Search

Abstract Background Recently, the C3-epimer of 25-hydroxyvitamin D [C3-epi-25(OH)D] has become a topic of interest among 25-hydroxyvitamin D [25(OH)D] metabolites. Although it can lead to an overestimation of vitamin D storage, its relationship with disease occurrence remains controversial, possibly related to the great extent of tracking of 25(OH)D by C3-epi-25(OH)D over time. This study aimed to investigate the differential performance of C3-epi-25(OH)D3 and its percentage [%C3-epi-25(OH)D3] with respect to 20 common paediatric diseases. Methods This study involved 805 healthy children and adolescents and 2962 patients with common paediatric diseases. We investigated sex, age, and seasonal differences in C3-epi-25(OH)D3 and %C3-epi-25(OH)D3 levels; their variations on 20 common paediatric diseases; and their degree of correlation with 25(OH)D3 levels and various diseases. Results Among the healthy underage participants, C3-epi-25(OH)D3 and %C3-epi-25(OH)D3 changed similarly, with no sex differences. Moreover, their levels were higher in the infant period than in the other periods (t = 5.329–5.833, t = 4.640–5.711, all Padj

In order to elucidate the effect of protein oxidation on physicochemical properties and protein structure of yak longissimus dorsi muscle, muscle samples were treated in a Fenton oxidation system (H2O2 concentrations of 1, 10, 20, 40 and 60 mmol/L) containing 0.6 mol/L NaCl at pH 5.0 or 8.0 for 1 h. The results showed that with the increase of H2O2 concentration, the carbonyl content, surface hydrophobicity and dityrosine content of yak myofibrillar proteins increased, while the contents of total sulfhydryl and active sulfhydryl, solubility, and tryptophan fluorescence intensity decreased. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis showed that the numbers of myosin heavy chain and actin bands decreased after protein oxidation, and covalent cross-linking occurred between protein molecules via disulfide bonds, which was accompanied by an increase in the centrifugal and cooking loss of muscle. The transverse relaxation time (T2) of muscle was measured by low-field nuclear magnetic resonance (NMR) spectroscopy and the microstructure of muscle was observed by scanning electron microscopy (SEM). It was found that the increase in the centrifugal loss and cooking loss of muscle was due to the destruction of muscle microstructure caused by protein oxidation as well as the decrease in unbound water content and the increase in free water content. Muscle centrifugal loss, cooking loss, free water content and the degree of damage of muscle microstructure at pH 8.0 were lower than those at pH 5.0. The results showed that under the same oxidation condition, yak muscle proteins are more prone to oxidative damage and lower water-holding capacity near the isoelectric point.

Abstract Background Although rheumatoid arthritis (RA) is a chronic systemic tissue disease often accompanied by osteoporosis (OP), the molecular mechanisms underlying this association remain unclear. This study aimed to elucidate the pathogenesis of RA and OP by identifying differentially expressed mRNAs (DEmRNAs) and long non-coding RNAs (lncRNAs) using a bioinformatics approach. Methods Expression profiles of individuals diagnosed with OP and RA were retrieved from the Gene Expression Omnibus database. Differential expression analysis was conducted. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway enrichment analyses were performed to gain insights into the functional categories and molecular/biochemical pathways associated with DEmRNAs. We identified the intersection of common DEmRNAs and lncRNAs and constructed a protein-protein interaction (PPI) network. Correlation analysis between the common DEmRNAs and lncRNAs facilitated the construction of a coding-non-coding network. Lastly, serum peripheral blood mononuclear cells (PBMCs) from patients with RA and OP, as well as healthy controls, were obtained for TRAP staining and qRT-PCR to validate the findings obtained from the online dataset assessments. Results A total of 28 DEmRNAs and 2 DElncRNAs were identified in individuals with both RA and OP. Chromosomal distribution analysis of the consensus DEmRNAs revealed that chromosome 1 had the highest number of differential expression genes. GO and KEGG analyses indicated that these DEmRNAs were primarily associated with " platelets (PLTs) degranulation”, “platelet alpha granules”, “platelet activation”, “tight junctions” and “leukocyte transendothelial migration”, with many genes functionally related to PLTs. In the PPI network, MT-ATP6 and PTGS1 emerged as potential hub genes, with MT-ATP6 originating from mitochondrial DNA. Co-expression analysis identified two key lncRNA-mRNA pairs: RP11 − 815J21.2 with MT − ATP6 and RP11 − 815J21.2 with PTGS1. Experimental validation confirmed significant differential expression of RP11-815J21.2, MT-ATP6 and PTGS1 between the healthy controls and the RA + OP groups. Notably, knockdown of RP11-815J21.2 attenuated TNF + IL-6-induced osteoclastogenesis. Conclusions This study successfully identified shared dysregulated genes and potential therapeutic targets in individuals with RA and OP, highlighting their molecular similarities. These findings provide new insights into the pathogenesis of RA and OP and suggest potential avenues for further research and targeted therapies.

Abstract In order to investigate the mechanism of plant growth promoting (PGP) effects of strain Bacillus velezensis WSW007, its PGP traits and production of volatile organic compounds (VOCs) were tested. The effects of VOCs produced by strain WSW007 on plant growth were observed by co-culturing this strain with tobacco seedlings in I-plates. Meanwhile, the effects of VOCs on tobacco gene expression were analysed by a transcriptome analysis and VOCs were identified by solid phase micro extraction coupled with gas chromatography-mass spectrometry (SPME-GC-MS) analysis. As results, strains WSW007 produced acetic acid and siderophore, and could solubilize phosphate; while it also significantly increased the fresh weight of tobacco seedlings via production of VOCs. In transcriptome analysis, plants co-cultured with strain WSW007 presented the highest up-regulated expression for the genes involved in plant growth and development processes, implying that the bacterial VOCs played a role as regulator of plant gene expression. Conclusively, the up-regulation in expression of growth- and development-related genes via VOCs production is an important PGP mechanism in strain B. velezensis WSW007.

Introduction Maternal smoking during pregnancy disturbs fetal lung development, and induces in their offspring childhood respiratory diseases. Whether it has a continued impact on offspring adult lung health and exerts a casual effect of chronic respiratory diseases (CRDs), remains uncertain. We seek to determine the causal relationships between maternal smoking around birth and offspring adult CRDs, using summary data from previously described cohorts. Methods Mendelian randomization (MR) study was used to analyze the genomewide associations of maternal smoking around birth and offspring adult CRDs, including respiratory insufficiency, chronic obstructive pulmonary disease (COPD), related respiratory insufficiency, emphysema, COPD, COPD hospital admissions, early onset of COPD, later onset of COPD, asthma, idiopathic pulmonary fibrosis (IPF), lung cancer (LC), small cell lung carcinoma (SCLC), and lung squamous cell carcinoma (LUSC). Results After removing single-nucleotide polymorphisms (SNPs) associated with smoking by the offspring, maternal smoking around birth was associated with increased risk of offspring adult respiratory diseases (OR=1.14; 95% CI: 1.013–1.284; p=0.030), respiratory insufficiency (OR=2.413; 95% CI: 1.039– 5.603; p=0.040), COPD (OR=1.14; 95% CI: 1.013–1.284; p=0.003), and asthma (OR=1.336; 95% CI: 1.161–1.538; p

Abstract In order to accurately predict the content and variation trend of dissolved gas in transformer oil and guide the condition maintenance of power transformers, a combined prediction model based on multi‐information fusion is proposed and its effectiveness is analysed. First of all, based on the possibility of pathological and missing historical sample data, a detection and filling method based on variable weight combination samples is established. Second, the authors propose two models. Aiming at the non‐linear and non‐stationary characteristics of gas content, a univariate decomposition prediction mode HBA‐VMD‐TCN which based on the Honey Badger algorithm, variational mode decomposition and time convolutional network (TCN) is established. Then the multivariate Informer prediction model is established for gas content affected by multiple variables. Third, the cross‐entropy theory is used to determine the weight coefficients of the two models, and the multi‐information fusion combined prediction model is formed. Finally, on the basis of the above, a method to determine the time step and the position information of the transition point adaptively in the process of prediction is proposed to further improve the prediction accuracy. The results show that, through a series of simulation experiments of model comparison and transformer anomaly prediction, the accuracy and effectiveness of the combined prediction model are verified.

Abstract Clarifying the relationship between the man–machine environment and its impact on the tunnel wall drilling task performance (TWDTP) is crucial for enhancing the task performance. Based on a questionnaire survey, indicators of the man–machine environment that affect the TWDTP were proposed in this study, and exploratory factor analysis and a structural equation model were employed to examine the potential factors influencing the task performance and their degrees of influence. By comparing the discrepancy between the perceived performance and importance, the satisfaction of potential factors was evaluated, and the priority order for optimizing these factors was determined by considering the degree of influence and dissatisfaction. The results of survey data analysis based on actual tunnel drilling operation scenarios indicated that tools had the greatest impact on the TWDTP, followed by the quality of the physical environment, while human factors had the least influence on the task performance. Convenient functional maintenance is the key to improving the TWDTP, along with enhancing the quality of the working environment. Once these main aspects are optimized, it is important to consider additional factors such as availability of spare tools, efficient personnel organization, man–tool matching, and safety and health assurance. This research approach provides significant guidance in understanding the relationships between the man–machine environmental factors affecting the performance of complex engineering tasks and identifying key influencing factors, thus providing essential insights for optimizing the TWDTP.

Abstract Objective This study aimed to assess the functions of cell division cycle protein 45 (CDC45) in Non-small cell lung cancer (NSCLC) cancer and its effects on stemness and metastasis. Methods Firstly, differentially expressed genes related to lung cancer metastasis and stemness were screened by differential analysis and lasso regression. Then, in vitro, experiments such as colony formation assay, scratch assay, and transwell assay were conducted to evaluate the impact of CDC45 knockdown on the proliferation and migration abilities of lung cancer cells. Western blotting was used to measure the expression levels of related proteins and investigate the regulation of CDC45 on the cell cycle. Finally, in vivo model with subcutaneous injection of lung cancer cells was performed to verify the effect of CDC45 on tumor growth. Results This study identified CDC45 as a key gene potentially influencing tumor stemness and lymph node metastasis. Knockdown of CDC45 not only suppressed the proliferation and migration abilities of lung cancer cells but also caused cell cycle arrest at the G2/M phase. Further analysis revealed a negative correlation between CDC45 and cell cycle-related proteins, stemness-related markers, and tumor mutations. Mouse experiments confirmed that CDC45 knockdown inhibited tumor growth. Conclusion As a novel regulator of stemness, CDC45 plays a role in regulating lung cancer cell proliferation, migration, and cell cycle. Therefore, CDC45 may serve as a potential target for lung cancer treatment and provide a reference for further mechanistic research and therapeutic development.

BackgroundLacunes, a characteristic feature of cerebral small vessel disease (CSVD), are critical public health concerns, especially in the aging population. Traditional neuroimaging techniques often fall short in early lacune detection, prompting the need for more precise predictive models.MethodsIn this retrospective study, 587 patients from the Neurology Department of the Affiliated Hospital of Hebei University who underwent cranial MRI were assessed. A nomogram for predicting lacune incidence was developed using LASSO regression and binary logistic regression analysis for variable selection. The nomogram’s performance was quantitatively assessed using AUC-ROC, calibration plots, and decision curve analysis (DCA) in both training (n = 412) and testing (n = 175) cohorts.ResultsIndependent predictors identified included age, gender, history of stroke, carotid atherosclerosis, hypertension, creatinine, and homocysteine levels. The nomogram showed an AUC-ROC of 0.814 (95% CI: 0.791–0.870) for the training set and 0.805 (95% CI: 0.782–0.843) for the testing set. Calibration and DCA corroborated the model’s clinical value.ConclusionThis study introduces a clinically useful nomogram, derived from binary logistic regression, that significantly enhances the prediction of lacunes in patients undergoing brain MRI for various indications, potentially advancing early diagnosis and intervention. While promising, its retrospective design and single-center context are limitations that warrant further research, including multi-center validation.

ObjectiveTo determine the relationship between school bullying victimization and social mindfulness and its mechanism in light of the interdependence and schema theories.MethodThe Chinese version of the Delaware Bullying Victimization Scale-student, Emotion Regulation Questionnaire, Self-Concept Clarity Scale and The Social Mindfulness Self-report Scale (SMSRS) were distributed to 553 middle school students.Results(1) The correlations of school bullying victimization with social mindfulness, self-concept clarity, and cognition reappraisal were statistically significant. (2) School bullying victimization had a significant effect on social mindfulness. (3) The simple mediating role of self-concept clarity and cognition reappraisal between school bullying victimization and social mindfulness were significant. (4) Self-concept clarity and cognition reappraisal played a chain mediating role between school bullying victimization and social mindfulness.

ObjectiveBy utilizing machine learning, we can identify genes that are associated with recurrence, invasion, and tumor stemness, thus uncovering new therapeutic targets.MethodsTo begin, we obtained a gene set related to recurrence and invasion from the GEO database, a comprehensive gene expression database. We then employed the Weighted Gene Co-expression Network Analysis (WGCNA) to identify core gene modules and perform functional enrichment analysis on them. Next, we utilized the random forest and random survival forest algorithms to calculate the genes within the key modules, resulting in the identification of three crucial genes. Subsequently, one of these key genes was selected for prognosis analysis and potential drug screening using the Kaplan-Meier tool. Finally, in order to examine the role of CDC20 in lung adenocarcinoma (LUAD), we conducted a variety of in vitro and in vivo experiments, including wound healing assay, colony formation assays, Transwell migration assays, flow cytometric cell cycle analysis, western blotting, and a mouse tumor model experiment.ResultsFirst, we collected a total of 279 samples from two datasets, GSE166722 and GSE31210, to identify 91 differentially expressed genes associated with recurrence, invasion, and stemness in lung adenocarcinoma. Functional enrichment analysis revealed that these key gene clusters were primarily involved in microtubule binding, spindle, chromosomal region, organelle fission, and nuclear division. Next, using machine learning, we identified and validated three hub genes (CDC45, CDC20, TPX2), with CDC20 showing the highest correlation with tumor stemness and limited previous research. Furthermore, we found a close association between CDC20 and clinical pathological features, poor overall survival (OS), progression-free interval (PFI), progression-free survival (PFS), and adverse prognosis in lung adenocarcinoma patients. Lastly, our functional research demonstrated that knocking down CDC20 could inhibit cancer cell migration, invasion, proliferation, cell cycle progression, and tumor growth possibly through the MAPK signaling pathway.ConclusionCDC20 has emerged as a novel biomarker for monitoring treatment response, recurrence, and disease progression in patients with lung adenocarcinoma. Due to its significance, further research studying CDC20 as a potential therapeutic target is warranted. Investigating the role of CDC20 could lead to valuable insights for developing new treatments and improving patient outcomes.

Abstract Structural modification based on existing drugs, which ensures the safety of marketed drugs, is an essential approach in developing new drugs. In this study, we modified the structure of cabotegravir by introducing the front alkyne on the core structure through chemical reaction, resulting in the synthesis of 9 compounds resembling 1,2,3‐triazoles. The potential of these new cabotegravir derivatives as tumor suppressors in gastrointestinal tumors was investigated. Based on the MTT experiment, most compounds showed a reduction in the viability of KYSE30 and HCT116 cells. Notably, derivatives 5b and 5h exhibited the most significant inhibitory effects. To further explore the effects of derivatives 5b and 5h on gastrointestinal tumors, KYSE30 cells were chosen as a representative cell line. Both derivatives can effectively curtail the migration and invasion capabilities of KYSE30 cells and induce apoptosis in a dose‐dependent manner. We further demonstrated these derivatives induce cell apoptosis in KYSE30 cells by inhibiting the expression of Stat3 protein and Smad2/3 protein. Based on the above results, we suggest they show promise in developing drugs for esophageal squamous cell carcinoma.

Abstract Background Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment of lung adenocarcinoma (LUAD) and are often associated with poorer clinical outcomes. This study aimed to screen for CAF-specific genes that could serve as promising therapeutic targets for LUAD. Methods We established a single-cell transcriptional profile of LUAD, focusing on genetic changes in fibroblasts. Next, we identified key genes associated with fibroblasts through weighted gene co-expression network analysis (WGCNA) and univariate Cox analysis. Then, we evaluated the relationship between glutathione peroxidase 8 (GPX8) and clinical features in multiple independent LUAD cohorts. Furthermore, we analyzed immune infiltration to shed light on the relationship between GPX8 immune microenvironment remodeling. For clinical treatment, we used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the immunotherapy prediction efficiency of GPX8. After that, we screened potential therapeutic drugs for LUAD by the connectivity map (cMAP). Finally, we conducted a cell trajectory analysis of GPX8+ CAFs to show their unique function. Results Fibroblasts were found to be enriched in tumor tissues. Then we identified GPX8 as a key gene associated with CAFs through comprehensive bioinformatics analysis. Further analysis across multiple LUAD cohorts demonstrated the relationship between GPX8 and poor prognosis. Additionally, we found that GPX8 played a role in inducing the formation of an immunosuppressive microenvironment. The TIDE method indicated that patients with low GPX8 expression were more likely to be responsive to immunotherapy. Using the cMAP, we identified beta-CCP as a potential drug-related to GPX8. Finally, cell trajectory analysis provided insights into the dynamic process of GPX8+ CAFs formation. Conclusions This study elucidates the association between GPX8+ CAFs and poor prognosis, as well as the induction of immunosuppressive formation in LUAD. These findings suggest that targeting GPX8+ CAFs could potentially serve as a therapeutic strategy for the treatment of LUAD.

Abstract Background Osteoporotic fractures are a growing problem in an aging society. The association between body mass index (BMI) and osteoporotic fractures varies by fracture site and ethnicity. Limited knowledge exists regarding this association in native Chinese, particularly utilizing local databases as reference sources. Objective To investigate the association between BMI and osteoporotic fractures at different sites in Chinese women. Methods Three thousand ninety-eight female patients with radiographic fractures and 3098 age- and sex-matched healthy controls without fractures were included in the study. Both of them underwent assessment using dual-energy X-ray absorptiometry (DXA), with BMD measurements calculated using our own BMD reference database. Participants were classified into underweight (BMI < 18.5 kg/m2), normal weight (18.5 ≤ BMI < 24.0 kg/m2), overweight (24 ≤ BMI < 28 kg/m2) and obese (BMI ≥ 28 kg/m2) according to the Chinese BMI classification standard. Results There were 2296 (74.1%) vertebral fractures, 374 (12.1%) femoral neck fractures, and 428 (13.8%) other types of fractures in the case group. Bone mineral density (BMD) was almost lower in the fracture groups compared to the control groups (p = 0.048 to < 0.001). Compared with normal weight, underweight had a protective effect on total [odds ratio (OR) = 0.61; 95% confidence interval (CI), 0.49 –0.75; P< 0.001], and lumbar fractures (OR = 0.52; 95% CI, 0.41 – 0.67; P < 0.001), while obesity was associated with an increased risk for total (OR = 2.26; 95% CI, 1.85 – 2.76; P < 0.001), lumbar (OR = 2.17; 95% CI, 1.72 – 2.73; P < 0.001), and femoral neck fractures (OR = 4.08; 95% CI, 2.18 – 7.63; P < 0.001). Non-linear associations were observed between BMI and fractures: A J-curve for total, lumbar, and femoral neck fractures, and no statistical change for other types of fractures. Underweight was found to be a risk factor for other types of fracturess after adjusting for BMD (OR = 2.29; 95% CI, 1.09 – 4.80; P < 0.001). Osteoporosis and osteopenia were identified as risk factors for almost all sites of fracture when compared to normal bone mass. Conclusions Underweight has a protective effect on total and lumbar spine fractures in Chinese women, while obesity poses a risk factor for total, lumbar, and femoral neck fractures. The effect of BMI on fractures may be mainly mediated by BMD.

Abstract Objection Investigating the key genes and mechanisms that influence stemness in lung adenocarcinoma. Methods First, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes. Then, machine learning methods were employed to screen and identify the key genes within these modules. Lastly, functional analysis of the key genes was conducted through cell scratch assays, colony formation assays, transwell migration assays, flow cytometry cell cycle analysis, and xenograft tumor models. Results First, two groups of patients with different stemness scores were obtained, where the high stemness score group exhibited poor prognosis and immunotherapy efficacy. Next, LASSO regression analysis and random forest regression were employed to identify genes (PBK, RACGAP1) associated with high stemness scores. RACGAP1 was significantly upregulated in the high stemness score group of lung adenocarcinoma and closely correlated with clinical pathological features, poor overall survival (OS), recurrence-free survival (RFS), and unfavorable prognosis in lung adenocarcinoma patients. Knockdown of RACGAP1 suppressed the migration, proliferation, and tumor growth of cancer cells. Conclusion RACGAP1 not only indicates poor prognosis and limited immunotherapy benefits but also serves as a potential targeted biomarker influencing tumor stemness.

Abstract The invasive capacity of lung adenocarcinoma (LUAD) is an important factor influencing patients’ metastatic status and survival outcomes. However, there is still a lack of suitable biomarkers to evaluate tumor invasiveness. LUAD molecular subtypes were identified by unsupervised consistent clustering of LUAD. The differences in prognosis, tumor microenvironment (TME), and mutation were assessed among different subtypes. After that, the invasion-related gene score (IRGS) was constructed by genetic differential analysis, WGCNA analysis, and LASSO analysis, then we evaluated the relationship between IRGS and invasive characteristics, TME, and prognosis. The predictive ability of the IRGS was verified by in vitro experiments. Next, the “oncoPredict” R package and CMap were used to assess the potential value of IRGS in drug therapy. The results showed that LUAD was clustered into two molecular subtypes. And the C1 subtype exhibited a worse prognosis, higher stemness enrichment activity, less immune infiltration, and higher mutation frequency. Subsequently, IRGS developed based on molecular subtypes demonstrated a strong association with malignant characteristics such as invasive features, higher stemness scores, less immune infiltration, and worse survival. In vitro experiments showed that the higher IRGS LUAD cell had a stronger invasive capacity than the lower IRGS LUAD cell. Predictive analysis based on the “oncoPredict” R package showed that the high IRGS group was more sensitive to docetaxel, erlotinib, paclitaxel, and gefitinib. Among them, in vitro experiments verified the greater killing effect of paclitaxel on high IRGS cell lines. In addition, CMap showed that purvalanol-a, angiogenesis-inhibitor, and masitinib have potential therapeutic effects in the high IRGS group. In summary we identified and analyzed the molecular subtypes associated with the invasiveness of LUAD and developed IRGS that can efficiently predict the prognosis and invasive ability of the tumor. IRGS may be able to facilitate the precision treatment of LUAD to some extent.

Background: The immune status is closely linked to cancer progression, metastasis, and prognosis. Lipid metabolism, crucial for reshaping immune status, plays a key role in regulating the advancement of lung adenocarcinoma (LUAD) and deserves further investigation. Methods: This study classifies LUAD patients into different immune subtypes based on lipid metabolism-related genes and compares the clinical characteristics among these subtypes. Single-multi COX analysis screens out key genes related to prognosis, and a risk feature and prognostic model are constructed. Cell cloning, scratch, transwell, western blotting and flow cytometry cell cycle analysis to detect the function of key genes. A subcutaneous tumor animal model is used to investigate the in vivo function and molecular mechanisms of key genes. Results: LUAD patients are classified into three immune subtypes, among which C3 subtype has lower immune status and higher frequency of gene mutations, and show lower immunoreactivity in immunotherapy. COX analysis identified a prognostic model for four lipid metabolism factors (IGFBP1, NR0B2, PPARA, and POMC). IGFBP1, a core gene in this model, is highly expressed in the C3 subtype. Functionally, knocking down IGFBP1 significantly inhibits tumor cell cloning, scratch, and migration abilities, and downregulates the expression of cell cycle and EMT-related proteins. Knocking down IGFBP1 significantly inhibits tumor burden (P < 0.05). Mechanistically, knocking down IGFBP1 inhibits the activation of PPARα to regulate tumor cell growth. Conclusions: This study found that lipid metabolism genes are closely related to LUAD, and IGFBP1 may be a key gene in regulating tumor growth and development.

BackgroundCerebral small vessel disease (CSVD) is a common neurodegenerative condition in the elderly, closely associated with cognitive impairment. Early identification of individuals with CSVD who are at a higher risk of developing cognitive impairment is crucial for timely intervention and improving patient outcomes.ObjectiveThe aim of this study is to construct a predictive model utilizing LASSO regression and binary logistic regression, with the objective of precisely forecasting the risk of cognitive impairment in patients with CSVD.MethodsThe study utilized LASSO regression for feature selection and logistic regression for model construction in a cohort of CSVD patients. The model’s validity was assessed through calibration curves and decision curve analysis (DCA).ResultsA nomogram was developed to predict cognitive impairment, incorporating hypertension, CSVD burden, apolipoprotein A1 (ApoA1) levels, and age. The model exhibited high accuracy with AUC values of 0.866 and 0.852 for the training and validation sets, respectively. Calibration curves confirmed the model’s reliability, and DCA highlighted its clinical utility. The model’s sensitivity and specificity were 75.3 and 79.7% for the training set, and 76.9 and 74.0% for the validation set.ConclusionThis study successfully demonstrates the application of machine learning in developing a reliable predictive model for cognitive impairment in CSVD. The model’s high accuracy and robust predictive capability provide a crucial tool for the early detection and intervention of cognitive impairment in patients with CSVD, potentially improving outcomes for this specific condition.

Xinyu mandarin is popular for its good flavor, but its flavor deteriorates during postharvest storage. To better understand the underlying basis of this change, the dynamics of the sensory profiles were investigated throughout fruit ripening and storage. Sweetness and sourness, determined especially by sucrose and citric acid content, were identified as the key sensory factors in flavor establishment during ripening, but not in flavor deterioration during storage. Postharvest flavor deterioration is mainly attributed to the reduction of retronasal aroma and the development of off-flavor. Furthermore, sugars, acids and volatile compounds were analyzed. Among the 101 detected volatile compounds, 10 changed significantly during the ripening process. The concentrations of 15 volatile components decreased during late postharvest storage, among which α-pinene and d-limonene were likely to play key roles in the reduction of aroma. Three volatile compounds were found to increase during storage, associated with off-flavor development.

In recent decades, there has been increasing interest in elucidating the role of sulfur-containing compounds in plant metabolism, particularly emphasizing their function as signaling molecules. Among these, thiocyanate (SCN−), a compound imbued with sulfur and nitrogen, has emerged as a significant environmental contaminant frequently detected in irrigation water. This compound is known for its potential to adversely impact plant growth and agricultural yield. Although adopting exogenous SCN− as a nitrogen source in plant cells has been the subject of thorough investigation, the fate of sulfur resulting from the assimilation of exogenous SCN− has not been fully explored. There is burgeoning curiosity in probing the fate of SCN− within plant systems, especially considering the possible generation of the gaseous signaling molecule, hydrogen sulfide (H2S) during the metabolism of SCN−. Notably, the endogenous synthesis of H2S occurs predominantly within chloroplasts, the cytosol, and mitochondria. In contrast, the production of H2S following the assimilation of exogenous SCN− is explicitly confined to chloroplasts and mitochondria. This phenomenon indicates complex interplay and communication among various subcellular organelles, influencing signal transduction and other vital physiological processes. This review, augmented by a small-scale experimental study, endeavors to provide insights into the functional characteristics of H2S signaling in plants subjected to SCN−-stress. Furthermore, a comparative analysis of the occurrence and trajectory of endogenous H2S and H2S derived from SCN−-assimilation within plant organisms was performed, providing a focused lens for a comprehensive examination of the multifaceted roles of H2S in rice plants. By delving into these dimensions, our objective is to enhance the understanding of the regulatory mechanisms employed by the gasotransmitter H2S in plant adaptations and responses to SCN−-stress, yielding invaluable insights into strategies for plant resilience and adaptive capabilities.

The power semiconductor joining technology through sintering of copper nanoparticles is well-suited for die attachment in wide bandgap (WBG) semiconductors, offering high electrical, thermal, and mechanical performances. However, sintered nanocopper will be prone to degradation resulting from corrosion in sulfur-containing corrosive environments such as offshore areas. In this study, experiments, including aging test and corrosion characterization, and simulations based on density functional theory (DFT) studies were conducted to explore the corrosion behavior and mechanism of elemental sulfur (S8) and hydrogen sulfide (H2S) on sintered nanocopper. The experimental results indicated that loose corrosion products were observed on the sintered nanocopper during the ageing process involving S8, and compact layered corrosion products formed during the ageing process involving H2S. Furthermore, similar corrosion product compositions (Cu2O, Cu2S, CuO, CuS, and potentially Cu2SO4 or CuSO4) were observed in both the S8- and H2S-ageing processes. However, the S8-ageing process exhibited more noticeable corrosion penetration. This was explained in simulations results: the unsaturated Cu sites on the oxide layer [Cu2O(111)] of the sintered nanocopper could adsorb both H2S and S8, while the saturated Cu sites only exhibited the potential to adsorb S8.

Background: The glucose derivative 3-O-methyl-D-glucose (OMG) is used as a cryoprotectant in freezing cells. However, its protective role and the related mechanism in static cold storage (CS) of organs are unknown. The present study aimed to investigate the effect of OMG on cod ischemia damage in cold preservation of donor kidney. Methods: Pretreatment of OMG on kidney was performed in an isolated renal cold storage model in rats. LDH activity in renal efflux was used to evaluate the cellular damage. Indicators including iron levels, mitochondrial damage, MDA level, and cellular apoptosis were measured. Kidney quality was assessed via a kidney transplantation (KTx) model in rats. The grafted animals were followed up for 7 days. Ischemia reperfusion (I/R) injury and inflammatory response were assessed by biochemical and histological analyses. Results: OMG pretreatment alleviated prolonged CS-induced renal damage as evidenced by reduced LDH activities and tubular apoptosis. Kidney with pCS has significantly increased iron, MDA, and TUNEL+ cells, implying the increased ferroptosis, which has been partly inhibited by OMG. OMG pretreatment has improved the renal function (p

Abstract National surveys in developed countries have examined the presence of C3-epimer of 25-hydroxyvitamin D3 [C3-epi-25(OH)D3]. However, controversy remains regarding its association with disease occurrence due to its high correlation with 25-hydroxyvitamin D3 [25(OH)D3]. This study aims to investigate whether %C3-epi-25(OH)D3 can serve as an indicator for this relationship with various diseases. A total of 3086 healthy participants and 4120 patients were included in this study. We investigated the association between C3-epi-25(OH)D3 and %C3-epi-25(OH)D3 levels with gender, age, and season; compared the performance of C3-epi-25(OH)D3 and %C3-epi-25(OH)D3 across different disease conditions; and explored the correlation between %C3-epi-25(OH)D3 and various diseases. Results indicated that C3-epi-25(OH)D3 varied significantly by gender, age, and season (z/χ2 = 3.765, 10.163, and 150.975, all P

Abstract Background The occurrence of epithelial-mesenchymal transition (EMT) and immune evasion is considered to contribute to poor prognosis in lung adenocarcinoma (LUAD). Therefore, this study aims to explore the key oncogenes that promote EMT and immune evasion and reveal the expression patterns, prognostic value, and potential biological functions. Methods Firstly, we identified gene modules associated with EMT and Tumor Immune Dysfunction and Exclusion (TIDE) through weighted gene co-expression network analysis (WGCNA). Next, we utilized differential analysis and machine learning to identify the key genes and validate them. Moreover, we analyzed the correlation between key genes and tumor microenvironment remodeling, drug sensitivity, as well as mutation frequency. Furthermore, we explored and validated their malignant biological characteristics through in vitro experiments and clinical samples. Finally, potential drugs for LUAD were screened based on CMap and validated through experiments. Results Firstly, WGCNA analysis revealed that red and green modules were highly correlated with EMT and TIDE. Among them, upregulated expression of SPOCK1 was observed in lung adenocarcinoma tissues and was associated with poor prognosis. Additionally, patients in the high SPOCK1 group showed more activation of malignant oncogenic pathways, higher infiltration of immunosuppressive components, and a higher frequency of mutations. The knockdown of SPOCK1 suppressed invasion and metastasis capabilities of lung adenocarcinoma cells, and the high expression of SPOCK1 was associated with low infiltration of CD8+ T cells. Therapeutic aspects, SPOCK1 can be a candidate indicator for drug sensitivity and CMap showed that VER-155008 was the drug candidate with the largest perturbation effect on the SPOCK1 expression profile. In vitro and in vivo experiments validated the cancer-inhibitory effect of VER-155008 in LUAD. Conclusion This study revealed through comprehensive bioinformatics analysis and experimental analysis that SPOCK1 can promote EMT and immune escape in LUAD, and it may serve as a promising candidate prognostic biomarker and therapeutic target for LUAD.

Exosomes are nanoscale membrane-enclosed extracellular vesicles secreted by various cells, which have enormous potential as disease biomarkers for clinical application. However, the isolation and detection of exosomes remain enormous challenges, which limits their further application. Herein, inspired by immunomagnetic beads, a magnetic nanoparticle conjugated aptamer was repurposed for the effective capture and detection of exosomes. The magnetic nanoparticles, composed of Fe3O4 synthesized by the hydrothermal method as the core and coupled with gold nanoparticles (Fe3O4@Au), provide a large specific surface area, making the resulting composite material an effective platform for exosome capture. Furthermore, the elution of captured exosomes with 1.0 M NaCl made downstream analysis of exosomes possible. The preliminary clinical application value of the composite in exosome analyses of serum from healthy individuals and patients with Alzheimer's disease (AD) has also been verified, which could provide a promising platform for biomedical and clinical diagnosis.

Light penetration depth, as a characteristic parameter reflecting light attenuation and transmission in biological tissues, has been applied in nondestructive detection of fruits and vegetables. Recently, with emergence of new optical detection technologies, researchers have begun to explore methods evaluating optical properties of double-layer or even multilayer fruit and vegetable tissues due to the differences between peel and pulp in the chemical composition and physical properties, which has gradually promoted studies on light penetration depth. A series of demonstrated research on light penetration depth could ensure the accuracy of the optical information obtained from each layer of tissue, which is beneficial to enhance detection accuracy for quality assessment of fruits and vegetables. Therefore, the aim of this review is to give detailed outlines about the theory and principle of light penetration depth based on several emerging optical detection technologies and to focus primarily on its applications in the field of quality evaluation of fruits and vegetables, its future applicability in fruits and vegetables and the challenges it may face in the future.

Traditional lettuce counting relies heavily on manual labor, which is laborious and time-consuming. In this study, a simple and efficient method for localization and counting lettuce is proposed, based only on lettuce field images acquired by an unmanned aerial vehicle (UAV) equipped with an RGB camera. In this method, a new lettuce counting model based on the weak supervised deep learning (DL) approach is developed, called LettuceNet. The LettuceNet network adopts a more lightweight design that relies only on point-level labeled images to train and accurately predict the number and location information of high-density lettuce (i.e., clusters of lettuce with small planting spacing, high leaf overlap, and unclear boundaries between adjacent plants). The proposed LettuceNet is thoroughly assessed in terms of localization and counting accuracy, model efficiency, and generalizability using the Shanghai Academy of Agricultural Sciences-Lettuce (SAAS-L) and the Global Wheat Head Detection (GWHD) datasets. The results demonstrate that LettuceNet achieves superior counting accuracy, localization, and efficiency when employing the enhanced MobileNetV2 as the backbone network. Specifically, the counting accuracy metrics, including mean absolute error (MAE), root mean square error (RMSE), normalized root mean square error (nRMSE), and coefficient of determination (R2), reach 2.4486, 4.0247, 0.0276, and 0.9933, respectively, and the F-Score for localization accuracy is an impressive 0.9791. Moreover, the LettuceNet is compared with other existing widely used plant counting methods including Multi-Column Convolutional Neural Network (MCNN), Dilated Convolutional Neural Networks (CSRNets), Scale Aggregation Network (SANet), TasselNet Version 2 (TasselNetV2), and Focal Inverse Distance Transform Maps (FIDTM). The results indicate that our proposed LettuceNet performs the best among all evaluated merits, with 13.27% higher R2 and 72.83% lower nRMSE compared to the second most accurate SANet in terms of counting accuracy. In summary, the proposed LettuceNet has demonstrated great performance in the tasks of localization and counting of high-density lettuce, showing great potential for field application.

Previous neuroimaging studies have revealed abnormal brain networks in patients with major depressive disorder (MDD) in emotional processing. While any cognitive task consists of a series of stages, little is yet known about the topology of functional brain networks in MDD for these stages during emotional face recognition. To address this problem, electroencephalography (EEG)-based functional brain networks of MDD patients at different stages of facial information processing were investigated in this study. First, EEG signals were collected from 16 patients with MDD and 18 age-, gender-, and education-matched normal subjects when performing an emotional face recognition task. Second, the global field power (GFP) method was employed to divide group-averaged event-related potentials into different stages. Third, using the phase transfer entropy (PTE) approach, the brain networks of MDD patients and normal individuals were constructed for each stage in negative and positive face processing, respectively. Finally, we compared the topological properties of brain networks of each stage between the two groups using graph theory approaches. The results showed that the analyzed three stages of emotional face processing corresponded to specific neurophysiological phases, namely, visual perception, face recognition, and emotional decision-making. It was also demonstrated that depressed patients showed abnormally decreased characteristic path length at the visual perception stage of negative face recognition and normalized characteristic path length in the stage of emotional decision-making during positive face processing compared to healthy subjects. Furthermore, while both the MDD and normal groups’ brain networks were found to exhibit small-world network characteristics, the brain network of patients with depression tended to be randomized. Moreover, for patients with MDD, the centro-parietal region may lose its status as a hub in the process of facial expression identification. Together, our findings suggested that altered emotional function in MDD patients might be associated with disruptions in the topological organization of functional brain networks during emotional face recognition, which further deepened our understanding of the emotion processing dysfunction underlying MDD.

During operation in environments containing hydrogen sulfide (H2S), such as in offshore and coastal environments, sintered nanoCu in power electronics is susceptible to degradation caused by corrosion. In this study, experimental and molecular dynamics (MD) simulation analyses were conducted to investigate the evolution and mechanism of H2S-induced corrosion of sintered nanoCu, and bulk Cu was used as the reference. The following results are obtained: (1) Both sintered nanoCu and bulk Cu reacted with O2 prior to reacting with H2S, forming Cu2O, Cu2S, CuO, and CuS. In addition, sintered nanoCu exhibited more severe corrosion. (2) For both sintered nanoCu and bulk Cu, H2S-induced corrosion resulted in the deterioration of electrical, thermal, and mechanical properties, and sintered nanoCu experienced a greater extent of deterioration. (3) As was ascertained through Reactive Force Field (ReaxFF) MD simulations, the penetration of H2S and O2 combined with the upward migration of Cu resulted in the formation of a corrosion film. In addition, compared to bulk Cu, the H2S and O2 penetration in the sintered nanoCu structure was observed to occur to a greater depth, accounting for the more pronounced performance degradation.

Idiopathic pulmonary fibrosis (IPF) is a life-threatening disease characterized by severe pulmonary fibrosis, for which there is an urgent need for effective therapeutic agents. Mefloquine (Mef) is a quinoline compound primarily used for the treatment of malaria. However, high doses (>25 mg/kg) may lead to side effects such as cardiotoxicity and psychiatric disorders. Here, we found that low-dose Mef (5 mg/kg) can safely and effectively treat IPF mice. Functionally, Mef can improve the pulmonary function of IPF mice (PIF, PEF, EF50, VT, MV, PENH), alleviating pulmonary inflammation and fibrosis by inhibiting macrophage activity. Mechanically, Mef probably regulates the Jak2/Stat3 signaling pathway by binding to the 492HIS site of Potassium voltage-gated channel subfamily H member 2 (KCNH2) protein in macrophages, inhibiting the secretion of macrophage inflammatory and fibrotic factors. In summary, Mef may inhibit macrophage activity by binding to KCNH2 protein, thereby slowing down the progress of IPF.

IntroductionThe cold stress is one of the most important factors for affecting production throughout year, so effectively evaluating frost damage is great significant to the determination of the frost tolerance in lettuce.MethodsWe proposed a high-throughput method to estimate lettuce FDI based on remote sensing. Red-Green-Blue (RGB) and multispectral images of open-field lettuce suffered from frost damage were captured by Unmanned Aerial Vehicle platform. Pearson correlation analysis was employed to select FDI-sensitive features from RGB and multispectral images. Then the models were established for different FDI-sensitive features based on sensor types and different groups according to lettuce colors using multiple linear regression, support vector machine and neural network algorithms, respectively.Results and discussionDigital number of blue and red channels, spectral reflectance at blue, red and near-infrared bands as well as six vegetation indexes (VIs) were found to be significantly related to the FDI of all lettuce groups. The high sensitivity of four modified VIs to frost damage of all lettuce groups was confirmed. The average accuracy of models were improved by 3% to 14% through a combination of multisource features. Color of lettuce had a certain impact on the monitoring of frost damage by FDI prediction models, because the accuracy of models based on green lettuce group were generally higher. The MULTISURCE-GREEN-NN model with R2 of 0.715 and RMSE of 0.014 had the best performance, providing a high-throughput and efficient technical tool for frost damage investigation which will assist the identification of cold-resistant green lettuce germplasm and related breeding.

As a promising technology for high-power and high-temperature power electronics packaging, nanocopper (nanoCu) paste sintering has recently received increasing attention as a die-attachment. The high-temperature deformation of sintered nanoCu paste and its underlying mechanisms challenge the reliability of high-power electronics packaging. In this study, the tensile deformation behaviors of sintered nanoCu paste were firstly characterized by high-temperature tensile tests performed at various temperatures and strain rates ranging from 180 °C to 360 °C, 1 × 10−4 s−1 to 1 × 10−3 s−1 respectively. It was found that the elastic modulus and tensile strength decreased at the higher tensile temperature while the ductility increased accordingly. The highest elastic modulus and tensile strength results were 12.15 GPa and 46.97 MPa, respectively. Second, failure analysis was conducted based on the fracture surface after tensile testing. Recrystallization was revealed as the main factor for ductility improvement. Subsequently, an Anand model was fitted by stress-strain curves to describe the tensile constitutive behavior of the sintered nanoCu paste. Multi-scale modelling techniques also investigated the impact of tensile temperature and strain rate on the tensile response. Molecular dynamics simulation was implemented using a hemispherical Cu nanoparticle model to reveal the properties from an atomistic perspective. In addition, a two-dimensional equivalent model was further established by using a stochastically distributed void morphology. The multi-scale modelling techniques successfully describe the evolution of tensile response to the different tensile temperatures and strain rates. Besides, the equivalent model with random void morphology was demonstrated as the finite element simulation results were highly consistent with the high-temperature tensile experiments.

Abstract Background Two staging systems, the 8th staging system by the American Joint Committee on Cancer (AJCC) and the 11th Japanese classification by Japan Esophageal Society (JES), are currently applied in the clinic for predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC). The differences between the two staging systems have been widely researched. However, little studies focus on the differences in specific staging between the two systems. Therefore, we aimed to compare the performance of different staging in predicting overall survival (OS) of Chinese patients with ESCC. Methods This retrospective study included 268 patients who underwent radical esophagectomy and mediastinal lymph node dissection for ESCC between January 2008 and December 2013. Patients were staged by the 8th AJCC and 11th JES staging systems. OS was estimated using the Kaplan–Meier method and compared between N stages and between stage groupings using the log-rank test. Cox proportional hazards regression analysis was performed to identify factors independently related to outcome. Further, we compared the concordance indexes (C-indexes) of the two staging systems. Results The mean age was 61.25 ± 7.056 years, median follow-up was 44.82 months, and 5-year OS rate was 47%. The OS was well predicted by the 8th AJCC N staging (P

Abstract Nasopharyngeal carcinoma (NPC) is a common malignant epithelial tumor of the head and neck that often exhibits local recurrence and distant metastasis. The molecular mechanisms are understudied, and effective therapeutic targets are still lacking. In our study, we found that the transcription factor ZIC2 was highly expressed in NPC. Although ZIC family members play important roles in neural development and carcinogenesis, the specific mechanism and clinical significance of ZIC2 in the tumorigenesis and immune regulation of NPC remain elusive. Here, we first reported that high expression of ZIC2 triggered the secretion of MCSF in NPC cells, induced M2 polarization of tumor-associated macrophages (TAMs), and affected the secretion of TAM-related cytokines. Mechanistically, ChIP-seq and RNA-seq analyses identified JUNB as a downstream target of ZIC2. Furthermore, ZIC2 was significantly enriched in the promoter site of JUNB and activated JUNB promoter activity, as shown by ChIP-qPCR and luciferase assays. In addition, JUNB and MCSF participated in ZIC2-induced M2 TAMs polarization. Thus, blocking JUNB and MCSF could reverse ZIC2-mediated M2 TAMs polarization. Moreover, Kaplan-Meier survival analyses indicated that high expression of ZIC2, JUNB, and CD163 was positively associated with a poor prognosis in NPC. Overexpression of ZIC2 induced tumor growth in vivo, with the increase of JUNB, MCSF secretion, and CD163. In summary, our study implies that ZIC2 induces M2 TAM polarization, at least in part through regulation of JUNB/MCSF and that ZIC2, JUNB, and CD163 can be utilized as prognostic markers for NPC and as therapeutic targets for cancer immunotherapy.

Accurately classifying the quality of apples is crucial for maximizing their commercial value. Deep learning techniques are being widely adopted for apple quality classification tasks, achieving impressive results. While existing research excels at classifying apple variety, size, shape, and defects, color and deformity analysis remain an under-explored area. Therefore, this study investigates the feasibility of utilizing convolutional neural networks (CNN) to classify the color and deformity of apples based on machine vision technology. Firstly, a custom-assembled machine vision system was constructed for collecting apple images. Then, image processing was performed to extract the largest fruit diameter from the 45 images taken for each apple, establishing an image dataset. Three classic CNN models (AlexNet, GoogLeNet, and VGG16) were employed with parameter optimization for a three-category classification task (non-deformed slice–red apple, non-deformed stripe–red apple, and deformed apple) based on apple features. VGG16 achieved the best results with an accuracy of 92.29%. AlexNet and GoogLeNet achieved 91.66% and 88.96% accuracy, respectively. Ablation experiments were performed on the VGG16 model, which found that each convolutional block contributed to the classification task. Finally, prediction using VGG16 was conducted with 150 apples and the prediction accuracy was 90.50%, which was comparable to or better than other existing models. This study provides insights into apple classification based on color and deformity using deep learning methods.

In response to the limitations of existing methods in differentiating between vegetables and all types of weeds in farmlands, a new image segmentation method is proposed based on the improved YOLOv7-tiny. Building on the original YOLOv7-tiny framework, we replace the CIoU loss function with the WIoU loss function, substitute the Leaky ReLU loss function with the SiLU activation function, introduce the SimAM attention mechanism in the neck network, and integrate the PConv convolution module into the backbone network. The improved YOLOv7-tiny is used for vegetable target detection, while the ExG index, in combination with the OTSU method, is utilized to obtain a foreground image that includes both vegetables and weeds. By integrating the vegetable detection results with the foreground image, a vegetable distribution map is generated. Subsequently, by excluding the vegetable targets from the foreground image using the vegetable distribution map, a single weed target is obtained, thereby achieving accurate segmentation between vegetables and weeds. The experimental results show that the improved YOLOv7-tiny achieves an average precision of 96.5% for vegetable detection, with a frame rate of 89.3 fps, Params of 8.2 M, and FLOPs of 10.9 G, surpassing the original YOLOv7-tiny in both detection accuracy and speed. The image segmentation algorithm achieves a mIoU of 84.8% and an mPA of 97.8%. This method can effectively segment vegetables and a variety of weeds, reduce the complexity of segmentation with good feasibility, and provide a reference for the development of intelligent plant protection robots.