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The relentless rise in heart disease incidence, a leading global cause of death, presents a significant public health challenge. Precise prediction of heart disease risk and early interventions are crucial. This study investigates the performance improvement of heart disease prediction models using machine learning and deep learning algorithms. Initially, we utilized the Heart Failure Prediction Dataset from Kaggle. After preprocessing to ensure data quality, three distinct feature engineering techniques were applied: PCA for dimensionality reduction, ET for feature selection, and Pearson's correlation coefficient for feature selection. We assessed their impact on model performance. The dataset was then partitioned into three different data split ratios—1:9, 2:8, and 3:7—to determine their specific effects on model performance. Twelve machine learning classifiers—LGBM, Adaboost, XGB, RF, DT, KNN, LR, GNB, ET, SVC, GB, and Bagging—were trained and evaluated based on five key metrics: accuracy, recall, precision, F1 score, and training time. The influence of different feature engineering methods and data partitioning ratios on model performance were systematically analyzed using paired-sample t-tests. Among the feature engineering methods compared, the Bagging classifier, when combined with feature selection via ET, exhibited superior performance. It achieved an accuracy of 97.48 % and an F1-Score of 97.48 % with a data split ratio of 1:9 between the test and training sets. With a 2:8 split, the accuracy was 94.96 % and the F1-Score was 94.95 %. For a 3:7 split, the accuracy was 94.12 % and the F1-Score was 94.11 %. Paired sample T-test results indicate that feature selection using Pearson correlation coefficient can shorten training duration, but this also leads to a decline in classifier performance. After applying PCA dimensionality reduction, compared with the control group, there was no significant difference in the training efficiency and efficacy of the classifier. However, feature selection through ET significantly reduced the training time for various classifiers while ensuring their performance.

Abstract Background Alcohol dehydrogenase (ADH) is an enzyme that binds to zinc, facilitating the interconversion of ethanol and acetaldehyde or other corresponding alcohols/aldehydes in the pathway of ethanol fermentation. It plays a pivotal role in responding to environmental stress. However, the response of the ADH family to abiotic stress remains unknown in rapeseed. Result In this study, we conducted a comprehensive genome-wide investigation of the ADH family in rapeseed, encompassing analysis of their gene structure, replication patterns, conserved motifs, cis-acting elements, and response to stress. A total of 47 ADH genes were identified within the rapeseed genome. Through phylogenetic analysis, BnADHs were classified into four distinct clades (I, II, IV, V). Prediction of protein domains revealed that all BnADH members possessed a GroES-like (ADH_N) domain and a zinc-bound (ADH_zinc_N) domain. Analysis of promoter sequences demonstrated that BnADHs contained numerous cis-acting elements associated with hormone and stress responses, indicating their widespread involvement in various biological regulatory processes. Expression profiling under different concentrations of salt stress treatments (0%, 0.4%, 0.8%, 1.0% NaCl) further highlighted the significant role played by the BnADH family in abiotic stress response mechanisms. Overexpression of BnADH36 in rapeseed significantly improved the salt tolerance of rapeseed. Conclusion The features of the BnADH family in rapeseed was comprehensively characterized in this study, which could provide reference to the research of BnADHs in abiotic stress response.

Abstract Optical fiber sensors (OFSs) have attracted more and more attention in the field of in-situ ocean observation because of their advantages of the small size, light weight, low cost, and intrinsic immunity to electromagnetic interference. Here, we comprehensively reviewed the development of various advanced physical and chemical OFSs for in-situ measurement of ocean key parameters, including temperature, salinity, pressure, acoustics, flow velocity and turbulence, potential of hydrogen (pH), heavy metal ions, nitrates, and gases. Moreover, the performances of different kinds of OFSs and their practical sea trial reports for in-situ measurement in the marine environment are provided. As we discussed, the field of OFS is rapidly evolving and is poised to make essential breakthroughs in marine monitoring, leading to better utility of marine resources.

Abstract Public spaces in traditional villages are the root of the development, preservation, and inheritance of rural cultural heritage. However, these spaces in tourism-oriented traditional villages continue to suffer from issues such as inconsistent vitality, more competition than cooperation, and inefficient revitalisation. Limited by the low precision of spatiotemporal data in rural areas, previous static and materialised vitality evaluation methods have failed to explore the dynamic nature of the flow of people in traditional village public spaces. This study investigated a collaborative active perception method using Wi-Fi probes and static snapshots to assess their dynamic vitality. An empirical study was conducted using Yantou Village in Lishui City, China, as an example. The empirical results indicate that this method can qualitatively and quantitatively analyze the spatiotemporal variations and the scenarios of the dynamic vitality of small public spaces in traditional villages, deepening the cognitive depth of their vitality from time and humanity, providing a basis for the spatiotemporal synergistic enhancement of their public spaces, and offering insights for their revitalisation.

Abstract Peroxisomes are dynamic organelles involved in various cellular processes, including lipid metabolism, redox homeostasis, and intracellular metabolite transfer. Accumulating evidence suggests that peroxisomal homeostasis plays a crucial role in human health and disease, particularly in metabolic disorders and ferroptosis. The abundance and function of peroxisomes are regulated by a complex interplay between biogenesis and degradation pathways, involving peroxins, membrane proteins, and pexophagy. Peroxisome-dependent lipid metabolism, especially the synthesis of ether-linked phospholipids, has been implicated in modulating cellular susceptibility to ferroptosis, a newly discovered form of iron-dependent cell death. This review discusses the current understanding of peroxisome homeostasis, its roles in redox regulation and lipid metabolism, and its implications in human diseases. We also summarize the main mechanisms of ferroptosis and highlight recent discoveries on how peroxisome-dependent metabolism and signaling influence ferroptosis sensitivity. A better understanding of the interplay between peroxisomal homeostasis and ferroptosis may provide new insights into disease pathogenesis and reveal novel therapeutic strategies for peroxisome-related metabolic disorders and ferroptosis-associated diseases.

Abstract Introduction Pyroptosis, inflammatory necrosis of cells, is a programmed cell death involved in the pathological process of diseases. Endoplasmic reticulum stress (ERS), as a protective stress response of cell, decreases the unfold protein concentration to inhibit the unfold protein agglutination. Whereas the relationship between endoplasmic reticulum stress and pyroptosis in pulmonary hypertension (PH) remain unknown. Previous evident indicated that circular RNA (circRNA) can participate in several biological process, including cell pyroptosis. However, the mechanism of circRNA regulate pyroptosis of pulmonary artery smooth muscle cells through endoplasmic reticulum stress still unclear. Here, we proved that circSSR1 was down-regulate expression during hypoxia in pulmonary artery smooth muscle cells, and over-expression of circSSR1 inhibit pyroptosis both in vitro and in vivo under hypoxic. Our experiments have indicated that circSSR1 could promote host gene SSR1 translation via m6A to activate ERS leading to pulmonary artery smooth muscle cell pyroptosis. In addition, our results showed that G3BP1 as upstream regulator mediate the expression of circSSR1 under hypoxia. These results highlight a new regulatory mechanism for pyroptosis and provide a potential therapy target for pulmonary hypertension. Methods RNA-FISH and qRT-PCR were showed the location of circSSR1 and expression change. RNA pull-down and RIP verify the circSSR1 combine with YTHDF1. Western blotting, PI staining and LDH release were used to explore the role of circSSR1 in PASMCs pyroptosis. Results CircSSR1 was markedly downregulated in hypoxic PASMCs. Knockdown CircSSR1 inhibited hypoxia induced PASMCs pyroptosis in vivo and in vitro. Mechanistically, circSSR1 combine with YTHDF1 to promote SSR1 protein translation rely on m6A, activating pyroptosis via endoplasmic reticulum stress. Furthermore, G3BP1 induce circSSR1 degradation under hypoxic. Conclusion Our findings clarify the role of circSSR1 up-regulated parental protein SSR1 expression mediate endoplasmic reticulum stress leading to pyroptosis in PASMCs, ultimately promoting the development of pulmonary hypertension.

ABSTRACT Aims/Introduction Women with gestational diabetes mellitus are at high risk for adverse maternal and neonatal outcomes. The study aimed to evaluate the performance of the triglyceride‐glucose index in predicting the risk of developing adverse outcomes in women with gestational diabetes mellitus. Materials and Methods This retrospective multicenter cohort study included 8,808 pregnant women with gestational diabetes mellitus in two grade‐A tertiary hospitals in China during 2018–2022. The triglyceride‐glucose index was defined as ln [triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2]. Significant adverse gestational diabetes mellitus outcomes were chosen by generalized linear models as the main outcomes. Multivariable logistic regression models evaluated their association with the triglyceride‐glucose index. Areas under the receiver operating characteristic curves predicted adverse pregnancy outcomes. The prediction efficiency was validated in the sensitivity analysis dataset and validation cohort. Results The triglyceride‐glucose index was associated with preeclampsia, severe preeclampsia, preterm birth, placenta accreta spectrum, and macrosomia before and after adjusting for confounding factors (P

Abstract Brown planthopper (BPH) is the most destructive insect pest of rice. Drought is the most detrimental environmental stress. BPH infestation causes adaxial leaf-rolling and bulliform cells (BCs) shrinkage similar to drought. The BC-related abaxially curled leaf1 (ACL1) gene negatively regulates BPH resistance and drought tolerance, with decreased cuticular wax in the gain-of-function mutant ACL1-D. ACL1 shows an epidermis-specific expression. The TurboID system and multiple biochemical assays reveal that ACL1 interacts with the epidermal-characteristic rice outermost cell-specific (ROC) proteins. ROC4 and ROC5 positively regulate BPH resistance and drought tolerance through modulating cuticular wax and BCs, respectively. Overexpression of ROC4 and ROC5 both rescue ACL1-D mutant in various related phenotypes. ACL1 competes with ROC4/ROC5 in homo-dimer and hetero-dimer formation, and interacts with the repressive TOPLESS-related proteins. Altogether, we illustrate that ACL1–ROC4/5 complexes synergistically mediate drought tolerance and BPH resistance through regulating cuticular wax content and BC development in rice, a mechanism that might facilitate BPH-resistant breeding.

Abstract Background Decellularized extracellular matrix (dECM) is an intriguing natural biomaterial that has garnered significant attention due to its remarkable biological properties. In our study, we employed a cell-matrixed nerve graft for the repair of sciatic nerve defects in rats. The efficacy of this approach was assessed, and concurrently, the underlying molecular regulatory mechanisms were explored to elucidate how such grafts facilitate nerve regeneration. Long noncoding RNAs (lncRNAs) regulate mRNA expression via multiple mechanisms, including post-transcriptional regulation, transcription factor effects, and competitive binding with miRNAs. These interactions between lncRNAs and mRNAs facilitate precise control of gene expression, allowing organisms to adapt to varying biological environments and physiological states. By investigating the expression profiles and interaction dynamics of mRNAs and lncRNAs, we can enhance our understanding of the molecular mechanisms through which cell-matrixed nerve grafts influence neural repair. Such studies are pivotal in uncovering the intricate networks of gene regulation that underpin this process. Results Weighted gene co-expression network analysis (WGCNA) utilizes clustering algorithms, such as hierarchical clustering, to aggregate genes with similar expression profiles into modules. These modules, which potentially correspond to distinct biological functions or processes, can subsequently be analyzed for their association with external sample traits. By correlating gene modules with specific conditions, such as disease states or responses to treatments, WGCNA enables a deeper understanding of the genetic architecture underlying various phenotypic traits and their functional implications. We identified seven mRNA modules and five lncRNA modules that exhibited associations with treatment or time-related events by WGCNA. We found the blue (mRNAs) module which displayed a remarkable enrichment in “axonal guidance” and “metabolic pathways”, exhibited strong co-expression with multiple lncRNA modules, including blue (related to “GnRH secretion” and “pyrimidine metabolism”), green (related to “arginine and proline metabolism”), black (related to “nitrogen metabolism”), grey60 (related to “PPAR signaling pathway”), and greenyellow (related to “steroid hormone biosynthesis”). All of the top 50 mRNAs and lncRNAs exhibiting the strongest correlation were derived from the blue module. Validation of key molecules were performed using immunohistochemistry and qRT-PCR. Conclusion Revealing the principles and molecular regulatory mechanisms of the interaction between materials and biological entities, such as cells and tissues, is a direction for the development of biomimetic tissue engineering technologies and clinically effective products.

Abstract Background “The hidden costs of informal caregiving” is an interdisciplinary concept. While caregivers make a significant contribution to the process of caregiving, they sacrifice their leisure time, and incur risks of dropping out of the job, impaired mental and physical health, and decreased well-being within the context of caregiving. Those invisible sacrifices are often overlooked and described as hidden costs of informal caregiving. However, the conceptualisation of hidden costs of informal caregiving has not yet been clarified and scientifically assessed. The research aimed to clarify the concept of hidden costs of informal caregiving and develop an operational definition. Methods Walker and Avant’s concept analysis was conducted. Databases of CBM, CNKI, WanFang, VIP, PubMed, Embase, CINAHL, Web of Science, MEDLINE, Cochrane Library, Econlit, CINAHL and ProQuest were searched with the term “hidden costs of informal caregiving”. Information about the uses of the concept, defining attributes, model cases, antecedents, consequences and empirical referents of hidden costs of informal caregiving was extracted and synthesized. Results A total of 25 articles were included. The six defining attributes of hidden costs of informal caregiving were identified as including “undertaken by informal caregivers”, “the time costs of caregiving”, “costs of career development” “physical well-being costs”, “mental well-being costs” and “social relationship costs”. Personal characteristics of the caregivers and care recipients, along with caregiving attributes, were among the antecedents. The consequences of hidden costs of informal caregiving resulted in negative influences which included poor quality of life, life-altering decisions, options for the type of care, some degree of economic hardship, decreased compliance with treatment plans and monetary value informal caregivers are willing to pay to be replaced. Conclusion This concept analysis decisively illuminated the hitherto nebulous concept and expanded the contents of hidden costs of informal caregiving, which will foster a deeper appreciation of the invisible cost of caregivers. Moreover, it will provide a reference for the study of the hidden costs of informal caregiving in future, contribute to the development of assessment tools and theoretical models of hidden costs of informal caregiving, and create a basis for designing an evidence-based care program.

Abstract Recently, multi-modal vision-language foundation models have gained significant attention in the medical field. While these models offer great opportunities, they still face crucial challenges, such as the requirement for fine-grained knowledge understanding in computer-aided diagnosis and the capability of utilizing very limited or even no task-specific labeled data in real-world clinical applications. In this study, we present MaCo, a masked contrastive chest X-ray foundation model that tackles these challenges. MaCo explores masked contrastive learning to simultaneously achieve fine-grained image understanding and zero-shot learning for a variety of medical imaging tasks. It designs a correlation weighting mechanism to adjust the correlation between masked chest X-ray image patches and their corresponding reports, thereby enhancing the model’s representation learning capabilities. To evaluate the performance of MaCo, we conducted extensive experiments using 6 well-known open-source X-ray datasets. The experimental results demonstrate the superiority of MaCo over 10 state-of-the-art approaches across tasks such as classification, segmentation, detection, and phrase grounding. These findings highlight the significant potential of MaCo in advancing a wide range of medical image analysis tasks.

Abstract Thyroid cancer is the most frequently observed endocrine-related malignancy among which anaplastic thyroid cancer (ATC) is the most fatal subtype. The synthesis of protein is active to satisfy the rapid growth of ATC tumor, but the mechanisms regulating protein synthesis are still unknown. Our research revealed that kinetochore protein NUF2 played an essential role in protein synthesis and drove the progression of ATC. The prognosis of patients with thyroid carcinoma was positively correlated with high NUF2 expression. Depletion of NUF2 in ATC cells notably inhibited the proliferation and induced apoptosis, while overexpression of NUF2 facilitated ATC cell viability and colony formation. Deletion of NUF2 significantly suppressed the growth and metastasis of ATC in vivo. Notably, knockdown of NUF2 epigenetically inhibited the expression of magnesium transporters through reducing the abundance of H3K4me3 at promoters, thereby reduced intracellular Mg2+ concentration. Furthermore, we found the deletion of NUF2 or magnesium transporters significantly inhibited the protein synthesis mediated by the PI3K/Akt/mTOR pathway. In conclusion, NUF2 functions as an emerging regulator for protein synthesis by maintaining the homeostasis of intracellular Mg2+, which finally drives ATC progression.

Abstract Background Promoting patient participation stands as a global priority in nursing care. Currently, there is a lack of a standardized tool to assess the culture of patient participation from the perspective of nurses in China. Aims To translate and examine the validity and reliability of the Patient Participation Culture Tool for healthcare workers (PaCT-HCW) on general hospital wards in Chinese nursing context. Methods A cross-sectional research study was conducted among 812 nurses. Brislin's recommendations were adhered to during the translation of the scale. Validity was assessed using construct validity, content validity, and face validity. Split-half reliability, test–retest reliability, and internal consistency reliability were used to evaluate dependability. The study was guided and reported following the STROBE checklist and recommendations for reporting the results of studies of instrument and scale development and testing. Results The Chinese version of PaCT-HCW (the PaCT-HCW-C) exhibits good face validity and content validity. A rigorous exploratory factor analyse verified a six-factor (competence, support, perceived lack of time, information sharing and dialogue, response to questions and acceptance of a new role) scale structure with a cumulative variance contribution of the factors with 44 items of 68.840%. With a Cronbach's α coefficient of 0.962, split-half reliability of 0.866, and intraclass correlation coefficients of 0.989, the instrument demonstrates great reliability. Confirmatory factor analysis results validated the consistency of the six factors with the structure of the PaCT-HCW-C scale. Conclusions The 44-item PaCT-HCW-C is a valid and reliable instrument with satisfactory psychometric properties. It could serve as a tool for assessing the effectiveness of international programs aimed at fostering patient participation from the perspective of nurses, while also providing insights from China's practical experiences.

Abstract Li metal batteries have been widely expected to break the energy‐density limits of current Li‐ion batteries, showing impressive prospects for the next‐generation electrochemical energy storage system. Although much progress has been achieved in stabilizing the Li metal anode, the current Li electrode still lacks efficiency and safety. Moreover, a practical Li metal battery requires a thickness‐controllable Li electrode to maximally balance the energy density and stability. However, due to the stickiness and fragile nature of Li metal, manufacturing Li ingot into thin electrodes from conventional approaches has historically remained challenging, limiting the sufficient utilization of energy density in Li metal batteries. Aiming at the practical application of Li metal anode, the current issues and their initiation mechanism are comprehensively summarized from the stability and processability perspectives. Recent advances in robust and ultra‐thin Li metal anode are outlined from methodology innovation to provide an overall insight. Finally, challenges and prospective developments regarding this burgeoning field are critically discussed to afford future outlooks. With the development of advanced processing and modification technology, we are optimistic that a truly great leap will be achieved in the foreseeable future toward the industrial application of Li metal batteries.

Abstract The inactivation of natural enzymes by radiation poses a great challenge to their applications for radiotherapy. Single-atom nanozymes (SAzymes) with high structural stability under such extreme conditions become a promising candidate for replacing natural enzymes to shrink tumors. Here, we report a CuN3-centered SAzyme (CuN3-SAzyme) that exhibits higher peroxidase-like catalytic activity than a CuN4-centered counterpart, by locally regulating the coordination environment of single copper sites. Density functional theory calculations reveal that the CuN3 active moiety confers optimal H2O2 adsorption and dissociation properties, thus contributing to high enzymatic activity of CuN3-SAzyme. The introduction of X-ray can improve the kinetics of the decomposition of H2O2 by CuN3-SAzyme. Moreover, CuN3-SAzyme is very stable after a total radiation dose of 500 Gy, without significant changes in its geometrical structure or coordination environment, and simultaneously still retains comparable peroxidase-like activity relative to natural enzymes. Finally, this developed CuN3-SAzyme with remarkable radioresistance can be used as an external field-improved therapeutics for enhancing radio-enzymatic therapy in vitro and in vivo. Overall, this study provides a paradigm for developing SAzymes with improved enzymatic activity through local coordination manipulation and high radioresistance over natural enzymes, for example, as sensitizers for cancer therapy.

Abstract Evolution of SARS-CoV-2 variants emphasizes the need for multivalent vaccines capable of simultaneously targeting multiple strains. SCTV01E is a tetravalent COVID-19 vaccine derived from the spike protein of SARS-CoV-2 variants Alpha, Beta, Delta, and Omicron BA.1. In this double-blinded placebo-controlled pivotal efficacy trial (NCT05308576), the primary endpoint was vaccine efficacy (VE) against COVID-19 seven days post-vaccination in individuals without recent infection. Other endpoints included evaluating safety, immunogenicity, and the VE against all SARS-CoV-2 infections in individuals meeting the study criteria. Between December 26, 2022, and January 15, 2023, 9,223 individuals were randomized at a 1:1 ratio to receive SCTV01E or a placebo. SCTV01E showed a VE of 69.4% (95% CI: 50.6, 81.0) 7 days post-vaccination, with 75 cases in the placebo group and 23 in the SCTV01E group for the primary endpoint. VEs were 79.7% (95% CI: 51.0, 91.6) and 82.4% (95% CI: 57.9, 92.6), respectively, for preventing symptomatic infection and all SARS-CoV-2 infections 14 days post-vaccination. SCTV01E elicited a 25.0-fold higher neutralizing antibody response against Omicron BA.5 28 days post-vaccination compared to placebo. Reactogenicity was generally mild and transient, with no reported vaccine-related SAE, adverse events of special interest (AESI), or deaths. The trial aligned with the shift from dominant variants BA.5 and BF.7 to XBB, suggesting SCTV01E as a potential vaccine alternative effective against present and future variants.

The forecast of the global numerical weather prediction model is often used as the background field to drive the regional mesoscale weather models, and its forecast quality has an important impact on the prediction skill of regional models. The mesoscale operational model in Central China uses the Global Forecast Field (NCEP GFS) of the US Center for Environmental Prediction as the background field, and its forecast accuracy needs to be improved. This paper proposes a method to improve the initial field of the model by using the three-dimensional variational method to assimilate the high-quality European Centre for Medium-range Weather Forecasts (ECMWF) fine-grid forecast field to improve the short-term forecasting ability of the model. At first, the error characters of the 12 h forecast products of NCEP GFS and ECMWF were analyzed by using sounding observations. The RMSE (root mean square error) of temperature, horizontal wind field and relative humidity of ECMWF 12 h forecast are smaller than those of NCEP GFS forecast. Second, sensitivity experiments of ECMWF forecast field assimilation with different resolutions were conducted. Finally, 1°×1° resolution was selected based on the sensitivity experiments and a series of the data assimilation experiments with 1°×1° resolution was performed for August 2021. The results are as follows. (1) The assimilation forecast of heavy rain from 11 to 13 August 2021 shows that after 12 hours of spin-up, the forecast error of the element field has been significantly improved, especially at the bottom of the model. The TS score of 12-36 h, 36-60 h and 60-84 h cumulative precipitation has a certain improvement, especially the forecast of rainstorm magnitude. (2) ECMWF forecast field assimilation sensitivity experiments with different resolutions show that the forecast effect of ECMWF forecast field with 1°×1° resolution is better than 0.5°×0.5° and 0.25°×0.25°. (3) A series of the data assimilation experiments for August 2021 shows that the assimilation of ECMWF 12 h 1°×1° predicted variables has a lower RMSE of the 12 h, 36 h and 60 h forecasted temperature, humidity and wind field in the vertical direction than the control experiments, and the TS score was significantly improved, especially for 50 mm heavy rain precipitation, with an increase of 13.33%, which can effectively improve the forecast skills of the Wuhan Mesoscale Model.

Abstract Background Q fever, caused by the zoonotic pathogen Coxiella burnetii, exhibits a worldwide prevalence. In China, Q fever is not recognized as a notifiable disease, and the disease is overlooked and underestimated in clinical practice, leading to diagnostic challenges. Case presentation We present a case series of three patients diagnosed with persistent Q fever between 2022 and 2023. The average age of our three cases was 63.33 years old, consisting of two males and one female. The medical history of the individuals included previous valve replacement, aneurysm followed by aortic stent-graft placement and prosthetic hip joint replacement. At the onset of the disease, only one case exhibited acute fever, while the remaining two cases were devoid of any acute symptoms. The etiology was initially overlooked until metagenomic next-generation sequencing test identified Coxiella burnetii from the blood or biopsy samples. Delayed diagnosis was noted, with a duration ranging from three months to one year between the onset of the disease and its confirmation. The epidemiological history uncovered that none of the three cases had direct exposure to domestic animals or consumption of unpasteurized dairy products. Case 1 and 2 resided in urban areas, while Case 3 was a rural resident engaged in farming. All patients received combination therapy of doxycycline and hydroxychloroquine, and no recurrence of the disease was observed during the follow-up period. Conclusion Q fever is rarely diagnosed and reported in clinical practice in our country. We should be aware of persistent Q fever in high-risk population, even with unremarkable exposure history. Metagenomic next-generation sequencing holds great potential as a diagnostic tool for identifying rare and fastidious pathogens such as Coxiella burnetii.

Abstract Background Accumulating evidence suggests that the gut microbiota and metabolites can modulate tumor responses to immunotherapy; however, limited data has been reported on biliary tract cancer (BTC). This study used metagenomics and metabolomics to identify characteristics of the gut microbiome and metabolites in immunotherapy-treated BTC and their potential as prognostic and predictive biomarkers. Methods This prospective cohort study enrolled 88 patients with BTC who received PD-1/PD-L1 inhibitors from November 2018 to May 2022. The microbiota and metabolites significantly enriched in different immunotherapy response groups were identified through metagenomics and LC-MS/MS. Associations between microbiota and metabolites, microbiota and clinical factors, and metabolites and clinical factors were explored. Results Significantly different bacteria and their metabolites were both identified in the durable clinical benefit (DCB) and non-durable clinical benefit (NDB) groups. Of these, 20 bacteria and two metabolites were significantly associated with survival. Alistipes were positively correlated with survival, while Bacilli, Lactobacillales, and Pyrrolidine were negatively correlated with survival. Predictive models based on six bacteria, four metabolites, and the combination of three bacteria and two metabolites could all discriminated between patients in the DCB and NDB groups with high accuracy. Beta diversity between two groups was significantly different, and the composition varied with differences in the use of immunotherapy. Conclusions Patients with BTC receiving immunotherapy have specific alterations in the interactions between microbiota and metabolites. These findings suggest that gut microbiota and metabolites are potential prognostic and predictive biomarkers for clinical outcomes of anti-PD-1/PD-L1-treated BTC.

This study was conducted to evaluate the effects of Monascus purpureus M-32 fermented soybean meal (MFSM) on growth, immunity, intestinal morphology, intestinal microbiota, and intestinal metabolome of Pacific white shrimp (Litopenaeus vannamei). Four groups of diets were formulated, including control group (30% fish meal and 30% soybean meal [SBM] included in the basal diet) and three experimental groups which MFSM replaced 20% (MFSM20), 40% (MFSM40), and 60% (MFSM60) of SBM in control group, respectively. Results showed that the soluble proteins larger than 49 kDa in MFSM were almost completely degraded. Meanwhile, the crude protein, acid-soluble protein, and amino acid in MFSM were increased. The results of shrimp culture experiment showed that the replacement of SBM with MFSM decreased FCR (P

This study examines the impact of political connections on charitable giving by private enterprises in China in the business environment context. The study constructs a nested structure model and empirically analyzes 1,426 sample enterprises from the 13th China Private Enterprise Survey (2018) data using stata15.1 software. The findings indicate that the business environment influences political connections, charitable giving, and their interaction. Political connections at the individual level of enterprise owners and core managers partly have a positive impact on the charitable giving of Chinese private enterprises. At the enterprise level, the formation of political connections, including the establishment of party organizations, cost-sharing, and receiving government subsidies, also enhances charitable giving. Additionally, certain attributes of private enterprises and entrepreneurs, such as age, year-on-year growth in net profit, and total bank loans, positively influence their charitable giving. However, a high debt-to-asset ratio may adversely affect a company’s charitable giving. These insights are invaluable for local entrepreneurs, authorities, and policymakers in understanding how to effectively conduct charitable giving within specific business and political environments. Academically, this study contributes to the corporate sociology literature by offering new perspectives and data support for future research.

Summary: Early prediction of acute pancreatitis (AP) with acute kidney injury (AKI) using abdominal contrast-enhanced CT could effectively reduce the mortality and the economic burden on patients and society. However, this challenge is limited by the imaging manifestations of early-stage AP that are not clearly visible to the naked eye. To address this, we developed a machine learning model using imperceptible variations in the structural changes of pancreas and peripancreatic region, extracted by radiomics and artificial intelligence technology, to screen and stratify the high-risk AP patients at the early stage of AP. The results demonstrate that the machine learning model could screen the high-risk AP with AKI patients with an area under the curve (AUC) of 0.82 for the external cohort, superior to the human radiologists. This finding confirms the significant potential of machine learning in the screening of acute pancreatitis and contributes to personalized treatment and management for AP patients.

Cancer poses a major threat to human health worldwide. The development of anti-tumor materials provides new modalities for cancer diagnosis and treatment. In this review, we comprehensively summarize the research progress and clinical applications of anti-tumor materials. First, we introduce the etiology and pathogenesis of cancer, and the significance and challenges of anti-tumor materials research. Then, we classify anti-tumor materials and discuss their mechanisms of action. After that, we elaborate the research advances and clinical applications of anti-tumor materials, including those targeting tumor cells and therapeutic instruments. Finally, we discuss the future perspectives and challenges in the field of anti-tumor materials. This review aims to provide an overview of the current status of anti-tumor materials research and application, and to offer insights into future directions in this rapidly evolving field, which holds promise for more precise, efficient and customized treatment of cancer.

Abstract Background Various epigenetic regulations systematically govern gene expression in cells involving various biological processes. Dysregulation of the epigenome leads to aberrant transcriptional programs and subsequently results in diseases, such as cancer. Therefore, comprehensive profiling epigenomics is essential for exploring the mechanisms underlying gene expression regulation during development and disease. Methods In this study, we developed single‐cell chromatin proteins and accessibility tagmentation (scCPA‐Tag), a multi‐modal single‐cell epigenetic profile capturing technique based on barcoded Tn5 transposases and a droplet microfluidics platform. scCPA‐Tag enables the simultaneous capture of DNA profiles of histone modification and chromatin accessibility in the same cell. Results By applying scCPA‐Tag to K562 cells and a hepatocellular carcinoma (HCC) sample, we found that the silence of several chromatin‐accessible genes can be attributed to lysine‐27‐trimethylation of the histone H3 tail (H3K27me3) modification. We characterized the epigenetic features of the tumour cells and different immune cell types in the HCC tumour tissue by scCPA‐Tag. Besides, a tumour cell subtype (C2) with more aggressive features was identified and characterized by high chromatin accessibility and a lower abundance of H3K27me3 on tumour‐promoting genes. Conclusions Our multi‐modal scCPA‐Tag provides a comprehensive approach for exploring the epigenetic landscapes of heterogeneous cell types and revealing the mechanisms of gene expression regulation during developmental and pathological processes at the single‐cell level. Highlights scCPA‐Tag offers a highly efficient and high throughput technique to simultaneously profile histone modification and chromatin accessibility within a single cell. scCPA‐Tag enables to uncover multiple epigenetic modification features of cellular compositions within tumor tissues. scCPA‐Tag facilitates the exploration of the epigenetic landscapes of heterogeneous cell types and provides the mechanisms governing gene expression regulation.

Dust deposition can supply nutrients to the upper ocean, and subsequently affect primary production and biodiversity in planktonic ecosystem, but the differential response among taxa and their interactions are not fully understood. Here, we performed 7-day onboard incubation experiment amended with different dust loadings (0, 0.2 and 2 mg L-1) in the Kuroshio-Oyashio transition region of the Northwest Pacific Ocean and characterized the community structure and microbial network of a planktonic microbiome in response to dust addition. Chlorophyll a and nutrient analysis indicated that dust-derived nitrogen promoted the growth of phytoplankton (165.8–293.6%) and phytoplankton size structure shifted towards larger cells (>3 μm). Metabarcoding sequencing, targeting prokaryotic and eukaryotic microbes, revealed the changes in community structure and co-occurrence network in response to dust addition. Dust induced a shift from dinoflagellate dominance toward diatom dominance in phytoplankton, and favored members of Cercozoa, Labyrinthulomycetes and Saprospirae, which showed positive correlation with diatom. Temporal response patterns among taxa were categorized into five clusters, and collectively pointed to a more sensitive microeukaryotic community than prokaryotic one in response to dust. The community turnover during the incubation was dominated by moderate taxa with 55.71-62.26% moderate OTUs transitioning to abundant or rare taxa, and dust addition stimulated the transitions of rare taxa. Moreover, biotic factors shaped planktonic microbiome more than abiotic factors, particularly the cross-domain interaction significantly affected microeukaryotic community. Notably, dust addition enhanced the co-occurrence network complexity, with the number of keystone taxa increased, suggesting more interspecies interactions were induced by dust. With integrated analysis, our findings highlight the differential sensitivity of planktonic microbiome to dust deposition and the effects could pass on other organisms through interspecies interaction.

Introduction6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase isoform 3 (PFKFB3) is highly expressed in several cancers and plays important roles during the whole pathological process of cancer. It is also involved in chemoresistance, while the intrinsic mechanism needs to be further revealed.MethodsThe different responses to cisplatin (DDP) between wild type (WT) and DDP-resistant (DDR) colorectal cancer (CRC) cells were analyzed by several assays. Coumarin conjugated DDP (CP-DDP) was utilized to trace the distribution of DDP. Pharmacological and genetic methods were used to deprive autophagy and PFKFB3, and the effects were investigated. The mouse xenograft model was performed to confirm the effect of the PFKFB3 inhibitor on reversing DDP resistance.ResultsDDR cells showed a lower capacity for apoptosis upon DDP treatment, but exhibited higher levels of autophagy and PFKFB3. CP-DDP partly co-localized with LC3, and its content lessened faster in DDR cells. Deprivation of both autophagy and PFKFB3 attenuated CP-DDP elimination, and reversed the DDP resistance. Moreover, PFKFB3 inhibition reduced DDP-induced autophagy. PFKFB3 inhibitor in combination with DDP led to a remarkable reduction in tumor growth in vivo.DiscussionsInhibition of PFKFB3 reduced the autophagy induced by DDP, and therefore extended the retention time of CP-DDP. Meanwhile, PFKFB3 deprivation reversed the DDP resistance and made it a potent therapeutic target for CRC.

Cytochromes P450 monooxygenases (CYP450s) constitute the largest enzymic protein family that is widely present in plants, animals, and microorganisms, participate in numerous metabolic pathways, and play diverse roles in development, metabolism, and defense. Rapeseed (Brassica napus) is an important oil crop worldwide and have many versions of reference genome. However, there is no systemically comparative genome-wide analysis of CYP450 family genes in rapeseed and its parental species B. rapa and B. oleracea. In this study, we identified 765, 293 and 437 CYP450 genes in B. napus, B. rapa and B. oleracea, respectively, which were unevenly located in A01-A10 and/or C01-C09 chromosomes in corresponding species. Phylogenetic relationship analysis indicated that 1745 CYP450 proteins from three Brassica species and Arabidopsis were divided into 4 groups. Whole genome duplication (WGD) or segmental duplication resulted in gene expansion of CYP450 family in three Brassica species. There were 33–83 SSR loci in CYP450 genes of three Brassica species, and numerous transcription factor binding sites were identified in their promoters. A total of 459–777 miRNAs were predicted to target 174–426 CYP450 genes in three Brassica species. Based on transcriptome data, BnCYP450s, BrCYP450s and BoCYP450s were differentially expressed in various tissues. There existed numerous BnCYP450 DEGs in response to pathogens and abiotic stresses. Besides, many BnCYP450 DEGs were involved in the regulation of important traits, such as seed germination, seed ALA content, and yellow-seed. The qRT-PCR experiment confirmed the transcriptome analysis results by validating two representative Sclerotinia-responsive BnCYP450 DEGs as an example. Three BnCYP450s genes (CYP707A1, CYP81F1, CYP81H1) might be regulated by seed-specific transcription factors BnTT1 and BnbZIP67 to participate in the development and metabolism of seed coat and embryo by undertaking related metabolic reactions.

Multiple myeloma (MM) is the second most prevalent hematological malignancy. Current MM treatment strategies are hampered by systemic toxicity and suboptimal therapeutic efficacy. This study addressed these limitations through the development of a potent MM-targeting chemotherapy strategy, which capitalized on the high binding affinity of alendronate for hydroxyapatite in the bone matrix and the homologous targeting of myeloma cell membranes, termed T-PB@M. The results from our investigations highlight the considerable bone affinity of T-PB@M, both in vitro and in vivo. Additionally, this material demonstrated a capability for drug release triggered by low pH conditions. Moreover, T-PB@M induced the generation of reactive oxygen species and triggered cell apoptosis through the poly(ADP-ribose) polymerase 1 (PARP1)–Caspase-3–B-cell lymphoma-2 (Bcl-2) pathway in MM cells. Notably, T-PB@M preferentially targeted bone-involved sites, thereby circumventing systemic toxic side effects and leading to prolonged survival of MM orthotopic mice. Therefore, this designed target-MM nanocarrier presents a promising and potentially effective platform for the precise treatment of MM.

Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease, and its morbidity and mortality are increasing. At present, there is no specific therapy available. An exacerbated IFN-I response and cytokine storm are related to the mortality of patients with SFTS. Ruxolitinib is a Janus kinase (JAK) 1/2 inhibitor that can block proinflammatory cytokines and inhibit the type I IFN pathway. We aimed to explore the use of ruxolitinib plus standard of care for severe SFTS. Methods We conducted a prospective, single-arm study of severe SFTS. We recruited participants aged 18 years or older who were admitted to the hospital with laboratory-confirmed severe SFTS and whose clinical score exceeded 8 points within 6 days of symptom onset. Participants received oral ruxolitinib (10 mg twice a day) for up to 10 days. The primary endpoint was 28-day overall survival. The secondary endpoints included the proportion of participants who needed intensive care unit (ICU) admission, total cost, changes in neurologic symptoms and clinical laboratory parameters, and adverse events (AEs) within 28 days. A historical control group (HC group, n = 26) who met the upper criteria for inclusion and hospitalized from April 1, 2021, to September 16, 2022, was selected and 1:1 matched for baseline characteristics by propensity score matching. Results Between Sep 16, 2022, and Sep 16, 2023, 26 participants were recruited into the ruxolitinib treatment group (RUX group). The 28-day overall mortality was 7.7% in the RUX group and 46.2% in the HC group (P = 0.0017). There was a significantly lower proportion of ICU admissions (15.4% vs 65.4%, p

Abstract Charge loss at grain boundaries of kesterite Cu2ZnSn(S, Se)4 polycrystalline absorbers is an important cause limiting the performance of this emerging thin-film solar cell. Herein, we report a Pd element assisted reaction strategy to suppress atomic vacancy defects in GB regions. The Pd, on one hand in the form of PdSe x compounds, can heterogeneously cover the GBs of the absorber film, suppressing Sn and Se volatilization loss and the formation of their vacancy defects (i.e. VSn and VSe), and on the other hand, in the form of Pd(II)/Pd(IV) redox shuttle, can assist the capture and exchange of Se atoms, thus contributing to eliminating the already-existing VSe defects within GBs. These collective effects have effectively reduced charge recombination loss and enhanced p-type characteristics of the kesterite absorber. As a result, high-performance kesterite solar cells with a total-area efficiency of 14.5% (certified at 14.3%) have been achieved.

Carbon nanotubes (CNTs), as a kind of nanopowder, can be used as reinforcing powder to improve various properties of coatings because of their good self-lubricating properties and three-dimensional structure. However, CNTs are difficult to mix uniformly with other powders due to their easily disrupted microstructure and extremely low density. Therefore, CoCrFeNiMn HEA and 2 wt% CNTs were mixed by a new mixing method—alcohol stirring and ball-less ball mill mixing methods. CoCrFeNiMn/2 wt% CNTs coatings prepared by laser cladding (LC). The phase composition, microstructure, wear resistance, and corrosion resistance of the HEA/CNTs coating were analyzed by various characterization techniques. The results showed that grain refinement occurred in the coatings after adding CNTs, generating fine carbides. It was calculated that the densification percentage of the HEA/CNTs coating increased and the porosity decreased. Compared with the HEA coating, the microhardness of the HEA/CNTs coating increased by 101.66%, and the friction coefficient and wear rate of the HEA/CNTs coating were only 63.30% and 6.22% of the HEA coating. The more positive Ecorr and smaller Icorr indicated that the HEA/CNTs coating has better corrosion resistance.

Abstract Self-powered skin attachable and detachable electronics are under intense development to enable the internet of everything and everyone in new and useful ways. Existing on-demand separation strategies rely on complicated pretreatments and physical properties of the adherends, achieving detachable-on-demand in a facile, rapid, and universal way remains challenging. To overcome this challenge, an ingenious cellulose nanofiber-mediated manifold dynamic synergy strategy is developed to construct a supramolecular hydrogel with both reversible tough adhesion and easy photodetachment. The cellulose nanofiber-reinforced network and the coordination between Fe ions and polymer chains endow the dynamic reconfiguration of supramolecular networks and the adhesion behavior of the hydrogel. This strategy enables the simple and rapid fabrication of strong yet reversible hydrogels with tunable toughness ((Value max -Value min )/Value max of up to 86%), on-demand adhesion energy ((Value max -Value min )/Value max of up to 93%), and stable conductivity up to 12 mS cm−1. We further extend this strategy to fabricate different cellulose nanofiber/Fe3+-based hydrogels from various biomacromolecules and petroleum polymers, and shed light on exploration of fundamental dynamic supramolecular network reconfiguration. Simultaneously, we prepare an adhesive-detachable triboelectric nanogenerator as a human-machine interface for a self-powered wireless monitoring system based on this strategy, which can acquire the real-time, self-powered monitoring, and wireless whole-body movement signal, opening up possibilities for diversifying potential applications in electronic skins and intelligent devices.

Bacteriocins from lactic acid bacteria are kinds of natural proteins or peptides with antibacterial activities produced by lactic acid bacteria in the process of metabolism. They have the advantages of non-drug resistance, biodegradation, good antibacterial activity, etc., which have broad application prospects in food, medicine and feed fields. Based on bibliometrics, the literatures related to bacteriocins from lactic acid bacteria are searched in CNKI database and Web of Science (WOS) core collection database from 2000 to 2023, obtains 627 Chinese literatures and 2543 English literatures. CiteSpace software is used to analyze the research status and hot spots in this field from the perspective of annual number of published papers, core countries, authors, institutions and journals, highly cited literatures, keyword co-occurrence and co-clustering, etc.. The results show that the number of literatures has an increasing trend from 2000 to 2022. Spain, India and China are the top three countries in terms of number of literatures. The authors with the highest number of publications in CNKI database and WOS database are LI Pinglan from China Agricultural University and Todorov SD from University of Sao Paulo in Brazil, respectively. The journals with the highest number of publications are “Science and Technology of Food Industry” and “Journal of Appled Micbiogy”. In the CNKI database, keyword analysis reveals that most of the literatures are isolated, screened and identified from different food samples to obtain bacteriocin-producing lactic acid bacteria, and further evaluates the antibacterial activity of bacteriocins, and discusses the application in the food industry. The analysis of burst words shows that the focus of current research are antibacterial mechanism of bacteriocin and the relationship between bacteriocin and probiotics. In WOS database, the keywords of "gastrointestinal tract", "genetic characteristics", "Listeria mononucleogenes" and "antibacterial activity" appears more frequently. The main focus is the mining of bacteriocins from lactic acid bacteria toward antibiotic-resistant bacteria, and analysis of the genetic characteristics. The comprehensive analysis provides a reference and help for Chinese scientific researchers to engage in related research and predict the future development trend of the industry.

Abstract The manipulation of excitation modes and resultant emission colors in luminescent materials holds pivotal importance for encrypting information in anti-counterfeiting applications. Despite considerable achievements in multimodal and multicolor luminescent materials, existing options generally suffer from static monocolor emission under fixed external stimulation, rendering them vulnerability to replication. Achieving dynamic multimodal luminescence within a single material presents a promising yet challenging solution. Here, we report the development of a phosphor exhibiting dynamic multicolor photoluminescence (PL) and photo-thermo-mechanically responsive multimodal emissions through the incorporation of trace Mn2+ ions into a self-activated CaGa4O7 host. The resulting phosphor offers adjustable emission-color changing rates, controllable via re-excitation intervals and photoexcitation powers. Additionally, it demonstrates temperature-induced color reversal and anti-thermal-quenched emission, alongside reproducible elastic mechanoluminescence (ML) characterized by high mechanical durability. Theoretical calculations elucidate electron transfer pathways dominated by intrinsic interstitial defects and vacancies for dynamic multicolor emission. Mn2+ dopants serve a dual role in stabilizing nearby defects and introducing additional defect levels, enabling flexible multi-responsive luminescence. This developed phosphor facilitates evolutionary color/pattern displays in both temporal and spatial dimensions using readily available tools, offering significant promise for dynamic anticounterfeiting displays and multimode sensing applications.

Abstract Background Timely and accurate identification of pathogens is crucial for appropriate treatment and prognosis of infectious diseases. As an increasingly popular pathogen detection method, the performance of metagenomic next-generation sequencing (mNGS) in detecting pathogens in febrile patients with suspected infection requires further exploration. Methods This study included 368 febrile patients with suspected infections who were admitted to the Infectious Disease Department of Qilu Hospital, Shandong University between January 5, 2021 and April 14, 2023. Both mNGS testing and conventional culture were performed in all patients. Clinical data of enrolled patients were collected, and the diagnostic performances of mNGS and culture were compared. Results Of the 368 enrolled patients, 231 were finally diagnosed with infection and 137 were with diseases other than infection. The sensitivity (58.01% vs. 21.65%, p

Abstract Based on the advantages of laser high brightness, a high-temperature mechanical property measuring device has been developed, which can measure the high-temperature strength of C/SiC composites under the condition of short-term high-temperature rise rate and solve the problem of over-oxidation of materials in conventional high-temperature mechanical properties experiments. The experimental results show that the maximum temperature rise rate is 260 ℃/s at the initial heating stage, and the test time is controlled within 35 s. The tensile strength of the prepared C/SiC composites decreased first and then increased at high temperatures and laser-induced high temperatures. The experimental results are similar to those in the literature under the inert atmosphere. Oxidation has less of an effect on the mechanical characteristics of materials under conditions of rapid temperature rise. The system can be used to test the mechanical properties of composite materials at high temperatures and as a simulation platform for the thermal response of specific thermal protection systems subjected to a constant heat flux. This study can provide a new idea for testing ultra-high temperature mechanical properties of C/SiC materials and provide key technical support for the engineering application and high-temperature testing of C/SiC materials in high-temperature environments.

Abstract The structural modeling of open-high-low-close (OHLC) data contained within the candlestick chart is crucial to financial practice. However, the inherent constraints in OHLC data pose immense challenges to its structural modeling. Models that fail to process these constraints may yield results deviating from those of the original OHLC data structure. To address this issue, a novel unconstrained transformation method, along with its explicit inverse transformation, is proposed to properly handle the inherent constraints of OHLC data. A flexible and effective framework for structurally modeling OHLC data is designed, and the detailed procedure for modeling OHLC data through the vector autoregression and vector error correction model are provided as an example of multivariate time-series analysis. Extensive simulations and three authentic financial datasets from the Kweichow Moutai, CSI 100 index, and 50 ETF of the Chinese stock market demonstrate the effectiveness and stability of the proposed modeling approach. The modeling results of support vector regression provide further evidence that the proposed unconstrained transformation not only ensures structural forecasting of OHLC data but also is an effective feature-extraction method that can effectively improve the forecasting accuracy of machine-learning models for close prices.

Objectives: This study aimed to investigate the association between drug exposure and adverse events (AEs) during the standardized multidrug-resistant tuberculosis (MDR-TB) treatment, as well as to identify predictive drug exposure thresholds. Methods: We conducted a prospective, observational multicenter study among participants receiving standardized MDR-TB treatment between 2016 and 2019 in China. AEs were monitored throughout the treatment and their relationships to drug exposure (e.g., the area under the drug concentration-time curve from 0 to 24 h, AUC0-24 h) were analyzed. The thresholds of pharmacokinetic predictors of observed AEs were identified by boosted classification and regression tree (CART) and further evaluated by external validation. Results: Of 197 study participants, 124 (62.9%) had at least one AE, and 15 (7.6%) experienced serious AEs. The association between drug exposure and AEs was observed including bedaquiline, its metabolite M2, moxifloxacin and QTcF prolongation (QTcF >450 ms), linezolid and mitochondrial toxicity, cycloserine and psychiatric AEs. The CART-derived thresholds of AUC0-24 h predictive of the respective AEs were 3.2 mg·h/l (bedaquiline M2); 49.3 mg·h/l (moxifloxacin); 119.3 mg·h/l (linezolid); 718.7 mg·h/l (cycloserine). Conclusions: This study demonstrated the drug exposure thresholds predictive of AEs for key drugs against MDR-TB treatment. Using the derived thresholds will provide the knowledge base for further randomized clinical trials of dose adjustment to minimize the risk of AEs.

Accurate predictions of species distribution and coexistence in response to environmental changes depend on a thorough understanding of how functional traits relate to environmental conditions. However, there is still limited evidence regarding the sources of functional trait variation and the environmental mechanisms that regulate these traits in tropical forests. This study focuses on Dacrydium pectinatum de Laub., a crucial and endangered species native to the tropical mountain forests of Hainan Island, China. We gathered functional trait data from 68 permanent plots of D. pectinatum situated in three regions: Bawangling (163 tree species), Diaoluoshan (127 tree species), and Jianfengling (175 tree species). Nine functional traits were measured at the species level, and their variation patterns and sources were analyzed using linear mixed-effects models and variance decomposition methods. Our findings reveal that environmental pressures cause variations in trait relationships across different site conditions at the species level. Typically, inter-specific trait variation exceeds intra-specific variation, particularly for leaf area (LA) and specific leaf area (SLA). This indicates that trait variability is influenced by how species adapt to and balance specific environmental conditions. Site conditions significantly impact trait variation, especially for SLA, leaf dry matter content (LDMC), and wood density (WD). Additionally, intraspecific variation is notable for certain traits, reflecting individual responses to environmental heterogeneity. At the community level, eight out of nine traits exhibit significant changes in community-weighted mean (CWM) across various site conditions and environmental gradients. For instance, LA's CWM increases with soil fertility, whereas SLA, leaf nitrogen content (LNC), and leaf phosphorus content (LPC) show differences between site conditions. LDMC and WD decrease significantly in high-fertility environments, suggesting a transition from resource conservation to resource acquisition strategies within communities as soil fertility rises. Geographic variables play a crucial role in trait distributions across different community levels, with elevation and soil factors also contributing significantly to trait variation. Overall, our study provides direct evidence of how environmental filtering influences plant functional trait distributions and community assembly. Future research should explore the mechanisms driving these trait-environment relationships and their responses across various ecological contexts.

Sorafenib (SF), a multi-targeted tyrosine kinase inhibitor, serves as a primary therapeutic modality for advanced liver cancer. Nonetheless, its clinical efficacy is hindered by various obstacles, such as limited bioavailability and inadequate accumulation. This study introduces a novel biomimetic mineralization enzyme, known as BSA@Pt/Ce6/SF@M (PCFM). The PCFM incorporates platinum (Pt) as a catalytic agent, SF as a molecular-targeted therapeutic agent, and Ce6 as a photosensitizer within liver cancer cell membranes. This strategy enables the combination of various anti-tumor treatments, such as photodynamic therapy (PDT) and autophagy induction, leading to increased bioavailability of SF and achieving a multidimensional synergistic anticancer effect. The PDT effect produced by Ce6 in PCFM greatly enhances SF-induced autophagy, effectively promoting autophagic cell death. Furthermore, Pt dissociates from the biomineralization process, acquiring peroxidase properties through chemokinetic reactions. This facilitates the catalysis of significant oxygen generation, addressing the challenge of hypoxia in the tumor microenvironment and improving the efficacy of PDT. Moreover, the SF further enhances therapeutic efficacy by inducing autophagy in response to energy deprivation, as indicated by the reduced levels of HIF-1α, p62, along with increased levels of ROS and LC3-Ⅱ/Ι. This biomineralization-based nanoenzyme exhibits strong anti-tumor characteristics, offering a novel strategy for overcoming challenges in liver cancer treatment.

Blue carbon refers to the carbon fixed in marine ecosystems such as mangroves, salt marshes, and seagrass beds. Considered a treasure house for capturing and storing carbon dioxide, it can alleviate environmental issues linked to climate change and positively influence the environments where people live. Thus, to clarify the hotspots and development trends of blue carbon research, bibliometric analysis incorporating ScientoPy and VOSviewer software were used to quantitatively analyze 4,604 blue carbon publications from Web of Science and Scopus databases between 1993 and 2023. The results indicate a rapidly growing number of published studies on blue carbon, with blue carbon research being multifaceted and gradually becoming an interdisciplinary and international topic. This study on blue carbon, which is based on keyword clustering analysis, comprises three stages. The analysis of the strength of the cooperative connections between scholars in various countries who have published work on blue carbon. found that the cooperation networks of developed countries are strong and those of developing countries are relatively weak. Quantitative trend analysis reveals a growing focus on the restoration and conservation of blue carbon ecosystems, with remote sensing being the predominant technology used in the blue carbon research field in recent years. In blue carbon research, increasing carbon sequestration capacity, climate change mitigation, and carbon sequestration in macroalgae remain potential hotspots for research and development.

Multi-functional triply periodic minimal surface (TPMS) structures have been widely studied and proven to have significant importance. Most studies are based on several typical TPMSs. However, some research suggests that the hybrid forms of the TPMSs can exhibit superior mechanical properties. The challenge lies in the unpredictability of the hybrid TPMS property. In this study, an approach is proposed for precisely identify the hybrid TPMS using fully connected neural network (FCNN) and particle swarm optimization (PSO) algorithm. A design space of four TPMSs hybridization is introduced and used to generate over 8000 samples. Stiffness constants obtained using the homogenization method is used in elastic characterization. The hybrid TPMSs is proved to lack common cubic symmetry but possess wide rotational symmetry. Indirect stiffness constant-based way exhibits better predictions for optimal stiffness and elastic isotropy than direct property parameter-based one. The approach successfully identified useful structures: quasi-elastic-isotropic ones and a ultra-stiff one that is ∼ 9 % stronger than the currently strongest TPMS. The method offers comprehensive guidance for stiffness constant-based TPMS design using DL technique.

Introduction: Numerous studies have explored the treatment outcomes of Nirmatrelvir-Ritonavir and Azvudine in older patients with COVID-19. However, direct comparisons between these two drugs are still relatively limited. This study aims to compare the safety and effectiveness of these two drugs in Chinese older patients with early infection to provide strategies for clinical treatment.Methods: Older COVID-19 patients (age ≥65) hospitalized during the winter 2022 epidemic in China were included and divided into Nirmatrelvir-Ritonavir and Azvudine. Demographics, medication information, laboratory parameters, and treatment outcomes were collected. All-cause 28-day mortality, delta cycle threshold (ΔCt), nucleic acid negative conversion time, and incidence of adverse events were defined as outcomes. Propensity score matching (PSM), Kaplan-Meier, Cox proportional hazards model, subgroup analysis, and nomograms were selected to evaluate the outcomes.Results: A total of 1,508 older COVID-19 patients were screened. Based on the inclusion and exclusion criteria, 1,075 patients were eligible for the study. After PSM, the final number of older COVID-19 patients included in the study was 375, and there were no significant differences in demographic characteristics between the two groups (p > 0.05). Compared to the Azvudine group, the Nirmatrelvir-Ritonavir group showed a higher incidence of multiple adverse events (12.8% vs 5.2%, p = 0.009). The incidence of adverse events related to abnormal renal function was higher in the Nirmatrelvir-Ritonavir group compared to the Azvudine group (13.6% vs 7.2%, p = 0.045). There were no significant differences between the two groups in terms of all-cause 28-day mortality (HR = 1.020, 95% CI: 0.542 - 1.921, p = 0.951), whereas there were significant differences in nucleic acid negative conversion time (HR = 1.659, 95% CI: 1.166 - 2.360, p = 0.005) and ΔCt values (HR = 1.442, 95% CI: 1.084 - 1.918, p = 0.012).Conclusion: Azvudine and Nirmatrelvir-Ritonavir have comparable effectiveness in reducing mortality risk. Azvudine may perform better in nucleic acid negative conversion time and virus clearance and shows slightly better safety in older patients. Further studies with a larger sample size were needed to validate the result.

Defective oocyte maturation is a common cause of female infertility. The loss of the zona pellucida (ZP) represents a specific condition of impaired oocyte maturation. The extracellular matrix known as the ZP envelops mammalian oocytes and preimplantation embryos, exerting significant influence on oogenesis, fertilization, and embryo implantation. However, the genetic factors leading to the loss of the ZP in oocytes are not well understood. This study focused on patients who underwent oocyte retrieval surgery after ovarian stimulation and were found to have abnormal oocyte maturation without the presence of the ZP. Ultrasonography was performed during the surgical procedure to evaluate follicle development. Peripheral blood samples from the patient were subjected to exome sequencing. Here, a novel, previously unreported heterozygous mutation in the ZP1 gene was identified. Within the ZP1 gene, we discovered a novel heterozygous mutation (ZP1 NM_207341.4:c.785A>G (p.Y262C)), specifically located in the trefoil domain. Bioinformatics comparisons further revealed conservation of the ZP1-Y262C mutation across different species. Model predictions of amino acid mutations on protein structure and cell immunofluorescence/western blot experiments collectively confirmed the detrimental effects of the ZP1-Y262C mutation on the function and expression of the ZP1 protein. The ZP1-Y262C mutation represents the novel mutation in the trefoil domain of the ZP1 protein, which is associated with defective oocyte maturation in humans. Our report enhances comprehension regarding the involvement of ZP-associated genes in female infertility and offers enriched understanding for the genetic diagnosis of this condition.

Background The association between gut bacteria and the response to immune checkpoint inhibitors (ICI) in hepatocellular carcinoma (HCC) has been studied; however, multi-kingdom gut microbiome alterations and interactions in ICI-treated HCC cohorts are not fully understood.Methods From November 2018 to April 2022, patients receiving ICI treatment for advanced HCC were prospectively enrolled. Herein, we investigated the multi-kingdom microbiota characterization of the gut microbiome, mycobiome, and metabolome using metagenomic, ITS2, and metabolomic data sets of 80 patients with ICI-treated HCC.Results Our findings demonstrated that bacteria and metabolites differed significantly between the durable clinical benefit (DCB) and non-durable clinical benefit (NDB) groups, whereas the differences were smaller for fungi. The overall diversity of bacteria and fungi before treatment was higher in the DCB group than in the NDB group, and the difference in diversity began to change with the use of immunotherapy after 6–8 weeks. We also explored the alterations of gut microbes in the DCB and NDB groups, established 18 bacterial species models as predictive biomarkers for predicting whether immunotherapy is of sustained benefit (area under the curve=75.63%), and screened two species of bacteria (Actinomyces_sp_ICM47, and Senegalimassilia_anaerobia) and one metabolite (galanthaminone) as prognostic biomarkers for predicting survival in patients with HCC treated with ICI.Conclusions In this study, the status and characterization of the multi-kingdom microbiota, including gut bacteria, fungi, and their metabolites, were described by multiomics sequencing for the first time in patients with HCC treated with ICI. Our findings demonstrate the potential of bacterial taxa as predictive biomarkers of ICI clinical efficacy, and bacteria and their metabolites as prognostic biomarkers.

ObjectivesUnder the system of health decentralization, there are differences in the level of expenditure decentralization at different levels of government, and their impact on residents’ health may also be different. This paper is one of the first to evaluate the effect of decentralization of health services at the municipal level from a multi-dimensional health perspective.Data and methodsThis paper uses the data of expenditure decentralization of health services at the municipal level to match the panel data from the China Household Panel Survey (CFPS) from 2010 to 2018, and uses the logit model, ordered logit model and two-way fixed effects model to empirically analyze the impact of health decentralization at the municipal level on health outcomes.ResultsBased on the perspective of multi-dimensional health, from the three aspects of physical health, depression status and cognitive ability, the six sub-indicators of self-rated health, BMI standards, depression scores (summation method), depression scores (factor method), phrase test scores and mathematics test scores are discussed separately. The results show that the decentralization of health services at the municipal level has a significant promotion effect on the multi-dimensional health of residents.ConclusionThe decentralization of health services at the municipal level has important theoretical significance for promoting the reasonable division of medical and health powers and expenditure responsibilities between provincial and municipal governments, improving the efficiency of health expenditure funds, and establishing a fiscal system that matches financial resources.

Abstract This article uses ultra‐high performance concrete (UHPC) to repair damaged concrete and analyzes the durability performance of the repaired concrete. Among them, three erosion solutions with a mass concentration of 2.8% NaCl + 0.29% Na2SO4, 5% NaCl, and 5% NaCl + 10% Na2SO4 were designed to soak the concrete specimens for 1 to 3 months. Taking the SWC test group as an example, when the concrete test block undergoes 30 dry wet cycles and the erosion depth is 20 mm, the difference in chloride ion concentration under different diffusion dimensions is not significant. After 90 dry wet cycles, at a depth of 20 mm, the chloride ion concentration inside the concrete in the three‐dimensional diffusion state reached 3 times that of one‐dimensional diffusion, and the chloride ion concentration in the two‐dimensional diffusion state also reached 2 times that of one‐dimensional diffusion. At a depth of 30 mm, a small amount of chloride ion content was also found in the two‐dimensional diffusion and three‐dimensional diffusion.