 0, 794, and 0.792, respectively). The XGBoost, RF, and lightGBM models were significantly better than logistic regression (P < 0.05). CONCLUSIONS: ML outperformed logistic regression, where XGBoost the boost was the best model for predicting poor functional outcomes in young AIS patients. It is important to consider living alone conditions with high severity scores to improve stroke prognosis.

Serum liver enzymes and risk of stroke: Systematic review with meta-analyses and Mendelian randomization studies.

BACKGROUND AND PURPOSE: Previous observational studies have identified correlations between liver enzyme levels and stroke risk. However, the strength and consistency of these associations vary. To comprehensively evaluate the relationship between liver enzymes and stroke risk, we conducted meta-analyses complemented by Mendelian randomization (MR) analyses. METHODS: Following the PRISMA guidelines, we performed meta-analyses of prospective studies and conducted subgroup analyses stratified by sex and stroke subtype. Subsequently, adhering to the STROBE-MR guidelines, we performed two-sample bidirectional univariable MR (UVMR) and multivariable MR (MVMR) analyses using the largest genome-wide association studies summary data. Finally, the single-nucleotide polymorphisms associated with liver enzymes on sex differences underwent gene annotation, gene set enrichment, and tissue enrichment analyses. RESULTS: In the meta-analyses of 17 prospective studies, we found the relative risks for serum γ-glutamyl transferase (GGT) and alkaline phosphatase (ALP) were 1.23 (95% CI: 1.16-1.31) and 1.3 (95% CI: 1.19-1.43), respectively. Subgroup analyses revealed sex and stroke subtype differences in liver enzyme-related stroke risk. Bidirectional UVMR analyses confirmed that elevated GGT, alanine aminotransferase, and aspartate aminotransferase levels were associated with increased stroke occurrence. The primary results from the MVMR analyses revealed that higher ALP levels significantly increased the risk of stroke and ischemic stroke. Gene set and tissue enrichment analyses supported genetic differences in liver enzymes across sexes. CONCLUSIONS: Our study provides evidence linking liver enzyme levels to stroke risk, suggesting liver enzymes as potential biomarkers for early identification of high-risk individuals. Personalized, sex-specific interventions targeting liver enzymes could offer new strategies for stroke prevention.

A Novel Anion Receptor Additive for -40ºC Sodium Metal Batteries by Anion/Cation Solvation Engineering.

Sodium metal batteries, known for their high theoretical specific capacity, abundant reserves, and promising low-temperature performance, have garnered significant attention. However, the large ionic radius of Na+ and sluggish transport kinetics across the interfacial structure hinder their practical application. Previous reviews have rarely regulated electrolyte performance from the perspective of anions; as important components of the electrolyte, the regulation mechanism is not well understood. Herein, a novel anion receptor additive, 4-aminophenylboronic acid pinalol ester (ABAPE), is proposed to weaken the coupling between anions and cations and accelerate Na+ transport kinetics. The results of theoretical calculations and X-ray photoelectron spectroscopy with deep Ar-ion etching demonstrate that the introduction of this additive alters the solvation structure of Na+, reduces the desolvation barrier and forms a stable and dense electrode-electrolyte interface. Moreover, ABAPE forms hydrogen bonds (-NH···O/F) with H2O/HF, effectively preventing the hydrolysis of NaPF6 and stabilizing acidic species. Consequently, the Na||Na symmetric cell exhibits excellent long-cycle performance of 500 h at 1 mA cm-2 and 0.5 mAh cm-2. The Na||Na3V2(PO4)3 (NVP) full cell with the addition of ABAPE maintains a capacity retention of 84.29% at 1 C after 1200 cycles and presents no capacity decay over 150 cycles at -40°C.

Predicting functional outcome in ischemic stroke patients using genetic, environmental, and clinical factors: a machine learning analysis of population-based prospective cohort study.

Ischemic stroke (IS) is a leading cause of adult disability that can severely compromise the quality of life for patients. Accurately predicting the IS functional outcome is crucial for precise risk stratification and effective therapeutic interventions. We developed a predictive model integrating genetic, environmental, and clinical factors using data from 7819 IS patients in the Third China National Stroke Registry. Employing an 80:20 split, we randomly divided the dataset into development and internal validation cohorts. The discrimination and calibration performance of models were evaluated using the area under the receiver operating characteristic curves (AUC) for discrimination and Brier score with calibration curve in the internal validation cohort. We conducted genome-wide association studies (GWAS) in the development cohort, identifying rs11109607 (ANKS1B) as the most significant variant associated with IS functional outcome. We employed principal component analysis to reduce dimensionality on the top 100 significant variants identified by the GWAS, incorporating them as genetic factors in the predictive model. We employed a machine learning algorithm capable of identifying nonlinear relationships to establish predictive models for IS patient functional outcome. The optimal model was the XGBoost model, which outperformed the logistic regression model (AUC 0.818 versus 0.756, P < .05) and significantly improved reclassification efficiency. Our study innovatively incorporated genetic, environmental, and clinical factors for predicting the IS functional outcome in East Asian populations, thereby offering novel insights into IS functional outcome.

Comparative First-Principles Study of the Y2Ti2O7/Matrix Interface in ODS Alloys.

Oxide-dispersion-strengthened (ODS) alloys generally exhibit extraordinary service performance under severe conditions through the formation of ultrafine nano oxides. Y2Ti2O7 has been characterized as the major strengthening oxide in Fe-based ODS alloys. First-principles energetic analyses were performed to investigate the structural, elastic and interface properties of Y2Ti2O7 in either Fe-based or Ni-based ODS alloys. Y2Ti2O7 has comparable elastic constants to bcc-Fe and fcc-Ni and similar elastic deformation compatibility in Y2Ti2O7-strengthened Fe-based and Ni-based ODS alloys is therefore expected. The Ni/oxide interface has generally better thermostability than Fe/oxide across the whole range of the concerned oxygen chemical potential. Further interface bonding and adhesion calculations revealed that Y2Ti2O7 can enhance the bonding strength of Ni/Y2Ti2O7 through d-d orbital interaction between the interfacial YTi layer and Ni layer, while the interface bonding between the Fe layer and YTi layer is weakened compared to the metal matrix. First-principles calculations suggest that Y2Ti2O7 can be a candidate for strengthening nano-oxides in either Fe-based or Ni-based ODS alloys with well-behaved mechanical properties for fourth-generation fission reactors and further experimental validations are encouraged.

miR-182-5p promotes the proliferation and invasion of hilar cholangiocarcinoma cells by inhibiting FBXW7.

BACKGROUND: Hilar cholangiocarcinoma (HCCA) is a common type of cholangiocarcinoma (CHOL) that originates from the right and/or left hepatic duct near the biliary tract confluence. The objective of this study is to investigate the impact of miR-182-5p on the proliferation and invasion of HCCA cells and identify a potential target for HCCA treatment. METHODS: HCCA tissues were collected and HCCA cells were cultured. miR-182-5p and F-box and WD repeat domain containing 7 (FBXW7) were detected. After transfection of miR-182-5p inhibitor into HCCA cells, cell proliferation and invasion were detected by cell counting 8-kit and Transwell assay. FBXW7 expression was detected by Western blot. The targeted relationship between miR-182-5p and FBXW7 3'UTR was verified by dual-luciferase report assay. si-FBXW7 and miR-182-5p inhibitor were transfected into cells for combined experiments. HCCA cells with lowly-expressed miR-182-5p were injected into nude mice to establish the xenograft tumor model, and subsequent observations were made on tumor growth and gene expression changes. RESULTS: miR-182-5p exhibited high expression levels in both HCCA tissues and cell lines. Inhibiting miR-182-5p effectively suppressed the proliferation and migration of HCCA cells. miR-182-5p bounded to FBXW7 3 'UTR and inhibited FBWX7 expression. Suppressing FBXW7 expression partially reversed the inhibitory effect of miR-182-5p inhibitor on HCCA cell proliferation and invasion. Silencing miR-182-5p could inhibit the HCCA growth in vivo. CONCLUSION: miR-182-5p promoted the proliferation and invasion of HCCA cells by targeting and inhibiting FBXW7 expression.

Flow-electrode capacitive separation of organic acid products and recovery of alkali cations after acidic CO2 electrolysis.

Acidic CO2 electrolysis, enhanced by the introduction of alkali cations, presents a strategic approach for improving carbon efficiency compared to processes conducted in neutral and alkaline environments. However, a significant challenge arises from the dissolution of both organic acids and alkali cations in a strongly acidic feed stream, resulting in a considerable energy penalty for downstream separation. In this study, we investigate the feasibility of using flow-electrode capacitive deionization (FCDI) technology to separate organic acids and recover alkali cations from a strongly acidic feed stream (pH ~ 1). We show that organic acids, such as formic acid and acetic acid, are retained in molecular form in the separation chamber, achieving a rejection rate of over 90% under all conditions. Alkali cations, such as K+ and Cs+, migrate to the cathode chamber in ionic form, with their removal and recovery significantly influenced by their concentration and the pH of the feed stream, but responding differently to the types and concentrations of organic acids. The energy consumption for the removal and recovery of K+ is 4 to 8 times higher than for Cs+, and the charge efficiency is significantly influenced by the types of organic acid products and alkali cations. We conduct a series of electrochemical measurements and analyze the impedance spectroscopy, identifying that hindered mass transfer governed the electrode process. Our findings underscore the potential of FCDI as an advanced downstream separation technology for acidic electrocatalysis processes.

The application of lung immune prognostic index in predicting the prognosis of 302 STS patients.

Background: Soft tissue sarcoma (STS) are heterogeneous and rare tumors, and few studies have explored predicting the prognosis of patients with STS. The Lung Immune Prognostic Index (LIPI), calculated based on baseline serum lactate dehydrogenase (LDH) and the derived neutrophils/(leukocytes minus neutrophils) ratio (dNLR), was considered effective in predicting the prognosis of patients with pulmonary cancer and other malignancies. However, the efficacy of the LIPI in predicting the prognosis of patients with STS remains unclear. Methods: This study retrospectively reviewed patients with STS admitted to our center from January 2016 to January 2021. Their hematological and clinical characteristics were collected and analyzed to construct the LIPI specific to STS. The correlations between various predictive factors and overall survival (OS) were examined using Kaplan-Meier and Cox regression analyses. Independent risk factors for OS were identified using univariate and multivariate analyses. Finally, a LIPI nomogram model for STS was established. Results: This study enrolled 302 patients with STS, of which 87 (28.9%), 162 (53.6%), and 53 (17.5%) were classified into three LIPI-based categories: good, moderate, and poor, respectively (P < 0.0001). The time-dependent operator curve showed that the LIPI had better prognostic predictive ability than other hematological and clinical characteristics. Univariate and multivariate analyses identified the Fédération Nationale des Centres de Lutte Contre le Cancer grade (FNCLCC/G), tumor size, and LIPI as independent risk factors. Finally, a nomogram was constructed by integrating the significant prognostic factors. Its C-index was 0.72, and the calibration curve indicated that it could accurately predict the three- and five-year OS of patients with STS. The decision and clinical impact curves also indicated that implementing this LIPI-nomogram could significantly benefit patients with STS. Conclusion: This study explored the efficacy of the LIPI in predicting the prognosis of 302 patients with STS, classifying them into three categories to evaluate the prognosis. It also reconstructed a LIPI-based nomogram to assist clinicians in predicting the three- and five-year OS of patients with STS, potentially enabling timely intervention and customized management.

Trait-based community assembly and functional strategies across three subtropical karst forests, Southwestern China.

Background: Variations in community-level plant functional traits are widely used to elucidate vegetation adaptation strategies across different environmental gradients. Moreover, studying functional variation among different forest types aids in understanding the mechanisms by which environmental factors and functional strategies shift community structure. Methods: Based on five plant functional traits, including four leaf and one wood trait, for 150 woody species, we analyzed shifts in the community-weighted mean trait values across three forest types in a karst forest landscape: deciduous, mixed, and evergreen forests. We also assessed the relative contributions of stochastic processes, environmental filtering, and niche differentiation to drive community structure using a trait-based null model approach. Results: We found marked changes in functional strategy, from resource acquisition on dry, fertile soil plots in deciduous forests to resource conservation on moist, infertile soil conditions in evergreen forests. The trait-based null model showed strong evidence of environmental filtering and convergent patterns in traits across three forest types, as well as low niche differentiation in most functional traits. Some evidence of overdispersion of LDMC and LT occurred to partially support the recent theory of Scheffer and Van Nes that competition could result in a clumped pattern of species along a niche axis. Discussion: Our findings suggest a change in environmental gradient from deciduous to evergreen forest, together with a shift from acquisitive to conservative traits. Environmental filtering, stochastic processes, niche differentiation, and overdispersion mechanisms together drive community assembly in karst forest landscapes. These findings will contribute to a deeper understanding of the changes in functional traits among karst plants and their adaptive strategies, with important implications for understanding other community assemblies in subtropical forest systems.

Methylation of KSHV vCyclin by PRMT5 contributes to cell cycle progression and cell proliferation.

Kaposi's sarcoma-associated herpesvirus (KSHV) is a double-stranded DNA virus that encodes numerous cellular homologs, including cyclin D, G protein-coupled protein, interleukin-6, and macrophage inflammatory proteins 1 and 2. KSHV vCyclin encoded by ORF72, is the homolog of cellular cyclinD2. KSHV vCyclin can regulate virus replication and cell proliferation by constitutively activating cellular cyclin-dependent kinase 6 (CDK6). However, the regulatory mechanism of KSHV vCyclin has not been fully elucidated. In the present study, we identified a host protein named protein arginine methyltransferase 5 (PRMT5) that interacts with KSHV vCyclin. We further demonstrated that PRMT5 is upregulated by latency-associated nuclear antigen (LANA) through transcriptional activation. Remarkably, knockdown or pharmaceutical inhibition (using EPZ015666) of PRMT5 inhibited the cell cycle progression and cell proliferation of KSHV latently infected tumor cells. Mechanistically, PRMT5 methylates vCyclin symmetrically at arginine 128 and stabilizes vCyclin in a methyltransferase activity-dependent manner. We also show that the methylation of vCyclin by PRMT5 positively regulates the phosphorylate retinoblastoma protein (pRB) pathway. Taken together, our findings reveal an important regulatory effect of PRMT5 on vCyclin that facilitates cell cycle progression and proliferation, which provides a potential therapeutic target for KSHV-associated malignancies.