Search

Rhodiola crenulate is the edible medicinal herbal medicine widely used for altitude sickness in China. Interestingly, our previous work has found that R. crenulate extract (RCE) could significantly improve the pathology associated with dextran sulfate sodium-induced colitis. Thus, the current research aims to reveal the pharmacodynamic material basis of RCE, as well as its mechanism against colitis. The chemical characterization of RCE was performed by UHPLC-HR-MS, through which a total of 88 constituents were identified. Meanwhile, our results also found 29 constituents absorbed into blood and 8 metabolized absorbable compounds. The decreased flavonoids prototype and the elevated sulfated products of phenols were observed under pathophysiological conditions of colitis. The metabolomics study revealed that colitis caused the alternation of fatty acid metabolism, steroid hormone biosynthesis and bile acid metabolism. Correspondingly, RCE could prevent colitis by improving fatty acid metabolism and secondary bile acid metabolism.

Abstract Recently, higher-order topological insulators (HOTIs) have been introduced, and were shown to host topological corner states under the theoretical framework of Benalcazar-Bernevig-Hughes. Here we unveil some topological effects in HOTIs by studying the three-dimensional (3D) non-Abelian Bloch oscillations (BOs). In HOTIs, BOs with a multiplied period occur when a force with a special direction is applied due to the effect of the non-Abelian Berry curvature. Along the direction of the oscillations we find a higher-order topological state that goes beyond the theoretical framework of multipole moments. The emergence of such a higher-order topological state coincides with the appearance of the 3D non-Abelian BOs. That is, the 3D non-Abelian BOs can be used as a tool to probe higher-order topological states. These phenomena are observed experimentally with designed electric circuit networks. Our work opens up a way to detect topological phases theoretically and experimentally.

Sinopodophyllum hexandrum (Royle) Ying, an endangered perennial medicinal herb, exhibits morpho-physiological dormancy in its seeds, requiring cold stratification for germination. However, the precise molecular mechanisms underlying this transition from dormancy to germination remain unclear. This study integrates transcriptome and plant hormone-targeted metabolomics techniques to unravel these intricate molecular regulatory mechanisms during cold stratification in S. hexandrum seeds. Significant alterations in the physicochemical properties (starch, soluble sugars, soluble proteins) and enzyme activities (PK, SDH, G-6-PDH) within the seeds occur during stratification. To characterize and monitor the formation and transformation of plant hormones throughout this process, extracts from S. hexandrum seeds at five stratification stages of 0 days (S0), 30 days (S1), 60 days (S2), 90 days (S3), and 120 days (S4) were analyzed using UPLC-MS/MS, revealing a total of 37 differential metabolites belonging to seven major classes of plant hormones. To investigate the biosynthetic and conversion processes of plant hormones related to seed dormancy and germination, the transcriptome of S. hexandrum seeds was monitored via RNA-seq, revealing 65,372 differentially expressed genes associated with plant hormone synthesis and signaling. Notably, cytokinins (CKs) and gibberellins (GAs) exhibited synergistic effects, while abscisic acid (ABA) displayed antagonistic effects. Furthermore, key hub genes were identified through integrated network analysis. In this rigorous scientific study, we systematically elucidate the intricate dynamic molecular regulatory mechanisms that govern the transition from dormancy to germination in S. hexandrum seeds during stratification. By meticulously examining these mechanisms, we establish a solid foundation of knowledge that serves as a scientific basis for facilitating large-scale breeding programs and advancing the artificial cultivation of this highly valued medicinal plant.

Abstract Small extracellular–vesicule-associated microRNA (sEV-miRNA) is an important biomarker for cancer diagnosis. However, rapid and sensitive detection of low-abundance sEV-miRNA in clinical samples is challenging. Herein, a simple electrochemical biosensor that uses a DNA nanowire to localize catalytic hairpin assembly (CHA), also called domino-type localized catalytic hairpin assembly (DT-LCHA), has been proposed for sEV-miRNA1246 detection. The DT-LCHA offers triple amplification, (i). CHA system was localized in DNA nanowire, which shorten the distance between hairpin substrate, inducing the high collision efficiency of H1 and H2 and domino effect. Then, larger numbers of CHAs were triggered, capture probe bind DT-LCHA by exposed c sites. (ii) The DNA nanowire can load large number of electroactive substance RuHex as amplified electrochemical signal tags. (iii) multiple DT-LCHA was carried by the DNA nanowire, only one CHA was triggered, the DNA nanowire was trapped by the capture probe, which greatly improve the detection sensitivity, especially when the target concentration is extremely low. Owing to the triple signal amplification in this strategy, sEV-miRNA at a concentration of as low as 24.55 aM can be detected in 20 min with good specificity. The accuracy of the measurements was also confirmed using reverse transcription quantitative polymerase chain reaction. Furthermore, the platform showed good performance in discriminating healthy donors from patients with early gastric cancer (area under the curve [AUC]: 0.96) and was equally able to discriminate between benign gastric tumors and early cancers (AUC: 0.77). Thus, the platform has substantial potential in biosensing and clinical diagnosis. Graphical Abstract

ObjectiveThe objective of this study was to investigate the effectiveness of a machine learning algorithm in diagnosing OSA in children based on clinical features that can be obtained in nonnocturnal and nonmedical environments.Patients and methodsThis study was conducted at Beijing Children's Hospital from April 2018 to October 2019. The participants in this study were 2464 children aged 3–18 suspected of having OSA who underwent clinical data collection and polysomnography(PSG). Participants’ data were randomly divided into a training set and a testing set at a ratio of 8:2. The elastic net algorithm was used for feature selection to simplify the model. Stratified 10-fold cross-validation was repeated five times to ensure the robustness of the results.ResultsFeature selection using Elastic Net resulted in 47 features for AHI ≥5 and 31 features for AHI ≥10 being retained. The machine learning model using these selected features achieved an average AUC of 0.73 for AHI ≥5 and 0.78 for AHI ≥10 when tested externally, outperforming models based on PSG questionnaire features. Linear Discriminant Analysis using the selected features identified OSA with a sensitivity of 44% and specificity of 90%, providing a feasible clinical alternative to PSG for stratifying OSA severity.ConclusionsThis study shows that a machine learning model based on children's clinical features effectively identifies OSA in children. Establishing a machine learning screening model based on the clinical features of the target population may be a feasible clinical alternative to nocturnal OSA sleep diagnosis.

ABSTRACTObjective To explore the clinical outcomes and characteristics of TP53-mutated primary myelodysplastic syndromes (MDS).Methods A total of 74 de novo primary MDS patients who were diagnosed and treated in the Department of Hematology of our hospital from January 2018 and September 2021 were analyzed retrospectively. All patients had evaluable blood cell counts, mean corpuscular volume (MCV), lactate dehydrogenase (LDH), bone marrow (BM) morphology, biopsy, and MDS-related 20-gene mutations sequencing. In addition, 69 of 74 patients had complete cytogenetic analysis through conventional chromosome analysis and fluorescence in-situ hybridization.Results Patients were divided into two cohorts, the TP53-mutated type (TP53Mut) group (n = 19) and TP53 wild type (TP53WT) group (n = 55). Compared with the TP53WT group, patients in the TP53Mut group had higher ratios of cytogenetic abnormalities (82.4% vs. 30.8%, P

AbstractPurpose To explore the transformational leadership competency of graduates from one medical university in China and its influencing variables.Method From 2020 to 2021, 851 medical graduates from seven hospitals affiliated with the Capital Medical University participated in this survey. The authors conducted a cross-sectional study to assess transformational leadership competency, particularly from three aspects, including values, Emotional Intelligence (EI) abilities, and behaviors using the socially responsible leadership scale (SRLS), emotionally intelligent leadership, and student leadership practices inventory (EILI and SLPI).Results The SRLS scores were medium except for ‘controversy with civility’. The EILI scores were medium. The SLPI scores were high except for ‘enable others to act’ and ‘encourage the heart’. The influencing variables of SRLS, EILI, and SLPI were serving as student cadres, serving longer than two semesters (p = 0.01, 0.02 in EILI and SLPI), joining student organizations, participating in social practice, voluntary service (p = 0.001 in SLPI), in training classes for student cadres (p = 0.02, 0.01, 0.02 in SRLS, EILI, and SLPI), and attending lectures on leadership (except for indicated, p

Abstract The profiling of small extracellular vesicle-associated microRNAs (sEV-miRNAs) plays a vital role in cancer diagnosis and monitoring. However, detecting sEV-miRNAs with low expression in clinical samples remains challenging. Herein, we propose a novel electrochemical biosensor using localized DNA tetrahedron-assisted catalytic hairpin assembly (LDT-CHA) for sEV-miRNA determination. The LDT-CHA contained localized DNA tetrahedrons with CHA substrates, leveraging an efficient localized reaction to enable sensitive and rapid sEV-miRNA measurement. Based on the LDT-CHA, the proposed platform can quantitatively detect sEV-miRNA down to 25 aM in 30 min with outstanding specificity. For accurate diagnosis of gastric cancer patients, a combination of LDT-CHA and a panel of four sEV-miRNAs (sEV-miR-1246, sEV-miR-21, sEV-miR-183-5P, and sEV-miR-142-5P) was employed in a gastric cancer cohort. Compared with diagnosis with single sEV-miRNA, the proposed platform demonstrated a higher accuracy of 88.3% for early gastric tumor diagnoses with higher efficiency (AUC: 0.883) and great potential for treatment monitoring. Thus, this study provides a promising method for the bioanalysis and determination of the clinical applications of LDT-CHA. Graphical Abstract

Abstract Objective : Acute ischemic stroke (AIS) stands as a leading cause of death and disability globally. This study aimed to investigate the risk factors linked with AIS in patients undergoing maintenance hemodialysis (MHD) and to create and validate nomogram models. Methods: We examined the medical records of 314 patients with stage 5 chronic kidney disease (CKD5) undergoing MHD, who sought neurology outpatient department consultation for suspected AIS symptoms between January 2018 and December 2023. These 314 patients were randomly divided into the training cohort (n=222) and validation cohort (n=92). The Least Absolute Shrinkage Selection Operator (LASSO) regression model was employed for optimal feature selection in the AIS risk model. Subsequently, multivariable logistic regression analysis was used to construct a predictive model incorporating the features selected through LASSO. This predictive model's performance was assessed using the C-index and the area under the receiver operating characteristic curve (AUC). Additionally, calibration and clinical utility were evaluated through calibration plots and decision curve analysis (DCA). The model's internal validation was conducted using the validation cohort. Resaults: Predictors integrated into the prediction nomogram encompassed cardiovascular disease (CVD) (Odds Ratio [OR] 7.95, 95% confidence interval [CI] 2.400-29.979), smoking (OR 5.7, 95% CI 1.661-21.955), dialysis time (OR 5.91, 95% CI 5.866-29.979), low-density lipoprotein (LDL) (OR 2.99, 95% CI 0.751-13.007), and fibrin degradation products (FDP) (OR 5.47, 95% CI 1.563-23.162). The model exhibited robust discrimination, with a C-index of 0.877 and 0.915 in the internal training and validation cohorts, respectively. The AUC for the training set was 0.857, and a similar AUC of 0.905 was achieved in the validation cohort. Decision curve analysis (DCA) demonstrated a positive net benefit within a threshold risk range of 2 to 96%. Conclusion: The proposed nomogram effectively identifies MHD patients at high risk of AIS at an early stage. This model holds the potential to aid clinicians in making preventive recommendations.

qRT-PCR is a common and key technical means to study gene expression in biological research. However, reliability and accuracy of quantification by qRT-PCR is entirely dependent on the identification of appropriate reference genes. Cucumber as an economical vegetable is widely cultivated worldwide and is subject to serious nematode infection, especially from M. incognita. Plant could employ beneficial soil bacteria in the rhizosphere to enhance plant adaptability to various stresses. In this study, the optimal reference genes in cucumber under M. incognita stress and Pseudomonas treatment were calculated and confirmed. A total of thirteen candidate reference genes were identified across three different treatments. Of these, geNorm, NormFinder and BestKeeper programs combined RefFinder software identified EF1 and UBI are the most suitable reference gene in the root knot and whole root of cucumber infected M. incognita, respectively, and CACS is the most suitable reference gene in the whole root of cucumber treated by Pseudomonas. The work first validated the most suitable reference genes for the normalization gene expression in cucumber by nematode infected or Pseudomonas inoculated, and these results would facilitate the further research on M. incognita or Pseudomonas soil rhizosphere microbe interaction with cucumber.

ABSTRACT Obstructive sleep apnea (OSA) is a common sleep‐disordered breathing disease that often leads to many comorbidities (e.g., cognitive dysfunction), which adversely affect the quality of life for patients with OSA. Thus far, the underlying mechanisms of this dysfunction remain unclear. Many studies have focused on OSA‐related characteristics, including intermittent hypoxemia and sleep fragmentation. There is increasing emphasis on neuroimaging studies to explore underlying relationships between neuropathological changes and cognitive dysfunction. This article reviews recent research progress concerning cognitive dysfunction associated with OSA to reveal potential mechanisms that contribute to this dysfunction.

Introduction: Excessive inflammation and the pyroptosis of vascular endothelial cells caused by estrogen deficiency is one cause of atherosclerosis in post-menopausal women. The autophagy is highly regulated by estrogen, however whether estrogen can reduce vascular endothelial cell pyroptosis through estrogen receptor-mediated activation of autophagy to improve atherosclerosis in post-menopausal stage is still unknown. Objectives: To explore whether estrogen can prevent atherosclerosis by regulating estrogen receptor and subsequently activating autophagy to reduce inflammation and pyroptosis. Methods: Aortic samples from pro-menopausal and post-menopausal women with ascending aortic arteriosclerosis were analyzed, and bilateral ovariectomized (OVX) female ApoE-/- mice and homocysteine (Hcy)-treated HUVECs were used to analyze the effect of estrogen supplementation therapy. Results: The aortic endothelium showed a decrease in ERα expression and autophagy, but presented an increase in inflammation and pyroptosis in female post-menopausal patients. Estrogen treatment accelerated autophagy and ameliorated cell pyroptosis in the cardiac aortas of OVX ApoE-/- mice and Hcy-treated HUVECs. Estrogen had therapeutic effect on atherosclerosis and improved the symptoms associated with lipid metabolism disorders in OVX ApoE-/- mice. Inhibition and silencing of ERα led to a reduction in the autophagy promoting ability of estrogen and aggravated pyroptosis. Moreover, the inhibition of autophagy promoted pyroptosis and abolished the protective effect of estrogen, but had no influence on ERα expression. Conclusion: The results of the present study demonstrated that post-menopausal women present decreased autophagy and ERα expression and excessive damage to the ascending aorta. In addition, in vitro and in vivo assay results demonstrated that estrogen prevents atherosclerosis by upregulating ERα expression and subsequently induces autophagy to reduce inflammation and pyroptosis.

Abstract Diabetic kidney disease (DKD) is closely associated with the high risk of cardiovascular disease and mortality. Exosomal circRNAs can exert significant roles in the pathology of various diseases. Nevertheless, the role of exosomal circRNAs in DKD progression remains barely known. Circular RNA DLGAP4 has been reported to be in involved in acute ischemic stroke. In our study, we found exosomal circ_DLGAP4 was increased in the exosomes isolated from HG-treated mesangial cells (MCs), DKD patients, and DKD rat models compared with the corresponding normal subjects. Then, we observed that exo-circ_DLGAP4 significantly promoted proliferation and fibrosis of MCs cells. Moreover, to study the underlying mechanism of circ_DLGAP4 in regulating DKD, bioinformatics method was consulted and miR-143 was predicted as its target. The direct correlation between miR-143 and circ_DLGAP4 was validated in MCs. MCs proliferation and fibrosis were increased by circ_DLGAP4, which could be decreased by mimic-miR-143. Next, elevated expression of Erb-b2 receptor tyrosine kinase 3 (ERBB3) is involved in various diseases. However, the function of ERBB3 in DKD development remains poorly known. Next, ERBB3 was predicted as the downstream target for miR-143. It was displayed that circ_DLGAP4 promoted proliferation and fibrosis of MCs by sponging miR-143 and regulating ERBB3/NF-κB/MMP-2 axis. Meanwhile, the loss of exo-circ_DLGAP4 induced miR-143 and repressed ERBB3/NF-κB/MMP-2 expression in MCs. Subsequently, in vivo assays were performed and it was proved that overexpression of circ_DLGAP4 markedly promoted DKD progression in vivo via modulating miR-143/ERBB3/NF-κB/MMP-2. In conclusion, we indicated that exosomal circ_DLGAP4 could prove a novel insight for DKD development.

The netrin receptor UNC-40/DCC is required to recruit GABAAR at neuromuscular junctions in C. elegans. Here, the authors show that UNC-40/DCC assembles an intracellular synaptic scaffold, regulating the content of GABAAR and inhibitory neurotransmission.

The existing urban distribution model does not consider both the environmental influence and time-varying factors. This paper studies the urban distribution optimization model considering both time-varying network factors and carbon emission factors and constructs the single period time-varying network urban distribution optimization model and cross-period time-varying network urban distribution optimization model. In this paper, the time-varying network in urban distribution is mathematically described and calculated. By considering the carbon penalty rate, the distribution optimization model is analyzed to formulate the optimal urban distribution scheme for enterprises. An improved variable neighborhood search (VNS) heuristic algorithm is designed to solve the model. The numerical example demonstrates that the higher the carbon emission cost, the greater the carbon penalty rate. When the carbon emission cost increases by 50%, the total cost of the distribution scheme considering carbon emission is saved by 1.21%. The numerical analysis also finds that only when the unit carbon emission cost is higher than 2.937, the carbon penalty rate will stimulate enterprises to reduce emissions.

Fluvial landscapes are a result of lithospheric tectonic movement, climate evolution and surface processes. Existing evidence proves that regional tectonic deformation can be reflected by the evolution of fluvial landforms. The southern Alashan Block lies the closest to the northeastern Tibetan Plateau and has become the latest plateau outward expansion boundary. Yabrai Shan is located at the intersection of the Tibetan Plateau, Alashan and Ordos Blocks, thereby recording the evolution of the surface processes and tectonic activities in the northeastern Tibetan Plateau and its surrounding regions. Herein, we conducted the quantitative landform analysis and field investigations of Yabrai Shan, and the spatiotemporal distribution of geomorphological parameters indicated that Yabrai Shan is in the mature stage of geomorphological evolution controlled by tectonic activities of the Yabrai range-front fault. Based on the paleochannel reconstruction model and previous research on fault activity, two tectonic acceleration events were identified, with estimated geomorphic response times of 0.15–1.10 Ma and 1.42–2.92 Ma. Different distribution characteristics of two-phase knickpoints are caused by the change of tectonic stress in this region, revealing that the late knickpoints are the result of tectonic acceleration under the influence of the northeast expansion of the Tibetan Plateau. The transformation of Yabrai Shan from the original extensional environment affected by the Ordos Block to the compressional environment affected by the northeast expansion of the Tibetan Plateau occurred after 1.10 Ma.

Childhood obstructive sleep apnea (OSA) is a common chronic sleep-related breathing disorder in children, which leads to growth retardation, neurocognitive impairments, and serious complications. Considering the previous studies about brain structural abnormalities in OSA, in the present study, we aimed to explore the altered spontaneous brain activity among OSA patients, using amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) methods based on resting-state functional magnetic resonance imaging (MRI). Thirty-one untreated OSA children and 33 age-and gender-matched healthy children (HC) were included in this study. Compared with controls, the OSA group showed significant lower ALFF in the right lingual gyrus, decreased fALFF in the left middle frontal gyrus (MFG), but increased fALFF in the left precuneus. Decreased ReHo was found in the left inferior frontal gyrus (orbital part) and left middle frontal gyrus. Notably, the mean fALFF value of left MFG was not only significantly related to multiple sleep parameters but also demonstrated the best performance in ROC curve analysis. These findings revealed OSA children were associated with dysfunctions in the default mode network, the frontal lobe, and the lingual gyrus, which may implicate the underlying neurophysiological mechanisms of intrinsic brain activity. The correlation between the altered spontaneous neuronal activity and the clinical index provides early useful diagnostic biomarkers for OSA children as well.

Atherosclerosis (AS) is exacerbated in the perimenopausal period, which significantly increases the incidence rate of cardiovascular disease. The disruption of the gut microbiota has been associated with AS or menopause, but the specific changes of AS-associated gut microbiota in the perimenopausal period remain largely unknown. As lipid abnormalities are mainly responsible for AS, the relationship between lipid metabolism abnormalities and gut microbiota disruptions during menopause is rarely reported hitherto. In the present study, ApoE−/- mice fed with a high-fat diet (HFD) were subjected to ovariectomy and supplemented with estrogen. The ovariectomized HFD-fed ApoE−/- mice underwent significant AS damage, hepatic lipid damage, hyperlipidemia, and changes of lipid metabolism- and transport-related enzymes. There was significantly higher abundance of some lipid metabolites in the plasma of ovariectomized HFD-fed ApoE−/- mice than in non-ovariectomized ones, including cholesterol esters, triglycerides, phospholipids, and other types of lipids (free fatty acids, acylcarnitine, sphingomyelins, and ceramides). The administration of estrogen significantly reduced the contents of most lipid metabolites. The diversity and composition of gut microbiota evidently changed in ovariectomized HFD-fed ApoE−/- mice, compared to HFD-fed ApoE−/- mice without ovariectomy. In contrast, with estrogen supplementation, the diversity and composition of gut microbiota were restored to approach that of non-ovariectomized HFD-fed ApoE−/- mice, and the relative abundances of some bacteria were even like those of C57BL/6 mice fed with a normal diet. On the other hand, the transplantation of feces from C57BL/6 mice fed with normal diet to ovariectomized HFD-fed ApoE−/- mice was sufficient to correct the hyperlipidemia and AS damage, and to reverse the characteristics changing of lipid metabolomics in ovariectomized HFD-fed ApoE−/- mice. These phenomena were also been observed after transplantation of feces from estrogen-treated ovariectomized HFD-fed ApoE−/- mice to ovariectomized HFD-fed ApoE−/- mice. Moreover, the gut microbiota and lipid metabolites were significantly correlated, demonstrating that the changes of serum lipids may be associated with the gut microbiota disruptions in the perimenopausal period. In conclusion, the gut microbiota during the progression of AS in the perimenopausal period showed specific compositional changes and significant correlations with circulating lipid metabolites. Estrogen supplementation may exert beneficial effects on gut bacteria and lipid metabolism.

BRASSINOSTEROID INSENSITIVE1-EMS-suppressor 1 (BES1) is an essential regulator downstream of brassinosteroid signaling and plays important roles in plant stress response, growth, and development. To date, the regulation mechanisms of BES1 transcription factors have been identified and elucidated in model plants Arabidopsis and rice. However, little information is available regarding the BES1 family in Cucumis sativus. Therefore, this study conducted a genome-wide analysis of BES1 genes in cucumber. In cucumber, a total of six CsBES1 genes were identified, and their phylogenetic relationships, gene structures, and cis-elements in promoters were studied. CsBES1 genes were distributed on four of seven chromosomes. Gene structure analysis showed that the intron–exon model of CsBES1 genes was conserved and the CsBES1 protein contained a DUF822-conserved motif. Promoter cis-element prediction showed that plenty of developmental and stress- and hormone-related elements have been found in promoter regions of CsBES1 genes. Meanwhile, BES1 was divided into three groups (I, II, and III) on the basis of phylogenetic relationship analysis in six plant species. In addition, CsBES1 gene expression patterns were confirmed by transcription database and qRT-PCR analysis; the results showed that the expression of CsBES1 genes had not only tissue-specific expression but also different types of CsBES1 isoform which might respond to specific plant stresses. In summary, genome-wide identification, phylogeny, gene structure, and expression profile analysis of CsBES1 genes in cucumber provided a referable theoretical information for further functional study of CsBES1 genes and further facilitated the molecular breeding of cucumber.

Synaptic positions underlie precise circuit connectivity. Synaptic positions can be established during embryogenesis and sustained during growth. The mechanisms that sustain synaptic specificity during allometric growth are largely unknown. We performed forward genetic screens in C. elegans for regulators of this process and identified mig-17, a conserved ADAMTS metalloprotease. Proteomic mass spectrometry, cell biological and genetic studies demonstrate that MIG-17 is secreted from cells like muscles to regulate basement membrane proteins. In the nematode brain, the basement membrane does not directly contact synapses. Instead, muscle-derived basement membrane coats one side of the glia, while glia contact synapses on their other side. MIG-17 modifies the muscle-derived basement membrane to modulate epidermal-glial crosstalk and sustain glia location and morphology during growth. Glia position in turn sustains the synaptic pattern established during embryogenesis. Our findings uncover a muscle-epidermis-glia signaling axis that sustains synaptic specificity during the organism’s allometric growth.

Co-worker safety support has been given prominence in manufacturing and transportation field for its positive effect on individual workers’ safety; however, there is little evidence to show if such supporting role of co-workers is significant in improving project-level safety performance in construction workplace. This study adopts agent-based modeling (ABM) to understand the effectiveness of two distinct co-worker-safety-support actions on the safety performance of a construction project. Based on the risk theory, the ABM model simulates a construction site where worker agents reinforce steel bars with the likelihood of suffering crane-related incidents. The results indicate that both co-worker-support actions can significantly reduce the occurrence of nonfatal incidents but shows little influence in fatal incidents, and in reducing high-severity incidents, the action of warning peers to leave the hazardous area has the same effectiveness as reminding peers to wear Personal Protective Equipment. The present study provides a fresh insight into the safety-related role of co-workers: not only reveals how the local-level effects of co-workers’ safety assistance emerge the system-level consequences, but demonstrates the effectiveness of specific peer-support actions on three levels of construction safety performance, and thereby extends our existing body of knowledge on co-worker safety support in the construction field.

Researchers have proposed that intergroup prejudice is partially caused by behavioral immune system mechanisms. Across four studies (total N = 1,849), we used both experimental (pathogen priming) and individual differences (pathogen disgust sensitivity [PDS]) approaches to test whether the behavioral immune system influences prejudice toward immigrants indiscriminately (the generalized out-group prejudice hypothesis) or specifically toward immigrants from a pathogen-rich ecology (the origin-specific out-group prejudice hypothesis). Internal meta-analyses lend some support to both hypotheses. At the experimental level, pathogen primes had no effect on attitudes toward origin-unspecified immigrants or immigrants from a pathogen-rich ecology. At the individual differences level, PDS has a unique negative effect on comfort with immigrants from pathogen-rich ecologies but not on comfort with immigrants from unspecified ecologies. However, pathogen disgust sensitivity was negatively related to the decision to allow entry to both origin-unspecified immigrants and immigrants from a pathogen-rich ecology.

Data is considered to be the most valuable asset of various organizations,and the research on data asset has been valued by various countries,industries and organizations.From the perspective of standardization,the theoretical research and practice of data assets of relevant organizations at home and abroad was introduced,as well as the progress of standardization research on data assets.The standardization idea of data assets and the basic requirements of data assets management were put forward,which provided reference for the management and application of data assets.

Recently, microRNAs have been recognized as crucial regulators of diabetic nephropathy (DN) development. Epithelial-to-mesenchymal transition (EMT) can play a significant role in tubulointerstitial fibrosis, and it is a hallmark of diabetic nephropathy progression. Nevertheless, the function of miR-98-5p in the modulation of EMT and renal fibrosis during DN remains barely investigated. Hence, identifying the mechanisms of miR-98-5p in regulating EMT and fibrosis is of huge significance. In our present research, decreased miR-98-5p was demonstrated in db/db mice and mice mesangial cells treated with the high dose of glucose. Meanwhile, activated EMT and increased fibrosis was accompanied with the decrease of miR-98-5p in vitro and in vivo. Additionally, to further find out the roles of miR-98-5p in DN development, overexpression of miR-98-5p was applied. Firstly, in vivo investigation exhibited that elevation of miR-98-5p restrained proteinuria, serum creatinine, BUN, the EMT process, and fibrosis. Furthermore, high glucose was able to promote mice mesangial cell proliferation, EMT process, and induced renal fibrosis, which could be prevented by overexpression of miR-98-5p. Moreover, high mobility group A (HMGA2) can exhibit an important role in diverse biological processes. Here, HMGA2 was investigated as a target of miR-98-5p currently. Luciferase reporter assay was conducted and the correlation of miR-98-5p and HMGA2 was validated. Moreover, it was displayed that HMGA2 was remarkably elevated in db/db mice and mice mesangial cells. Furthermore, miR-98-5p strongly depressed HMGA2 protein and mRNA levels in mice mesangial cells. Overall, these revealed miR-98-5p could suppress the EMT process and renal fibrosis through targeting HMGA2 in DN.

The soil-rock mixture is a cohesive-frictional geomaterial subjected to impacts of composition and structure seriously. When it suffers from gravity or other kinds of loadings, the loss of its bearing capacity always appears a progressive failure. In this study, the ultimate criterion of the frictional material changing from the deformation stage to the failure stage is analyzed first and then the deformation and failure characteristics of the soil-rock mixture with different compositions and structures are discussed by the discrete element method. The results indicate that the deformation and failure of the soil-rock mixture under axial pressure appear a significant phenomenon of detouring around rock blocks. The bond failure zones and the ultimate shear strain increase with the increase of rock block proportion. The distribution of the bond failure zones always has a good uniformity with the inclination of rock block inclinations. The increase of cementation degree between particles expands the distribution of the bond failure zones but minifies the ultimate shear strain.

Understanding the nature of rail transit dwell time has potential benefits for both the users and the operators. Crowded passenger trains cause longer dwell times and may prevent some passengers from boarding the first available train that arrives. Actual dwell time and the process of passenger alighting and boarding are interdependent through the sequence of train stops and propagated delays. A comprehensive and feasible dwell time simulation model was developed and optimized to address the problems associated with scheduled timetables. The paper introduces the factors that affect dwell time in urban rail transit systems, including train headway, the process and number of passengers alighting and boarding the train, and the inability of train doors to properly close the first time because of overcrowded vehicles. Finally, based on a time-driven micro-simulation system, Shanghai rail transit Line 8 is used as an example to quantify the feasibility of scheduled dwell times for different stations, directions of travel and time periods, and a proposed dwell time during peak hours in several crowded stations is presented according to the simulation results.

Abstract Chronic kidney disease (CKD) is a global health challenge associated with lifestyle factors such as diet, alcohol, BMI, smoking, sleep, and physical activity. Metabolomics, especially nuclear magnetic resonance(NMR), offers insights into metabolic profiles’ role in diseases, but more research is needed on its connection to CKD and lifestyle factors. Therefore, we utilized the latest metabolomics data from the UK Biobank to explore the relationship between plasma metabolites and lifestyle factors, as well as to investigate the associations between various factors, including lifestyle-related metabolites, and the latent phase of CKD onset. The study enrolled approximately 500,000 participants from the UK Biobank (UKB) between 2006 and 2010, excluding 447,163 individuals with missing data for any metabolite in the NMR metabolomics, any biomarker in the blood chemistry (including eGFR, albumin, or cystatin C), any factor required for constructing the lifestyle score, or a baseline diagnosis of CKD. Lifestyle scores (LS) were calculated based on several factors, including diet, alcohol consumption, smoking, BMI, physical activity, and sleep. Each healthy lifestyle component contributed to the overall score, which ranged from 0 to 6. A total of 249 biological metabolites covering multiple categories were determined by the NMR Metabolomics Platform. Random forest algorithms and LASSO regression were employed to identify lifestyle-related metabolites. Subsequently, accelerated failure time models(AFT) were used to assess the relationship between multiple factors, including traditional CKD-related biomarkers (such as eGFR, cystatin C, and albumin) and lifestyle-related metabolites, with the latent phase of incident CKD. Finally, we performed Kaplan–Meier survival curve analysis on the significant variables identified in the AFT model. Over a mean follow-up period of 13.86 years, 2,279 incident chronic kidney disease (CKD) cases were diagnosed. Among the 249 metabolites analyzed, 15 were identified as lifestyle-related, primarily lipid metabolites. Notably, among these metabolites, each 1 mmol/L increase in triglycerides in large LDL particles accelerated the onset of CKD by 24%. Diabetes, hypertension, and smoking were associated with a 56.6%, 31.5% and 22.3% faster onset of CKD, respectively. Additionally, each unit increase in age, BMI, TDI, and cystatin C was linked to a 3.2%, 1.4%, 1.6% and 32.3% faster onset of CKD. In contrast, higher levels of albumin and eGFR slowed the onset of CKD, reducing the speed of progression by 3.0% and 3.9% per unit increase, respectively. Nuclear magnetic resonance metabolomics offers new insights into renal health, though further validation studies are needed in the future.

Abstract Background Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies. Methods We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis. We integrated multi-dataset analyses, single-cell transcriptomic data, and functional experiments to explore the role of OSBPL3 in pancreatic cancer. Results Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. Notably, the “rf” algorithm model showed an AUC of 1 in the training set and AUCs of 0.887 and 0.977 in two validation datasets. Ridge regression analysis identified OSBPL3 as a core prognostic feature gene. High OSBPL3 expression in pancreatic cancer samples was associated with immunosuppressive characteristics, including reduced CD8 + T cell infiltration and increased immunosuppressive cell populations such as Treg cells and M2 macrophages. Transcriptomic sequencing following OSBPL3 knockdown revealed enrichment of immune-related pathways, suggesting OSBPL3’s influence on the immune microenvironment. Single-cell analyses further confirmed OSBPL3’s role in shaping the immunosuppressive landscape by modulating Treg cells and M2 macrophages. Additionally, OSBPL3 expression was linked to resistance to immunotherapy, with high OSBPL3 expression associated with lower Immunophenoscore (IPS) scores, indicating poor responsiveness to immunotherapy. Conclusions Our study reveals OSBPL3 as a critical regulator of the immunosuppressive microenvironment in pancreatic cancer and a potential therapeutic target. Targeting OSBPL3 may enhance the efficacy of immunotherapy and improve patient outcomes. Further research is warranted to explore OSBPL3 as a biomarker for predicting immunotherapy response and as a potential therapeutic target in combination with anti-PD1 therapy.

Abstract Uncoupling protein 1 (UCP1) is a crucial protein located in the mitochondrial inner membrane that mediates nonshivering thermogenesis. However, the molecular mechanisms by which enhancer–promoter chromatin interactions control Ucp1 transcriptional regulation in brown adipose tissue (BAT) are unclear. Here, we employed circularized chromosome conformation capture coupled with next-generation sequencing (4C-seq) to generate high-resolution chromatin interaction profiles of Ucp1 in interscapular brown adipose tissue (iBAT) and epididymal white adipose tissue (eWAT) and revealed marked changes in Ucp1 chromatin interaction between iBAT and eWAT. Next, we identified four iBAT-specific active enhancers of Ucp1, and three of them were activated by cold stimulation. Transcriptional repression of the Ucp1-En4 or Ucp1-En6 region significantly downregulated Ucp1 and impaired mitochondrial function in brown adipocytes. Furthermore, depletion of the cohesin subunit RAD21 decreased the interaction intensity between Ucp1-En4 and the Ucp1 promoter and downregulated Ucp1. EBF2 cooperated with the acetyltransferase CBP to regulate Ucp1-En4 activity and increase Ucp1 transcriptional activity. In vivo, lentivirus-mediated repression of Ucp1-En4 was injected into iBAT, resulting in impacted iBAT thermogenic capacity and impaired iBAT mitochondrial function under cold acclimation conditions. Studying the functional enhancers regulating Ucp1 expression in iBAT will provide important insights into the regulatory mechanisms of BAT activity.

In the field of autonomous driving, the accuracy and real-time requirements for 3D object detection technology continue to improve, which is directly related to the commercialization process and market popularity of autonomous vehicles. Despite the efficiency of pillar-based coding for onboard systems, it falls short in terms of accuracy and the reduction of incorrect positives. In this paper, we will examine how to solve the problem of high incorrect rate and low accuracy of existing methods. Firstly, a MAP coding module is introduced to optimize previous point cloud feature coding modules, allowing for the efficient extraction of fine-grained features from point cloud data. Then, we introduce an innovative sparse dual attention (SDA) to efficiently filter out irrelevant details in feature extraction, thereby improving the pertinence and efficiency of information extraction. Finally, to address the potential loss of information from single local feature extraction, a local and global fusion module (CTGC) is introduced. Our method has proactively demonstrated its efficiency and accuracy through rigorous experimentation across diverse datasets. Analysis of the results leads to the conclusion that our solutions provide accurate and robust detection results. Code will be available at https://github.com/lcy199905/MyOpenPCDet.git.