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Abstract The outbreaks of severe acute respiratory syndrome coronavirus (SARS-CoV-1), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2 highlight the need for countermeasures to prevent future coronavirus pandemics. Given the unpredictable nature of spillover events, preparing antibodies with broad coronavirus-neutralizing activity is an ideal proactive strategy. Here, we investigated whether SARS-CoV-2 infection and vaccination could provide cross-neutralizing antibodies (nAbs) against zoonotic sarbecoviruses. We evaluated the cross-neutralizing profiles of plasma and monoclonal antibodies constructed from B cells from coronavirus disease 2019 (COVID-19) convalescents and vaccine recipients; against sarbecoviruses originating from bats, civets, and pangolins; and against SARS-CoV-1 and SARS-CoV-2. We found that the majority of individuals with natural infection and vaccination elicited broad nAb responses to most tested sarbecoviruses, particularly to clade 1b viruses, but exhibited very low cross-neutralization to SARS-CoV-1 in both natural infection and vaccination, and vaccination boosters significantly augmented the magnitude and breadth of nAbs to sarbecoviruses. Of the nAbs, several exhibited neutralization activity against multiple sarbecoviruses by targeting the spike receptor-binding domain (RBD) and competing with angiotensin-converting enzyme 2 (ACE2) binding. SCM12-61 demonstrated exceptional potency, with half-maximal inhibitory concentration (IC50) values of 0.001–0.091 μg/mL against tested sarbecoviruses; while VSM9-12 exhibited remarkable cross-neutralizing breadth against sarbecoviruses and SARS-CoV-2 Omicron subvariants, highlighting the potential of these two nAbs in combating sarbecoviruses and SARS-CoV-2 Omicron subvariants. Collectively, our findings suggest that vaccination with an ancestral SARS-CoV-2 vaccine, in combination with broad nAbs against sarbecoviruses, may provide a countermeasure for preventing further sarbecovirus outbreaks in humans.

Abstract Background Atherosclerosis and metabolic syndrome are the main causes of cardiovascular events, but their underlying mechanisms are not clear. In this study, we focused on identifying genes associated with diagnostic biomarkers and effective therapeutic targets associated with these two diseases. Methods Transcriptional data sets of atherosclerosis and metabolic syndrome were obtained from GEO database. The differentially expressed genes were analyzed by RStudio software, and the function-rich and protein-protein interactions of the common differentially expressed genes were analyzed.Furthermore, the hub gene was screened by Cytoscape software, and the immune infiltration of hub gens was analyzed. Finally, relevant clinical blood samples were collected for qRT-PCR verification of the three most important hub genes. Results A total of 1242 differential genes (778 up-regulated genes and 464 down-regulated genes) were screened from GSE28829 data set. A total of 1021 differential genes (492 up-regulated genes and 529 down-regulated genes) were screened from the data set GSE98895. Then 23 up-regulated genes and 11 down-regulated genes were screened by venn diagram. Functional enrichment analysis showed that cytokines and immune activation were involved in the occurrence and development of these two diseases. Through the construction of the Protein–Protein Interaction(PPI) network and Cytoscape software analysis, we finally screened 10 hub genes. The immune infiltration analysis was further improved. The results showed that the infiltration scores of 7 kinds of immune cells in GSE28829 were significantly different among groups (Wilcoxon Test 0.3 & P 0.3 & P

Abstract Periodontitis is a critical risk factor for the occurrence and development of diabetes. Porphyromonas gingivalis may participate in insulin resistance (IR) caused by periodontal inflammation, but the functional role and specific mechanisms of P. gingivalis in IR remain unclear. In the present study, clinical samples were analysed to determine the statistical correlation between P. gingivalis and IR occurrence. Through culturing of hepatocytes, myocytes, and adipocytes, and feeding mice P. gingivalis orally, the functional correlation between P. gingivalis and IR occurrence was further studied both in vitro and in vivo. Clinical data suggested that the amount of P. gingivalis isolated was correlated with the Homeostatic Model Assessment for IR score. In vitro studies suggested that coculture with P. gingivalis decreased glucose uptake and insulin receptor (INSR) protein expression in hepatocytes, myocytes, and adipocytes. Mice fed P. gingivalis tended to undergo IR. P. gingivalis was detectable in the liver, skeletal muscle, and adipose tissue of experimental mice. The distribution sites of gingipain coincided with the downregulation of INSR. Gingipain proteolysed the functional insulin-binding region of INSR. Coculture with P. gingivalis significantly decreased the INSR–insulin binding ability. Knocking out gingipain from P. gingivalis alleviated the negative effects of P. gingivalis on IR in vivo. Taken together, these findings indicate that distantly migrated P. gingivalis may directly proteolytically degrade INSR through gingipain, thereby leading to IR. The results provide a new strategy for preventing diabetes by targeting periodontal pathogens and provide new ideas for exploring novel mechanisms by which periodontal inflammation affects the systemic metabolic state.

Abstract Background Metabolic dysfunction-associated fatty liver disease (MAFLD) is a growing threat leading to substantial disease burden globally. Poor sleep and physical inactivity are common in modern societies and independently associated with MAFLD, however, their joint effects on MAFLD remains unclear. Methods This population-based cross-sectional study was conducted in Xinjiang Uygur Autonomous Region, China, between July 2019 and September 2021. Self-reported sleep behaviors and physical activity (PA) were assessed using validated questionnaires. The primary outcome was radiological diagnosis of MAFLD. Results Of the 10 089 participants aged 47.0 (9.1) years (51.6% men), 3854 (38.2%) individuals had MAFLD. Poor sleep quality and physical inactivity were independently and jointly associated with an increased prevalence of MAFLD, independent of traditional risk factors (P

Abstract Background Women at middle age are puzzled by a series of menopausal disturbances, can be distressing and considerably affect the personal, social and work lives. We aim to estimate the global prevalence of nineteen menopausal symptoms among middle-aged women by performing a systematic review and meta-analysis. Methods Comprehensive search was performed in multiple databases from January, 2000 to March, 2023 for relevant studies. Random-effect model with double-arcsine transformation was used for data analysis. Results A total of 321 studies comprised of 482,067 middle-aged women were included for further analysis. We found varied prevalence of menopausal symptoms, with the highest prevalence of joint and muscular discomfort (65.43%, 95% CI 62.51–68.29) and lowest of formication (20.5%, 95% CI 13.44–28.60). Notably, South America shared dramatically high prevalence in a sort of menopausal symptoms including depression and urogenital symptoms. Besides, countries with high incomes (49.72%) had a significantly lower prevalence of hot flashes than those with low (65.93%), lower-middle (54.17%), and upper-middle (54.72%, p

Abstract Autophagy is a highly conserved eukaryotic pathway and plays a crucial role in cell survival under stress conditions. Here, we applied a full-length transcriptome approach to study an Arabidopsis autophagy mutant (atg5-1) subjected to nitrogen-starvation, using Oxford Nanopore Technologies. A total of 39,033 transcripts were identified, including 11,356 new transcripts. In addition, alternative splicing (AS) events and lncRNAs were also detected between Col-0 (WT) and atg5-1. Differentially expressed transcript enrichment showed that autophagy upregulates the expression of many stress-responsive genes and inhibits the transcription of photosynthesis-associated genes. The qRT-PCR results showed that the expression patterns of photosynthesis-related genes in the atg5-1 differed under the conditions of nitrogen starvation and carbon starvation. Under nitrogen starvation treatment, many genes related to photosynthesis also exhibited AS. Chlorophyll fluorescence images revealed that the Fv/Fm and ΦPSII of old atg5-1 leaves were significantly reduced after nitrogen starvation treatment, but the Y(NPQ) indices were significantly increased compared to those of the WT plants. The results of qRT-PCR suggest that autophagy appears to be involved in the degradation of genes related to photodamage repair in PSII. Taken together, the full-length transcriptiome sequencing provide new insights into how new transcripts, lncRNAs and alternative splicing (AS) are involved in plant autophagy through full-length transcriptome sequencing and suggest a new potential link between autophagy and photosynthesis.

Background and objective: Empowering rural life through digital technology reflects the collective aspirations of millions of farmers striving for a better quality of life. Ensuring that the benefits of digital advancements reach every corner of the population is a crucial and inevitable choice. To expedite the establishment of an inclusive digital life for all citizens, the Chinese government has exerted substantial efforts by positioning the development of digital villages as a national strategy. Through comprehensive initiatives in digital village construction, facilitating the extension of ''Internet+'' services such as education, healthcare, transportation, and entertainment to rural areas. 24-hour digital village libraries, smart health stations, intelligent homes, facial recognition payments, unmanned supermarkets, and a variety of digitized, networked, and intelligent lifestyle applications are increasingly prevalent in Chinese rural regions. The digital gap between urban and rural areas in China is gradually diminishing, and the ongoing evolution of rural digital lifestyles paints a picturesque picture of an enhanced rural life. This study endeavors to provide a meticulous analysis of the digital landscape in Chinese villages, seeking to unravel the intricacies behind the swift development of rural digital life. Methods: Using the top 100 counties in China's 2020 Rural Life Digitization Index ranking as case studies, this research collected the necessary data through industry research reports and official statistical sources. To begin with, based on the Technology-Organization-Environment (TOE) analysis framework, variables such as digital infrastructure, government policy support, funds are put into utilization, digital economy level, and farmer digital literacy were identified. The fuzzy set qualitative comparative analysis (fsQCA) method was then employed to recognize the influencing factors of rural digital life and combinations of condition variables. Subsequently, utilizing the system dynamics methodology, the relationships between factors were analyzed, simulating changes in rural digital life development to gain a deeper understanding of the key elements affecting rural digital life. Sensitivity analysis was conducted to further reveal the extent of influence of these key elements on rural digital life. Results: The fuzzy set qualitative comparative analysis reveals that the evolution of rural digital life in China is a complex outcome influenced by the simultaneous interplay of multiple factors. It demonstrates a pattern of diverse combinations and parallel pathways encompassing various variables. Among these configurations, six paths stand out with the highest coverage. These six paths can be further classified into three modes of rural digital life development in China: environment-empowered type, organization-pushed type, and compound-driven type. Further dissection of causal combinations through a system dynamics model unveils that the progression of rural digital life is intricately linked to key factors such as information infrastructure, policy intensity, and digital learning and development. Over time, there is a discernible upward trajectory in the level of rural digital life, characterized by an accelerating pace of improvement. The influence of policy intensity on rural digital life surpasses that of information infrastructure and digital learning and development, indicating that policy intensity exerts the most significant impact overall. Conclusion: The evolution of rural digital life in China is a complex, long-term process propelled by a combination of multiple factors. China's experience demonstrates that achieving high-level development in rural digital life demands attention not only to the synergistic interplay of various factors but also a strategic focus on leveraging specific key elements. This entails skillfully integrating diverse factors and identifying pivotal areas to maximize the impact of relevant conditions to the greatest extent possible.

By engaging in redox processes, ferroptosis plays a crucial role in sepsis-induced acute lung injury (ALI). Although iron stimulates calcium signaling through the stimulation of redox-sensitive calcium pathways, the function of calcium signals in the physiological process of ferroptosis in septic ALI remains unidentified. Iron homeostasis disequilibrium in ferroptosis is frequently accompanied by aberrant calcium signaling. Intracellular calcium overflow can be a symptom of dysregulation of the cellular redox state, which is characterized by iron overload during the early phase of ferroptosis. This can lead to disruptions in calcium homeostasis and calcium signaling. The mechanisms controlling iron homeostasis and ferroptosis are reviewed here, along with their significance in sepsis-induced acute lung injury, and the potential role of calcium signaling in these processes is clarified. We propose that the development of septic acute lung injury is a combined process involving the bidirectional interaction between iron homeostasis and calcium signaling. Our goal is to raise awareness about the pathophysiology of sepsis-induced acute lung injury and investigate the relationship between these mechanisms and ferroptosis. We also aimed to develop calcium-antagonistic therapies that target ferroptosis in septic ALI and improve the quality of survival for patients suffering from acute lung injury.

The WRKY gene family consists of unique transcription factors (TFs) found exclusively in plants. These TFs play a crucial role in regulating how plants respond to various abiotic stresses, such as saline-alkaline conditions, temperature fluctuations, drought, UV radiation and others. Scientists have been progressively studying the roles and mechanisms of WRKY in several plant species, including both model plants and essential agricultural crops. This study focus has emerged due to the understanding that alkaline and saline soil stressors considerably impede global agricultural productivity. Multiple research efforts have underscored the significant biological functions of WRKY TFs in assisting plants in coping with various abiotic challenges, particularly in enhancing their ability to withstand alkaline-salt stress. This review aims to investigate the structural capabilities of WRKY TFs and their impact on plant responses to alkaline and salt stresses. Additionally, it seeks to elucidate the role of these TFs in alleviating diverse abiotic and biotic stressors. The objective of this review study is to provide comprehensive insights into the current state of the field and the importance of WRKY TFs in regulating plant responses to salt and alkaline stress.

Abstract Fulvestrant, as the first selective estrogen receptor degrader, is widely used in the endocrine treatment of breast cancer. However, in the real world, there is a lack of relevant reports on adverse reaction data mining for fulvestrant. To perform data mining on adverse events (AEs) associated with fulvestrant and explore the risk factors contributing to severe AEs, providing a reference for the rational use of fulvestrant in clinical practice. Retrieved adverse event report information associated with fulvestrant from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database, covering the period from market introduction to September 30, 2023. Suspicious AEs were screened using the reporting odds ratio (ROR) and proportional reporting ratio methods based on disproportionality analysis. Univariate and multivariate logistic regression analyses were conducted on severe AEs to explore the risk factors associated with fulvestrant-induced severe AEs. A total of 6947 reports related to AEs associated with fulvestrant were obtained, including 5924 reports of severe AEs and 1023 reports of non-severe AEs. Using the disproportionality analysis method, a total of 210 valid AEs were identified for fulvestrant, with 45 AEs (21.43%) not listed in the product labeling, involving 11 systems and organs. The AEs associated with fulvestrant were sorted by frequency of occurrence, with neutropenia (325 cases) having the highest number of reports. By signal strength, injection site pruritus showed the strongest signal (ROR = 658.43). The results of the logistic regression analysis showed that concurrent use of medications with extremely high protein binding (≥ 98%) is an independent risk factor for severe AEs associated with fulvestrant. Age served as a protective factor for fulvestrant-related AEs. The co-administration of fulvestrant with CYP3A4 enzyme inhibitors did not show statistically significant correlation with the occurrence of severe AEs. Co-administration of drugs with extremely high protein binding (≥ 98%) may increase the risk of severe adverse reactions of fulvestrant. Meanwhile, age (60–74 years) may reduce the risk of severe AEs of fulvestrant. However, further clinical research is still needed to explore and verify whether there is interaction between fulvestrant and drugs with high protein binding through more clinical studies.

BackgroundThe staff in centers for disease control and prevention (CDC) were at a great risk for psychological distress when they were faced with outbreak-related prevention and control work and routine tasks during the COVID-19 period. Psychological resilience and burnout are two key influencing factors on psychological distress. ObjectiveTo explore the status and mechanisms of psychological resilience, burnout, and psychological distress among CDC staff. MethodsFrom September to October 2022, a cross-sectional survey was conducted in all CDC staff in Beijing, and 2228 CDC staff from 17 units (including 1 municipality-level CDC and 16 district-level CDCs) participated the questionnaire survey. The basic information questionnaire, Connor-Davidson Resilience Scale (CD-RISC-10) Chinese version, Maslach Burnout Inventory-General Survey (MBI-GS) Chinese version, and the 10-item Kessler Psychological Distress Scale (Kessler10) Chinese version were selected in our study. Mann-Whitney U test or Kruskal-Wallis H test was used to analyze the differences in the scores of psychological resilience, burnout, and psychological distress by demographic and sociological characteristics. The correlations among the three elements were analyzed by Spearman correlation analysis. Potential influencing factors of psychological distress of the CDC staff were evaluated by multiple linear regression. A potential mediating effect of psychological resilience-burnout-psychological distress was analyzed by the mediation package of R 4.2.0, and validated by Bootstrap method. ResultsOf 2228 questionnaires distributed, 2022 valid questionnaires were collected, and the recovery rate was 90.75%. The median (P25, P75) psychological distress score of CDC staff was 13.00 (8.00, 24.00), and the number of participants with psychological distress levels of 1, 2, 3, and 4 was 358 (17.71%), 546 (27.00%), 362 (17.90%), and 756 (37.39%), respectively. The median (P25, P75) psychological resilience score was 24.00 (20.00, 30.00) and the median (P25, P75) burnout score was 38.00 (25.00, 50.00). The results of the multiple linear regression showed that psychological resilience, burnout, caring for the elderly, having a chronic disease, and monthly income had independent influences on psychological distress (P

Abstract Along with the progress of natural language processing technology and deep learning, the subjectivity, slow feedback, and long grading time of traditional English essay grading have been addressed. Intelligent English automatic scoring has been widely concerned by scholars. Given the limitations of topic relevance feature extraction methods and traditional automatic grading methods for English compositions, a topic decision model is proposed to calculate the topic relevance score of the topic richness in English composition. Then, based on the Score of Relevance Based on Topic Richness (TRSR) calculation method, an intelligent English composition scoring method combining artificial feature extraction and deep learning is designed. From the findings, the Topic Decision (TD) model achieved the best effect only when it was iterated 80 times. The corresponding accuracy, recall and F1 value were 0.97, 0.93 and 0.95 respectively. The model training loss finally stabilized at 0.03. The Intelligent English Composition Grading Method Integrating Deep Learning (DLIECG) method has the best overall performance and the best performance on dataset P. To sum up, the intelligent English composition scoring method has better effectiveness and reliability.

Flooding, as a natural disaster, plays a pivotal role in constraining the growth and development of plants. Flooding stress, including submergence and waterlogging, not only induces oxygen, light, and nutrient deprivation, but also alters soil properties through prolonged inundation, further impeding plant growth and development. However, hypoxia (or anoxia) is the most serious and direct damage to plants caused by flooding. Moreover, flooding disrupts the structural integrity of plant cell walls and compromises endoplasmic reticulum functionality, while hindering nutrient absorption and shifting metabolic processes from normal aerobic respiration to anaerobic respiration. It can be asserted that flooding exerts comprehensive effects on plants encompassing phenotypic changes, transcriptional alterations, protein dynamics, and metabolic shifts. To adapt to flooding environments, plants employ corresponding adaptive mechanisms at the phenotypic level while modulating transcriptomic profiles, proteomic characteristics, and metabolite levels. Hence, this study provides a comprehensive analysis of transcriptomic, proteomic, and metabolomics investigations conducted on flooding stress on model plants and major crops, elucidating their response mechanisms from diverse omics perspectives.

Introduction Care workers play a fundamental role in delivering care services in long-term care institutions. Burnout has been found to have a negative impact on care recipients and organisations providing care. Little is known about the key factors associated with care workers’ burnout. This systematic review aims to explore the prevalence, severity and correlates of burnout among care workers before and during COVID-19 pandemic.Methods and analysis A five-stage framework outlined by Whittemore and Knafl will be used. The following databases will be used to identify relevant literature, including Medline (PubMed), EMBASE, Cochrane library, PsycINFO, CINAHL, Scopus and Web of Science. RevMan will be used to assist the meta-analysis. Heterogeneity of the included studies will be tested using the I2 test.Ethics and dissemination No ethics approval is required as this study only involves secondary data analysis. The findings will be published in peer-reviewed journals and presented at relevant conferences.PROSPERO registration number CRD42024499178.

BackgroundSerum ferritin (SF) is clinically found to be elevated in many disease conditions, and our research examines serum ferritin in patients with acute kidney injury (AKI) and its implication on the risk of short-term mortality in AKI.MethodsData were extracted from the Medical Information Mart for Intensive Care IV 2.2 (MIMIC-IV 2.2) database. Adult patients with AKI who had serum ferritin tested on the first day of ICU admission were included. The primary outcome was 28-day mortality. Kaplan–Meier survival curves and Cox proportional hazards models were used to test the relationship between SF and clinical outcomes. Subgroup analyses based on the Cox model were further conducted.ResultsKaplan–Meier survival curves showed that a higher SF value was significantly associated with an enhanced risk of 28-day mortality, 90-day mortality, ICU mortality and hospital mortality (log-rank test: p 0.05).ConclusionHigh level of SF is an independent prognostic predictor of 28-day mortality in patients with AKI.

Abstract Objective This study aims to investigate the prevalence of dyslipidemia and assess the joint association of physical activity (PA) and diet quality on dyslipidemia risk in urban areas of Xinjiang. Methods Conducted from July 2019 to September 2021 in Xinjiang, China, this cross-sectional study involved 11,855 participants (mean age 47.1 ± 9.4 years, 53.1% male). Standard methods were used to measure plasma cholesterol levels, and validated questionnaires were employed to evaluate dietary habits and PA. The definition of dyslipidemia is based on 2023 Chinese guidelines for lipid management. PA was divided into guideline-recommended moderate-to-vigorous physical activity (MVPA) and non-MVPA, following World Health Organization guidelines. The Food Frequency Questionnaire was used to obtain the intake frequency of each dietary term. Each item was scored based on consumption frequency and divided into three groups (good, intermediate, and poor) based on total dietary score. Multivariate logistic regression analysis was performed to identify dyslipidemia risk factors, as well as the joint association of PA and diet quality. Results Dyslipidemia prevalence among urban adults in Xinjiang was 39.3%, with notable sex disparities (52.6% in males vs. 24.3% in females, P

As an assistive device to restore lower limb athletic ability, human lower limb rehabilitation robots are becoming increasingly important in the field of rehabilitation and clinical applications. With the advancement of science and technology, both domestic and foreign research in this field has been developed. This study provides a detailed overview of the development of lower limb rehabilitation robots and reviews the current status of clinical applications, with a focus on mechanism research, from the perspectives of degrees of freedom, workspace, singularity, gait simulation, kinematic simulation and human-robot interaction, etc. The results show that domestic research on lower limb rehabilitation robots focus on the design and optimization of the mechanism configuration, while foreign research focus on the improvement and innovation of the control system and training mode based on human-computer interaction. Finally, the current state of research is combined with an outlook on future trends.

Abstract Background The mortality rate of acute respiratory distress syndrome (ARDS) increases with age (≥ 65 years old) in critically ill patients, and it is necessary to prevent mortality in elderly patients with ARDS in the intensive care unit (ICU). Among the potential risk factors, dynamic subphenotypes of respiratory rate (RR), heart rate (HR), and respiratory rate-oxygenation (ROX) and their associations with 28-day mortality have not been clearly explored. Methods Based on the eICU Collaborative Research Database (eICU-CRD), this study used a group-based trajectory model to identify longitudinal subphenotypes of RR, HR, and ROX during the first 72 h of ICU stays. A logistic model was used to evaluate the associations of trajectories with 28-day mortality considering the group with the lowest rate of mortality as a reference. Restricted cubic spline was used to quantify linear and nonlinear effects of static RR-related factors during the first 72 h of ICU stays on 28-day mortality. Receiver operating characteristic (ROC) curves were used to assess the prediction models with the Delong test. Results A total of 938 critically ill elderly patients with ARDS were involved with five and 5 trajectories of RR and HR, respectively. A total of 204 patients fit 4 ROX trajectories. In the subphenotypes of RR, when compared with group 4, the odds ratios (ORs) and 95% confidence intervals (CIs) of group 3 were 2.74 (1.48–5.07) (P = 0.001). Regarding the HR subphenotypes, in comparison to group 1, the ORs and 95% CIs were 2.20 (1.19–4.08) (P = 0.012) for group 2, 2.70 (1.40–5.23) (P = 0.003) for group 3, 2.16 (1.04–4.49) (P = 0.040) for group 5. Low last ROX had a higher mortality risk (P linear = 0.023, P nonlinear = 0.010). Trajectories of RR and HR improved the predictive ability for 28-day mortality (AUC increased by 2.5%, P = 0.020). Conclusions For RR and HR, longitudinal subphenotypes are risk factors for 28-day mortality and have additional predictive enrichment, whereas the last ROX during the first 72 h of ICU stays is associated with 28-day mortality. These findings indicate that maintaining the health dynamic subphenotypes of RR and HR in the ICU and elevating static ROX after initial critical care may have potentially beneficial effects on prognosis in critically ill elderly patients with ARDS.

The study was enforced to probe the conversion and migration behavior of phosphorus speciation in sludge and the biochar received from pyrolysis of municipal sludge (MS), town sludge (TS), and slaughterhouse sludge (SS). This study creatively used fractionation of soil phosphorus to further differentiate speciation of phosphorus in three sludges (MS, TS, and SS). According to the x-ray diffraction (XRD) analysis and sequential extraction, the study proved the dependence of P speciation conversion on pyrolysis temperature and different types of raw sludge. The results of P-fractionation indicated that Ca-bound IP (Ca-IP) content in all biochars significantly increased at pyrolysis temperature of 350–800 ℃, and the proportion of soluble and loosely bound IP (SL-IP), aluminum-bound IP (Al-IP), and Fe-bound IP (Fe-IP) of MS and SS decreased. The difference is that the Al-IP in the TS increased slightly as the pyrolysis temperature increased. Among the three kinds of sludge, the Olsen-P of TS is the lowest because the content of Olsen-P in sludge will decrease with the decrease of pH in the process of sewage treatment after acidification. In addition, XRD patterns of three sludges and biochar further confirmed the low crystallinity of AlPO4 minerals. Through in-depth research on the environmental behavior of phosphorus, this study might additionally provide essential knowledge for the recovery and utilization of phosphorus in sludge.

Camellia luteoflora is a rare and endangered plant endemic to China. It has high ornamental and potential economic and medicinal value, and is an important germplasm resource of Camellia. To understand the distributions and differences in metabolites from different parts of C. luteoflora, in this study, we used liquid chromatography–tandem mass spectrometry (LC–MS/MS) to examine the types and contents of chemical constituents in five organs of C. luteoflora: roots, stems, leaves, flowers, and fruits. The results showed that a total of 815 metabolites were identified in the five organs and were classified into 18 main categories, including terpenoids (17.1%), amino acids (10.4%), flavonoids (10.3%), sugars and alcohols (9.8%), organic acids (9.0%), lipids (7.1%), polyphenols (4.8%), alkaloids (4.8%), etc. A total of 684 differentially expressed metabolites (DEMs) in five organs were obtained and annotated into 217 KEGG metabolic pathways, among which metabolic pathways, ABC transporters, the biosynthesis of cofactors, and the biosynthesis of amino acids were significantly enriched. In DEMs, flowers are rich in flavonoids, polyphenols, organic acids, and steroids; fruits are rich in amino acids, alkaloids, vitamins, and xanthones; stems are rich in lignans; and leaves have the highest relative content of phenylpropanoids, ketoaldehydic acids, quinones, sugars and alcohols, terpenoids, coumarins, lipids, and others; meanwhile, the metabolite content is lower in roots. Among the dominant DEMs, 58 were in roots, including arachidonic acid, lucidone, isoliquiritigenin, etc.; 75 were in flowers, including mannose, shikimic acid, d-gluconic acid, kaempferol, etc.; 45 were in the fruit, including pterostilbene, l-ascorbic acid, riboflavin, etc.; 27 were in the stems, including salicylic acid, d-(-)-quinic acid, mannitol, (-)-catechin gallate, etc.; there was a maximum number of 119 dominant metabolites in the leaves, including oleanolic acid, l-glucose, d-arabitol, eugenol, etc. In sum, the rich chemical composition of C. luteoflora and the significant differences in the relative contents of metabolites in different organs will provide theoretical references for the study of tea, flower tea, edible oil, nutraceuticals, and the medicinal components of C. luteoflora.

MicroRNAs (miRNAs) play a crucial role in the prevention, prognosis, diagnosis, and treatment of complex diseases. Existing computational methods primarily focus on biologically relevant molecules directly associated with miRNA or disease, overlooking the fact that the human body is a highly complex system where miRNA or disease may indirectly correlate with various types of biomolecules. To address this, we propose a novel prediction model named MHGTMDA (miRNA and disease association prediction using heterogeneous graph transformer based on molecular heterogeneous graph). MHGTMDA integrates biological entity relationships of eight biomolecules, constructing a relatively comprehensive heterogeneous biological entity graph. MHGTMDA serves as a powerful molecular heterogeneity map transformer, capturing structural elements and properties of miRNAs and diseases, revealing potential associations. In a 5-fold cross-validation study, MHGTMDA achieved an area under the receiver operating characteristic curve of 0.9569, surpassing state-of-the-art methods by at least 3%. Feature ablation experiments suggest that considering features among multiple biomolecules is more effective in uncovering miRNA-disease correlations. Furthermore, we conducted differential expression analyses on breast cancer and lung cancer, using MHGTMDA to further validate differentially expressed miRNAs. The results demonstrate MHGTMDA’s capability to identify novel MDAs.

IntroductionAsian soybean rust is a highly aggressive leaf-based disease triggered by the obligate biotrophic fungus Phakopsora pachyrhizi which can cause up to 80% yield loss in soybean. The precise image segmentation of fungus can characterize fungal phenotype transitions during growth and help to discover new medicines and agricultural biocides using large-scale phenotypic screens.MethodsThe improved Mask R-CNN method is proposed to accomplish the segmentation of densely distributed, overlapping and intersecting microimages. First, Res2net is utilized to layer the residual connections in a single residual block to replace the backbone of the original Mask R-CNN, which is then combined with FPG to enhance the feature extraction capability of the network model. Secondly, the loss function is optimized and the CIoU loss function is adopted as the loss function for boundary box regression prediction, which accelerates the convergence speed of the model and meets the accurate classification of high-density spore images.ResultsThe experimental results show that the mAP for detection and segmentation, accuracy of the improved algorithm is improved by 6.4%, 12.3% and 2.2% respectively over the original Mask R-CNN algorithm.DiscussionThis method is more suitable for the segmentation of fungi images and provide an effective tool for large-scale phenotypic screens of plant fungal pathogens.

Through a variety of mechanisms, including increasing the amount of readily available mineral nutrients, regulating phytohormone levels, and biocontrol of phytopathogens, plant growth-promoting rhizobacteria (PGPR) associated with the plant rhizosphere either directly or indirectly stimulates plant growth and development. The establishment, survival, and persistence of PGPR inoculants are widely acknowledged to be contingent upon these two parameters, in addition to the intricate network of interactions within the rhizosphere. In general, the soil is a moist environment with significant amounts of carbon that have been degraded and harbors a large population of soil microbes. The rhizo-microbiome is crucial to agriculture because a wide variety of root exudates and plant cell debris attract unique and distinct patterns of microbial colonization. The rhizo-microbiome plays a crucial role in the manufacture and regulation of extracellular molecules, including hormones, secondary metabolites, antibiotics, and various signaling chemicals. Additionally, the microbial composition within the rhizo-microbiome influences soil texture enhancement. Research has shown that PGPR can be used to treat plants or inoculate plants to promote plant development. PGPR alters the physiology of the entire plant, which enhances nutrient uptake and affects the effectiveness of root activity. The specific biochemical processes of plants involved in this phenomenon are often not well understood. Nevertheless, new studies have shed light on the mechanisms via which signaling by PGPR can induce various plant responses, both at the local and systemic levels. Insufficient information is available regarding the impact of the PGPR mechanism and molecules on metabolic pathways in root characteristics. Consequently, this review will concentrate on elucidating the PGPR mechanism and identifying the essential molecules that exert influence on root-microbe interactions.

Abstract Methyltransferase-like 3 (METTL3) is the key subunit of methyltransferase complex responsible for catalyzing N6-methyladenosine (m6A) modification on mRNA, which is the most prevalent post-transcriptional modification in eukaryotes. In this study, we utilized online databases to analyze the association between METTL3 expression and various aspects of tumorigenesis, including gene methylation, immunity, and prognosis. Our investigation revealed that METTL3 serves as a prognostic marker and therapeutic target for liver hepatocellular carcinoma (LIHC). Through experimental studies, we observed frequent upregulation of METTL3 in LIHC tumor tissue and cells. Subsequent inhibition of METTL3 using a novel small molecule inhibitor, STM2457, significantly impeded tumor growth in LIHC cell lines, spheroids, and xenograft tumor model. Further, transcriptome and m6A sequencing of xenograft bodies unveiled that inhibition of METTL3-m6A altered genes enriched in SMAD and MAPK signaling pathways that are critical for tumorigenesis. These findings suggest that targeting METTL3 represents a promising therapeutic strategy for LIHC.

Abstract Prescribing appropriate exercise is an important means to improve the safety and efficacy of cardiac rehabilitation. Improper exercise may induce an increased cardiovascular risk in older persons with coronary heart disease. Cardiopulmonary exercise testing (CPET)-guided cardiac rehabilitation could be helpful for providing clinical evidence for cardiac rehabilitation therapy in older persons after percutaneous coronary intervention (PCI). We retrospectively included older persons who underwent PCI and cardiac rehabilitation based on CPET at the Cardiac Rehabilitation Center of Peking University Third Hospital from January 2014 to December 2019. Patients’ baseline and follow-up clinical data were collected. A total of 403 older persons after PCI were included in the study. The mean age was 80.5 ± 4.3. The mean follow-up time was 12 ± 2 months. During the follow-up period, no significant exercise-related adverse events occurred, and the peak oxygen uptake (VO2peak) increased compared with baseline (15.5 ± 3.8 ml/min/kg vs. 17.3 ± 4.1 ml/min/kg). Among the 90 patients (22.2%) without exercise habits at baseline who started regular exercise during follow-up, the improvement in VO2peak was most significant, at 3.2 ± 0.4 ml/min/kg. Cardiac rehabilitation based on CPET improved exercise habits and exercise tolerance in older persons with coronary heart disease after PCI.

Abstract Background Atherogenic index of plasma (AIP) has been confirmed as a novel marker for myocardial infarction (MI), but few evidence on the long-term AIP and MI risk in general populations. We thus aimed to evaluate the relationships of cumulative exposure to AIP and its accumulation time course with the risk of MI. Methods A total of 54,440 participants were enrolled in the Kailuan study. Time-weighted cumulative AIP was calculated as the weighted sum of the mean AIP value for each time interval, then normalized by total exposure duration, the exposure duration was from 2006 to 2010. Duration of high AIP exposure was defined as the duration with high AIP and ranged from 0 to 6 years. The time course of AIP accumulation was categorized by the combination of time-weighted cumulative AIP

Abstract Objective The aim of this study was adopts meta-analysis in evaluating the correlation between TSH and BMD, as well as osteoporosis in the postmenopausal women with normal thyroid function. Methods Six databases were searched for articles concerning correlation between TSH and BMD in postmenopausal women. The retrieval time was set from the date of database establishment to November 30, 2020. Revman5.3 and Stata12.0 software were used for meta-analysis. Results A total of 19 articles were incorporated. The Summary Fisher’ Z of the correlation between TSH and BMD was 0.16, 95% CI (0.00, 0.32), and the correlation coefficient of Summary Fisher’ Z conversion was 0.158. Study on the relationship between TSH and osteoporosis based on OR demonstrated that the combined OR was 1.76, 95% CI (1.27, 2.45), P 2.5 mIu/L) within the normal range is possibly helpful to decrease the risk of osteoporosis in postmenopausal women.

Abstract Background At present, the relationship between severe acute pancreatitis (SAP) and albumin infusion is not clear. We aimed to identify the impact of serum albumin on the prognosis of SAP and the association between albumin infusions and mortality for hypoalbuminemia patients. Methods This was a retrospective cohort study that analyzed 1000 patients with SAP who were admitted to the First Affiliated Hospital of Nanchang University between January 2010 and December 2021 using data from a prospectively maintained database. Multivariate logistic regression analysis was conducted to reveal the relationship between serum albumin within 1 week after admission and poor prognosis of SAP. Propensity score matching (PSM) analysis was adopted to evaluate the effect of albumin infusion for hypoalbuminemia patients with SAP. Results The prevalence of hypoalbuminemia (≤ 30 g/L) was 56.9% within 1 week after admission. Multivariate logistic regression identified that age (OR: 1.02; 95% CI: 1.00-1.04; P = 0.012), serum urea (OR: 1.08; 95% CI: 1.04–1.12; P 100 g within 1 week after admission for hypoalbuminemia patients with albumin infusions was associated with lower mortality than doses ≤ 100 g (OR: 0.51, 95% CI: 0.28–0.90, P = 0.020). Conclusions Hypoalbuminemia in early-stage SAP is significantly related to poor prognosis. However, albumin infusions could significantly decrease mortality in hypoalbuminemia patients with SAP. Additionally, infusing sufficient albumin within a week after admission may decrease mortality in hypoalbuminemia patients.

Abstract Background Caesarean-section (C-section) may influence children’s long-term health by affecting bacterial colonization. However, few studies have focused on the association between C-section delivery (CSD) and dental caries, and previous conclusions have been conflicting. This study aimed to explore whether CSD would increase the risk of early childhood caries (ECC) in preschool children in China. Methods This study was a retrospective cohort study. Three-year-old children with full primary dentition were included through the medical records system. Children in the nonexposure group were vaginally delivered (VD), while children in the exposure group were delivered through C-section. The outcome was the occurrence of ECC. After agreeing to participate in this study, guardians of included children completed a structured questionnaire on maternal sociodemographic factors, children’s oral hygiene and feeding habits. The chi-square test was used to determine differences in the prevalence and severity of ECC between the CSD and VD groups and to analyse the prevalence of ECC according to sample characteristics. Subsequently, potential risk factors for ECC were preliminarily identified through univariate analysis, and the adjusted odds ratios (ORs) were further calculated through multiple logistic regression analysis after controlling for confounding factors. Results The VD group included 2115 participants while CSD group included 2996 participants. The prevalence of ECC was higher in CSD children than in VD children (27.6% vs. 20.9%, P

Abstract Objective To investigate the possible association between AT1R gene polymorphisms and major adverse cardiovascular and cerebrovascular events (MACCEs) in hypertension patients combined with or without coronary artery disease (CAD) in Xinjiang. Methods 374 CAD patients and 341 non-CAD individuals were enrolled as study participants and all of them have a hypertension diagnosis. AT1R gene polymorphisms were genotyped by SNPscan™ typing assays. During the follow-up in the clinic or by telephone interview, MACCEs were recorded. Kaplan–Meier curves and Cox survival analyses were used to explore the association between AT1R gene polymorphisms and the occurrence of MACCEs. Results AT1R gene rs389566 was associated with MACCEs. The TT genotype of the AT1R gene rs389566 had a significantly higher probability of MACCEs than the AA + AT genotype (75.2% vs. 24.8%, P = 0.033). Older age (OR = 1.028, 95% CI: 1.009–1.0047, P = 0.003) and TT genotype of rs389566 (OR = 1.770, 95% CI: 1.148–2.729, P = 0.01) were risk factors of MACCEs. AT1R gene rs389566 TT genotype may be a predisposing factor for the occurrence of MACCEs in hypertensive patients. Conclusion We should also pay more attention to the prevent of MACCEs in hypertension patients combined with CAD. Especially those elderly hypertensive patients carrying AT1R rs389566 TT genotype requires avoidance of unhealthy lifestyle, better management of blood pressure control and reduce the occurrence of MACCEs.

IntroductionSince December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have been used to induce neutralizing antibodies (nAbs) and memory B-cell responses against the viral spike (S) glycoprotein, and many essential epitopes have been defined. Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine-induced immunity remains unknown.MethodsTo elucidate the characteristics of preexisting SARS-CoV-2 S-reactive B cells as well as their maturation after antigen encounter, we assessed the relationship of spike-reactive B cells before and after vaccination in unexposed human individuals. We further characterized the sequence identity, targeting domain, broad-spectrum binding activity and neutralizing activity of these SARS-CoV-2 S-reactive B cells by isolating monoclonal antibodies (mAbs) from these B cells.ResultsThe frequencies of both spike-reactive naïve B cells and preexisting memory B cells before vaccination correlated with the frequencies of spike-reactive memory B cells after vaccination. Isolated mAbs from spike-reactive naïve B cells before vaccination had fewer somatic hypermutations (SHMs) than mAbs isolated from spike-reactive memory B cells before and after vaccination, but bound SARS-CoV-2 spike in vitro. Intriguingly, these germline-like mAbs possessed broad binding profiles for SARS-CoV-2 and its variants, although with low or no neutralizing capacity. According to tracking of the evolution of IGHV4-4/IGKV3-20 lineage antibodies from a single donor, the lineage underwent SHMs and developed increased binding activity after vaccination.DiscussionOur findings suggest that spike-reactive naïve B cells can be expanded and matured by vaccination and cocontribute to vaccine-elicited antibody responses with preexisting memory B cells. Selectively and precisely targeting spike-reactive B cells by rational antigen design may provide a novel strategy for next-generation SARS-CoV-2 vaccine development.

Metabolic syndrome (MetS) is a collection of metabolic abnormalities including insulin resistance, atherogenic dyslipidemia, central obesity, and hypertension. Recently, long noncoding RNAs (lncRNAs) have emerged as pivotal regulators of metabolic balance, influencing the genes associated with MetS. Although the prevalence of insulin resistance is rising, leading to an increased risk of type 2 diabetes mellitus (T2DM) and its vascular complications, there is still a notable gap in understanding the role of lncRNAs in the context of clinical diabetes. Among lncRNAs, lung adenocarcinoma metastasis-associated transcript 1 (MALAT1) has been identified as a significant regulator of metabolism-related disorders, including T2DM and cardiovascular disease (CVD). This review explores the mechanism of lncRNA MALAT1 and suggests that targeting it could offer a promising strategy to combat MetS, thereby enhancing the prognosis of MetS.

BackgroundUlcerative colitis (UC) is a lifelong inflammatory disease affecting the rectum and colon with numerous treatment options that require an individualized treatment plan. Histone modifications regulate chromosome structure and gene expression, resulting in effects on inflammatory and immune responses. However, the relationship between histone modification-related genes and UC remains unclear.MethodsTranscriptomic data from GSE59071 and GSE66407 were obtained from the Gene Expression Omnibus (GEO), encompassing colonic biopsy expression profiles of UC patients in inflamed and non-inflamed status. Differentially expressed gene (DEG) analyses, functional enrichment analyses, weighted gene co-expression network analysis (WGCNA), and random forest were performed to identify histone modification-related core genes associated with UC inflammation. Features were screened through the least absolute shrinkage and selection operator (LASSO) and support vector machine‐recursive feature elimination (SVM‐RFE), establishing a molecular inflammatory predictive model using logistic regression. The model was validated in the GSE107499 dataset, and the performance of the features was assessed using receiver operating characteristic (ROC) and calibration curves. Immunohistochemistry (IHC) staining of colonic biopsy tissues from UC patients treated with infliximab was used to further confirm the clinical application value. Univariate logistic regression on GSE14580 highlighted features linked to infliximab response.ResultsA total of 253 histone modification-related DEGs were identified between inflammatory and non-inflammatory patients with UC. Seven key genes (IL-1β, MSL3, HDAC7, IRF4, CAMK2D, AUTS2, and PADI2) were selected using WGCNA and random forest. Through univariate logistic regression, three core genes (CAMK2D, AUTS2, and IL-1β) were further incorporated to construct the molecular inflammatory predictive model. The area under the curve (AUC) of the model was 0.943 in the independent validation dataset. A significant association between CAMK2D protein expression and infliximab response was observed, which was validated in another independent verification set of GSE14580 from the GEO database.ConclusionThe molecular inflammatory predictive model based on CAMK2D, AUTS2, and IL-1β could reliably distinguish the mucosal inflammatory status of UC patients. We further revealed that CAMK2D was a predictive marker of infliximab response. These findings are expected to provide a new evidence base for personalized treatment and management strategies for UC patients.

BackgroundThe poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANoptosis in sepsis has not been fully elucidated.MethodsWe obtained Sepsis samples and scRNA-seq data from the GEO database. PANoptosis-related genes were subjected to consensus clustering and functional enrichment analysis, followed by identification of differentially expressed genes and calculation of the PANoptosis score. A PANoptosis-based prognostic model was developed. In vitro experiments were performed to verify distinct PANoptosis-related genes. An external scRNA-seq dataset was used to verify cellular localization.ResultsUnsupervised clustering analysis using 16 PANoptosis-related genes identified three subtypes of sepsis. Kaplan-Meier analysis showed significant differences in patient survival among the subtypes, with different immune infiltration levels. Differential analysis of the subtypes identified 48 DEGs. Boruta algorithm PCA analysis identified 16 DEGs as PANoptosis-related signature genes. We developed PANscore based on these signature genes, which can distinguish different PANoptosis and clinical characteristics and may serve as a potential biomarker. Single-cell sequencing analysis identified six cell types, with high PANscore clustering relatively in B cells, and low PANscore in CD16+ and CD14+ monocytes and Megakaryocyte progenitors. ZBP1, XAF1, IFI44L, SOCS1, and PARP14 were relatively higher in cells with high PANscore.ConclusionWe developed a machine learning based Boruta algorithm for profiling PANoptosis related subgroups with in predicting survival and clinical features in the sepsis.

Abstract Tumor microenvironment (TME)‐triggered phototheranostic platform offers a feasible strategy to improve cancer diagnosis accuracy and minimize treatment side effects. Developing a stable and biocompatible molecular phototheranostic platform for TME‐activated second near‐infrared (NIR‐II) fluorescence imaging‐guided multimodal cascade therapy is a promising strategy for creating desirable anticancer agents. Herein, a new NIR‐II fluorescence imaging‐guided activatable molecular phototheranostic platform (IR‐FEP‐RGD‐S‐S‐S‐Fc) is presented for actively targeted tumor imaging and hydrogen sulfide (H2S) gas‐enhanced chemodynamic‐hypothermal photothermal combined therapy (CDT/HPTT). It is revealed for the first time that the coupling distance between IR‐FE and ferrocene is proportional to the photoinduced electron transfer (PET), and the aqueous environment is favorable for PET generation. The part of Cyclic‐RGDfK (cRGDfk) peptides can target the tumor and benefit the endocytosis of nanoparticles. The high‐concentration glutathione (GSH) in the TME will separate the fluorescence molecule and ferrocene by the GSH‐sensitive trisulfide bond, realizing light‐up NIR‐II fluorescence imaging and a cascade of trimodal synergistic CDT/HPTT/gas therapy (GT). In addition, the accumulation of hydroxyl radicals (•OH) and down‐regulation of glutathione peroxidase 4 (GPX4) can produce excessive harmful lipid hydroperoxides, ultimately leading to ferroptosis.

IntroductionMetacognition and self-directed learning are key components in educational research, recognized for their potential to enhance learning efficiency and problem-solving skills. This study explores the effects of musical feedback training on these competencies.MethodsThe study involved 84 preservice teachers aged 18 to 21. Participants were randomly assigned to either an experimental group, which received musical feedback training, or a control group.ResultsThe findings indicate that musical feedback training effectively improved metacognitive abilities. However, its impact on the readiness for self-directed learning was inconclusive. A notable difference in metacognition and self-directed learning readiness was observed between the experimental and control groups during the session, indicating a significant interaction effect. Furthermore, a positive correlation was identified between metacognition and self-directed learning.DiscussionThese results contribute to educational discourse by providing empirical evidence on the utility of musical feedback training in fostering metacognition. They also highlight the importance of consistent and long-term engagement in self-directed learning practices. The significance of these findings advocates for incorporating music feedback training into music education curricula to enhance metacognition and improve overall learning efficiency.

Introduction/aimsThe time span for the approval of nusinersen to treat SMA remains short. Most studies on the efficacy and safety of this drug within clinical trials, are lacking real-world research data. This study is based on real-world studies of SMA patients in children with type II and III SMA and is committed to objectively evaluating the effectiveness and safety of this drug.MethodsA retrospective analysis was conducted on the clinical data of 18 children with type II and III SMA from January 2022 to June 2023. The motor function assessment scale, SMN protein, platelet, liver and kidney function, and other laboratory indicators of all patients before and after treatment were collected for statistical analysis.ResultsAfter load dose treatment (after 64 days of treatment), compared with baseline, the Revised Upper Limb Module (RULM) of SMA patients showed significant improvement (improvement rate: 44%), confirming the short-term effectiveness of the drug. The increase in cerebrospinal fluid SMN protein was greater in patients with significant improvement in motor function than in patients without improvement in motor function. Compared with baseline, there was no significant increase in AST and ALT levels in SMA patients, indicating that the drug had almost no effect on the liver. After each treatment, thrombocytopenia and partial urinary protein positivity may occur, but it could recover before the next treatment. This indicates that nusinersen is potentially harmful to platelet and renal function, although the effect is weak and reversible.DiscussionNusinersen has shown good efficacy and overall safety, but platelets and urinary protein are still indicators that require long-term monitoring. The increase in cerebrospinal fluid SMN protein was greater in patients with significant improvement in motor function than in patients without improvement in motor function.

Intestinal fibrosis associated stricture is a common complication of inflammatory bowel disease usually requiring endoscopic or surgical intervention. Effective anti-fibrotic agents aiming to control or reverse intestinal fibrosis are still unavailable. Thus, clarifying the mechanism underpinning intestinal fibrosis is imperative. Fibrosis is characterized by an excessive accumulation of extracellular matrix (ECM) proteins at the injured sites. Multiple cellular types are implicated in fibrosis development. Among these cells, mesenchymal cells are major compartments that are activated and then enhance the production of ECM. Additionally, immune cells contribute to the persistent activation of mesenchymal cells and perpetuation of inflammation. Molecules are messengers of crosstalk between these cellular compartments. Although inflammation is necessary for fibrosis development, purely controlling intestinal inflammation cannot halt the development of fibrosis, suggesting that chronic inflammation is not the unique contributor to fibrogenesis. Several inflammation-independent mechanisms including gut microbiota, creeping fat, ECM interaction, and metabolic reprogramming are involved in the pathogenesis of fibrosis. In the past decades, substantial progress has been made in elucidating the cellular and molecular mechanisms of intestinal fibrosis. Here, we summarized new discoveries and advances of cellular components and major molecular mediators that are associated with intestinal fibrosis, aiming to provide a basis for exploring effective anti-fibrotic therapies in this field.

LiBH4 has been considered as one of the most promising energy storage materials with its ultrahigh hydrogen capacity, which can supply hydrogen through hydrolysis process or realize hydrogen-to-electricity conversion via anodic oxidation reaction of direct borohydride fuel cells (DBFCs). However, the realization of practical hydrogen applications heavily depends on the effective synthesis of high-purity LiBH4 and recycling of the spent fuels (LiBO2·xH2O). The present work demonstrates a convenient and high-efficiency solvent-free strategy for regenerating LiBH4 with a maximum yield close to 80%, by retrieving its by-products with MgH2 as a reducing agent under ambient conditions. Besides, the hydrogen released from the regeneration course can completely compensate the demand for consumed MgH2. The isotopic tracer method reveals that the hydrogen stored in LiBH4 comes from both MgH2 and coordinated water bound to LiBO2. Here, the expensive MgH2 can be substituted with the readily available and cost-effective MgH2−Mg mixtures to simplify the regeneration route. Notably, LiBH4 catalyzed by CoCl2 can stably supply hydrogen to proton exchange membrane fuel cell (PEMFC), thus powering a portable prototype vehicle. By combining hydrogen storage, production and utilization in a closed cycle, this work offers new insights into deploying boron-based hydrides for energy applications.

Abstract Background Epigenetic dysregulation is essential to the tumorigenesis of oral squamous cell carcinoma (OSCC). SET and MYND domain-containing protein 3 (SMYD3), a histone lysine methyltransferase, is implicated in gene transcription regulation and tumor development. However, the roles of SMYD3 in OSCC initiation are not fully understood. The present study investigated the biological functions and mechanisms involved in the SMYD3-mediated tumorigenesis of OSCC utilizing bioinformatic approaches and validation assays with the aim of informing the development of targeted therapies for OSCC. Results 429 chromatin regulators were screened by a machine learning approach and aberrant expression of SMYD3 was found to be closely associated with OSCC formation and poor prognosis. Data profiling of single-cell and tissue demonstrated that upregulated SMYD3 significantly correlated with aggressive clinicopathological features of OSCC. Alterations in copy number and DNA methylation patterns may contribute to SMYD3 overexpression. Functional experimental results suggested that SMYD3 enhanced cancer cell stemness and proliferation in vitro and tumor growth in vivo. SMYD3 was observed to bind to the High Mobility Group AT-Hook 2 (HMGA2) promoter and elevated tri-methylation of histone H3 lysine 4 at the corresponding site was responsible for transactivating HMGA2. SMYD3 also was positively linked to HMGA2 expression in OSCC samples. Furthermore, treatment with the SMYD3 chemical inhibitor BCI-121 exerted anti-tumor effects. Conclusions Histone methyltransferase activity and transcription-potentiating function of SMYD3 were found to be essential for tumorigenesis and the SMYD3–HMGA2 is a potential therapeutic target in OSCC.

Abstract Objective The aim of this work was to evaluate the predictive value of FAR combined with CACS for MACCEs. Background The fibrinogen-albumin-ratio (FAR), a novel biomarker of inflammation, is associated with the severity of coronary artery disease (CAD). Coronary calcification score (CACS) is associated with the severity of coronary stenosis and is closely related to the prognosis of CAD patients. What is the prognostic value of FAR in patients with chest pain, which has not been reported. This study aims to evaluate the relationship between CACS and FAR and their impact on prognosis in patients with suspected CAD. Methods We used information from 12,904 individuals who had coronary computed tomography angiography (CTA) for chest pain and tracked down any significant adverse cardiac and cerebrovascular events (MACCEs). The following formula was used to calculate FAR: fibrinogen (g/L)/albumin (g/L). Patients were separated into groups with greater levels of FAR (FAR-H) and lower levels of FAR (FAR-L) in accordance with the ideal cut-off value of FAR for MACCEs prediction. In addition, patients were divided into three groups based on their CACS scores (CACS ≤ 100, 100 400). Results 4946 patients [62(55–71) years, 64.4% male] were ultimately enrolled in the present study. During follow-up, a total of 234 cases (4.7%) of MACCEs were documented. Linear regression analysis results showed that CACS (R2 = 0.004, Standard β = 0.066, P

This paper delves into the realm of cryptographic analysis by employing mixed-integer linear programming (MILP), a powerful tool for automated cryptanalysis. Building on this foundation, we apply the division property method alongside MILP to conduct a comprehensive cryptanalysis of the IIoTBC (industrial Internet of Things block cipher) algorithm, a critical cipher in the security landscape of industrial IoT systems. Our investigation into IIoTBC System A has led to identifying a 14-round integral distinguisher, further extended to a 22-round key recovery. This significant finding underscores the cipher’s susceptibility to sophisticated cryptanalytic attacks and demonstrates the profound impact of combining the division property method with MILP in revealing hidden cipher weaknesses. In the case of IIoTBC System B, our innovative approach has uncovered a full-round distinguisher. We provide theoretical validation for this distinguisher and uncover a pivotal structural issue in the System B algorithm, specifically the non-diffusion of its third branch. This discovery sheds light on inherent security challenges within System B and points to areas for potential enhancement in its design. Our research, through its methodical examination and analysis of the IIoTBC algorithm, contributes substantially to the field of cryptographic security, especially concerning industrial IoT applications. By uncovering and analyzing the vulnerabilities within IIoTBC, we enhance the understanding of cipher robustness and pave the way for advancements in securing industrial IoT communications.

The cytoskeleton is a fundamental component found in all eukaryotic organisms, serving as a critical factor in various essential cyto-biological mechanisms, particularly in the locomotion and morphological transformations of plant cells. The cytoskeleton is comprised of three main components: microtubules (MT), microfilaments (MF), and intermediate filaments (IF). The cytoskeleton plays a crucial role in the process of cell wall formation and remodeling throughout the growth and development of cells. It is a highly organized and regulated network composed of filamentous components. In the basic processes of intracellular transport, such as mitosis, cytokinesis, and cell polarity, the plant cytoskeleton plays a crucial role according to recent studies. The major flaws in the organization of the cytoskeletal framework are at the root of the aberrant organogenesis currently observed in plant mutants. The regulation of protein compartmentalization and abundance within cells is predominantly governed by the process of vesicle/membrane transport, which plays a crucial role in several signaling cascades.The regulation of membrane transport in eukaryotic cells is governed by a diverse array of proteins. Recent developments in genomics have provided new tools to study the evolutionary relationships between membrane proteins in different plant species. It is known that members of the GTPases, COP, SNAREs, Rabs, tethering factors, and PIN families play essential roles in vesicle transport between plant, animal, and microbial species. This Review presents the latest research on the plant cytoskeleton, focusing on recent developments related to the cytoskeleton and summarizing the role of various proteins in vesicle transport. In addition, the report predicts future research direction of plant cytoskeleton and vesicle trafficking, potential research priorities, and provides researchers with specific pointers to further investigate the significant link between cytoskeleton and vesicle trafficking.

Most of the existing oversampling algorithms based on clustering do not consider the spatial distribution of Majority class, and it is easy to overlap classes and ignore important information points when synthesizing new samples. To solve this problem, this paper analyzes the influence of the spatial distribution on the oversampling process, and proposes an oversampling algorithm based on Adaptive Density Difference Peak Clustering and Spatial Distribution Entropy. Firstly, the spatial distribution situation of two classes samples is introduced into the clustering process, and the local density difference is used to cluster of Minority class by the peak value, so as to achieve scientific and reasonable selection of sub-cluster centers and reduce the occurrence of class overlap. At the same time, the method of determining the truncation distance according to the previous experience is change. The spatial distribution situation of two classes samples is characterized by constructing Spatial Distribution Entropy. On this basis, the automatic selection and optimization of truncation distance are realized. Then the boundary points and sparse points are screened according to the absolute value of local density difference, and the sampling probabilities of each minority class sample are determined to focus on these important information points. Finally, Spatial Distribution Entropy is used to evaluate the synthetic samples set to ensure that they can balance the distribution of the two classes samples in the dataset. To test the effectiveness of the algorithm, five oversampling algorithms are used to perform comparative experiments on four classifiers and 16 common datasets. The results show that compared with SMOTE, K-means-SMOTE, BS-SMOTE, ADASYN, DPC-SMOTE, the algorithm has significantly improved in all evaluation indexes.

Abstract KDM6B (Lysine-specific demethylase 6B) is a histone lysine demethyltransferase that plays a key role in many types of cancers. However, its potential role in gastric cancer (GC) remains unclear. Here, we focused on the clinical significance and potential role of KDM6B in GC. We found that the KDM6B expression is upregulated in GC tissues and that its high expression in patients is related to poor prognosis. KDM6B ectopic expression promotes GC cells’ proliferation and metastasis, while its inhibition has opposite effects in vitro and in vivo. Mechanistically, KDM6B promotes GC cells proliferation and metastasis through its enzymatic activity through the induction of H3K27me3 demethylation near the CXCR4 (C-X-C chemokine receptor type 4) promoter region, resulting in the upregulation of CXCR4 expression. Furthermore, H. pylori was found to induce KDM6B expression. In conclusion, our results suggest that KDM6B is aberrantly expressed in GC and plays a key role in gastric carcinogenesis and metastasis through CXCR4 upregulation. Our work also suggests that KDM6B may be a potential oncogenic factor and a therapeutic target for GC.

Abstract Background Single nucleotide polymorphisms (SNPs) located in microRNA (miRNA) binding sites can affect the interactions between miRNAs and target genes, which is related to cancer susceptibility and tumorigenesis. However, the association between SNPs located in miR-17-92 cluster binding sites and ESCC risk remains unclear. Therefore, we aimed to explore the relationship between polymorphisms in miR-17-92 cluster binding sites and ESCC susceptibility. Methods Six SNPs in the binding sites of miR-17-92 cluster were selected using bioinformatics databases, and their association with ESCC risk was investigated in a case-control study (including 488 cases and 512 controls) based on the population from high incidence areas of ESCC in China. We evaluated the SNP-SNP and SNP-smoking interactions using generalized multifactor dimensionality reduction (GMDR). Moreover, the expression of the miR-17-92 cluster and its target genes was determined in ESCC and adjacent normal tissues by quantitative real-time polymerase chain reaction (qRT-PCR). The dual-luciferase reporter assay was conducted to verify the effect of SNPs on the binding affinity between miRNAs and target genes. Results We found that the SNP rs1804506 C > T had a significant association with the decreased ESCC risk. The SNP rs1804506 T allele was associated with a significantly decreased risk of ESCC in the additive model (OR = 0.817, 95% CI = 0.681–0.981, P = 0.030). The rs1804506 T allele had more striking effects on reducing ESCC risk in older individuals, female or non-smoker subgroups. We also found a significant interaction effect between rs1366600 and smoking by GMDR methods (P = 0.011). Additionally, the expression levels of miR-19a-3p and TGFBR3 were significantly downregulated in ESCC tissues compared with normal tissues, and the carriers of rs1804506 TT genotype had lower expression level of TGFBR3 than those of rs1804506 CC/CT genotype. Following dual-luciferase reporter assay showed that the rs1804506 T allele reduced the binding of miR-19a-3p and TGFBR3 3′-UTR. Conclusions Our findings suggest that the rs1804506 polymorphism in miR-17-92 cluster binding sites contributes to the susceptibility of ESCC, which might provide new clues and scientific evidence for the etiology and biomarkers for the prevention and treatment of ESCC.

PurposeThis study aimed to explore the efficacy of the computed tomography (CT) radiomics model for predicting the Ki-67 proliferation index (PI) of pure-solid non-small cell lung cancer (NSCLC).Materials and methodsThis retrospective study included pure-solid NSCLC patients from five centers. The radiomics features were extracted from thin-slice, non-enhanced CT images of the chest. The minimum redundancy maximum relevance (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to reduce and select radiomics features. Logistic regression analysis was employed to build predictive models to determine Ki-67-high and Ki-67-low expression levels. Three prediction models were established: the clinical model, the radiomics model, and the nomogram model combining the radiomics signature and clinical features. The prediction efficiency of different models was evaluated using the area under the curve (AUC).ResultsA total of 211 NSCLC patients with pure-solid nodules or masses were included in the study (N=117 for the training cohort, N=49 for the internal validation cohort, and N=45 for the external validation cohort). The AUC values for the clinical models in the training, internal validation, and external validation cohorts were 0.73 (95% CI: 0.64–0.82), 0.75 (95% CI:0.62–0.89), and 0.72 (95% CI: 0.57–0.86), respectively. The radiomics models showed good predictive ability in diagnosing Ki-67 expression levels in the training cohort (AUC, 0.81 [95% CI: 0.73-0.89]), internal validation cohort (AUC, 0.81 [95% CI: 0.69-0.93]) and external validation cohort (AUC, 0.78 [95% CI: 0.64-0.91]). Compared to the clinical and radiomics models, the nomogram combining both radiomics signatures and clinical features had relatively better diagnostic performance in all three cohorts, with the AUC of 0.83 (95% CI: 0.76–0.90), 0.83 (95% CI: 0.71–0.94), and 0.81 (95% CI: 0.68–0.93), respectively.ConclusionThe nomogram combining the radiomics signature and clinical features may be a potential non-invasive method for predicting Ki-67 expression levels in patients with pure-solid NSCLC.