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Abstract Glioblastoma (GBM) is a highly aggressive, infiltrative malignancy that cannot be completely cured by current treatment modalities, and therefore requires more precise molecular subtype signatures to predict treatment response for personalized precision therapy. Expression subtypes of GBM samples from the Cancer Genome Atlas (TCGA) were identified using BayesNM and compared with existing molecular subtypes of GBM. Biological features of the subtypes were determined by single-sample gene set enrichment analysis. Genomic and proteomic data from GBM samples were combined and Genomic Identification of Significant Targets in Cancer analysis was used to screen genes with recurrent somatic copy-number alterations phenomenon. The immune environment among subtypes was compared by assessing the expression of immune molecules and the infiltration of immune cells. Molecular subtypes adapted to immunotherapy were identified based on Tumor Immune Dysfunction and Exclusion (TIDE) score. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was performed on the expression profiles of S2, S3 and S4 in TCGA-GBM and RPPA to determine the respective corresponding best predictive model. Four novel molecular subtypes were classified. Specifically, S1 exhibited a low proliferative profile; S2 exhibited the profile of high proliferation, IDH1 mutation, TP53 mutation and deletion; S3 was characterized by high immune scores, innate immunity and adaptive immune infiltration scores, with the lowest TIDE score and was most likely to benefit from immunotherapy; S4 was characterized by high proliferation, EGFR amplification, and high protein abundance, and was the most suitable subtype for bevacizumab. LASSO analysis constructed the best prediction model composed of 13 genes in S2 with an accuracy of 96.7%, and the prediction model consisting of 17 genes in S3 with an accuracy of 86.7%, and screened 14 genes as components of the best prediction model in S4 with an accuracy of 93%. To conclude, our study classified reproducible and robust molecular subtypes of GBM, and these findings might contribute to the identification of patients responding to immunotherapy, thereby improving GBM prognosis.

Abstract Patchouli alcohol (PA) is a widely used pharmaceutical ingredient in various Chinese traditional herbal medicine (THM) formulations, known for its modulatory effects on the gut microbiota. The present study investigated PA's anti-inflammatory and regulatory effects on gut microbiota and its mode of action (MOA). Based on the assessments of ulcerative colitis (UC) symptoms, PA exhibited promising preventions against inflammatory response. In accordance, the expressions of pro-inflammatory factors, including interleukin (IL)-1β, IL-6, tumor necrosis factor-α, and chemokine ligand 5 were significantly attenuated under PA treatment. Furthermore, PA enhanced the intestinal barrier damage caused by dextran sodium sulfate (DSS). Interestingly, PA exhibited negligible inventions on DSS-induced gut microbiota dysbiosis. PA did not affect the diversity of the DSS gut microbiota, it did alter the composition, as evidenced by a significant increase in the Firmicutes-Bacteroidetes (F/B) ratio. Finally, the MOA of PA against inflammation in DSS-treated mice was addressed by suppressing the expressions of heme oxygenase-1 (HO-1) and inducible nitric oxide synthase (iNOS). In conclusion, PA prevented inflammatory response in the DSS-induced UC mice model via directly suppressing HO-1 and iNOS-associated antioxidant signal pathways, independent of its effects on gut microbiota composition.

Abstract The triglyceride-glucose (TyG) index is a novel marker of insulin resistance that has been strongly associated with many diseases related to metabolic disorders, such as diabetes, coronary heart disease, myocardial infarction, obesity, nonalcoholic fatty liver disease, and stroke. However, whether the TyG index is associated with the prevalence of gallstones has not been determined. Therefore, the purpose of this study was to evaluate the relationship between the TyG index and the prevalence of gallstones in American adults, as well as the age at which adults in America undergo their first gallstone surgery. We selected individuals from the National Health and Nutrition Examination Survey (NHANES) database from 2017 to March 2020. Based on the goal of our study, comprehensive inclusion and exclusion criteria were created. A logistic regression analysis, dose–response curve, and subgroup analysis were computed to assess the relationship between the TyG index and gallstone prevalence and age at first surgery for gallstone. A total of 3905 participants aged > 20 years were included in our study, of whom 421 had a self-reported history of gallstones. A total of 1884 (48.2%) males and 2021 (51.8%) females were included. After confounders adjustment, it was found single-unit increases in the TyG index were linked with a 25.0% increase in gallstone prevalence (odds ratio [OR] = 1.25, 95% confidence interval [95%CI]: 1.04, 1.51). After conversion of the TyG index values from continuous to categorical variables with tertiles, a marked 48% increase in gallstone incidence was found in tertile 3 relative to tertile 1 (OR = 1.48, 95% CI: 1.09, 1.99). The dose–response curve results indicated positive associations between gallstone prevalence and the TyG index, while the latter was negatively associated with age at first gallstone surgery. Based on subgroup analysis, the positive association between TyG index and high-incidence of gallstones was more significant in females (OR = 1.39, 95% CI: 1.09, 1.77), age

Abstract China, is characterized by its remarkable ethnical diversity, which necessitates whole genome variation data from multiple populations as crucial tools for advancing population genetics and precision medical research. However, there has been a scarcity of research concentrating on the whole genome of ethnic minority groups. To fill this gap, we developed the Guizhou Multi-ethnic Genome Database (GMGD). It comprises whole genome sequencing data from 476 healthy unrelated individuals spanning 11 ethnic minorities groups in Guizhou Province, Southwest China, including Bouyei, Dong, Miao, Yi, Bai, Gelo, Zhuang, Tujia, Yao, Hui, and Sui. The GMGD database comprises more than 16.33 million variants in GRCh38 and 16.20 million variants in GRCh37. Among these, approximately 11.9% (1,956,322) of the variants in GRCh38 and 18.5% (3,009,431) of the variants in GRCh37 are entirely new and do not exist in the dbSNP database. These novel variants shed light on the genetic diversity landscape across these populations, providing valuable insights with an average coverage of 5.5 ×. This makes GMGD the largest genome-wide database encompassing the most diverse ethnic groups to date. The GMGD interactive interface facilitates researchers with multi-dimensional mutation search methods and displays population frequency differences among global populations. Furthermore, GMGD is equipped with a genotype-imputation function, enabling enhanced capabilities for low-depth genomic research or targeted region capture studies. GMGD offers unique insights into the genomic variation landscape of different ethnic groups, which are freely accessible at https://db.cngb.org/pop/gmgd/ .

Abstract Immunogenic cell death (ICD) is a newly discovered form of cellular demise that triggers adaptive immune responses mediated by T cells. However, the immunogenic cell death-related lncRNAs (ICDRLs) involved in bladder cancer (BC) development and progression remain to be further elucidated. Molecular profiling data and clinicopathological information for BC patients were obtained from TCGA, and the ICDRGs list was obtained from published literature. For the identification of ICDRLs, Pearson co-expression analysis was performed, and a prognostic signature based on 13 ICDRLs was constructed by univariate assays and LASSO assays. Herein, an ICDRLSig consisting of 13 ICDRLs was constructed. KM curves and ROC curves demonstrated that the constructed signature in the TCGA training, testing, entire and external sets have good predictive performance. Multivariate assays illuminated that the signature is an independent predictor for BC patients’ OS, exhibiting greater predictive power for the survival than traditional clinicopathological features. Additionally, patients in the high-ICDRLSig risk subgroup had more abundant immune infiltration, higher immune checkpoint gene expression, lower TMB and poorer response to immunotherapy. We have developed a novel ICDRLSig that can be exploited for survival prediction and provide a reference for further individualized treatment.

Abstract The rail profile milling process allows considerable thickness to be removed in a single pass. However, the residual waviness formation law after milling and its subsequent effect on rail performance remains uncertain. In this paper, the wavelength and wave height of the residual waviness are identified as the key characteristics. The relationship between milling speed and residual waviness is determined, and a numerical model of the residual waviness formed on the surface after milling is established based on the commonly used three milling speeds of 300, 600, and 1000 m/h, and its accuracy is verified using the parameters of the residual waviness detected by the milling experiments. A three-dimensional finite element analysis model of wheel-rail contact was employed to analyze the contact stresses and low fatigue cycles at a wheel load of 11.5 tons with no residual waviness on the rail profile surface and with three types of residual waviness, respectively. The results show that the residual waviness changes the wheel-rail contact position and the morphology of the contact area, reduces the maximum contact stress and increases the strain fatigue cycles. The application of elevated milling speeds reduces the wheel-rail contact stresses after milling, thereby increasing the low fatigue cycles.

Abstract Ardisia crispa(Myrsinaceae) is an ethnomedicine with horticultural and important medicinal values. Its morphology is complex, and its identification is difficult. We analyse the chloroplast genome characteristics and phylogenetic position of A. crispa to provide basic research data for the identification of A. crispa species and resource conservation. This study assemble and annotate the chloroplast genome of A. crispa and to compare it with the chloroplast genome within Ardisia. The A. crispa chloroplast genome is 156,785 bp in length, with a typical quadripartite structure containing 131 genes, including 86 protein-coding genes, 37 tRNA genes, and 8 rRNA genes; a total of 59 SSRs sites were identified, and the codon preference of this chloroplast genome is greater in A/U than in G/C, and leucine is the amino acid with the highest frequency of use. The chloroplast genomes of the nine Ardisia species are conserved in gene content and number, with more stable boundaries and less variation. In the phylogenetic tree, A. crispa is clustered on a branch with A. crispa var dielsii, and is closely related to A. mamillata and A. pedalis. In this study, we constructed and analyzed the chloroplast genome structure of A. crispa, and conducted phylogenetic analysis using the whole chloroplast genome sequence data of Ardisia plants, which is of great significance in understanding the genetic basis of A. crispa and adaptive evolution in Ardisia plants, and this will lay the foundation for the future research on A. crispa resource conservation and species identification.

Abstract Acute pancreatitis, a common exocrine inflammatory disease affecting the pancreas, is characterized by intense abdominal pain and multiple organ dysfunction. However, the alterations in retinal blood vessels among individuals with acute pancreatitis remain poorly understood. This study employed optical coherence tomography angiography (OCTA) to examine the superficial and deep retinal blood vessels in patients with pancreatitis. Sixteen patients diagnosed with pancreatitis (32 eyes) and 16 healthy controls (32 eyes) were recruited from the First Affiliated Hospital of Nanchang University for participation in the study. Various ophthalmic parameters, such as visual acuity, intraocular pressure, and OCTA image for retina consisting of the superficial retinal layer (SRL) and the deep retinal layer (DRL), were recorded for each eye. The study observed the superficial and deep retinal microvascular ring (MIR), macrovascular ring (MAR), and total microvessels (TMI) were observed. Changes in retinal vascular density in the macula through annular partitioning (C1–C6), hemispheric quadrant partitioning (SR, SL, IL, and IR), and early diabetic retinopathy treatment studies (ETDRS) partitioning methods (R, S, L, and I). Correlation analysis was employed to investigate the relationship between retinal capillary density and clinical indicators. Our study revealed that in the superficial retinal layer, the vascular density of TMI, MIR, MAR, SR, IR, S, C2, C3 regions were significantly decreased in patients group compared with the normal group. For the deep retinal layer, the vascular density of MIR, SR, S, C1, C2 regions also reduced in patient group. The ROC analysis demonstrated that OCTA possesses significant diagnostic performance for pancreatitis. In conclusion, patients with pancreatitis may have retinal microvascular dysfunction, and OCTA can be a valuable tool for detecting alterations in ocular microcirculation in pancreatitis patients in clinical practice.

Abstract Endoscopic submucosal dissection (ESD) of fibrotic colorectal lesions is difficult and has a high complication rate. There are only a few reports on the utility of orthodontic rubber band (ORB) traction in reducing the difficulty of this procedure. This study aimed to investigate the risk factors for perforation when applying ORB traction during ESD of fibrotic colorectal lesions. We continuously collected the clinical data of 119 patients with fibrotic colorectal lesions who underwent ESD with ORB and clip traction between January 2019 and January 2024. Possible risk factors for perforation were analyzed. The median ORB-ESD operative time was 40 (IQR 28–62) min, and the en bloc and R0 resection rates were 94.1% and 84.0%, respectively. Perforation occurred in 16 of 119 patients (13.4%). The lesion size, lesion at the right half of the colon or across an intestinal plica, the degree of fibrosis, operation time, and the surgeon’s experience were associated with perforation during ORB-ESD (P

Abstract Numerous observational studies have suggested a potential causal relationship between skipping breakfast and cardiovascular diseases, including heart failure (HF). However, these studies are susceptible to inherent confounders and the challenge of reverse causation, and the underlying metabolic factors are not yet clear. Therefore, our aim is to assess the causal impact of breakfast skipping on HF and the role of potential mediating metabolic products from a genetic perspective, by conducting Mendelian Randomization (MR) studies and mediation analysis. We leveraged summary data from the most extensive genome-wide association studies to date on breakfast skipping (with 193,860 participants), blood metabolites (with 118,461 participants), and HF (involving 47,309 cases and 930,014 controls). To explore the causal relationship between breakfast skipping and HF, as well as the role of 249 potential blood metabolite mediators, we conducted bidirectional MR and mediation MR analyses. We primarily employed the Inverse Variance Weighted (IVW) method, complemented by various other techniques to ensure the comprehensiveness and reliability of our analysis. Our research confirms a causal association between breakfast skipping and an increased risk of HF (odds ratio [OR]: 1.378, 95% confidence interval [CI]: 1.047–1.813; p = 0.022). Furthermore, our research findings demonstrate that breakfast skipping is positively correlated with 6 blood metabolites and negatively correlated with 2 others. Notably, our mediation MR analysis further reveals that three blood metabolites act as mediators in the relationship between breakfast skipping and the risk of HF. Specifically, the mediating effects are attributed to the ratio of docosahexaenoic acid (DHA) to total fatty acids (proportion mediated = 9.41%, 95% CI: 2.10–28.61%), glucose (proportion mediated = 6.17%, 95% CI: 0.97–28.53%), and glycoprotein acetyls (GlycA) (proportion mediated = 5.68%, 95% CI: 0.94–21.62%). The combined mediating effects of these three factors total 20.53% (95%CI: 8.59–91.06%). Our research confirms the causal relationship between genetically instrumented breakfast skipping and HF, underscoring the potential mediating roles played by three key blood metabolites: ratio of DHA to total fatty acids, glucose and GlycA. This discovery offers valuable perspectives for clinical strategies targeting HF.

Abstract To accurately measure the vaginal mucosa thickness across different age groups using histopathologic techniques and investigate the factors that may influence the thickness changes. This study aims to provide clinicians with objective evidence of variations in vaginal mucosal thickness, facilitating personalized medical decisions for patients. A retrospective analysis was conducted on clinical data from 348 patients who underwent local vaginal wall resection at the West China Second University Hospital, Sichuan University, from January 2021 and May 2022. The thickness of vaginal mucosa, epithelium and lamina propria was measured precisely under the microscope. And the 10th, 25th, 50th, 75th, and 90th percentile values of vaginal mucosa thickness across different age groups were counted and charted a dot-line plot. The percentile values for vaginal mucosa thickness exhibited a decreasing trend with increasing age; vaginal mucosa thickness showed significant correlations with times of delivery (P = 0.031) and age (P

Abstract Cisplatin is the most commonly used platinum-based treatment for nasopharyngeal carcinoma (NPC). However, its clinical application is limited owing to its nephrotoxicity and gastrointestinal reactions. Proton pump inhibitors (PPIs) have been reported to increase nephrotoxicity risk in previous studies. We aimed to evaluate whether PPIs increase cisplatin-induced nephrotoxicity in patients with NPC. In total, 295 patients were included in this prospective cohort study: 145 in the PPIs group and 150 in the non-PPIs group. All patients underwent cisplatin-based induction chemotherapy, followed by cisplatin-based concurrent chemoradiotherapy. The PPIs group received 40 mg of intravenous esomeprazole sodium for 7 days in each chemotherapy cycle. Chi-squared test and logistic regression analyses with odds ratios and 95% confidence intervals were applied to assess the association between PPIs and the risk of acute kidney injury (AKI). AKI incidence in the PPIs group was significantly higher than that in the non-PPIs group (P = 0.005). After adjusting for various confounders including demographic features, clinical features, and renal function indices, PPIs use was significantly associated with a higher AKI risk (odds ratio: 2.775; 95% confidence interval 1.280–6.020; P = 0.010). The incidences of acute and chronic kidney diseases were similar between both groups (P > 0.05), whereas the incidence of nausea was lower in the PPIs group than in the non-PPIs group (P = 0.029). This study has shown that PPIs use may increase the risk of cisplatin-induced acute nephrotoxicity in patients with NPC.

Abstract To investigate whether peritumoral edema (PE) could enhance deep learning radiomic (DLR) model in predicting axillary lymph node metastasis (ALNM) burden in breast cancer. Invasive breast cancer patients with preoperative MRI were retrospectively enrolled and categorized into low (

Abstract Abdominal adhesions manifests following abdominal infections triggered by intestinal fistulas. The severity of such adhesions depends on the extent of fiber deposition and peritoneal fibrinolysis following peritoneal injury, which may be influenced by sustained inflammation within the abdominal cavity. In this regard, the visceral-to-subcutaneous fat area (VFA/SFA) ratio has been implicated as a potential marker of inflammation. This study aimed to explore the relationship between VFA/SFA and abdominal adhesions. This multicenter study was conducted across four tertiary institutions and involved patients who had undergone definitive surgery (DS) for intestinal fistula from January 2009 and October 2023. The presence of abdominal adhesions was determined intraoperatively. VFA/SFA was investigated as a potential risk factor for severe adhesions. The study comprised 414 patients with a median age of 50 [interquartile range (IQR) 35–66] years and a median body mass index of 20.0 (IQR 19.2–22.4) kg/m2, including 231 males with a median VFA/SFA of 1.0 (IQR 0.7–1.2) and 183 females a median VFA/SFA of 0.8 (0.6–1.1). VFA/SFA was associated with severe abdominal adhesions in males [odds ratio (OR) = 3.34, 95% CI 1.14–9.80, p = 0.03] and females (OR = 2.99, 95% CI 1.05–8.53, p = 0.04). J-shaped association between VFA/SFA ratio and severe adhesions was revealed in both sex. The increasing trend can be revealed when OR more than 0.8, and 0.6 in males and females respectively. Preoperative VFA/SFA demonstrates predictive value for statues of severe abdominal adhesions in DS for anastomotic fistula after small intestine resection.

Abstract Hepatocellular carcinoma (HCC) still presents poor prognosis with low overall survival rates and limited therapeutic options available. Recently, attention has been drawn to peptidomic analysis, an emerging field of proteomics for the exploration of new potential peptide drugs for the treatment of various diseases. However, research on the potential function of HCC peptides is lacking. Here, we analyzed the peptide spectrum in HCC tissues using peptidomic techniques and explored the potentially beneficial peptides involved in HCC. Changes in peptide profiles in HCC were examined using liquid chromatography-mass spectrometry (LC–MS/MS). Analyze the physicochemical properties and function of differently expressed peptides using bioinformatics. The effect of candidate functional peptides on HCC cell growth and migration was evaluated using the CCK-8, colony formation, and transwell assays. Transcriptome sequencing analysis and western blot were employed to delve into the mode of action of potential peptide on HCC. Peptidomic analysis of HCC tissue yielded a total of 8683 peptides, of which 452 exhibited up-regulation and 362 showed down-regulation. The peptides that were differentially expressed, according to bioinformatic analysis, were closely linked to carbon metabolism and the mitochondrial inner membrane. The peptide functional validation identified a novel peptide, PDLC (peptide derived from liver cancer), which was found to dramatically boost HCC cell proliferation through the Ras/Raf/MEK/ERK signaling cascade. Our research defined the peptide’s properties and pattern of expression in HCC and identified a novel peptide, PDLC, with a function in encouraging HCC progression, offering an entirely new potential therapeutic target the disease.

Abstract This study spanned 6 years and 4 generations, involving the progressive crossbreeding of South African Kalahari Goat (SK) and Guizhou Black Goat (GB) over three generations, followed by cross fixation F3 with F1 in the fourth generation, accompanied by the use of molecular markers technology to select a high fertility population, resulting in the creation of a hybrid goat, BKF4 (11/16 SK lineage and 5/16 GB lineage). A comparative evaluation of the BKF4 hybrid breed and its parental breeds was conducted. Reproductive and production parameters of GB, SK, and BKF4 goat groups were monitored, including lambing rate (LR), survival rate (SR), daily weight gain at 3 months of age (DWG), and adult body weight (ABW) (n = 110, 106, 112 per group). In addition, dressing percentage (DP) (n = 12 per group) and analyses of amino acids (n = 8, 6, 10 per group) and fatty acids (n = 6 per group) were conducted to evaluate meat quality indicators. Results: (1) Reproductive and production performance: The index of LR reached 199%, significantly higher than GB and SK (p ≤ 0.001), with a SR of 95.0%, markedly higher than SK (p ≤ 0.001); DWG was 276.5 g, ABW reached 56.6 kg and with a dressing percentage (DP) of 54.5%, they are significantly surpassing GB (p ≤ 0.001). (2) Regarding meat quality: pH45-value and crude protein content (CP) increased, while intramuscular fat content increased compared to GB and ash content decreased. The amino acid composition was similar to GB, but the taste was more similar to SK. However, there were some negative impacts on fatty acid composition and functionality. (3) PCA analysis revealed that: BKF4 exhibited superior meat quality compared to GB and SK, influenced by two key factors contributing 83.49% and 16.51% to the explained variance, respectively. The key factors affecting meat quality include intramuscular fat (IMF), nutrient index (NI), PUFAs/MUFAs, n-6FAs, and drip loss (DL).

Abstract Semantic segmentation plays a crucial role in interpreting remote sensing images, especially in high-resolution scenarios where finer object details, complex spatial information and texture structures exist. To address the challenge of better extracting semantic information and ad-dressing class imbalance in multiclass segmentation, we propose utilizing diffusion models for remote sensing image semantic segmentation, along with a lightweight classification module based on a spatial-channel attention mechanism. Our approach incorporates unsupervised pretrained components with a classification module to accelerate model convergence. The diffusion model component, built on the UNet architecture, effectively captures multiscale features with rich contextual and edge information from images. The lightweight classification module, which leverages spatial-channel attention, focuses more efficiently on spatial-channel regions with significant feature information. We evaluated our approach using three publicly available datasets: Postdam, GID, and Five Billion Pixels. In the test of three datasets, our method achieved the best results. On the GID dataset, the overall accuracy was 96.99%, the mean IoU was 92.17%, and the mean F1 score was 95.83%. In the training phase, our model achieved good performance after only 30 training cycles. Compared with other models, our method reduces the number of parameters, improves the training speed, and has obvious performance advantages.

Abstract Accurate diagnosis of white blood cells from cytopathological images is a crucial step in evaluating leukaemia. In recent years, image classification methods based on fully convolutional networks have drawn extensive attention and achieved competitive performance in medical image classification. In this paper, we propose a white blood cell classification network called ResNeXt-CC for cytopathological images. First, we transform cytopathological images from the RGB color space to the HSV color space so as to precisely extract the texture features, color changes and other details of white blood cells. Second, since cell classification primarily relies on distinguishing local characteristics, we design a cross-layer deep-feature fusion module to enhance our ability to extract discriminative information. Third, the efficient attention mechanism based on the ECANet module is used to promote the feature extraction capability of cell details. Finally, we combine the modified softmax loss function and the central loss function to train the network, thereby effectively addressing the problem of class imbalance and improving the network performance. The experimental results on the C-NMC 2019 dataset show that our proposed method manifests obvious advantages over the existing classification methods, including ResNet-50, Inception-V3, Densenet121, VGG16, Cross ViT, Token-to-Token ViT, Deep ViT, and simple ViT about 5.5–20.43% accuracy, 3.6–23.56% F1-score, 3.5–25.71% AUROC and 8.1–36.98% specificity, respectively.

Abstract Polycystic ovary syndrome (PCOS), which is the most prevalent endocrine disorder among women in their reproductive years, is linked to a higher occurrence and severity of atherosclerosis (AS). Nevertheless, the precise manner in which PCOS impacts the cardiovascular well-being of women remains ambiguous. The Gene Expression Omnibus database provided four PCOS datasets and two AS datasets for this study. Through the examination of genes originating from differentially expressed (DEGs) and critical modules utilizing functional enrichment analyses, weighted gene co-expression network (WGCNA), and machine learning algorithm, the research attempted to discover potential diagnostic genes. Additionally, the study investigated immune infiltration and conducted gene set enrichment analysis (GSEA) to examine the potential mechanism of the simultaneous occurrence of PCOS and AS. Two verification datasets and cell experiments were performed to assess biomarkers' reliability. The PCOS group identified 53 genes and AS group identified 175 genes by intersecting DEGs and key modules of WGCNA. Then, 18 genes from two groups were analyzed by machine learning algorithm. Death Associated Protein Kinase 1 (DAPK1) was recognized as an essential gene. Immune infiltration and single-gene GSEA results suggest that DAPK1 is associated with T cell-mediated immune responses. The mRNA expression of DAPK1 was upregulated in ox-LDL stimulated RAW264.7 cells and in granulosa cells. Our research discovered the close association between AS and PCOS, and identified DAPK1 as a crucial diagnostic biomarker for AS in PCOS.

Abstract The Qinling water conveyance tunnel has a large buried depth and high in-situ stress level, and rockburst disasters frequently occurred during excavation. In order to find out the mechanical mechanism of rockburst, the research work in this paper is as follows: (1) In-situ three-dimensional hydraulic fracturing method was used to measure the in-situ stress of the deep buried tunnel crossing the ridge. (2) Based on the measured in-situ stress results, the stress distribution characteristics of the tunnel crossing the ridge were obtained by the multiple linear regression method, and the rockburst tendency during construction was predicted. (3) A three-dimensional numerical model of tunnel excavation was established to analyze the dynamic adjustment characteristics of the surrounding rock stress and elastic strain energy during TBM excavation, and to clarify the mechanical mechanism of rockburst. The research results show that the maximum principal stress of the deep-buried tunnel crossing the ridge of Qinling is 40–66 MPa, which belongs to extremely high in-situ stress level, and medium-strong rockburst may occur during excavation. In the process of TBM excavation, the stress of the surrounding rock in the range of 2.6 times the diameter of the tunnel before and after the working face is adjusted violently, and the concentrated zones after the stress redistribution are mainly distributed in the arch roof and arch bottom, and the stress concentration coefficient can reach 2.06. The arch roof, arch waist, and arch bottom are susceptible to immediate rockburst due to stress transient unloading at the moment of excavation. After the elastic strain energy of the surrounding rock at the arch roof and the arch bottom is released and accumulated, it is easy to cause time delayed rockburst, and the depth of the rockburst pit can reach 3.5 m, which is consistent with the rockburst phenomenon in the field.

Abstract Ultra-precision machining requires system modelling that both satisfies explainability and conforms to data fidelity. Existing modelling approaches, whether based on data-driven methods in present artificial intelligence (AI) or on first-principle knowledge, fall short of these qualities in high-demanding industrial applications. Therefore, this paper develops an explainable and generalizable ‘grey-box’ AI informatics method for real-world dynamic system modelling. Such a grey-box model serves as a multiscale ‘world model’ by integrating the first principles of the system in a white-box architecture with data-fitting black boxes for varying hyperparameters of the white box. The physical principles serve as an explainable global meta-structure of the real-world system driven by physical knowledge, while the black boxes enhance local fitting accuracy driven by training data. The grey-box model thus encapsulates implicit variables and relationships that a standalone white-box model or black-box model fails to capture. Case study on an industrial cleanroom high-precision temperature regulation system verifies that the grey-box method outperforms existing modelling methods and is suitable for varying operating conditions.

Abstract The cytokine interleukin-6 (IL-6) plays a crucial role in autoimmune and inflammatory diseases. Understanding the precise mechanism of IL-6 interaction at the amino acid level is essential to develop IL-6-inhibiting compounds. In this study, we employed computer-guided drug design tools to predict the key residues that are involved in the interaction between IL-6 and its receptor IL-6R. Subsequently, we generated IL-6 mutants and evaluated their binding affinity to IL-6R and the IL-6R − gp130 complex, as well as monitoring their biological activities. Our findings revealed that the R167A mutant exhibited increased affinity for IL-6R, leading to enhanced binding to IL-6R − gp130 complex and subsequently elevated intracellular phosphorylation of STAT3 in effector cells. On the other hand, although E171A reduced its affinity for IL-6R, it displayed stronger binding to the IL-6R − gp130 complex, thereby enhancing its biological activity. Furthermore, we identified the importance of R178 and R181 for the precise recognition of IL-6 by IL-6R. Mutants R181A/V failed to bind to IL-6R, while maintaining an affinity for the IL-6 − gp130 complex. Additionally, deletion of the D helix resulted in complete loss of IL-6 binding affinity for IL-6R. Overall, this study provides valuable insights into the binding mechanism of IL-6 and establishes a solid foundation for future design of novel IL-6 inhibitors.

Abstract Particle geometric is a key parameter that defines the eometric attributes of calcareous sand particles and is intricately related to their mechanical traits, such as compression and shear. The scanning electron microscopy and digital imaging were applied to capture the microscopic properties and geometric projections of calcareous sand. The qualitative analysis, conventional statistical methods and fractal theory were employed to describe the geometric morphology of sand particles. Additionally, we analyzed the structural and physical traits of calcareous sand based on its unique biological genesis. We developed a hypothetical structural-physical model for calcareous sand. Our findings revealed the interwoven reticulation on the surface of calcareous gravel particles, along with an uneven distribution of pores on the external surface. As the particle size increased, the global profile factor decreased and the angularity increased. The critical threshold for the variations in flatness, surface roughness, and circularity was observed at a particle size of 5 mm, with the particle size having a relatively minor effect on these characteristics for particles smaller than 5 mm. The shape of the calcareous sand particles exhibited fractal characteristics, with fractal dimension serving as a measure of surface smoothness, particle breakage, and strength. These experimental results could significantly enhance our understanding of the mechanical behavior of calcareous sand.

Abstract To gain insights into the spatial distribution of non-penetrating cracks during the rock fracture process, a comprehensive uniaxial compression test is conducted on cubic gypsum specimens (100 mm × 100 mm × 100 mm) containing two non-penetrating cracks. The two pre-formed cracks are rectangular, with dimensions of 25 mm length, 2 mm width, and depths of 80 mm and 35 mm on adjacent sides of the specimen. The depth of the 80 mm crack can be adjusted from 0° to 150° in increments of 30°, while the other is fixed at a 45° angle. The results show that the spatial distribution of non-penetrating cracks can significantly influence the strength of the specimen. Initially, the strength of the specimen exhibits an upward trend and subsequently declines as the pre-crack inclination angle of the main rupture plane increases, ultimately reaching its pinnacle at 90°. The total percentage of tensile cracks in specimens with different inclinations are found to be 57%, 57%, 63%, 77%, 68%, and 61%, respectively. This change aligns seamlessly with the fluctuation in specimen strength as influenced by the angle of inclination. Non-penetrating cracks can also induce spalling on the specimen surface and give rise to anti-wing cracks, thereby exacerbating the spalling on the specimen surface. The inclinations of non-penetrating cracks can inevitably exert a certain influence on the propagation of neighboring non-penetrating cracks. Additionally, the macro-scale shear fracture of the specimen often occurs on the side of the non-penetrating crack that is deeper. The curved tensile fracture surface formed by the extension of the non-penetrating crack bears resemblance to the non-penetrating region in its ability to somewhat restrain the propagation of new cracks. Even under uniaxial compression, the spalling surface of the specimen containing spatial non-penetrating cracks frequently exhibits fracture characteristics belonging to I-III mode fracture, while its interior may display characteristics belonging to I-II-III mode fracture. These findings hold significant implications for comprehending and elucidating the genuine fracture process and three-dimensional fracture theory of rocks.

Abstract Chemotherapy, particularly with oxaliplatin, is a key treatment for advanced gastric cancer (GC), and exosomes derived from human bone marrow mesenchymal stem cells (hBM-MSCs) play a vital role in the tumor microenvironment. The study aims to elucidate the previously unexplored role of exosomes derived from hBM-MSCs in GC tumorigenesis, especially under the influence of chemotherapy. We conducted an experimental study, utilizing miRNA sequencing and biological experiments, to analyze the tumorigenicity of exosomal miR-424-3p secreted by hBM-MSCs and its target gene RHOXF2 in GC cell lines. The results were confirmed through experimentation using a xenograft mouse model. This study demonstrated the role of hBM-MSCs in the GC microenvironment, focusing on their epithelial-mesenchymal transition (EMT) facilitation through exosomes, which led to enhanced tumorigenicity in GC cells. Intriguingly, this pro-tumor effect was abrogated when hBM-MSCs were treated with oxaliplatin. Exosomal miRNA sequencing revealed that oxaliplatin can upregulate the levels of miR-424-3p in exosomes secreted by hBM-MSCs, thereby inhibiting the EMT process in GC cells. Furthermore, miR-424-3p was identified to target and downregulate RHOXF2 expression, impeding the malignant behavior of GC cells both in vitro and in the mouse model. These findings uncover a potential hidden mechanism of oxaliplatin's anti-tumor action and propose the delivery of miR-424-3p via exosomes as a promising avenue for anti-tumor therapy.

Abstract Olfactory cues are considered a new sensory medium that can enhance learning, but the lack of empirical data has hampered their widespread use in educational practice. This requires empirical research to explore the effects of olfactory cues on learning. To address this research need, an experimental research study was conducted among 87 fourth graders from a Chinese elementary school. It explored the innovative design of adding olfactory cues to text materials by examining their effects on retention and schemata construction as learning outcomes, as well as their influence on learners’ cognitive load and learning experience. In this between-subjects design experiment, the experimental group (n = 44) learned text materials with the introduction of olfactory cues, while the control group (n = 43) only learned text materials. After the learning activity, participants were asked to complete the questionnaires, immediate test, and delayed test. The results revealed that the usage of olfactory cues synchronized with text materials can enhance delayed retention, facilitate schemata construction, and improve learner experience without increasing cognitive load. This study confirms the potential of well-designed olfactory cues in educational practice and provides insights for designing and presenting multimedia learning resources.

Abstract Cloud products from geostationary satellites are the main alternative to surface synoptic cloud observations (SYNOP), and have become the baseline products for the development and construction of the Quality Management System (QMS) of integrated meteorological observation in China. This study addresses the needs of the China Meteorological Administration (CMA) for such an operational reform, and it is carried out using real-time observations obtained from the Fengyun-2E (FY-2E) geostationary satellite in 2012 to derive cloud total amount and classification using two different methods. Compared to surface SYNOP observations, the cloud total amount estimated by FY-2E is generally significantly lower (about 30% lower on average). The cloud classification resulting from the two methods used in this study is also significantly different from the classification obtained from surface observations (difference between 22 and 32%). The difference is smaller for the classification method, which uses additional auxiliary temperature profiles.

Abstract Breast cancer remains a leading cause of cancer-related mortality among women, with triple-positive breast cancer (TPBC) being a particularly aggressive subtype. GATA binding protein 3 (GATA3) plays a crucial role in the luminal differentiation of breast epithelium and T-cell differentiation. However, the relationship between GATA3 and immune infiltration in TPBC remains unclear. This study collected and analyzed TPBC data from The Cancer Genome Atlas (TCGA), METABRIC, and GSE123845 databases. Univariate and multivariate Cox regression analyses, along with Kaplan–Meier survival analyses, were employed to assess the prognostic value of GATA3 and other clinical features. Subsequently, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and regulatory mechanisms of GATA3 in TPBC. Additionally, ssGSEA analysis revealed the connection between GATA3 and immune infiltration. And the effects of neoadjuvant chemotherapy and immunotherapy on GATA3 expression were also explored. Finally, clinical samples were used to detect the relationship between GATA3 expression and tumor infiltrating lymphocyte (TIL) levels. Our results demonstrated that GATA3 was significantly overexpressed in TPBC tissues compared to normal tissues (P

Abstract Lung cancer is intricately associated with genetic susceptibility, leading to familial clustering among affected individuals. This cross-sectional study aimed to assess the knowledge, attitude, and practice (KAP) toward lung cancer risk among the offspring of lung cancer patients. This study was conducted at Guangdong Provincial People’s Hospital between April 2023 and August 2023. Participants’ demographic characteristics and KAP toward lung cancer risk were collected through questionnaires. A total of 481 valid questionnaires were enrolled, with 243 (50.52%) males, and 242 (50.31%) aged > 40 years old. The mean scores for knowledge, attitude, and practice were 8.54 ± 2.60 (range: 0–13), 25.93 ± 3.16 (range: 7–35), and 17.47 ± 4.30 (range: 5–25), respectively. Structural equation modeling indicated that knowledge exerted a negative direct effect on attitude (β = − 0.417, P = 0.006) but a positive direct effect on practice (β = 0.733, P = 0.025). Additionally, attitudes displayed a negative direct effect on practice (β = − 1.707, P = 0.002). In conclusion, offspring of lung cancer patients exhibited insufficient knowledge, positive attitude, and suboptimal practice toward lung cancer risk.

Abstract Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission risk prediction models for elderly patients with HF, few have integrated ML-selected features with those chosen by human experts to assess HF patients readmission. A retrospective analysis of 8396 elderly HF patients hospitalized at the Affiliated Hospital of North Sichuan Medical College from January 1, 2018 to December 31, 2021 was conducted. Variables selected by XGBoost, LASSO regression, and random forest constituted the machine group, while the human expert group comprised variables chosen by two experienced cardiovascular professors. The variables selected by both groups were combined to form a human–machine collaboration group. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) method was used to elucidate the importance of each predictive feature, explain the impact of individual features on the model, and provide visual representation. A total of 73 features were included for model development. The human–machine collaboration model, utilizing CatBoost, achieved an AUC of 0.83617, an F1-score of 0.73521, and a Brier score of 0.16536 on the validation set. This model demonstrated superior predictive performance compared to those created solely by human experts or machine. The SHAP plot was then used to visually display the feature analysis of the human–machine collaboration model, revealing HGB, NT-proBNP, smoking history, NYHA classification, and LVEF as the 5 most important features. This study indicate that the human–machine collaboration model outperforms those relying solely on human expert selection or machine algorithm at predicting all-cause readmission in elderly HF patients. The application of the SHAP method enhanced the interpretability of the model outcomes, aiding clinicians in accurately pinpointing risk factors associated with HF readmission. This advancement enables the formulation of tailored treatment strategies, offering a more personalized approach to patient care.

Abstract Different delivery methods can cause variations in the composition and structure of intestinal microbiota in neonates. However, the impact of the microecological environment on host immune function requires further investigation. In this study, 75 healthy neonates were divided into two groups: vaginal delivery group (n = 36) and cesarean section group (n = 39). Fecal and peripheral blood samples were collected from the 7th to the 10th day. 16S rRNA sequencing technique was performed to investigate the gut microbiota on fecal samples. Levels of immunoglobulins and Th1 and Th2 cells in the peripheral blood of neonates were measured. The abundance of Escherichia, Bifidobacterium, and Bacteroides in neonates in the cesarean section group was significantly lower than that in the vaginal delivery group. Metabolic pathway analysis showed three significantly up-regulated metabolic pathways in the intestinal microbiota of neonates in the cesarean section group. The levels of serum IgG and IL-12p70 in the cesarean section group were lower than those in the vaginal delivery group, and the proportion of IFN-γ/IL-4 was significantly lower in the cesarean section group compared to the vaginal delivery group. The mode of delivery has potential impact on the intestinal microbiota and immune functions of neonates, potentially leading to an imbalance of Th1/Th2 cells in neonates delivered by cesarean section.

Abstract The application of exogenous paclobutrazol (PP333) can improve the ability of winter warming to promote flowering in Chaenomeles speciosa, but the underlying mechanism is unclear. In this study, the cultivar ‘Changshouguan’ was sprayed with different concentrations of PP333 during flower bud differentiation, and the changes in the anatomical structures and physiological characteristics of the flower buds during the differentiation process, as well as the growth state of the flower buds and the effect on flowering promotion after winter warming treatment, were comprehensively investigated. The results showed that different concentrations of PP333 could advance the flowering time of ‘Changshouguan’ by 15–24 d under the warming treatment and increase the flowering duration to 17 d compared with those under the warming treatment alone (CK), and 1000 mg/L was the best treatment. Compared with the CK treatment, the PP333 treatment decreased the contents of indole acetic acid (IAA) and gibberellic acid (GAs) and increased the contents of zeatin ribosides (ZRs) and abscisic acid (ABA), thus changing the balance of hormones during flower bud differentiation. The inflection point (low point) of the curve shapes of the ZRs/GAs and ZRs/IAA ratios appeared significantly earlier, which showed a pattern consistent with soluble sugar and protein content and antioxidant activity. Interestingly, the above changes also corresponded to earlier flowering times during the warming process. Taken together, these results indicate that spraying an appropriate concentration of PP333 in the early stage of ‘Changshouguan’ flower bud differentiation promotes the early differentiation of flower buds and early flowering under winter warming treatment by altering their endogenous hormone content and homeostasis and changing their physiological state. The key to maintaining a relatively long flowering period in plants in the PP333 treatment group after flowering promotion was the increased accumulation of sugars and proteins.

Abstract Preoperatively predicting extensive intraductal component in invasive breast cancer through imaging is crucial for informed decision-making, guiding surgical planning to mitigate risks of incomplete resection or re-operation for positive margins in breast-conserving surgery. This study aimed to characterize intra- and peri-tumor heterogeneity using high-spatial resolution ultrafast DCE-MRI to predict the extensive intraductal component in invasive breast cancer (IBC-EIC) preoperatively. A retrospective analysis included invasive breast cancer patients who underwent preoperative high-spatial resolution ultrafast DCE-MRI, categorized based on intraductal component status (IBC-EIC vs. IBC without EIC). Propensity score matching (PSM) was employed to balance clinicopathological covariates between the groups. Personalized kinetic intra-tumor heterogeneity (ITHkinetic) and peri-tumor heterogeneity (PTHkinetic) scores were quantified using clustered voxels with similar enhancement patterns. An image combined model, incorporating MRI features, ITHkinetic, and PTHkinetic scores, was developed and assessed. Of 368 patients, 26.4% (97/368) had IBC-EIC. PSM yielded well-matched pairs of 97 patients each. After PSM, ITHkinetic and PTHkinetic scores were significantly higher in the IBC-EIC group (ITHkinetic: 0.68 ± 0.23; PTHkinetic: 0.58 ± 0.19) compared to IBC without EIC (ITHkinetic: 0.32 ± 0.25; PTHkinetic: 0.42 ± 0.18; p

Abstract This paper investigates the soliton solutions and dynamical analysis of (2+1)-dimensional Heisenberg ferro-magnetic spin chains model with beta fractional derivative, which is transformed into the ordinary differential equation. By using the second-order complete discriminant system, the soliton solutions are presented. By utilizing the theory of planar dynamical system, the phase portraits of the dynamical system and its disturbance system are drawn. Moreover, three-dimensional, two-dimensional, and contour plots of soliton solutions for (2+1)-dimensional Heisenberg ferro-magnetic spin chains model with beta fractional derivative have also been plotted.

Abstract Nematodes serve as key indicators of soil health in ecological studies. Therefore, the current study examined the community structure and metabolic footprint of soil nematodes in alfalfa fields across varying levels of N supply in the semi-arid Loess Plateau. The findings offer theoretical guidance for the sustainable management of artificial alfalfa grasslands in this region. The research was based on alfalfa fields with different N application rates (0, 50, 100, 150 kg/ha2) as the research object, The shallow plate method was used to separate and extract soil nematodes, identify soil nematode groups, calculate ecological function index and metabolic footprint, and identify indicator species. A total of 6346 nematodes were isolated in this study, belonging to 27 genera and 19 families. Notably, the plant parasitic nematode Helicotylenchus was predominant. As N addition increased, the plant parasitic index (PPI) increased significantly. A N50 application significantly enhanced the soil nematode diversity index ( $$\text{H}$$ H ) and the free-living index (MI). The findings showcased a noticeable decrease in disturbance within the N50 soil nematode community. This resulted in a mature and stable community structure primarily attributed to the heightened abundance of omnivorous/predatory nematodes. Across various N levels, soil nematode communities underwent significant alterations in the soil food web structure through shifts in their metabolic footprint. Future strategies should focus on refining N management practices and integrating sustainable approaches like crop rotation and pest management. These efforts will contribute to guidelines ensuring artificial alfalfa grasslands lasting health and productivity.

Abstract To enhance the energy efficiency and financial gains of the park integrated energy system (PIES). This paper constructs a bi-level optimization model of PIES-cloud energy storage (CES) based on source-load uncertainty. Firstly, the scheduling framework of PIES with refined power-to-gas (P2G), carbon capture and storage (CCS) and CES coupling is constructed. Moreover, a bi-level optimization model with the upper tier subject being the PIES operator and the lower tier subject being the CES operator is established under the ladder-type carbon price mechanism with reward and punishment (LCPMRP). Then a proposed entropy weight adaptive information gap decision theory method (EAIGDT) is proposed to eliminate the subjectivity factor and retain its non-probabilistic features while dealing with multiple source-load uncertainties, and according to the operator’s risk preference to build risk-averse (RA) and risk-seeking (RS) strategies, respectively. Finally, the measured data in a certain area of Xinjiang verifies the proposed optimal scheduling method. The results show that the method can effectively take into account the interests of various subjects and realise PIES low-carbon economic operation.

Abstract Chemical molecular structures are a direct and convenient means of expressing chemical knowledge, playing a vital role in academic communication. In chemistry, hand drawing is a common task for students and researchers. If we can convert hand-drawn chemical molecular structures into machine-readable formats, like SMILES encoding, computers can efficiently process and analyze these structures, significantly enhancing the efficiency of chemical research. Furthermore, with the progress of educational technology, automated grading is gaining popularity. When machines automatically recognize chemical molecular structures and assess the correctness of the drawings, it offers great convenience to teachers. We created ChemReco, a tool designed to identify chemical molecular structures involving three atoms: C, H, and O, providing convenience for chemical researchers. Currently, there are limited studies on hand-drawn chemical molecular structures. Therefore, the primary focus of this paper is constructing datasets. We propose a synthetic image method to rapidly generate images resembling hand-drawn chemical molecular structures, enhancing dataset acquisition efficiency. Regarding model selection, the hand-drawn chemical molecule structural recognition model developed in this article achieves a final recognition accuracy of 96.90%. This model employs the encoder-decoder architecture of EfficientNet + Transformer, demonstrating superior performance compared to other encoder-decoder combinations.

Abstract Long-term exposure to hyperglycemic conditions leads to β-cell dysfunction, particularly mitochondrial dysfunction, and inflammatory and oxidative stress responses, which are considered the primary causes of β-cell death and the hallmarks of diabetes. Plant-active ingredients may play a key role in glycemic control. Epigallocatechin gallate (EGCG) is a characteristic catechin derived from tea that possesses anti-diabetic properties. Nonetheless, its underlying mechanisms remain elusive. Herein, the protective role of EGCG on high glucose (33 mM)-induced pancreatic beta cell dysfunction and its possible molecular mechanisms were investigated. Briefly, MIN6 cells were treated with glucose and EGCG (10 µM, 20 µM, and 40 µM) for 48 h. Our results revealed that EGCG dose-dependently restored mitochondrial membrane potential and concomitantly alleviated cell apoptosis. Mechanistically, the expression level of apoptotic protein BAX and Dynamic related protein 1 (DRP1) was significantly downregulated following EGCG treatment, whereas that of the anti-apoptotic protein BCL-2 was significantly upregulated. Taken together, EGCG alleviated high glucose-induced pancreatic beta cell dysfunction by targeting the DRP1-related mitochondrial apoptosis pathway and thus can serve as a nutritional intervention for the preservation of beta cell dysfunction in patients with type 2 diabetes mellitus.

Abstract The available evidence on the connection between excessive alcohol consumption and diabetes is controversial. Therefore, the primary objective of this investigation was to examine the connection between excessive alcohol consumption and incident diabetes in a Japanese population through the utilization of propensity score matching (PSM) analysis. Our retrospective cohort study encompassed a sample of 15,464 Japanese individuals who were initially free of diabetes between the years 2004 and 2015. The study utilized comprehensive medical records of individuals who underwent a physical examination. Employing a one:one PSM analysis, the current research included 2298 individuals with and without excessive alcohol consumption. Furthermore, a doubly robust estimation method was employed to ascertain the connection between excessive alcohol consumption and diabetes. The findings revealed that individuals with excessive alcohol consumption exhibited a 73% higher likelihood of developing diabetes (HR = 1.73, 95% CI 1.08–2.77). Furthermore, upon adjusting for variables, the PSM cohort demonstrated that individuals with excessive alcohol consumption had a 78% increased risk of developing diabetes in comparison to those with non-excessive alcohol consumption (HR = 1.78, 95% CI 1.08–2.93). Individuals with excessive alcohol consumption were found to have a 73% higher risk of developing diabetes compared to those with non-excessive alcohol consumption, even after controlling for propensity score (HR = 1.73, 95% CI 1.08–2.78). Participants in the PSM cohort with excessive alcohol consumption had a 73% higher risk of developing diabetes than those with non-excessive alcohol consumption after controlling for confounding factors. These findings underscore the importance of alcohol consumption guidelines aimed at reducing excessive drinking. Clinicians should be vigilant in screening for alcohol use in patients, particularly those at risk for diabetes, and provide appropriate counseling and resources to support alcohol reduction.

Abstract To address the low efficiency and high labor demands of manual Codonopsis pilosula cultivation, as well as the limitations of existing flat-type transplanting machines that create trenches of inconsistent depth hindering root growth and seedling emergence, a C. pilosula film-covered outcrop tilted transplanting machine was developed. Based on theoretical analysis of the prototype's key components and agronomic requirements for oblique C. pilosula transplanting, the structure and working parameters of the rotary tiller soil throwing device, soil lifting device, track-type soil conveying device, seedling throwing device, and film covering device were determined. The core components' working principles were analyzed, and the soil throwing process of the rotary tiller device was simulated using the discrete element method (DEM). A calculation domain was established, and the results showed that the average mass of the rotary tiller device was 49.44 kg, while the required soil lifting amount for the scraper-type soil lifting device was 21.84 kg, meeting the soil throwing requirements. Field experiments in 10 test areas demonstrated an average qualified rate of 89.50% for planting depth, 84.00% for planting posture, 90% for exposed plant spacing, 4.51 cm for plant spacing, and 8.67% coefficient of variation for planting spacing. These results meet industry standards for planting depth and planting spacing, confirming the machine's effectiveness in achieving high-quality tilted transplanting of C. pilosula seedlings.

Abstract During the true triaxial hydraulic fracturing experiments, the compression stress applied to the specimen surface cannot be transferred to the interior immediately, resulting in inconsistency with in-situ stress conditions. To quantitatively analyze the stress transfer process from the surface to the interior of the specimen, an experimental method for monitoring the inside stress was proposed based on Fiber Bragg Grating (FBG) sensing technique, based on which the true triaxial stress loading experiments were conducted on a concrete-like specimen of 30 cm × 30 cm × 30 cm. The results show that the stresses inside the specimen require a certain loading time to reach the uniform state. The loading time required for stress transfer from the surface to the interior of the specimen decreases with the increase of compression stresses. The stress transfer process in rock materials is determined by creep. The closure of microcracks results in stress redistribution inside the specimen during creep. Moreover, a 3-D Burgers model is modified to describe the stress transfer process. Finally, the stress transfer phenomenon during hydraulic fracturing was verified by coal fracturing experiments. This study can help to understand the stress transfer mechanism, providing guidance for standardizing the laboratory simulation of in-situ stress.

Abstract Secure multi-party computation of Chebyshev distance represents a crucial method for confidential distance measurement, holding significant theoretical and practical implications. Especially within electronic archival management systems, secure computation of Chebyshev distance is employed for similarity measurement, classification, and clustering of sensitive archival information, thereby enhancing the security of sensitive archival queries and sharing. This paper proposes a secure protocol for computing Chebyshev distance under a semi-honest model, leveraging the additive homomorphic properties of the NTRU cryptosystem and a vector encoding method. This protocol transforms the confidential computation of Chebyshev distance into the inner product of confidential computation vectors, as demonstrated through the model paradigm validating its security under the semi-honest model. Addressing potential malicious participant scenarios, a secure protocol for computing Chebyshev distance under a malicious model is introduced, utilizing cryptographic tools such as digital commitments and mutual decryption methods. The security of this protocol under the malicious model is affirmed using the real/ideal model paradigm. Theoretical analysis and experimental simulations demonstrate the efficiency and practical applicability of the proposed schemes.

Abstract We conducted a retrospective study to investigate risk factors for tuberculosis care-seeking delay and diagnostic delays among pediatric pulmonary tuberculosis cases in Zhejiang Province from 2013 to 2022. Among 1274 cases, 49.61% experienced tuberculosis care-seeking delays (> 14 days from symptom onset to first hospital visit) and 14.91% faced diagnostic delays (> 14 days from initial consultation to diagnosis). The proportion of care-seeking delays ranged from 37.42 to 64.89%, while diagnostic delay fluctuated from 6.11 to 21.02%. Urban residence (OR = 0.78, 95% CI 0.62–0.98, P = 0.030), first visiting a municipal-level hospital (OR = 0.57, 95% CI 0.45–0.72, P

Abstract In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multiple sclerosis (MS) patients and may represent early or distinct disease processes. The role of MRI-observed DAWM is understudied due to a lack of automated assessment methods. Supervised deep learning (DL) methods are highly capable in this domain, but require large sets of labeled data. To overcome this challenge, a DL-based network (DAWM-Net) was trained using semi-supervised learning on a limited set of labeled data for segmentation of DAWM, focal lesions, and normal-appearing brain tissues on multiparametric MRI. DAWM-Net segmentation performance was compared to a previous intensity thresholding-based method on an independent test set from expert consensus (N = 25). Segmentation overlap by Dice Similarity Coefficient (DSC) and Spearman correlation of DAWM volumes were assessed. DAWM-Net showed DSC > 0.93 for normal-appearing brain tissues and DSC > 0.81 for focal lesions. For DAWM-Net, the DAWM DSC was 0.49 ± 0.12 with a moderate volume correlation (ρ = 0.52, p

Abstract Data regarding the association of sarcopenia with hospitalization has led to inconclusive results in patients undergoing dialysis. The main goal of this research was to investigate the association between sarcopenia and hospitalization in Chinese individuals on continuous ambulatory peritoneal dialysis (CAPD). Eligible patients on CAPD were prospectively included, and followed up for 48 weeks in our PD center. Sarcopenia was identified utilizing the criteria set by the Asian Working Group on Sarcopenia in 2019 (AWGS 2019). Participants were categorized into sarcopenia (non-severe sarcopenia + severe sarcopenia) and non-sarcopenia groups. The primary outcome was all-cause hospitalization during the 48-week follow-up period. Association of sarcopenia with all-cause hospitalization was examined by employing multivariate logistic regression models. The risk of cumulative incidence of hospitalization in the 48-week follow-up was estimated using relative risk (RR and 95% CI). The cumulative hospitalization time and frequency at the end of 48-week follow-up were described as categorical variables, and compared by χ2 test or fisher's exact test as appropriate. Subgroup and sensitivity analyses were also conducted to examine whether the potential association between sarcopenia and hospitalization was modified. A total of 220 patients on CAPD (5 of whom were lost in follow-up) were included. Prevalences of total sarcopenia and severe sarcopenia were 54.1% (119/220) and 28.2% (62/220) according to AWGS 2019, respectively. A total of 113 (51.4%) participants were hospitalized during the 48-week follow-up period, of which, the sarcopenia group was 65.5% (78/119) and the non-sarcopenia group was 34.7% (35/101), with an estimated RR of 1.90 (95%CI 1.43–2.52). The cumulative hospitalization time and frequency between sarcopenia and non-sarcopenia groups were significantly different (both P

Abstract Investigate the effect of long-term COVID-19 on maternal and fetal complications. A retrospective cohort study was conducted. A total of 623 pregnant women who delivered in Kunming First People's Hospital from November 1, 2022 to July 31, 2023 were selected. By employing statistical methods, we compared the associations between maternal and fetal complications in pregnant women with acute COVID-19 during pregnancy, long-term COVID-19, and non-COVID-19 pregnant women. In the final 623 samples, there were 209 pregnant women with acute COVID-19, 72 pregnant women with long-term COVID-19, and 342 pregnant women without COVID-19. The epidemiological and clinical characteristics of all subjects were similar. Pregnant individuals who developed long-term COVID-19 during their pregnancy had an increased risk of experiencing gestational hypertension (OR 3.344, 95% CI 1.544–7.243), gestational diabetes mellitus (OR 2.301, 95% CI 1.290–4.102), and fetal intrauterine growth restriction (OR 2.817, 95% CI 1.385–5.952). Multivariate binary logistic regression analysis showed that this association remained consistent even after adjusting for confounders and performing subgroup analyses. Other maternal and fetal complications, such as premature rupture of membranes, preterm delivery, neonatal asphyxia, and transfer of neonates to NICU, did not exhibit statistically significant associations. After linear regression analysis, the platelet count (β: − 0.127, 95% CI − 0.001–0.000) of pregnant women with long-term COVID-19 was slightly lower than that of non-COVID-19 pregnant women, and the other coagulation parameters were not statistically significant. The incidence of gestational hypertension, gestational diabetes mellitus and fetal intrauterine growth restriction in pregnant women with long-term COVID-19 is significantly increased, but it does not further increase the coagulation status.

Abstract To quantitatively evaluate chronic kidney disease (CKD), a deep convolutional neural network-based segmentation model was applied to renal enhanced computed tomography (CT) images. A retrospective analysis was conducted on a cohort of 100 individuals diagnosed with CKD and 90 individuals with healthy kidneys, who underwent contrast-enhanced CT scans of the kidneys or abdomen. Demographic and clinical data were collected from all participants. The study consisted of two distinct stages: firstly, the development and validation of a three-dimensional (3D) nnU-Net model for segmenting the arterial phase of renal enhanced CT scans; secondly, the utilization of the 3D nnU-Net model for quantitative evaluation of CKD. The 3D nnU-Net model achieved a mean Dice Similarity Coefficient (DSC) of 93.53% for renal parenchyma and 81.48% for renal cortex. Statistically significant differences were observed among different stages of renal function for renal parenchyma volume (VRP), renal cortex volume (VRC), renal medulla volume (VRM), the CT values of renal parenchyma (HuRP), the CT values of renal cortex (HuRC), and the CT values of renal medulla (HuRM) (F = 93.476, 144.918, 9.637, 170.533, 216.616, and 94.283; p

Abstract The relationship between blood urea nitrogen to albumin ratio (BAR) and the prognosis of patients with tuberculosis (TB) complicated by sepsis remains unclear. This study aimed to explore the association between BAR and overall patient prognosis. This was a retrospective cohort study of patients with TB complicated by sepsis who were admitted to the intensive care unit (ICU) of the Public Health Clinical Center of Chengdu between January 2019 and February 2023. The relationship between BAR values and prognosis in these patients was investigated using multivariate Cox regression, stratified analysis with interaction, restricted cubic spline (RCS), and threshold effect analysis. Sensitivity analyses were conducted to assess the robustness of the results. Our study included 537 TB patients complicated by sepsis admitted in the ICU, with a median age of 63.0 (48.0, 72.0) years; 76.7% of whom were men. The multivariate-restricted cubic spline analysis showed a non-linear association between BAR and patient prognosis. In the threshold analysis, we found that TB patients complicated by sepsis and a BAR

Abstract The small Extracellular vesicles (sEV) has been recognized to be significant for intercellular communication due to their ability to transfer important cellular cargoes like miRNAs through circulation. The pituitary gland has not been clearly known about the role of its secreted sEV under normal physiological conditions. And Liver disease is a global public health burden. The present study is the first to investigate the effect of pituitary sEV on the liver. Sequencing and qRT-PCR revealed miR-143-3p is one of the richest in the pituitary sEV. MiR-143 Knockout (KO) mice resulted in a remarkable decrease in insulin-like growth factor 1 (IGF-1) levels and a significant increase in insulin-like growth factor binding protein 5 (IGFBP5) levels along with a reduction in liver primary cell growth. More importantly, compared with miR-143-KO-sEV, WT-sEV possesses a more robust capacity to improve miR-143 KO mice liver repair through the Wnt/β-catenin pathway after an acute injury caused by carbon tetrachloride (CCl4). Our results indicate that pituitary-derived sEV promotes hepatocyte proliferation and liver repair by its cargo miR-143-3p and provides new insight into the regulation mechanism of the pituitary-liver axis, and open a new window for endocrine regulation by using sEV.

Abstract The purpose of this work is to explore the properties of the lignin-derived amine-free photoinitiating systems (PISs) during the curing process. Four novel hydrogen donors (HD1, HD2, HD3, and HD4) derived from lignin α-O-4 structural were designed and synthesized by simple methods, and their low C–H bond dissociation energies on methylene were determined by molecular orbitals theory. Four experimental groups using CQ (camphorquinone)/HD PIs formulated with Bis-GMA/TEGDMA (70 w%/30 w%) were compared to CQ/EDB (ethyl 4-dimethylamino benzoate) system. The photopolymerization profiles and double bond conversion rate was tracked by FTIR experiments; the color bleaching ability of the samples and color aging test assay were performed using color indexes measurements; The cytotoxicity of the samples was also compared to EDB related systems. All of the experimental groups with new HDs were compared to the control group with EDB by statistical analysis. Compared to CQ/EDB system, new lignin-derived hydrogen donors combined with CQ showed comparable or even better performances in polymerization initiation to form resin samples, under a blue dental LED in air. Excellent color bleaching property was observed with the new HDs. Aging tests and cytotoxicity examination of the resin were performed, indicating the new lignin compounds to be efficient hydrogen donors for amine-free CQ-based photo-initiating system. Novel lignin α-O-4 derived hydrogen donors are promising for further usage in light-curing materials.