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Abstract. Background:. The association and its population heterogeneities between low-density lipoprotein cholesterol (LDL-C) and all-cause and cardiovascular mortality remain unknown. We aimed to examine the dose-dependent associations of LDL-C levels with specific types of cardiovascular disease (CVD) mortality and heterogeneities in the associations among different population subgroups. Methods:. A total of 2,968,462 participants aged 35–75 years from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) (2014–2019) were included. Cox proportional hazard models and Fine–Gray subdistribution hazard models were used to estimate associations between LDL-C categories (

Abstract Background Accurately deciphering clonal copy number substructure can provide insights into the evolutionary mechanism of cancer, and clustering single-cell copy number profiles has become an effective means to unmask intra-tumor heterogeneity (ITH). However, copy numbers inferred from single-cell DNA sequencing (scDNA-seq) data are error-prone due to technically confounding factors such as amplification bias and allele-dropout, and this makes it difficult to precisely identify the ITH. Results We introduce a hybrid model called scGAL to infer clonal copy number substructure. It combines an autoencoder with a generative adversarial network to jointly analyze independent single-cell copy number profiles and gene expression data from same cell line. Under an adversarial learning framework, scGAL exploits complementary information from gene expression data to relieve the effects of noise in copy number data, and learns latent representations of scDNA-seq cells for accurate inference of the ITH. Evaluation results on three real cancer datasets suggest scGAL is able to accurately infer clonal architecture and surpasses other similar methods. In addition, assessment of scGAL on various simulated datasets demonstrates its high robustness against the changes of data size and distribution. scGAL can be accessed at: https://github.com/zhyu-lab/scgal . Conclusions Joint analysis of independent single-cell copy number and gene expression data from a same cell line can effectively exploit complementary information from individual omics, and thus gives more refined indication of clonal copy number substructure.

AimsThis study aims to systematically analyze the global trends in glioma methylation research using bibliometric methodologies. We focus on identifying the scholarly trajectory and key research interests, and we utilize these insights to predict future research directions within the epigenetic context of glioma.MethodsWe performed a comprehensive literature search of the Web of Science Core Collection (WoSCC) to identify articles related to glioma methylation published from January 1, 2004, to December 31, 2023. The analysis included full-text publications in the English language and excluded non-research publications. Analysis and visualization were performed using GraphPad Prism, CiteSpace, and VOSviewer software.ResultsThe search identified 3,744 publications within the WoSCC database, including 3,124 original research articles and 620 review articles. The research output gradually increased from 2004 to 2007, followed by a significant increase after 2008, which peaked in 2022. A minor decline in publication output was noted during 2020–2021, potentially linked to the coronavirus disease 2019 pandemic. The United States and China were the leading contributors, collectively accounting for 57.85% of the total research output. The Helmholtz Association of Germany, the German Cancer Research Center (DKFZ), and the Ruprecht Karls University of Heidelberg were the most productive institutions. The Journal of Neuro-Oncology led in terms of publication volume, while Neuro-Oncology had the highest Impact Factor. The analysis of publishing authors revealed Michael Weller as the most prolific contributor. The co-citation network analysis identified David N. Louis's article as the most frequently cited. The keyword analysis revealed “temozolomide,” “expression,” “survival,” and “DNA methylation” as the most prominent keywords, while “heterogeneity,” “overall survival,” and “tumor microenvironment” showed the strongest citation bursts.ConclusionsThe findings of this study illustrate the increasing scholarly interest in glioma methylation, with a notable increase in research output over the past two decades. This study provides a comprehensive overview of the research landscape, highlighting the importance of temozolomide, DNA methylation, and the tumor microenvironment in glioma research. Despite its limitations, this study offers valuable insights into the current research trends and potential future directions, particularly in the realm of immunotherapy and epigenetic editing techniques.

Summary: Background: The triglyceride-glucose (TyG) index has been recognized as a crucial risk factor for cardiovascular diseases. However, the association between the TyG index and mortality in the general population remains elusive. Methods: Participants were enrolled from the China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART), a nationwide prospective cohort study. The outcomes of interest were all-cause, cardiovascular, and cancer mortality. Restricted cubic splines and Cox regression models were used to assess the associations between the TyG index and outcomes. Findings: In total, 3,524,459 participants with a median follow-up of 4.6 (IQR, 3.1–5.8) years were included. The associations of the TyG index with all-cause and cardiovascular mortality were reverse L-shaped, with cut-off values of 9.75 for all-cause mortality and 9.85 for cardiovascular mortality. For each 1-unit increase in the TyG index, when below the cut-off values, the TyG index was not significantly associated with all-cause mortality (HR = 1.02, 95% CI: 1.00–1.03) and was only modestly associated with cardiovascular mortality (HR = 1.09, 95% CI: 1.06–1.11). Conversely, when the cut-off values were exceeded, the HRs (95% CI) were 2.10 (1.94–2.29) for all-cause mortality and 1.99 (1.72–2.30) for cardiovascular mortality. However, the association between the TyG index and cancer mortality was linearly negative (HR = 0.97, 95% CI: 0.94–0.99). Interpretation: The associations of the TyG index with all-cause and cardiovascular mortality displayed reverse L-shaped patterns, while an elevated TyG index showed a slight negative association with cancer mortality. We suggest that

BackgroundThis study analyzed the risk factors associated with positive surgical margins (PSM) and five-year survival after prostate cancer resection to construct a positive margin prediction model.MethodsWe retrospectively analyzed the clinical data of 148 patients treated with prostatectomy. The patients were divided into PSM group and Negative surgical margins (NSM) group. Several parameters were compared between the groups. All patients were followed up for 60 months. The risk factors for PSM and five-year survival were evaluated by univariate analysis, followed by multifactorial dichotomous logistic regression analysis. Finally, ROC curves were plotted for the risk factors to establish a predictive model for PSM after prostate cancer resection.Results(1) Serum PSA, percentage of positive puncture stitches, clinical stage, surgical approach, Gleason score on puncture biopsy, and perineural invasion were significantly associated with the risk of PSM (P < 0.05). Serum PSA, perineural invasion, Gleason score on puncture biopsy, and percentage of positive puncture stitches were independent risk factors for PSM. (2) Total prostate-specific antigen (tPSA) by puncture, nutritional status, lymph node metastasis, bone metastasis, and seminal vesicle invasion may be risk factors for five-year survival. Lymph node metastasis and nutritional status were the main risk factors for the five-year survival of patients with prostate cancer. (3) After plotting the ROC curve, the area under the curve (AUC) [AUC: 0.776, 95%, confidence interval (CI): 0.725 to 0.854] was found to be a valid predictor of PSM; the AUC [AUC: 0.664, 95%, confidence interval (CI): 0.576 to 0.753] was also a valid predictor of five-year survival (P < 0.05). (4) The scoring system had a standard error of 0.02 and a cut-off value of 6. It predicted PSM after prostate cancer resection with moderate efficacy.ConclusionsSerum PSA, perineural invasion, puncture biopsy Gleason score, and percentage of positive puncture stitches were independent risk factors for positive surgical margins (PSM). Also, lymph node metastasis and nutritional status were the main risk factors for the five-year survival of patients with prostate cancer. Overall, the prediction efficacy of this scoring system concerning the risk of PSM after prostate cancer resection was moderate.

Abstact: Objective: To examine the joint association of healthy lifestyles and statin use with all-cause and cardiovascular mortality in high-risk individuals, and evaluate the survival benefits by life expectancy. Methods: During 2015–2021, participants aged 35–75 years were recruited by the China Health Evaluation And risk Reduction through nationwide Teamwork. Based on number of healthy lifestyles related to smoking, alcohol drinking, physical activity, and diet, we categorized them into: very healthy (3–4), healthy (2), and unhealthy (0–1). Statin use was determined by self-report taking statin in last two weeks. Results: Among the 265,209 included participants at high risk, 6979 deaths were observed, including 3236 CVD deaths during a median 3.6 years of follow-up. Individuals taking statin and with a very healthy lifestyle had the lowest risk of all-cause (HR: 0.70; 95 %CI: 0.57–0.87) and cardiovascular mortality (0.56; 0.40–0.79), compared with statin non-users with an unhealthy lifestyle. High-risk participants taking statin and with a very healthy lifestyle had the highest years of life gained (5.90 years at 35-year-old [4.14–7.67; P < 0.001]) compared with statin non-users with an unhealthy lifestyle among high-risk people. And their life expectancy was comparable with those without high risk but with a very healthy lifestyle (4.49 vs. 4.68 years). Conclusion: The combination of preventive medication and multiple healthy lifestyles was associated with lower risk of all-cause and cardiovascular mortality and largest survival benefits. Integrated strategy to improve long-term health for high-risk people was urgently needed.

Genome-wide association studies (GWAS) have identified thousands of variants in the human genome with autoimmune diseases. However, identifying functional regulatory variants associated with autoimmune diseases remains challenging, largely because of insufficient experimental validation data. We adopt the concept of semi-supervised learning by combining labeled and unlabeled data to develop a deep learning-based algorithm framework, sscNOVA, to predict functional regulatory variants in autoimmune diseases and analyze the functional characteristics of these regulatory variants. Compared to traditional supervised learning methods, our approach leverages more variants’ data to explore the relationship between functional regulatory variants and autoimmune diseases. Based on the experimentally curated testing dataset and evaluation metrics, we find that sscNOVA outperforms other state-of-the-art methods. Furthermore, we illustrate that sscNOVA can help to improve the prioritization of functional regulatory variants from lead single-nucleotide polymorphisms and the proxy variants in autoimmune GWAS data.

Astragaloside IV (AST IV), a major saponin component and active ingredient isolated from Astragalus membranaceus, has been well known to exhibit neuroprotective effects on diverse models of neurological diseases. Accumulating evidence suggests that dynamic balance of microglia/macrophages and astrocytes plays a vital role in neuroprotection and remyelination. However, dysregulation of microglia/macrophages and astrocytes orchestrate the pathogenesis of nervous system disorders. Therefore, we hypothesized that switching the transformation of microglia/macrophages and astrocytes into the neuroprotective M2 and A2 phenotypes, respectively, could be a potential target for therapeutic intervention. In the present study, we evaluate the efficacy of AST IV intervention on the effects of microglia/macrophages and astrocytes in an experimental autoimmune encephalomyelitis (EAE) model. AST IV improved paralysis and pathology of EAE by inhibiting the neurotoxic M1 microglia/macrophage phenotype, promoting M2 phenotype, shifting astrocytes towards a neuroprotective A2 phenotype, and protecting neurons from apoptosis through inhibition of TLR4/Myd88/NF-kB signalling pathway. Our study showed that AST IV could be a potential and promising drug for multiple sclerosis treatment.

Abstract Background Propofol is the most commonly used drug for procedural sedation during gastroscopy. However, independent use of propofol can lead to increased dosage and additional side effects. Esketamine was found to be exceptional in combination with propofol for painless gastroscopy. No studies have calculated the median effective dose (ED50) of esketamine combined with propofol in pediatric painless gastroscopy. Here, we designed a research to study the ED50 of esketamine combined with propofol using the Dixon and Massey up-and-down sequential method for inhibiting the response of gastroscope insertion. Methods Children who met the inclusion and exclusion criteria were included in this study. Propofol and esketamine were used as anesthetics for painless gastroscopy in children. To explore the ED50, the initial propofol dose was set at 3 mg/kg in all children. The first child was given an esketamine dose of 0.1 mg/kg, followed by 30 s of slow bolus injection propofol. If anesthesia induction failed (coughing or body movement of children during gastroscope insertion), the esketamine dose was elevated in the next child, with a interval difference of 0.05 mg/kg. Otherwise, if the anesthesia induction was successful, the next dosage was reduced by 0.05 mg/kg. The study was stopped if nine crossover inflection points were reached. The ED50 of esketamine was calculated using probit regression, and the blood pressure, pulse oxygen saturation, heart rate, recovery time, and side effects were recorded in all children. Results A total of 26 children were included in this study. The ED50 of esketamine combined with 3 mg/kg propofol was 0.143 mg/kg (95% CI 0.047–0.398 mg/kg). The total consumption of propofol was 16.04 ± 5.37 mg. The recovery time was 16.38 ± 8.70 min. Adverse effects recorded were delayed awakening in two cases and increased oral secretions of another child during the examination inducing cough and hypoxemia (86% was the lowest). Discussion The ED50 of esketamine was 0.143 mg/kg when combined with 3 mg/kg propofol for successful sedation in pediatric gastroscope insertion. This sub-anaesthetic dose of esketamine was safe and efficacious with few complications in pediatric painless gastroscopy. Trial registration The study was registered at the Chinese Clinical Trial Registry ( www.chictr.org.cn ; registration number: ChiCTR2100052830 on 06/11/2021).

Abstract Hydroformylation is one of the largest industrially homogeneous processes that strongly relies on catalysts with phosphine ligands such as the Wilkinson’s catalyst (triphenylphosphine coordinated Rh). Heterogeneous catalysts for olefin hydroformylation are highly desired but suffer from poor activity compared with homogeneous catalysts. Herein, we demonstrate that rhodium nanoparticles supported on siliceous MFI zeolite with abundant silanol nests are very active for hydroformylation, giving a turnover frequency as high as ~50,000 h−1 that even outperforms the classical Wilkinson’s catalyst. Mechanism study reveals that the siliceous zeolite with silanol nests could efficiently enrich olefin molecules to adjacent rhodium nanoparticles, enhancing the hydroformylation reaction.

Aboveground biomass (AGB) is a crucial physiological parameter for monitoring crop growth, assessing nutrient status, and predicting yield. Texture features (TFs) derived from remote sensing images have been proven to be crucial for estimating crops AGB, which can effectively address the issue of low accuracy in AGB estimation solely based on spectral information. TFs exhibit sensitivity to the size of the moving window and directional parameters, resulting in a substantial impact on AGB estimation. However, few studies systematically assessed the effects of moving window and directional parameters for TFs extraction on rice AGB estimation. To this end, this study used Unmanned aerial vehicles (UAVs) to acquire multispectral imagery during crucial growth stages of rice and evaluated the performance of TFs derived with different grey level co-occurrence matrix (GLCM) parameters by random forest (RF) regression model. Meanwhile, we analyzed the importance of TFs under the optimal parameter settings. The results indicated that: (1) the appropriate window size for extracting TFs varies with the growth stages of rice plant, wherein a small-scale window demonstrates advantages during the early growth stages, while the opposite holds during the later growth stages; (2) TFs derived from 45° direction represent the optimal choice for estimating rice AGB. During the four crucial growth stages, this selection improved performance in AGB estimation with R2 = 0.76 to 0.83 and rRMSE = 13.62% to 21.33%. Furthermore, the estimation accuracy for the entire growth season is R2 =0.84 and rRMSE =21.07%. However, there is no consensus regarding the selection of the worst TFs computation direction; (3) Correlation (Cor), Mean, and Homogeneity (Hom) from the first principal component image reflecting internal information of rice plant and Contrast (Con), Dissimilarity (Dis), and Second Moment (SM) from the second principal component image expressing edge texture are more important to estimate rice AGB among the whole growth stages; and (4) Considering the optimal parameters, the accuracy of texture-based AGB estimation slightly outperforms the estimation accuracy based on spectral reflectance alone. In summary, the present study can help researchers confident use of GLCM-based TFs to enhance the estimation accuracy of physiological and biochemical parameters of crops.

Summary: Background: The chronic effects of fine particulate matter (PM2.5) at high concentrations remains uncertain. We aimed to examine the relationship of long-term PM2.5 exposure with all-cause and the top three causes of death (cardiovascular disease [CVD], cancer, and respiratory disease), and to analyze their concentration-response functions over a wide range of concentrations. Methods: We enrolled community residents aged 35–75 years from 2014 to 2017 from all 31 provinces of the Chinese Mainland, and followed them up until 2021. We used a long-term estimation dataset for both PM2.5 and O3 concentrations with a high spatiotemporal resolution to assess the individual exposure, and used Cox proportional hazards models to estimate the associations between PM2.5 and mortalities. Findings: We included 1,910,923 participants, whose mean age was 55.6 ± 9.8 years and 59.4% were female. A 10 μg/m3 increment in PM2.5 exposure was associated with increased risk for all-cause death (hazard ratio 1.02 [95% confidence interval 1.012–1.028]), CVD death (1.024 [1.011–1.037]), cancer death (1.037 [1.023–1.052]), and respiratory disease death (1.083 [1.049–1.117]), respectively. Long-term PM2.5 exposure nonlinearly related with all-cause, CVD, and cancer mortalities, while linearly related with respiratory disease mortality. Interpretation: The overall effects of long-term PM2.5 exposure on mortality in the high concentration settings are weaker than previous reports from settings of PM2.5 concentrations < 35 μg/m³. The distinct concentration-response relationships of CVD, cancer, and respiratory disease mortalities could facilitate targeted public health efforts to prevent death caused by air pollution. Funding: The Chinese Academy of Medical Sciences Innovation Fund for Medical Science, the National High Level Hospital Clinical Research Funding, the Ministry of Finance of China and National Health Commission of China, the 111 Project from the Ministry of Education of China.

Background Knowledge gaps remain in how gender‐related socioeconomic inequality affects sex disparities in cardiovascular diseases (CVD) prevention and outcome. Methods and Results Based on a nationwide population cohort, we enrolled 3 737 036 residents aged 35 to 75 years (2014–2021). Age‐standardized sex differences and the effect of gender‐related socioeconomic inequality (Gender Inequality Index) on sex disparities were explored in 9 CVD prevention indicators. Compared with men, women had seemingly better primary prevention (aspirin usage: relative risk [RR], 1.24 [95% CI, 1.18–1.31] and statin usage: RR, 1.48 [95% CI, 1.39–1.57]); however, women's status became insignificant or even worse when adjusted for metabolic factors. In secondary prevention, the sex disparities in usage of aspirin (RR, 0.65 [95% CI, 0.63–0.68]) and statin (RR, 0.63 [95% CI, 0.61–0.66]) were explicitly larger than disparities in usage of angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers (RR, 0.88 [95% CI, 0.84–0.91]) or β blockers (RR, 0.67 [95% CI, 0.63–0.71]). Nevertheless, women had better hypertension awareness (RR, 1.09 [95% CI, 1.09–1.10]), similar hypertension control (RR, 1.01 [95% CI, 1.00–1.02]), and lower CVD mortality (hazard ratio, 0.46 [95% CI, 0.45–0.47]). Heterogeneities of sex disparities existed across all subgroups. Significant correlations existed between regional Gender Inequality Index values and sex disparities in usage of angiotensin‐converting enzyme inhibitors/angiotensin receptor blockers (Spearman correlation coefficient, r=−0.57, P=0.0013), hypertension control (r=−0.62, P=0.0007), and CVD mortality (r=0.45, P=0.014), which remained significant after adjusting for economic factors. Conclusions Notable sex disparities remain in CVD prevention and outcomes, with large subgroup heterogeneities. Gendered socioeconomic factors could reinforce such disparities. A sex‐specific perspective factoring in socioeconomic disadvantages could facilitate more targeted prevention policy making.

Snoring is a typical and intuitive symptom of the obstructive sleep apnea hypopnea syndrome (OSAHS), which is a kind of sleep-related respiratory disorder having adverse effects on people’s lives. Detecting snoring sounds from the whole night recorded sounds is the first but the most important step for the snoring analysis of OSAHS. An automatic snoring detection system based on the wavelet packet transform (WPT) with an eXtreme Gradient Boosting (XGBoost) classifier is proposed in the paper, which recognizes snoring sounds from the enhanced episodes by the generalization subspace noise reduction algorithm. The feature selection technology based on correlation analysis is applied to select the most discriminative WPT features. The selected features yield a high sensitivity of 97.27% and a precision of 96.48% on the test set. The recognition performance demonstrates that WPT is effective in the analysis of snoring and non-snoring sounds, and the difference is exhibited much more comprehensively by sub-bands with smaller frequency ranges. The distribution of snoring sound is mainly on the middle and low frequency parts, there is also evident difference between snoring and non-snoring sounds on the high frequency part.

Background Based on evidence from existing observational research, clarifying the causal relationship between gastro-oesophageal reflux disease (GORD) and obstructive sleep apnoea (OSA) is challenging. Here, Mendelian randomisation, a method based on genetics, was used to provide new evidence for causality. Methods Summary statistics from two publicly available genome-wide association studies were used to evaluate the causal relationship between GORD and OSA (the GORD database was used as an exposure variable and the OSA database as an outcome). Inverse variance weighting was used as the main analytical tool in Mendelian randomisation to estimate causal effects. The robustness of the results was evaluated by sensitivity analysis. Possible mediators were evaluated using multivariate Mendelian randomisation. Results A statistically significant causal relationship was observed between GORD and OSA (OR 1.597, 95% CI 1.401–1.821, p

Abstract Background Patients with type 2 diabetes mellitus (T2DM) usually have higher blood viscosity attributed to high blood glucose that can decrease blood supply to the pancreas. A mild increase in blood pressure (BP) has been reported as a potential compensatory response that can maintain blood perfusion in the islet. However, how BP influences beta-cell function in T2DM subjects remains inconsistent. This study aimed to examine the relationship between BP and beta-cell function in patients with T2DM under different HbA1c levels. Methods This is a cross-sectional study of 615 T2DM patients, whose clinical data were extracted from hospital medical records. Beta-cell function was assessed by insulin secretion-sensitivity index-2 (ISSI2). Multivariable linear regression analysis and restricted cubic splines (RCS) analysis were performed to identify the association between systolic BP (SBP) and ISSI2. Mediation analysis was performed to determine whether higher SBP could reduce blood glucose by enhancing beta-cell function. Results After adjustment of potential confounders, in participants with HbA1c ≥ 10%, the SBP between 140 to150 mmHg had the highest log ISSI2 (b = 0.227, 95% CI 0.053–0.402), an association specific to participants with

Abstract Alzheimer's disease (AD) is the most common cause of progressive dementia. In the present study, we showed hippocampal tissue transcriptome analysis in APPswe/PSEN1dE9 (APP/PS1, AD model) mice treated with fasudil (ADF) and compared with AD mice treated with saline (ADNS) and wild type mice (WT). The competing endogenous RNA (ceRNA) network was constructed and validated the differential expression of mRNA, lncRNA, miRNA, and circRNA. Our study showed differentially expressed mRNAs (DEMs) between WT and ADNS, while enriched in cell growth and death and nervous system pathways. DEMs between ADNS-ADF were enriched in the nervous system, glycosaminoglycan biosynthesis-keratan sulfate (KS) and Quorum sensing pathways. We validated four genes with RT-PCR, whereas enrichment of Acyl-CoA Synthetase Long Chain Family Member 4 (Acsl4, ENSMUST00000112903) in Quorum sensing pathways, and BTG anti-proliferation factor 1 (Btg1, ENSMUST00000038377) in RNA degradation pathways were conducted. Expression of these two genes were higher in ADNS, but were significantly reduced in ADF. Histone H4 transcription factor (Hinfp, ENSMUST00000216508) orchestrate G1/S transition of mitotic cell cycle and co-expressed with mmu-miR-26a-2-3p-mediated ceRNA and mmu-miR-3065-5p-mediated ceRNA; Wnt family member 4 (Wnt4, ENSMUST00000045747) was enriched in mTOR, Hippo and Wnt signaling pathway. Expression of these two genes were significantly lower in ADNS, and fasudil treatment reverse it. The present studies demonstrated four genes: Acsl4, Btg1, Hinfp, Wnt4 could be potential biomarkers of AD and the targets of fasudil treatment. These results will pave a novel direction for future clinic studies for AD and fasudil treatment.

Accurate retrieval of ice surface temperature (IST) over the Arctic ice-water mixture zone (IWMZ) is significantly essential for monitoring the change of the polar sea ice environment. Previous researchers have focused on evaluating the accuracy of IST retrieval in pack ice regions, possibly on account of the availability of in situ measurement data. Few of them have assessed the accuracy of IST retrieval on IWMZ. This study utilized Landsat 8/TIRS and Operation IceBridge observations (OIB) to evaluate the accuracy of the current IST retrieval method in IWMZ and proposed an adjustment method for improving the overall accuracy. An initial comparison shows that Landsat 8 IST and OIB IST have minor differences in the pack ice region with RMSE of 0.475 K, MAE of 0.370 K and cold bias of −0.256 K. In the thin ice region, however, the differences are more significant, with RMSE of 0.952 K, MAE of 0.776 K and warm bias of 0.703 K. We suggest that this phenomenon is because the current ice-water classification method misclassified thin ice as water. To address this issue, an adjusted method is proposed to refine the classification of features within the IWMZ and thus improve the accuracy of IST retrieval using Landsat 8 imagery. The results demonstrate that the accuracy of the retrieved IST in the two cases was improved in the thin ice region, with RMSE decreasing by about 0.146 K, Bias decreasing by about 0.311 K, and MAE decreasing by about 0.129 K. After the adjustment, high accuracy was achieved for both pack ice and thin ice in IWMZ.

Abstract Background The Interaction between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with Angiotensin converting enzyme 2 (ACE2) on the host cells is a crucial step for the viral entry and infection. Therefore, investigating the molecular mechanism underlying the interaction is of great importance for the prevention of the infection of SARS-CoV-2. In this study, we aimed to establish a virus-free in vitro system to study the interaction between the spike protein and host cells of SARS-CoV-2. Results Our results show that ACE2-overexpressing HEK293T cells are captured by immobilized spike S1 protein, and the cell capturing process can be inhibited by the receptor binding domain of the spike protein or antibodies against S protein. Furthermore, spike S1 protein variant with D614G mutant show a higher cell capturing ability than wild type spike S1 protein and stronger binding capacity of its receptor ACE2. In addition, the captured cells can be eluted as living cells for further investigation. Conclusions This study provides a new in vitro system for investigating the interaction between SARS-CoV-2 and host cells and purifying ACE2-expressing cells.

BackgroundElevated blood pressure (BP) is associated with substantial morbidity and mortality in stroke survivors. China has the highest prevalence of stroke survivors and accounts for one-third of stroke-related deaths worldwide. We aimed to describe the prevalence and treatment of elevated BP across age, sex, and region, and assess the mortality attributable to elevated BP among stroke survivors in China.Materials and methodsBased on 3,820,651 participants aged 35–75 years from all 31 provinces in mainland China recruited from September 2014 to September 2020, we assessed the prevalence and treatment of elevated BP (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) among those with self-reported stroke and stratified by age group, sex, and geographic region. We estimated the age- and sex-specific population attributable fractions of death from elevated BP.ResultsAmong 91,406 stroke survivors, the mean (SD) age was 62 (8) years, and 49.0% were male. The median interquartile range (IQR) stroke duration was 4 (2, 7) years. The prevalence of elevated BP was 61.3% overall, and increased with age (from 47.5% aged 35–44 years to 64.6% aged 65–75 years). The increment of prevalence was larger in female patients than male patients. Elevated BP was more prevalent in northeast (66.8%) and less in south (54.3%) China. Treatment rate among patients with elevated BP was 38.1%, and rates were low across all age groups, sexes, and regions. Elevated BP accounted for 33 and 21% of cardiovascular and all-cause mortality among stroke survivors, respectively. The proportion exceeded 50% for cardiovascular mortality among patients aged 35–54 years.ConclusionIn this nationwide cohort of stroke survivors from China, elevated BP and its non-treatment were highly prevalent across all age groups, sexes, and regions. Elevated BP accounted for nearly one-third cardiovascular mortality in stroke survivors, and particularly higher in young and middle-aged patients. National strategies targeting elevated BP are warranted to address the high stroke burden in China.

BackgroundStroke, including ischemic stroke and hemorrhagic stroke, possesses complex pathological mechanisms such as neuroinflammation, oxidative stress and blood-brain barrier damage. Astrocyte functions have been reported during injury, neuroprotection and cell crosstalk. It plays a key role in exacerbating stroke injury, promoting neurological repair and enhancing neuroregeneration.AimThis holistic bibliometric analysis aimed to provide a general overview of the recent advancement and the hotspots in the field of stroke and astrocyte from 2001 to 2021.Materials and methodsPublications between 2001 and 2021, related to stroke and astrocyte were retrieved from the Web of Science (WOS) and analyzed in Gephi and VOSviewer.ResultsIn total, 3789 documents were extracted from the WOS databases. The publications showed stable growth since 2001. The United States and China were the most prolific countries and University of California San Francisco and Oakland University were the most influential institutes. The top four most productive journals were Brain Research, Journal of Cerebral Blood Flow and Metabolism, Glia and Journal of Neuroinflammation. Keywords frequency and co-occurrence analysis revealed that the topics related to “micro-RNA”, “toll like receptor”, “neuroinflammation”, “autophagy” and “interleukin” were research frontiers. The field of stroke and astrocyte focused on several aspects, such as the role of astrocytes in the treatment of stroke, metabolic changes in astrocytes, the protective role of apoptosis in astrocytes after oxidative stress injury and neurovascular units.ConclusionThis comprehensive bibliometric study provides an updated perspective on the trend of research associated with stroke and astrocyte. It will benefit scientific community to identify the important issues, future directions and provide a novel understanding of stroke pathophysiology, hotspots and frontiers to facilitate future research direction.

Early-season crop mapping and information extraction is essential for crop growth monitoring and yield prediction, and it facilitates agricultural management and rapid response to agricultural disasters. However, training classifiers by remote sensing classification features for early crop prediction can be challenging, as early-season mapping can only use remote sensing image data during part of the crop growth period. In order to overcome this limitation, this study takes the Sanjiang Plain as an example to investigate the earliest identification time of rice, maize and soybean based on Sentinel-2 time-series data and the random forest classification algorithm. Crop information extraction was then performed. Following the analysis of the remote sensing classification features by the random forest importance approach and the subsequent normalization, the optimal features greater than or equal to 0.5 have yielded quite results in early crop mapping, and their overall accuracy was the highest in early-season mapping. The overall accuracy was observed to improve by 5% for 10 to 20 days of delay. In addition, rice, maize, and soybean were mapped at the irrigation transplanting period (10 May), jointing stage (9 July) and flowering (29 July), with an overall accuracy of 90.4%, 90.0% and 90.9%, respectively. This study shows that features suitable for early crop classification can be selected by random forest importance analysis as well as the ability of remote sensing to extract crop acreage information within the reproductive period.

Abstract Background Patients with nasopharyngeal cancer (NPC) differ in prognosis, even at the same stage; therefore, new biomarkers are urgently required to identify early-stage NPC patients at high risk of poor prognosis. Although Epstein–Barr virus (EBV) DNA has been used for prognosis, the value of many other biomarkers expressed during the infection cycle of EBV remains unclarified. This study aimed to evaluate the prognostic potential of EA-IgA, VCA-IgA and d-dimer in patients with NPC. Methods Electronic databases, including PubMed, Embase and Web of Science, were searched up to February 1, 2021. Pooled data were extracted from studies that evaluated the relationship between NPC and overall survival (OS), distant metastasis-free survival (DMFS) or disease-free survival (DFS) and then were subjected to a meta-analysis. Results Nine studies with 5729 patients were included in this meta-analysis. In patients with NPC, EA-IgA levels significantly predicted OS (HR = 1.63, 95% CI 1.07–2.48). d-Dimer levels significantly predicted OS (HR = 1.75, 95% CI 1.24–2.47) and DMFS (HR = 1.91, 95% CI 1.31–2.79). However, high levels of VCA-IgA were not associated with OS (HR = 1.24, 95% CI 0.95–1.60), DMFS (HR = 1.41, 95% CI 0.92–2.17) or DFS (HR = 2.39, 95% CI 0.78–7.26). Conclusions The present findings reveal that EA-IgA and d-dimer, but not VCA-IgA, can be used as prognostic biomarkers in NPC.

The experience value of online education is a hot topic in both theoretical and practical circles, but research on its mechanism of action is limited. Therefore, this study systematically investigates the relationship between brand image, experience value, and continuance intention through a theoretical analysis of brand image, and discusses the boundary role of effective commitment in it. In this study, 475 users were used to conduct structural equation modeling analysis. The results of the study found that experience value had a positive and significant effect on user continuance intention under the significant influence of brand image, but affective commitment did not play a positive moderating role in the relationship between experience value and continuance intention. This study examines the mechanism of the antecedents and consequences of experience value, and provides a new direction for the construction of online education and the development of online education and marketing strategies.

Harsh work environments can include very cold, hot, dusty, and noisy workplaces, as well as exposure in the workplace with chemicals and other fumes, cigarette smoke, and diesel exhaust. Although working in these harsh environments can have a negative effect on health, there are no effective biomarkers for monitoring health conditions until workers develop disease symptoms. Plasma protein concentrations, which reflect metabolism and immune status, have great potential as biomarkers for various health conditions. Using a Mendelian-randomization (MR) design, this study analyzed the effects of these harsh environments on plasma proteins to identify proteins that can be used as biomarkers of health status. Preliminary analysis using inverse variance weighted (IVW) method with a p-value cutoff of 0.05 showed that workplace environments could affect the concentrations of hundreds of plasma proteins. After filtering for sensitivity via MR-Egger, and Weighted Median MR approaches, 28 plasma proteins altered by workplace environments were identified. Further MR analysis showed that 20 of these plasma proteins, including UNC5D, IGFBP1, SCG3, ST3GAL6, and ST3GAL2 are affected by noisy workplace environments; TFF1, RBM39, ACYP2, STAT3, GRB2, CXCL1, EIF1AD, CSNK1G2, and CRKL that are affected by chemical fumes; ADCYAP1, NRSN1, TMEM132A, and CA10 that are affected by passive smoking; LILRB2, and TENM4 that are affected by diesel exhaust, are associated with the risk of at least one disease. These proteins have the potential to serve as biomarkers to monitor the occupational hazards risk of workers working in corresponding environments. These findings also provide clues to study the biological mechanisms of occupational hazards.

Study region: The upper Brahmaputra River, China. Study focus: The long-term water level and storage variations of the upper Brahmaputra River (UBR) are not yet clear due to the low accessibility of gauged data in high-altitude and harsh environments. The main objective of this study is to facilitate investigations of long-term river water level and storage variations over the UBR. Here we developed a hypsometric method to reconstruct temporally resolved long-term river water level observations based on remote sensing-derived accumulative water inundation area information and short-term altimetric water level data at 24 virtual stations (VSs) of the UBR. We further analyzed the intra-annual and inter-annual variations of the water level (storage) changes of the studied river reaches. New hydrological insights: The results reveal that the reconstructed water levels of the UBR are quite consistent with the water levels from the Hydroweb with an average R2 of 0.79 and the reconstructed water levels are generally consistent with the variation of the gauged runoff. The ascending amplitudes of the annual water level cycle of VSs were observed from upstream to downstream of the UBR, varying from 0.58 m to 6.92 m. Additionally, we find that the seasonal change in river water storage approximately accounted for one-tenth of the net mass seasonal amplitude of the UBR basin, as revealed from the Gravity Recovery and Climate Experiment (GRACE) data.

In recent years, neurovascular unit (NVU) which is composed of neurons, astrocytes (Ast), microglia (MG), vascular cells and extracellular matrix (ECM), has become an attractive field in ischemic stroke. As the important component of NVU, Ast closely interacts with other constituents, which has been playing double-edged sword roles, beneficial or detrimental after ischemic stroke. Based on the pathophysiological changes, we evaluated some strategies for targeting Ast in treating ischemic stroke. The present review is focused on the roles of Ast in NVU and its complex signaling molecular network after ischemic stroke, which may be a prospective approach to the treatment of ischemic diseases in central nervous system.

Abstract Background Numerous individual studies have investigated the diagnostic value of EBV-DNA, EA-IgA, VCA-IgA, EBNA1-IgA and Rta-IgG detection for nasopharyngeal carcinoma (NPC), but the conclusions remain controversial. This meta-analysis aimed to determine the value of EBV-DNA, EA-IgA, VCA-IgA, EBNA1-IgA and Rta-IgG detection in the diagnosis of NPC. Methods PROSPERO registration number: CRD42019145532. PubMed, EMBASE, Cochrane Library, and Chinese data libraries (Wanfang, CNKI, and CBM) were searched up to January 2019. The pooled sensitivity, specificity, and positive likelihood, negative likelihood, and diagnostic odds ratios were conducted in this meta-analysis. Summary receiver operating characteristic curves evaluated the test-performance global summary. Publication bias was examined by Deek’s funnel plot asymmetry test. Results Forty-seven studies with 8382 NPC patients (NPC group) and 15,089 individuals without NPC (Control group) were included in this meta-analysis. The sensitivity, specificity, positive likelihood (+ LR), negative likelihood (-LR), DOR and AUC of EBV-DNA in diagnosis of NPC were: 0.76 (95% CI 0.73–0.77), 0.96 (95% CI 0.95–0.97), 14.66 (95% CI 9.97–21.55), 0.19 (95% CI 0.13–0.28), 84 (95% CI 50.45–139.88), 0.96 (SE: 0.001), and 0.55 (95% CI 0.54–0.57), 0.96 (95% CI 0.96–0.97), 12.91 (95% CI 9.55–17.45), 0.35 (95% CI 0.29–0.43), 39.57 (95% CI 26.44–59.23), 0.94 (SE: 0.002) for the EA-IgA, and 0.85 (95% CI 0.84–0.85), 0.89 (95% CI 0.88–0.89), 6.73 (95% CI5.38–8.43), 0.17 (95% CI 0.12–0.23), 43.03 (95% CI 31.51–58.76), 0.93 (SE: 0.007) for the VCA-IgA, and 0.86 (95% CI 0.85–0.88), 0.87 (95% CI 0.88–0.90), 7.55 (95% CI 5.79–9.87), 0.16 (95% CI 0.13–0.19), 50.95 (95% CI 34.35–75.57), 0.94 (SE: 0.008) for the EBNA1-IgA, and 0.70 (95% CI 0.69–0.71), 0.94 (95% CI 0.94–0.95), 9.84 (95% CI 8.40–11.54), 0.25 (95% CI 0.21–0.31), 40.59 (95% CI 32.09–51.35), 0.95 (SE: 0.005) for the Rta-IgG. The EBV-DNA had larger AUC compared with other EBV-based antibodies (P 0.05). Conclusions EBV-DNA, VCA-IgA, EBNA1-IgA and Rta-IgG detection have high accuracy in early diagnosis NPC. In addition, EBV-DNA detection has the higher diagnosis accuracy in NPC. On the other hand, EA-IgA is suitable for the diagnosis but not NPC screening.

Alzheimer’s disease (AD) is a severe neurodegenerative disorder of the central nervous system (CNS) characterized by neuron loss and dementia. Previous abundant evidence demonstrates that the first critical step in the course of AD is the state of oxidative stress and the neuronal loss is closely related to the interaction of several signalling pathways. The neuroprotective efficacy of Rho-associated protein kinase (ROCK) inhibitor in the treatment of AD has been reported, but its exact mechanism has not been well elucidated. The purpose of this study is to investigate the therapeutic effects of Fasudil on amyloid precursor protein/presenilin-1 (APP/PS1) mice and to discover the potential underlying mechanism. Sixteen 8-month-old APP/PS1 mice were divided into model and Fasudil treatment groups and 8 wild-type mice were used as a normal control group. After the behavioural test, all mice were sacrificed for immunofluorescence and other biochemical tests. The results showed that the administration of Fasudil improved learning and memory ability, elevated the concentration of antioxidative substances and decreased lipid peroxides, as well as inhibited neuronal apoptosis by increasing the expression of B-cell lymphoma-2 (Bcl-2) (p < 0.05), reducing Bcl-2 Associated X (Bax) (p < 0.05) and cleaved caspase-3 (p < 0.05) of APP/PS1 mice. Moreover, Fasudil treatment also ameliorated the phosphorylation of p38 (p < 0.01), c-Jun N-terminal kinase (JNK) (p < 0.001) and extracellular regulated protein kinases (ERK) (p < 0.001), and accelerated the nuclear factor-erythroid 2 p45-related factor 2 (Nrf2) (p < 0.01) expression and its antioxidative downstream molecules (p < 0.05, p < 0.05, and p < 0.05, respectively). Data from the present study demonstrate that Fasudil significantly restored cognitive function, restrained oxidative stress and reduced neuronal apoptosis in the hippocampus, probably by inhibiting ROCK/MAPK and activating Nrf2 signalling pathways in APP/PS1 mice.

Background: Physical activity (PA) is an important component of secondary prevention after myocardial infarction (MI). The mortality risk of MI survivors varies at different post-MI periods, yet the time-varying effect of total PA is unclear. We aimed to investigate the association between different volumes and patterns of total PA and mortality at different post-MI periods. Methods: Using data from the China Patient-centered Evaluative Assessment of Cardiac Events Million Persons Project, we divided the screened MI survivors into within-1-year and beyond-1-year groups based on the duration between their baseline interview and MI onset. Total PA was divided into insufficient (4500 MET minutes/week) volumes; leisure (≥50%) and non-leisure (>50%) patterns. Data on mortality were derived from the National Mortality Surveillance System and Vital Registration of the Chinese Center for Disease Control and Prevention. Cox proportional hazard models were fitted to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Restricted cubic spline regression analyses were performed to examine the dose-response association between PA and mortality. Results: During the follow-up (median 3.7 years) of the 20,653 post-MI patients, 751 patients died. In the within-1-year group, moderate (HR: 0.59, 95% CI: 0.40 to 0.88) and high (0.63, 0.45 to 0.88) volumes and both patterns (leisure: 0.52, 0.29 to 0.94; non-leisure: 0.64, 0.46 to 0.88) of PA were all associated with significantly lower risk of mortality, compared with insufficient PA. In the beyond-1-year group, the association was observed in high volume (0.69, 0.56 to 0.86) and both patterns (leisure: 0.64, 0.48 to 0.87; non-leisure: 0.79, 0.65 to 0.97). A non-linear relationship between PA and mortality was found in the within-1-year group (p for non-linearity

BackgroundLipid-lowering therapy (LLT) is one of the key strategies for reducing the atherosclerotic cardiovascular disease (ASCVD) burden. However, little is known about the percentage of people in need of different LLT regimens to achieve optimal targets of low-density lipoprotein cholesterol (LDL-C), and the corresponding cost and benefit.MethodsWe conducted a simulation study based on the data from the nationwide China PEACE MPP population cohort (2015–2020), from which we included 2,904,914 participants aged 35–75 years from all the 31 provinces in mainland China. Participants were grouped based on their 10-year ASCVD risks, then entered into a Monte Carlo model which was used to perform LLT intensification simulation scenarios to achieve corresponding LDL-C goals in each risk stratification.ResultsAfter standardizing age and sex, the proportions of participants included at low, moderate, high, and very-high risk were 70.8%, 15.6%, 11.5%, and 2.1%, respectively. People who failed to achieve the corresponding LDL-C goals −8.1% at low risk, 19.6% at moderate risk, 53.2% at high risk, and 93.6% at very-high risk (either not achieving the goal or not receiving LLT)—would be in need of the LLT intensification simulation. After the use of atorvastatin 20 mg was simulated, over 99% of the population at low or moderate risk could achieve the LDL-C goals; while 11.3% at high and 24.5% at very-high risk would still require additional non-statin therapy. After the additional use of ezetimibe, there were still 4.8% at high risk and 11.3% at very-high risk in need of evolocumab; and 99% of these two groups could achieve the LDL-C goals after the use of evolocumab. Such LLT intensification with statin, ezetimibe, and evolocumab would annually cost $2.4 billion, $4.2 billion, and $24.5 billion, respectively, and prevent 264,170, 18,390, and 17,045 cardiovascular events, respectively.ConclusionsModerate-intensity statin therapy is pivotal for the attainment of optimal LDL-C goals in China, and around 10–25% of high- or very-high-risk patients would require additional non-statin agents. There is an opportunity to reduce the rising ASCVD burden in China by optimizing LLT.

ObjectivesWe aimed to assess the dose–response association between weight gain from young to middle adulthood and odds of metabolic syndrome, across body mass index (BMI) categories at young adulthood.MethodsBased on a national population-based screening project, middle-aged (35–64 years) participants who recalled weight at age 25 years and received standardized measurements were included. Multivariable adjusted restricted cubic splines and logistic regression models were applied.ResultsIn total, 437,849 participants were included (62.1% women, 52.0 ± 7.6 years). Larger weight gains from young to middle adulthood were associated with higher odds of metabolic syndrome at middle adulthood, with odds of 2.01 (1.98–2.05), 1.93 (1.92–1.94), and 1.67 (1.64–1.7) per 5-kg weight gain across participants who were underweight, normal-weight, and overweight/obese at young adulthood, respectively. After further adjusting for current BMI, larger weight gains still correlated with higher odds of metabolic syndrome among underweight and normal-weight participants, while an inverted U-shaped association was observed in overweight/obese participants.ConclusionsWeight maintenance from young to middle adulthood could be effective to mitigate metabolic syndrome burden, especially among underweight and normal-weight people. Historical weight gain confers varied information about metabolic syndrome risk independent of attained BMI across BMI categories at young adulthood.

Objectives: To develop and evaluate a new coordinate system for MRI of the vestibular system.Methods: In this study, 53 internal auditory canal MRI and 78 temporal bone CT datasets were analyzed. Mimics Medical software version 21.0 was used to visualize and three-dimensionally reconstruct the image data. We established a new coordinate system, named W–X, based on the center of the bilateral eyeballs and vertex of the bilateral superior semicircular canals. Using the W–X coordinate system and Reid's coordinate system, we measured the orientations of the planes of the anterior semicircular canal (ASCC), the lateral semicircular canal (LSCC), and the posterior semicircular canal (PSCC).Results: No significant differences between the angles measured using CT and MRI were found for any of the semicircular canal planes (p > 0.05). No statistical differences were found between the angles measured using Reid's coordinate system (CT) and the W–X coordinate system (MRI). The mean values of ∠ASCC & LSCC, ∠ASCC & PSCC, and ∠LSCC & PSCC were 84.67 ± 5.76, 94.21 ± 3.81, and 91.79 ± 5.22 degrees, respectively. The angle between the LSCC plane and the horizontal imaging plane was 15.64 ± 3.92 degrees, and the angle between the PSCC plane and the sagittal imaging plane was 48.79 ± 4.46 degrees.Conclusion: A new W–X coordinate system was developed for MRI studies of the vestibular system and can be used to measure the orientations of the semicircular canals.

Lakes are of significant importance in regulating floods and providing water sources. The seasonal water storage variations for the plain lake group in the Yangtze–Huai River Basin (YHRB) are significant for alleviating flood pressure and regulating runoff. However, to date, the seasonal amplitude of lake water storage variations and its capacity of buffering floodwater in the YHRB is not quantified well and remains to be investigated comprehensively. To advance the understanding of such a critical scientific issue, the water level data of the plain lake group (area>100 km2, 29 lakes) in the YHRB is collected from multi-source data between 1990 and 2020. Using lake inundation area obtained from Global Surface Water and water level variations, water storage dynamics for the plain lake group are quantified. Furthermore, this study also uses the Gravity Recovery and Climate Experiment (GRACE) products to analyze the terrestrial water storage anomalies (TWSA) in the whole basin. The results indicate that the seasonal amplitude of water level change and water storage variation of the plain lake group are 2.80 ± 0.71 m and 37.38 ± 14.19 Gt, respectively. Poyang and Dongting Lakes, two lakes that maintain the natural connection with the Yangtze River, have the most substantial seasonal amplitude in the hydrological situation. The amplitude in water level and water storage in Poyang Lake is 9.53 ± 2.02 m and 14.13 ± 5.54 Gt respectively, and that in Dongting Lake is 7.39 ± 1.29 m and 7.31 ± 3.42 Gt respectively. The contribution of seasonal variation of water storage for large plain lakes to TWSA in the YHRB is approximately 33.25%, fully reflecting these lake’s imperative position in the YHRB. This study is expected to enhance the scientific understanding of the seasonal hydrologic regime for the large lakes in the YHRB and contribute to the management of flood risks and water resources in East China.

Single-cell DNA sequencing (scDNA-seq) enables high-resolution profiling of genetic diversity among single cells and is especially useful for deciphering the intra-tumor heterogeneity and evolutionary history of tumor. Specific technical issues such as allele dropout, false-positive errors, and doublets make scDNA-seq data incomplete and error-prone, giving rise to a severe challenge of accurately inferring clonal architecture of tumor. To effectively address these issues, we introduce a new computational method called SCClone for reasoning subclones from single nucleotide variation (SNV) data of single cells. Specifically, SCClone leverages a probability mixture model for binary data to cluster single cells into distinct subclones. To accurately decipher underlying clonal composition, a novel model selection scheme based on inter-cluster variance is employed to find the optimal number of subclones. Extensive evaluations on various simulated datasets suggest SCClone has strong robustness against different technical noises in scDNA-seq data and achieves better performance than the state-of-the-art methods in reasoning clonal composition. Further evaluations of SCClone on three real scDNA-seq datasets show that it can effectively find the underlying subclones from severely disturbed data. The SCClone software is freely available at https://github.com/qasimyu/scclone.

Poyang Lake, the largest freshwater lake in China, is featured with high-frequency fluctuations and unique seasonal changes in water level and inundation areas, which plays a substantial part in regulating the runoff of the Yangtze River and maintaining the ecological balance of the region. Frequent observations enable more effectively reflecting the water budgets and related driving force of Poyang Lake. This study first utilized the Sentinel-1 SAR data and cloud-free Sentinel-2 images in conjugation with lake bathymetry to reconstruct the time series of the water inundation area and storage of Poyang Lake from 2017 to 2020. Further, a simple and straightforward method, named the Fitting Curves of each Block and Total area (FCoBT), is developed to reconstruct the complete inundation area of Poyang Lake from partially cloud-free Sentinel-2 images to densify the original time series. This method takes full advantage of the significant characteristics on the strong correlations of the block areas (one small part of lake area) varying with the complete lake areas, with a mean R2 and ρ value of 0.94 and 0.98, respectively. The complete inundation area of Poyang Lake can be reconstructed from 113 scenes of partially cloudless Sentinel-2 images acquired from 2017 to 2020 by using the FCoBT. After integrating the Sentinel-1 and Sentinel-2 images, a maximum of 13 measurements are available within one month, with the temporal intervals of 2–3 days. Results show that our reconstructed time series of water inundation area can finely depict significant seasonal fluctuation (wet season: from April to September, dry season: from October to the next March) and inter-annual variations (larger areas: 2017 and 2020, smaller areas: 2018 and 2019) of Poyang Lake during 2017–2020. Similar to the area change, the water storage of Poyang Lake also shows evident seasonal variation and inter-annual fluctuation, reaching the peaks in July and the lowest stages during November to February. This study cannot only provide an efficient and feasible remote sensing means of constructing long-term observations for highly variable lakes at high spatial–temporal resolutions, but also greatly refine our understanding on the intra-annual and inter-annual variations of Poyang Lake.

Background: Fasudil, a Rho kinase inhibitor, exerts therapeutic effects in a mouse model of Alzheimer's disease (AD), a chronic neurodegenerative disease with progressive loss of memory. However, the mechanisms remain unclear. In addition, the gut microbiota and its metabolites have been implicated in AD.Methods: We examined the effect of fasudil on learning and memory using the Morris water-maze (MWM) test in APPswe/PSEN1dE9 transgenic (APP/PS1) mice (8 months old) treated (i.p.) with fasudil (25 mg/kg/day; ADF) or saline (ADNS) and in age- and gender-matched wild-type (WT) mice. Fecal metagenomics and metabolites were performed to identify novel biomarkers of AD and elucidate the mechanisms of fasudil induced beneficial effects in AD mice.Results: The MWM test showed significant improvement of spatial memory in APP/PS1 mice treated with fasudil as compared to ADNS. The metagenomic analysis revealed the abundance of the dominant phyla in all the three groups, including Bacteroidetes (23.7–44%) and Firmicutes (6.4–26.6%), and the increased relative abundance ratio of Firmicutes/Bacteroidetes in ADNS (59.1%) compared to WT (31.7%). In contrast, the Firmicutes/Bacteroidetes ratio was decreased to the WT level in ADF (32.8%). Lefse analysis of metagenomics identified s_Prevotella_sp_CAG873 as an ADF potential biomarker, while s_Helicobacter_typhlonius and s_Helicobacter_sp_MIT_03-1616 as ADNS potential biomarkers. Metabolite analysis revealed the increment of various metabolites, including glutamate, hypoxanthine, thymine, hexanoyl-CoA, and leukotriene, which were relative to ADNS or ADF microbiota potential biomarkers and mainly involved in the metabolism of nucleotide, lipids and sugars, and the inflammatory pathway.Conclusions: Memory deficit in APP/PS1 mice was correlated with the gut microbiome and metabolite status. Fasudil reversed the abnormal gut microbiota and subsequently regulated the related metabolisms to normal in the AD mice. It is believed that fasudil can be a novel strategy for the treatment of AD via remodeling of the gut microbiota and metabolites. The novel results also provide valuable references for the use of gut microbiota and metabolites as diagnostic biomarkers and/or therapeutic targets in clinical studies of AD.

In the process of ischemic stroke (IS), cellular macroautophagy/autophagy and apoptosis play a vital role in neuroprotection against it. Therefore, regulating their balance is a potential therapeutic strategy. It has been proved that hydroxysafflor yellow A (HSYA) has anti-inflammatory and antioxidant effects, which can both protect neurons. By exploring bioinformatics combined with network pharmacology, we found that HIF1A and CASP3, key factors regulating autophagy and apoptosis, may be important targets of HSYA for neuroprotection in an oxygen glucose deprivation and reperfusion (OGD/R) model. In this study, we explored a possible new mechanism of HSYA neuroprotection in the OGD/R model. The results showed that OGD/R increased the expression of HIF1A and CASP3 in SH-SY5Y cells and induced autophagy and apoptosis, while HSYA intervention further promoted the expression of HIF1A and inhibited the level of CASP3, accompanied by an increase in autophagy and a decrease in apoptosis in SH-SY5Y cells. The inhibition of HIF1A diminished the activation of autophagy induced with HSYA, while the inhibition of autophagy increased cell apoptosis and blocked the neuroprotective effect of HSYA, suggesting that the neuroprotective effect of HSYA should be mediated by activating the HIF1A/BNIP3 signaling pathway to induce autophagy. These results demonstrate that HSYA may be a promising agent for treating IS.

Structural network pruning is an effective way to reduce network size for deploying deep networks to resource-constrained devices. Existing methods mainly employ knowledge distillation from the last layer of network to guide pruning of the whole network, and informative features from intermediate layers are not yet fully exploited to improve pruning efficiency and accuracy. In this paper, we propose a block-wisely supervised network pruning (BNP) approach to find the optimal subnet from a baseline network based on knowledge distillation and Markov Chain Monte Carlo. To achieve this, the baseline network is divided into small blocks, and block shrinkage can be independently applied to each block under a same manner. Specifically, block-wise representations of the baseline network are exploited to supervise subnet search by encouraging each block of student network to imitate the behavior of the corresponding baseline block. A score metric measuring block accuracy and efficiency is assigned to each block, and block search is conducted under a Markov Chain Monte Carlo scheme to sample blocks from the posterior. Knowledge distillation enables effective feature representations of the student network, and Markov Chain Monte Carlo provides a sampling scheme to find the optimal solution. Extensive evaluations on multiple network architectures and datasets show BNP outperforms the state of the art. For instance, with 0.16% accuracy improvement on the CIFAR-10 dataset, it yields a more compact subnet of ResNet-110 than other methods by reducing 61.24% FLOPs.

Planting rice in saline–alkali land can effectively improve saline–alkali soil and increase grain yield, but traditional identification methods for saline–alkali-tolerant rice varieties require tedious and time-consuming field investigations based on growth indicators by rice breeders. In this study, the Python machine deep learning method was used to analyze the Raman molecular spectroscopy of rice and assist in feature attribution, in order to study a fast and efficient identification method of saline–alkali-tolerant rice varieties. A total of 156 Raman spectra of four rice varieties (two saline–alkali-tolerant rice varieties and two saline–alkali-sensitive rice varieties) were analyzed, and the wave crests were extracted by an improved signal filtering difference method and the feature information of the wave crest was automatically extracted by scipy.signal.find_peaks. Select K Best (SKB), Recursive Feature Elimination (RFE) and Select F Model (SFM) were used to select useful molecular features. Based on these feature selection methods, a Logistic Regression Model (LRM) and Random Forests Model (RFM) were established for discriminant analysis. The experimental results showed that the RFM identification model based on the RFE method reached a higher recognition rate of 89.36%. According to the identification results of RFM and the identification of feature attribution materials, amylum was the most significant substance in the identification of saline–alkali-tolerant rice varieties. Therefore, an intelligent method for the identification of saline–alkali-tolerant rice varieties based on Raman molecular spectroscopy is proposed.

Background Studies have reported a close relationship between depression and sleep apnoea, yet it is unknown whether these are causally related. Thus, we aimed to determine whether depression is associated with the aetiology of sleep apnoea. Methods We used publicly available genetic summary data from two large consortia: the Psychiatric Genomics Consortium, with data from 36 single-nucleotide polymorphisms (SNPs) closely associated with major depressive disorder (MDD), and the UK Biobank, including 456 736 patients with sleep apnoea and 766 964 controls. For Mendelian randomisation (MR) analysis, we used the inverse-variance weighted method, weighted median method, MR-Egger regression, MR pleiotropy residual sum and outlier test to retrieve summary data. Analyses were performed using the “TwoSampleMR” package in R. Results Out of the 36 SNPs associated with MDD, we found statistically significant evidence of a potential causal effect of MDD on the risk of sleep apnoea (OR 1.004, 95% CI 1.001–1.006; p=0.001). Similar results were obtained using the MR-Egger and weighted median methods. Additionally, we found no heterogeneity or pleiotropy. Conclusions Our findings suggest that depression slightly increases the risk of sleep apnoea. Further investigation of the potential biological mechanisms is necessary.

Personal review record, as a form of personally identifiable information, refers to the past review information of a reviewer. The disclosure of reviewers’ personal information on electronic commerce websites has been found to substantially impact consumers’ perception regarding the credibility of online reviews. However, personal review record has received little attention in prior research. The current study investigated whether the disclosure of personal review record influenced consumers’ information processing and decision making by adopting event-related potentials (ERPs) measures, as ERPs allow for a nuanced examination of the neural mechanisms that underlie cognitive processes. At the behavioral level, we found that the purchase rate was higher and that the reaction time was shorter when the review record was disclosed (vs. when it was not), indicating that the disclosed condition was more favorable to the participants. Moreover, ERPs data showed that the disclosed condition induced an attenuated N400 component and an increased LPP component relative to the undisclosed condition, suggesting that the former condition gave rise to less cognitive and emotional conflict and to more positive evaluations. Thus, by elucidating potential cognitive and neural underpinnings, this study demonstrates the positive impact of reviewers’ disclosure of personal review record on consumers’ purchase decisions.

Electronic skin (e-skin) with skin-like flexibility and tactile sensation will promote the great advancements in the fields of wearable equipment. Thus, the multifunction and high robustness are two important requirements for sensing capability of the e-skin. Here, a fully organic self-powered e-skin (FOSE-skin) based on the triboelectric nanogenerator (TENG) is developed. FOSE-skin based on TENG can be fully self-healed within 10 hours after being sheared by employing the self-healing polymer as a triboelectric layer and ionic liquid with the temperature sensitivity as an electrode. FOSE-skin based on TENG has the multifunctional and highly robust sensing capability and can sense the pressure and temperature simultaneously. The sensing capability of the FOSE-skin based on TENG can be highly robust with no changes after self-healing. FOSE-skin based on TENG can be employed to detect the arm swing, the temperature change of flowing water, and the motion trajectory. This work provides a new idea for solving the issues of monofunctional and low robust sensing capability for FOSE-skin based on TENG, which can further promote the application of wearable electronics in soft robotics and bionic prosthetics.

The effect of the silicon to aluminum ratio (SAR) and alkali metal cations on adsorption and diffusion properties of ZSM-5 and silicate-1 zeolites was investigated using n-hexane as the model probe via giant canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. A wide range of SAR was considered in this study to explore the possible adsorption sites in the zeolites. The findings show that, at 298 K and 423 K, adsorption and diffusion of n-hexane on/in low SAR (≤50) H-ZSM-5 models were promoted due to the preferable distribution of n-hexane in straight channels and enhanced interaction between protons and n-hexane molecules (about 24 kcal·mol−1). In alkali metal cation (i.e., Na+ and K+) exchanged ZSM-5, the alkali metal cations affected transport of molecules, which led to significant differences in their adsorption and diffusion properties compared to HZSM-5. In the Na+ and K+ systems, lower saturated adsorption capacities were predicted compared to that of silicate-1, which could be attributed to the decrease in effective void size posed by alkali–metal cations. In addition, simulation results also suggested that the T9 and T3 are the most likely sites for n-hexane adsorption, followed by T2, T5, and T10. Findings of the work can be beneficial to the rational design of high-performance zeolite catalysts for n-hexane conversion.

This article studies the effects of some basic parameters of a parallel-axis helix gear stage on wind turbine gearbox vibration in a case study: a multibody dynamic model is constructed to simulate the drive train of a faulted multistage wind turbine gearbox with serious vibrations. The significant vibration behaviour of the drive train for typical excitations is calculated, and the results according to specified geometric parameters of the gears are analysed in detail to investigate effective solutions for vibration reduction. The results indicate that the helix angle and numbers of teeth of a gear pair are the most significant factors for solving the problem. The effectiveness of the proposed solutions and relevant mechanisms are discussed and validated by a prototype vibration test.

Background/Aims: GATA4, a protein related to osteoblast differentiation and mineralization, whose acetylation is essential for cardiac defects. Here, we aimed to explore the functional impacts of GATA4 acetylation on osteoporosis (OS). Methods: GATA4 acetylation in hFOB1.19 and 293T cells was detected after exposure of HDAC inhibitors (TSA and SAHA). Co-immunoprecipitation was conducted to determine which HATs and HDACs was involved in the modulation of GATA4 acetylation/deacetylation, and to identify the acetylation site. The transcriptional activity of GATA4 was measured in the presence or absence of cycloheximide. Furthermore, hFOB1.19 cells viability and apoptosis were evaluated after transfection with acetylation-defective mutant of GATA4. Results: As a result, GATA4 acetylation was identified as a pivotal event in hFOB1.19 cells. GATA4 can be acetylated by P300/CBP, and the acetylation site was on lysine residue K313. Besides, the acetylation of GATA4 can be impaired by HDAC1, rather than by HDAC2-5. GATA4 acetylation contributed to the stability and transcription of GATA4. Moreover, GATA4 acetylation activated CCND2 transcription, and mutation of GATA4 on K-313 reduced cell viability and increased a mitochondria-dependent apoptosis in hFOB1.19 cells. Conclusion: Our data suggest that GATA4 exists as an acetylated protein in hFOB1.19 cells. Acetylation regulates the stability and transcription of GATA4, and activates CCND2 transcription, which may explain the growth-promoting functions of GATA4 in hFOB1.19 cells.