Search

Abstract Background Previous observational studies have suggested diabetic patients should synchronize their foods and nutrient intake with their biological rhythm; however, the optimal intake time of coffee and tea for reducing all-cause and disease-specific mortality in diabetes is still unknown. This study aims to examine by investigating the association of timing for coffee and tea consumption with long-term survival in people with diabetes. Methods A total of 5378 people with diabetes who enrolled in the National Health and Nutrition Examination Survey from 2003 to 2014 were recruited for this study. Coffee and tea intakes were measured by a 24-h dietary recall, which were divided by different time intervals across the day, including dawn to forenoon, forenoon to noon, noon to evening, and evening to dawn. Weighted cox proportional hazards regression models were developed to evaluate the survival-relationship of coffee and tea consumption with mortality of all-cause, cardiovascular disease (CVD), stroke, and diabetes. Results During 47,361 person-year follow up, total 1639 death cases were documented, including 731 CVD deaths, 467 heart disease deaths, 99 stroke deaths, and 462 diabetes deaths. After adjustment for potential confounders, compared with participants without drinking coffee during dawn to forenoon, drinking coffee at this period was associated with increased mortality risk of all-cause (HR 1.25, 95% CI 1.05–1.50), CVD (HR 1.41, 95% CI 1.07–1.86), heart-disease (HR 1.47, 95% CI 1.05–2.07), and diabetes (HR 1.50, 95% CI 1.10–2.04). In contrast, drinking coffee during forenoon to noon had lower mortality risk of all-cause (HR 0.80, 95% CI 0.69–0.92), CVD (HR 0.79, 95% CI 0.63–0.99), and heart disease (HR 0.70, 95% CI 0.52–0.94). Similarly, drinking tea during forenoon to noon had lower risk of CVD mortality (HR = 0.62, 95% CI 0.44–0.87). Conclusions This study suggests that drinking coffee in dawn to forenoon is linked to a higher risk of death, but having coffee and tea from forenoon to noon is linked to a lower risk of overall mortality, CVD, and heart disease in individuals with diabetes. Graphical Abstract

Autoimmune encephalitis (AE) associated with autoantibodies against γ-aminobutyric acid-B receptor (GABABR-AE) is frequently identified in middle-aged and elderly males. The disease is characterized by seizures, mental, and behavioral abnormalities, as well as recent memory decline. Anti-GABABR antibody-associated encephalitis, presenting with syncope as the first symptom is rare. Here we report a case of AE with syncope as the first symptom. A 55-year-old male presented to the emergency department with transient loss of consciousness, initially diagnosed as syncope. As the disease progressed, the patient exhibited seizures, abnormal mental behavior, and cognitive impairment. Ultimately, the patient was diagnosed with right lung small cell lung cancer. The initial atypical symptoms and the lack of clear imaging features of GABABR encephalitis hinder early diagnosis. This case highlights the importance of screening for the underlying etiology of syncope in middle-aged and elderly patients.

Abstract Background Dental filling is a prevalent method for treating dental defects. This study aimed to investigate the knowledge, attitude, and practice (KAP) toward dental defects and dental fillings among dental patients in Jinan, Shandong Province, China. Methods This cross-sectional study was conducted at the main campus and several branch campuses of Jinan Stomatological Hospital, and community locations within Jinan city between October 2023, and January 2024. Spearman correlation analysis and mediation analysis were used to assess the associations and interrelationships between KAP scores. Results In this study, 2529 dental patients participated, with 69.1% being females. Of these, 1711 had no dental defects, 551 had defects and fillings, and 267 had defects without fillings. Their median knowledge, attitude, and practice (Questions 1–6) scores were 8.00 [5.00, 12.00] (possible range: 0–18), 27.00 [26.00, 29.00] (possible range: 10–50), and 19.00 [15.00, 24.00] (possible range: 9–45), respectively. Mediation analysis revealed that in patients without dental defects, knowledge had a direct effect on attitude (β = -0.983, 95% CI: -0.999, -0.966, P

Abstract Aim The aim of this review is to evaluate and summarize the evidence for preoperative visit-care of transcatheter aortic valve replacement (TAVR) and to provide evidence-based support for clinical intervention. Design The review presents an evidence summary report, following the standard of the Fudan University Center for Evidence-based Nursing. Methods Literature related to preoperative visit-care for transcatheter aortic valve replacement have been retrieved based on the “6S” pyramid model of evidence. The types of literature included systematic reviews, expert consensus, evidence summary, and guidelines. Data sources Up To Date, Cochrane Library, Joanna Briggs Institute, National Institute for Health and Care Excellence, Medlive, American Heart Association, Registered Nurses Association of Ontario, Scottish Intercollegiate Guidelines Network, European Society of Cardiology, American College of Cardiology, PubMed, CINAHL, Wanfang database, VIP database, Chinese biomedical literature database, CNKI. The search period is limited to the time when each database was established until February 2024. Results A total of 18 articles were included in this review, consisting of 1 systematic review, 1 evidence summary, 3 guidelines and 13 expert consensuses. This review summarized 30 pieces of the best evidence for preoperative visit-care for transcatheter aortic valve replacement, encompassing three evidence themes: multidisciplinary team collaboration, preoperative assessment, and preoperative education. Conclusion The study has established an ideal foundation of evidence for preoperative visit-care in TAVR. However, throughout the particular application process, it was crucial to assess the feasibility and relevance of the evidence in clinical practice by taking into account elements such as the application setting, recommendations from experts with diverse expertise, and the preferences of the patients.

Abstract Background We aimed to develop multiple machine learning models to predict the risk of early intracranial aneurysms (IAs) rupture, evaluate and compare the performance of predictive models. Methods Information related to patients diagnosed with IA by CT angiography and clinicians in Central hospital of Dalian University of Technology from January 2010 to June 2022 was collected, including clinical characteristics, blood indicators and IA morphological parameters. IA with rupture or maximum growth ≥ 0.5 mm within 1 month of first diagnosis was considered unstable. The relevant factors affecting IA stability were screened and predictive models were developed based on the above three levels, including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). Sensitivity, specificity, accuracy and area under curve (AUC) value were used to evaluate the predictive models. Results A total of 989 IA patients were included in the study, including 561 stable patients and 428 unstable patients. For RF models, the training set showed that sensitivity, specificity, accuracy and the AUC values were 72.8–83.7%, 76.9–86.9%, 75.1–84.1% and 0.748 (0.719–0.778)–0.839 (0.814–0.864), respectively; after test set validation, the results were 71.9–78.8%, 75.0–84.0%, 73.6–81.1% and 0.734 (0.688–0.781)–0.809 (0.768–0.850), respectively. For SVM models, the training set were 66.0–80.2%, 76.5–85.5%, 71.7–82.3%, 0.712 (0.682–0.743)–0.913 (0.884–0.924), respectively; the test set were 44.2–78.3%, 63.4–84.4%, 57.9–80.9%, 0.699 (0.651–0.747)–0.806 (0.765–0.848), respectively. For ANN models, the training set were 66.8–83.0%, 75.3–82.3%, 71.6–82.1%, 0.783 (0.757–0.808)–0.897 (0.879–0.914); the test set were 63.1–76.3%, 65.5–84.0%, 64.4–80.6%, 0.680 (0.593–0.694)–0.860 (0.821–0.899). The results of variable importance showed that age, white blood cell count (WBC) and uric acid (UA) played an important role in predicting the stability of IA. Conclusions The predictive stability models of IA based on three artificial intelligence methods shows good clinical application. Age, WBC and UA played an important role in predicting the IA stability, and were potentially important predictors.

Abstract Background This study explores the factors contributing to the occurrence of delirium following cardiac surgery and devises nursing strategies rooted in behavior change theory. Methods A cohort of 320 cardiac surgery patients was selected, categorized into two groups: 93 cases where postoperative delirium (POD) was anticipated, and 227 cases where it was not. Preoperative, intraoperative, and postoperative factors of POD were scrutinized using single-factor analysis, while binary logistic regression analysis was employed to pinpoint risk factors. Results Among the 320 patients, 93 displayed POD symptoms post-surgery, yielding an incidence of 29.06%. Preoperative univariate analysis disclosed significant differences in gender, age, smoking, hypertension, and diabetes (P

Abstract Gastric premalignant lesions can develop into cancer through multiple steps and inflammation plays a critical role. The aim of this study is to uncover the characteristics of macrophages and their gene expression in premalignant gastric lesions to identify novel biomarkers and potential targets for treatment. We used the computational algorithm CIBERSORT to estimate immune cell subsets present in gastric tissue. We applied WGCNA to identify inflammation-related modules and hub genes. Single-cell analysis was used to identify macrophage sub-clusters specific to pathology. In addition, the in-vitro experiment was performed to verify the mechanism of the key inflammatory factors in the growth of gastric cancer. WGCNA identified a module that was positively correlated with pathological changes and highly related to inflammation scores. Single-cell analysis revealed a macrophage subset, and we observed that S100A8 and S100A9 + macrophages made up a significantly higher proportion in early gastric cancer (EGC) tissues. Our functional enrichment analysis suggested that these macrophages may play a role in gastric tumorigenesis through the activation of the NFκB signaling pathway. In vitro experiments verified that S100A9 can promote the proliferation and migration of AGS cells through the TLR4-NFκB signaling pathway, and the S100A8/S100A9 inhibitor Paquinimod can inhibit their proliferation and migration. Our findings suggest that S100A8 and S100A9 + macrophages may activate the TLR4-NFκB signaling pathway to promote cell proliferation and migration leading to gastric tumor progression. Macrophages with high expression of S100A8/S100A9 are critical in the progression of gastric inflammation to cancer. Cytokine S100A9 can activate the TLR4-NFκB signaling pathway and promote the proliferation and migration of gastric adenocarcinoma cells.

Abstract Background Up to 17% of cancer survivors have been reported to develop second primary cancers (SPC), which cause significant physical and economic distress and often complicate clinical decision-making. However, understanding of SPC remains limited and superficial. Human leukocyte antigen (HLA) is characterized by its polymorphism and has been associated with various diseases. This study aims to explore the role of HLA diversity in SPC incidence. Methods We analyzed a cohort of 47,550 cancer patients from the UK Biobank. SNP-derived HLA alleles were used and SPC-related HLA alleles were identified using logistic regression, followed by stepwise filtering based on the Akaike information criterion (AIC) and permutation tests. Additionally, we examined the association between extragenetic factors and the risk of SPC in patients carrying hazardous HLA alleles. Results During a median follow-up of 3.11 years, a total of 2894 (6.09%) participants developed SPC. We identified three protective HLA alleles (DRB1*04:03 and DPA1*02:02 for males and DRB5*01:01 for females) and two hazardous alleles (A*26:01 for males and DPB1*11:01 for females) about SPC. The presence of the protective alleles was associated with a reduced SPC risk (males: hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.59–0.89; females: HR 0.81, 95% CI 0.70–0.93), while the hazardous alleles were linked to an increased risk (males: HR 1.27, 95% CI 1.03–1.56; females: HR 1.35, 95% CI 1.07–1.70). The hazardous allele A*26:01 indicated skin-lung organ-specific SPC occurrence in males. Animal fat and vitamin C were associated with SPC risk in males carrying the hazardous alleles, while free sugar and vegetable fat were linked to SPC risk in females. Conclusions These results suggest that HLA alleles may serve as biomarkers for the susceptibility and organ-specific occurrence of SPC, while dietary modulation may mitigate hazardous alleles-related SPC risk, potentially aiding in the early prediction and prevention of SPC.

Abstract Epilepsy is one of the most common symptoms in patients with gliomas; however, the mechanisms underlying its interaction are not yet clear. Moreover, epidemiological studies have not accurately identified patients with glioma-related epilepsy (GRE), and there is an urgent need to identify the molecular mechanisms and markers of its occurrence. We analyzed the demographics, transcriptome, whole-genome, and methylation sequences of 997 patients with glioma, to determine the genetic differences between glioma and GRE patients and to determine the upregulated molecular function, cellular composition, biological processes involved, signaling pathways, and immune cell infiltration. Twelve machine learning algorithms were refined into 113 combinatorial algorithms for building diagnostic recognition models. A total of 342 patients with GRE were identified with WHO grade 2 (174), grade 3 (107), and grade 4 (61). The mean age of the patients with GREs, with IDH mutations (n = 217 [63%]) and 1p19q non-codeletion (n = 169 [49%]), was 38 years old. GRE molecular functions were mainly passive transmembrane transporter protein activity, ion channel activity, and gated channel activity. Cellular components were enriched in the cation-channel and transmembrane transporter complexes. Cerebral cortical development regulates the membrane potential and synaptic organization as major biological processes. The signaling pathways mainly focused on cholinergic, GABAergic, and glutamatergic synapses. LASSO, combined with Random Forest, was the best diagnostic model and identified nine diagnostic genes. This study provides new insights and future perspectives for resolving the molecular mechanisms of GRE.

Abstract Background In terms of predicting surgery mortality, it is controversial whether red blood cell width works independently. In non-cardiac surgery patients older than 18 years, we intend to examine the relationship between red blood cell width and postoperative 30-day mortality. Methods In this retrospective cohort study, 90,785 Singapore General Hospital patients were matched by propensity score between January 1, 2012 and October 31, 2016. It was determined that red blood cell width at baseline and mortality within 30 days after surgery were the independent and dependent variables. We used a non-parametric multivariate logistic regression to balance the confounders among 7807 patients with high RDW and 7807 patients with non-high RDW in the propensity score matching. We investigated the association between RDW and 30-day mortality after surgery using the doubly robust estimation method. Results Cohorts matched according to propensity score, the risk of 30-day mortality after surgery increased by 114.6.0% among the high RDW group (OR = 2.146, 95% CI 1.645–2.799, P

Abstract Background Identification of active components of traditional Chinese Medicine (TCM) and their respective targets is important for understanding the mechanisms underlying TCM efficacy. However, there are still no effective technical methods to achieve this. Methods Herein, we have established a method for rapidly identifying targets of a specific TCM and interrogating the targets with their corresponding active components based on Isothermal Shift Assay (iTSA) and database interrogation. Results We optimized iTSA workflow and identified 110 targets for Danhong injection (DHI) which is used as an effective remedy for cardiovascular and cerebrovascular diseases. Moreover, we identified the targets of the nine major ingredients found in DHI. Database interrogation found that the potential targets for DHI, in which we verified that ADK as the target for salvianolic acid A and ALDH1B1 as the target for protocatechualdehyde in DHI, respectively. Conclusion Overall, we established a novel paradigm model for the identification of targets and their respective ingredients in DHI, which facilitates the discovery of drug candidates and targets for improving disease management and contributes to revealing the underlying mechanisms of TCM and fostering TCM development and modernization. Graphical Abstract

Abstract Background The global rise in developmental delays underscores the critical need for a thorough understanding and timely interventions during early childhood. Addressing this issue, the Chinese Baby Connectome Project (CBCP)’s behavior branch is dedicated to examining language acquisition, social-emotional development, and environmental factors affecting Chinese children. The research framework is built around three primary objectives: developing a 0–6 Child Development Assessment Toolkit, implementing an Intelligent Coding System, and investigating environmental influence. Methods Utilizing an accelerated longitudinal design, the CBCP aims to enlist a minimum of 1000 typically developing Chinese children aged 0–6. The data collected in this branch constitutes parental questionnaires, behavioral assessments, and observational experiments to capture their developmental milestones and environmental influences holistically. The parental questionnaires will gauge children’s developmental levels in language and social-emotional domains, alongside parental mental well-being, life events, parenting stress, parenting styles, and family relationships. Behavioral assessments will involve neurofunctional developmental evaluations using tools such as the Griffiths Development Scales and Wechsler Preschool and Primary Scale of Intelligence. Additionally, the assessments will encompass measuring children’s executive functions (e.g., Head-Toe-Knee-Shoulder), social cognitive abilities (e.g., theory of mind), and language development (e.g., Early Chinese Vocabulary Test). A series of behavior observation. experiments will be conducted targeting children of different age groups, focusing primarily on aspects such as behavioral inhibition, compliance, self-control, and social-emotional regulation. To achieve the objectives, established international questionnaires will be adapted to suit local contexts and devise customized metrics for evaluating children’s language and social-emotional development; deep learning algorithms will be developed in the observational experiments to enable automated behavioral analysis; and statistical models will be built to factor in various environmental variables to comprehensively outline developmental trajectories and relationships. Discussion This study’s integration of diverse assessments and AI technology will offer a detailed analysis of early childhood development in China, particularly in the realms of language acquisition and social-emotional skills. The development of a comprehensive assessment toolkit and coding system will enhance our ability to understand and support the development of Chinese children, contributing significantly to the field of early childhood development research. Trial registration This study was registered with clinicaltrials.gov NCT05040542 on September 10, 2021.

Objective Increasing breast meat production is one of the primary goals of the broiler industry. Over the past few decades, tremendous progress has been made in genetic selection and the identification of candidate genes for improving the breast muscle mass. However, the molecular network contributing to muscle production traits in chickens still needs to be further illuminated. Methods A total of 150 1-day-old male 817 broilers were reared in a floor litter system. At the market age of 50 d, eighteen healthy 817 broilers were slaughtered and the left pectoralis major muscle sample from each bird was collected for RNA-seq sequencing. The birds were then plucked and eviscerated and the whole breast muscle was removed and weighed. Breast muscle yield was calculated as the ratio of the breast muscle weight to the eviscerated weight. To identify the co-expression networks and hub genes contributing to breast muscle yield in chickens, we performed weighted gene co-expression network analysis (WGCNA) based on the 18 transcriptome datasets of pectoralis major muscle from eighteen 817 broilers. Results The WGCNA analysis classified all co-expressed genes in the pectoral muscle of 817 broilers into 44 modules. Among these modules, the turquoise and skyblue3 modules were found to be most significantly positively (r = 0.78, p = 1e–04) and negatively (r = −0.57, p = 0.01) associated with breast meat yield, respectively. Further analysis identified several hub genes (e.g., DLX3, SH3RF2, TPM1, CAV3, MYF6, and CFL2) that involved in muscle structure and muscle development were identified as potential regulators of breast meat production. Conclusion The present study has advanced our understanding of the molecular regulatory networks contributing to muscle growth and breast muscle production and will contribute to the molecular breeding of chickens in the future.

Background The phenomenon of coronary slow flow (CSF) is characterized by recurrent angina pectoris, which may lead to acute myocardial infarction, fatal arrhythmia and sudden cardiac death, and reduce the quality of life of patients. With the improvement of the safety, feasibility and reliability of coronary angiography (CAG), the detection rate of CSF increased gradually. However, there are few studies on the mechanism of early-onset CSF and clinical characteristics of young patients with CSF. Objective To explore the clinical characteristics in young patients with CSF and compare them with the elderly patients in order to provide its pathogenesis. Methods Continuity analysis from January 2017 to January 2019, 86 young patients (18 years ≤ age

By establishing the characterization model of variable sectional area distributions, a cascade design method of torque converter based on variable sectional area distribution is proposed. Additionally, the corresponding collaborative design method for multi-impeller turbomachinery is proposed and further studied. The design cases of the impellers with different sectional area distributions are constructed through the response surface method, and the corresponding hydrodynamic characteristics are further compared and explored. However, the design of different impeller sectional area distributions for the optimal performance of the whole turbomachinery requires the collaborative design of each component’s distribution results rather than a simple combination of such optimal impeller’s area distribution result. Thus a collaborative design strategy is proposed, which can improve the pump’s capacity performance by 8.83%, the maximum torque ratio performance can also increased by 6.33%, which proves that such a collaborative design method is an effective optimization design approach to improve the performance of the torque converter without altering the overall dimension. The experimental results of the optimal prototype show that the torque ratio reaches 5.33% higher than the original value, which indicates that such a collaborative optimization method for multi-impeller turbomachinery is effective and reliable.

Ulcerative colitis (UC) is a kind of inflammatory bowel disease. Female patients with UC may face nutritional problems during pregnancy, therefore, the management of nutritional status and disease conditions is important to pregnant women with UC. For example, nausea and vomiting of pregnancy (NVP) lasting until the middle and late stages of pregnancy can further aggravate the difficulty of nutrition management during pregnancy in UC patients. In this paper, we report a case of nutritional management of a patient with UC and persistent NVP during pregnancy, with the aim of sharing our experience in dealing with complex nutritional problems during pregnancy.

Abstract Background Maternal feeding practices play a major role in children’s dietary intakes. However, there is limited data on the associations between trajectories of dietary patterns (DPs) and patterns of maternal feeding practices during early childhood. Methods Using data from a multi-ethnic Asian cohort study, namely the Growing Up in Singapore Towards healthy Outcomes (GUSTO), dietary intakes were measured using Food Frequency Questionnaires in children at 18 months, 5 and 7 years of age. Maternal feeding practices were assessed using validated questionnaires at 15 months, 3 and 5 years of age. Principal component analysis was used to derive 2 major DPs at all time-points as well as patterns of maternal feeding practices. Group-based trajectory modelling was used to identify trajectory groups for the derived DPs. Multivariable logistic regression examined associations between patterns of maternal feeding practices and DP trajectory groups. Results Two DPs, namely the ‘healthy’ and ‘less healthy’ were consistently derived at 18 months, 5 and 7 years of age. From each DP, 2 stable DP trajectory groups were further identified between 18 months and 7 years of age. For the ‘healthy’ DP trajectory, majority of the children (Group 1) formed a consistent average adherence trajectory group (91.8%) while the remaining children (Group 2) showed a higher but decreasing adherence (8.2%) to this DP. For the ‘less healthy’ DP trajectory, most children (Group 1) formed a consistent average adherence trajectory (95.5%), while the remainder (Group 2) showed consistent higher adherence to this ‘less healthy’ DP (4.5%). Two patterns of maternal feeding practices were derived and labelled as ‘structured with autonomy support’ and ‘coercive control’, respectively, at ages 15 months, 3 and 5 years. Children whose mothers showed high adherence to the structured with autonomy support feeding practices at age 5 years were significantly more likely to be associated with the higher but decreasing ‘healthy’ DP trajectory group [OR = 3.62 (95% CI: 1.64, 7.99)]. Conclusions A small number of children in this multi-ethnic study showed high adherence to the ‘healthy’ or ‘less healthy’ DP trajectory groups, respectively, while the majority showed average adherence to either of these trajectories. The positive association between structured with autonomy support maternal feeding practices and higher z-scores for the healthy DP trajectory highlights the importance of guiding parents on appropriate feeding practices.

Abstract Background Preoperative visit-care for transcatheter aortic valve replacement (TAVR) plays a crucial role in improving the quality of care and patient safety. However, preoperative care for TAVR patients is still in its early stages in China, with the care often being experience-based. The application of relevant evidence in nursing practice is necessary. Little is known regarding the facilitators and barriers to apply and compliance to the evidences about preoperative visit-care for TAVR in nursing. Methods The Nurse’s Compliance Checklist was used to investigate the evidence-based compliance of nurses (n = 21) who worked in the TAVR team in the evidence-based implementation setting. Meanwhile, an Evidence-Based Practice Beliefs Scale, and Influencing Factors Checklist were used to investigate all nurses (n = 66) who work in the same setting. Stakeholders (Middle and senior-level nursing administrators, frontline clinical nurses, and patients) interview was carried out to further disclose the barriers and facilitators in the process of evidence-based practice. Results The results of this study showed that only 1 evidence implemented fully (100%) by nurses, 3 evidences with 0% implementation rate, and implementation rate of the other evidences were 9.5∼71.4%. The overall score of nurses’ evidence-based nursing belief level was (3.52 ± 0.82). Three domains of barriers were identified: the Context Domain included lack of nursing procedures, inadequate health education materials, insufficient training; the Practitioner Domain included insufficient attention, lack of relevant knowledge, high work pressure and uncertainty of expected results, and Patient Domain included lack of relational knowledge. Facilitating factors included leadership support, nurse’ high evidence-based nursing belief, high executive ability and enthusiasm for learning. Conclusion The study indicated that the nurses’ compliance of evidence-based practice in preoperative visit-care for TAVR was in lower level. There were some factors influencing the application of the evidences. The study revealed potential modifiable barriers to the successful implementation of evidence-based preoperative visit-care, including a lack of preoperative visit- care routine, related knowledge and training. Leadership support and nurse training should be considered to improve nurses’ compliance with evidence-based practice.

Abstract Objective To evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa). Materials and methods A retrospective study was performed on 126 patients with BCa who underwent DECT urography (DECTU) in our hospital. Patients were randomly divided into training and test cohorts with a ratio of 7:3. Quantitative parameters derived from DECTU were identified through univariate and multivariate logistic regression analysis to construct a DECT model. Radiomics features were extracted from the 40, 70, 100 keV and iodine-based material-decomposition (IMD) images in the venous phase to construct radiomics models from individual and combined images using a support vector machine classifier, and the optimal performing model was chosen as the final radiomics model. Subsequently, a fusion model combining the DECT parameters and the radiomics model was established. The diagnostic performances of all three models were evaluated through receiver operating characteristic (ROC) curves and the clinical usefulness was estimated using decision curve analysis (DCA). Results The normalized iodine concentration (NIC) in DECT was an independent factor in diagnosing muscle invasion of BCa. The optimal multi-image radiomics model had predictive performance with an area-under-the-curve (AUC) of 0.867 in the test cohort, better than the AUC = 0.704 with NIC. The fusion model showed an increased level of performance, although the difference in AUC (0.893) was not statistically significant. Additionally, it demonstrated superior performance in DCA. For lesions smaller than 3 cm, the fusion model showed a high predictive capability, achieving an AUC value of 0.911. There was a slight improvement in model performance, although the difference was not statistically significant. This improvement was observed when comparing the AUC values of the DECT and radiomics models, which were 0.726 and 0.884, respectively. Conclusion The proposed fusion model combing NIC and the optimal multi-image radiomics model in DECT showed good diagnostic capability in predicting muscle invasiveness of BCa.

Abstract Schizophrenia (SZ) is a severe psychiatric disorder characterized by perceptual, emotional, and behavioral abnormalities, with cognitive impairment being a prominent feature of the disorder. Recent studies demonstrate irregularity in SZ with increased variability on the neural level. Is there also irregularity on the psychophysics level like in visual perception? Here, we introduce a methodology to analyze the irregularity in a trial-by-trial way to compare the SZ and healthy control (HC) subjects. In addition, we use an unsupervised clustering algorithm K-means + + to identify SZ subgroups in the sample, followed by validation of the subgroups based on intraindividual visual perception variability and clinical symptomatology. The K-means + + method divided SZ patients into two subgroups by measuring durations across trials in the motion discrimination task, i.e., high, and low irregularity of SZ patients (HSZ, LSZ). We found that HSZ and LSZ subgroups are associated with more negative and positive symptoms respectively. Applying a mediation model in the HSZ subgroup, the enhanced irregularity mediates the relationship between visual perception and negative symptoms. Together, we demonstrate increased irregularity in visual perception of a HSZ subgroup, including its association with negative symptoms. This may serve as a promising marker for identifying and distinguishing SZ subgroups.

Abstract Background To establish the pathological diagnosis of UTUC before treatment is profitable. At present, the conventional pathological diagnostic methods have certain problems. Besides, the urine-based DNA methylation test have been already utilized to detect bladder cancer. Objective To evaluate the sensitivity and specificity of DNA methylation plus 17 genes mutation test and compare the combined test with cytology. Materials and methods We included 45 patients from April 2019 to May 2022, all of whom underwent radical nephroureterectomy (RNU), nephrectomy, diagnostic ureteroscopy or tissue biopsy. Before surgery, the urine samples were collected for DNA methylation plus 17 genes mutation test and cytology. The test performance was calculated, and comparative ROC curves were drawn. Results The median age of the patients was 67 years. The Kappa value of the DNA methylation plus 17 genes mutation test and tissue pathology was 0.59 (p

Abstract The rapid variation of influenza challenges vaccines and treatments, which makes an urgent task to develop the high-efficiency and low-toxicity new anti-influenza virus drugs. Selenium is one of the essential trace elements for the human body that possesses a good antiviral activity. In this study, we assessed anti-influenza A virus (H1N1) activity of polyethylene glycol (PEG)-modified gray selenium nanoparticles (PEG-SeNPs) on Madin-Darby Canine Kidney (MDCK) cells in vitro. CCK-8 assay showed that PEG-SeNPs had a protective effect on H1N1-infected MDCK cells. Moreover, PEG-SeNPs significantly reduced the mRNA level of H1N1. TUNEL-DAPI test showed that DNA damage reached a high level but effectively prevented after PEG-SeNPs treatment. Meanwhile, JC-1, Annexin V-FITC and cell cycle assay demonstrated the apoptosis induced by H1N1 was reduced greatly when treated with PEG-SeNPs. Furthermore, the downregulation of p-ATM, p-ATR and P53 protein, along with the upregualation of AKT protein indicated that PEG-SeNPs could inhibit H1N1-induced cell apoptosis through reactive oxygen species (ROS)-mediated related signaling pathways. Finally, Cytokine detection demonstrated PEG-SeNPs inhibited the production of pro-inflammatory factors after infection, including IL-1β, IL-5, IL-6, and TNF-α. To sum up, PEG-SeNPs might become a new potential anti-H1N1 influenza virus drug due to its antiviral and anti-inflammatory activity.

Abstract Revealing the heterogeneity among tissues is the greatest advantage of single-cell-sequencing. Marker genes not only act as the key to correctly identify cell types, but also the bio-markers for cell-status under certain experimental imputations. Current analysis methods such as Seurat and Monocle employ algorithms which compares one cluster to all the rest and select markers according to statistical tests. This pattern brings redundant calculations and thus, results in low calculation efficiency, specificity and accuracy. To address these issues, we introduce starTracer, a novel algorithm designed to enhance the efficiency, specificity and accuracy of marker gene identification in single-cell RNA-seq data analysis. starTracer operates as an independent pipeline, which exhibits great flexibility by accepting multiple input file types. The primary output is a marker matrix, where genes are sorted by the potential to function as markers, with those exhibiting the greatest potential positioned at the top. The speed improvement ranges by 2 ~ 3 orders of magnitude compared to Seurat, as observed across three independent datasets with lower false positive rate as observed in a simulated testing dataset with ground-truth. It’s worth noting that starTracer exhibits increasing speed improvement with larger data volumes. It also excels in identifying markers in smaller clusters. These advantages solidify starTracer as an important tool for single-cell RNA-seq data, merging robust accuracy with exceptional speed.

The increase in extreme precipitation (EP) may pose a serious threat to the health and safety of population in arid and semi-arid regions. The current research on the impact of EP on population in Central Asia (CA) is insufficient and there is an urgent need for a comprehensive assessment. Hence, we opted for precipitation and temperature data under two Shared Socioeconomic Pathways (SSP2–4.5 and SSP5–8.5) from ten Global Climate Models (GCMs), which were obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). By integrating population data in 2020 and 2050 (SSP2 and SSP5), we investigated the future changes in EP and population exposure in CA under 1.5 °C and 2 °C global warming scenarios (GWSs). Our analysis indicates that EP in CA is projected to increase with global warming. Under the SSP5–8.5, the maximum daily precipitation (Rx1day) exhibits an average response rate to global warming of 3.58 %/K (1.99–4.06 %/K). With rising temperatures, an increasing number of areas and populations in CA will be impacted by EP, especially in the Fergana valley. Approximately 25% of the population (land area) in CA is exposed to Rx1day with increases of more than 8.31% (9.32%) under 1.5 °C GWS and 14.18% (13.25%) under 2 °C GWS. Controlling temperature rise can be effective in reducing population exposures to EP. For instance, limiting the temperature increase to 1.5 °C instead of 2 °C results in a 2.79% (1.75%–4.59%) reduction in population exposure to Rx1day. Finally, we found that climate change serves as the predominant factor influencing the population exposure to EP, while the role of population redistribution, although relatively minor, should not be disregarded. Particularly for prolonged drought, the role of population redistribution manifests negatively.

Objectives: Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders. Materials & methods: This was a retrospective analysis involving 120 patients with unresectable HCC. They were divided into training (n = 72) and validation (n = 48) cohorts. We developed an interpretable deep learning model using multiphase computed tomography (CT) images to predict whether patients will respond or not to CLICI treatment, based on the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1). We evaluated the models' performance and analyzed the impact of each CT phase. Critical regions influencing predictions were identified and visualized through heatmaps. Results: The multiphase model outperformed the best biphase and uniphase models, achieving an area under the curve (AUC) of 0.802 (95% CI = 0.780–0.824). The portal phase images were found to significantly enhance the model's predictive accuracy. Heatmaps identified six critical features influencing treatment response, offering valuable insights to clinicians. Additionally, we have made this model accessible via a web server at http://uhccnet.com/ for ease of use. Conclusions: The integration of multiphase CT images with deep learning-generated heatmaps for predicting treatment response provides a robust and practical tool for guiding CLICI therapy in patients with unresectable HCC.

Abstract Despite the importance of radiation therapy as a non-surgical treatment for non-small cell lung cancer (NSCLC), radiation resistance has always been a concern, due to poor patient response and prognosis. Therefore, it is crucial to uncover novel targets to enhance radiotherapy and investigate the mechanisms underlying radiation resistance. Previously, we demonstrated that NRP1 was connected to radiation resistance in NSCLC cells. In the present study, bioinformatics analysis of constructed radiation-resistant A549 and H1299 cell models revealed that transcription coactivator YAP is a significant factor in cell proliferation and metastasis. However, there has been no evidence linking YAP and NRP1 to date. In this research, we have observed that YAP contributes to radiation resistance in NSCLC cells by stimulating cell proliferation, migration, and invasion. Mechanistically, YAP dephosphorylation after NSCLC cell radiation. YAP acts as a transcription co-activator by binding to the transcription factor TEAD4, facilitating TEAD4 to bind to the NRP1 promoter region and thereby increasing NRP1 expression. NRP1 has been identified as a new target gene for YAP/TEAD4. Notably, when inhibiting YAP binds to TEAD4, it inhibits NRP1 expression, and Rescue experiments show that YAP/TEAD4 influences NRP1 to regulate cell proliferation, metastasis and leading to radiation resistance generation. According to these results, YAP/TEAD4/NRP1 is a significant mechanism for radioresistance and can be utilized as a target for enhancing radiotherapy efficacy.

Abstract Background This study aimed to investigate the cognitive and affective factors associated with cross-cultural differences in arithmetic tasks. Methods A total of 404 third- and fourth- graders were recruited from China and Italy to complete exact arithmetic, arithmetic estimation and cognitive tasks (i.e., short-term memory, executive functions, and fluid reasoning). Their mathematical anxiety was also measured. Results The results showed that Chinese children performed better than Italian children in both arithmetic tasks and in shifting task. Italian children performed better in visuospatial updating task and reported higher levels of mathematical anxiety than their Chinese peers. Multi-group path analyses showed that the patterns of relations among cognitive factors (i.e., short-term memory, inhibition and shifting), mathematical anxiety, and arithmetic performance were similar across groups. The only exception was that visuospatial updating uniquely predicted arithmetic estimation for Chinese but not for Italian children. Conclusions Chinese children outperformed their Italian peers in the exact arithmetic task, likely due to the greater emphasis on arithmetic fluency in Chinese mathematics education, both in schools and at home. They also had a slight advantage than Italian peers in the arithmetic estimation task. The unique link between updating and arithmetic estimation found in Chinese children but not Italian children suggests that, although arithmetic estimation is not emphasized in the curricula of either country, instruction and practice in exact arithmetic may enhance Chinese children’s efficiency in solving arithmetic estimation problems.

A M3.1 earthquake occurred in Qingpu District of Shanghai at 1:39 on June 15，2023. The Shanghai Earthquake Early Warning Network successfully received the earthquake early warning information released by the China Earthquake Early Warning Network，and the locally deployed Fujian Early Warning System EEW also successfully processed and produced the earthquake early warning results. In this paper，the results of 7 earthquake early warnings produced by Shanghai Earthquake Early Warning System and the earthquake early warning information released by China Earthquake Early Warning Network are compared and analyzed. The epicenter of the earthquake is located in the Shanghai Earthquake Early Warning Network. The first early warning information was released at 6.8 s after the earthquake. All 7 early warning processing results were produced within 15 s after the earthquake. Compared with the official earthquake catalogue，the first early warning processing result has an epicentral position deviation of 5 km and a magnitude deviation of −0.1. With the increase of the number of early warning stations involved in the calculation，the epicenter position is finally consistent with the official catalogue，and the magnitude deviation is also maintained at 0.5. The results of this earthquake early warning show that although Shanghai and its surrounding areas belong to the general early warning area with small and micro earthquakes as the main seismic activities，due to the large density of early warning stations，more accurate early warning processing results can also be produced in a short time after the earthquake，which is of great reference significance for the ongoing integration of monitoring and early warning business in the Yangtze River Delta.

In this study, three insect-resistant transgenic Bacillus thuringiensis (Bt) oilseed rape events (GT1, GT5 and GT9) under field conditions were utilised to analyse the dynamics of Cry1Ac protein and the changes in soil enzyme activities in the rhizosphere soil of transgenic Bt plants during different growth stages over two successive cultivation years. The results indicated that compared to the non-transgenic control plant cv. Westar, the amount of Cry1Ac protein in the rhizosphere soil of the three transgenic oilseed rape events was significantly higher during the flowering and podding stages in the first cultivation year. Additionally, in the second cultivation year, transgenic GT1 and GT9 had significantly higher amounts of Cry1Ac protein in the rhizosphere soil during the flowering stage, and all three transgenic oilseed rape events had significantly higher amounts of Cry1Ac protein in the rhizosphere soil during the podding stage. Over the two successive cultivation years, the sucrase activity in the rhizosphere soil of transgenic events showed significant changes during bolting, flowering and podding stages, while all three transgenic events exhibited significant changes in phosphatase activity during the four different stages. Furthermore, different transgenic events showed varying significant changes in urease and protease activities during the bolting, flowering and podding stages of the first year, and all three transgenic events had significant changes in dehydrogenase activities during the four different stages of the second cultivation year. PCA and correlation analysis clearly demonstrated a strong correlation between the Cry1Ac protein and five soil enzyme activities, as well as a close interconnectedness among those five soil enzyme activities. These findings suggest that the amount of insecticidal crystal proteins in the rhizosphere soil of transgenic Bt (Cry1Ac) oilseed rape varies with different growth periods, and the enzyme activities in the rhizosphere soil of transgenic Bt oilseed rape plants undergo significant changes over two successive planting years.

Abstract Intracranial aneurysm is the primary cause of nontraumatic subarachnoid hemorrhage. To assess aneurysm metabolism, we present a method of intra-operatively collecting blood samples from the aneurysm neck, as well as the proximal and distal responsible vessels, using microcatheters. Through these paired comparisons, we can eliminate the interpatient variation usually observed in plasma samples taken from the peripheral vein. We utilized 39 plasma samples from 13 intracranial patients to characterize the metabolite profiles using untargeted liquid chromatography-mass spectrometry. Our findings revealed that l-tyrosine is upregulated at relatively high levels at the aneurysm neck than the proximal and distal aneurysm, whereas phenylpyruvic acid, l-cystine, and l-ornithine are downregulated. Based on this, there was also a significant decrease in arginine within small aneurysm of the internal carotid artery. The 6-month follow-up indicated that patients who experienced good recovery had lower levels of biliverdin, bilirubin, and metabolites of coenzyme Q within the aneurysm. In conclusion, our investigation provides a comprehensive overview of plasma metabolites in patients with intracranial aneurysms, shedding light on potential pathogenetic mechanisms in unruptured intracranial aneurysms. Moreover, the study proposes innovative ideas for establishing postoperative follow-up timelines for flow diverter devices.

Abstract Background With the development of Internet information technology, especially the impact of the sudden outbreak of the novel coronavirus disease 2019 epidemic, along with the call for “classes suspended but learning continues,” a large number of medical educators have learned and experienced online teaching. They have understood the shortcomings of traditional teaching methods. Not only the blended BOPPPS teaching mode combines the advantages of the BOPPPS teaching mode but also the online teaching platform breaks through the limitation of time and space. However, a general consensus on the effectiveness of the blended BOPPPS teaching strategy in China is lacking, and few studies use quantitative synthesis to evaluate the effectiveness of this teaching strategy. Hence, this study aimed to assess the overall effectiveness of online and offline blended BOPPPS teaching strategies in higher medical education in China compared with the lecture-based learning (LBL) teaching model. Methods Studies that blended learning with the BOPPPS model in China from January 2000 to October 2023 were searched in the Chinese and English-language online databases. We analyzed the objective and subjective scores of students and performed subgroup analysis for specialties and online teaching platforms. The data were analyzed using the Stata version 14.0 software. The quality assessment was performed using the Jadad scoring scale. Results Forty-four studies were included in this meta-analysis. Compared with the LBL mode, the blended the BOPPPS teaching mode was more effective in terms of the overall capacity [standardized mean difference (SMD) = 1.193, 95% confidence interval (CI): 0.813–1.572], mastery of medical theory knowledge (SMD = 1.090, 95% CI: 0.730–1.450), and practical skills (SMD = 1.246, 95% CI: 0.799–1.693). The analyzed questionnaire surveys indicated the positive effects of the blended BOPPPS teaching mode on classroom satisfaction, autonomous learning ability, learning interest, teamwork ability, interpersonal skills, ability to analyze and solve problems, group interaction, learning engagement, and learning strategies. Conclusions The study underscored that the blended BOPPPS teaching mode could effectively improve the comprehensive quality of students. The subjective scores also indicated that students generally preferred this novel teaching mode.

Abstract Background Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predicting the diagnosis of Non-Alcoholic Steatohepatitis. Method An SD rat model of hepatic steatosis was established through a high-fat diet and subcutaneous injection of CCl4. Liver ultrasound images and elastography were acquired, along with serum data and histopathological results of rat livers.The Pyradiomics software was used to extract radiomic features from 2D ultrasound images of rat livers. The rats were then randomly divided into a training set and a validation set, and feature selection was performed through dimensionality reduction. Various machine learning (ML) algorithms were employed to build clinical diagnostic models, radiomic models, and combined diagnostic models. The efficiency of each diagnostic model for diagnosing NASH was evaluated using Receiver Operating Characteristic (ROC) curves, Clinical Decision Curve Analysis (DCA), and calibration curves. Results In the machine learning radiomic model for predicting the diagnosis of NASH, the Area Under the Curve (AUC) of ROC curve for the clinical radiomic model in the training set and validation set were 0.989 and 0.885, respectively. The Decision Curve Analysis revealed that the clinical radiomic model had the highest net benefit within the probability threshold range of > 65%. The calibration curve in the validation set demonstrated that the clinical combined radiomic model is the optimal method for diagnosing Non-Alcoholic Steatohepatitis. Conclusion The combined diagnostic model constructed using machine learning algorithms based on ultrasound image radiomics has a high clinical predictive performance in diagnosing Non-Alcoholic Steatohepatitis.

Abstract Vigilance represents an ability to sustain prolonged attention and plays a crucial role in ensuring the reliability and optimal performance of various tasks. In this report, we describe a MultiModal Vigilance (MMV) dataset comprising seven physiological signals acquired during two Brain-Computer Interface (BCI) tasks. The BCI tasks encompass a rapid serial visual presentation (RSVP)-based target image retrieval task and a steady-state visual evoked potential (SSVEP)-based cursor-control task. The MMV dataset includes four sessions of seven physiological signals for 18 subjects, which encompasses electroencephalogram(EEG), electrooculogram (EOG), electrocardiogram (ECG), photoplethysmogram (PPG), electrodermal activity (EDA), electromyogram (EMG), and eye movement. The MMV dataset provides data from four stages: 1) raw data, 2) pre-processed data, 3) trial data, and 4) feature data that can be directly used for vigilance estimation. We believe this dataset will achieve flexible reuse and meet the various needs of researchers. And this dataset will greatly contribute to advancing research on physiological signal-based vigilance research and estimation.

Abstract Background The SET domain group (SDG) genes encode histone lysine methyltransferases, which regulate gene transcription by altering chromatin structure and play pivotal roles in plant flowering determination. However, few studies have investigated their role in the regulation of flowering in upland cotton. Results A total of 86 SDG genes were identified through genome-wide analysis in upland cotton (Gossypium hirsutum). These genes were unevenly distributed across 25 chromosomes. Cluster analysis revealed that the 86 GhSDGs were divided into seven main branches. RNA-seq data and qRT‒PCR analysis revealed that lysine methyltransferase 3 (KMT3) genes were expressed at high levels in stamens, pistils and other floral organs. Using virus-induced gene silencing (VIGS), functional characterization of GhKMT3;1a and GhKMT3;2a revealed that, compared with those of the controls, the GhKMT3;1a- and GhKMT3;2a-silenced plants exhibited later budding and flowering and lower plant heightwere shorter. In addition, the expression of flowering-related genes (GhAP1, GhSOC1 and GhFT) significantly decreased and the expression level of GhSVP significantly increased in the GhKMT3;1a- and GhKMT3;2a-silenced plants compared with the control plants. Conclusion A total of 86 SDG genes were identified in upland cotton, among which GhKMT3;1a and GhKMT3;2a might regulate flowering by affecting the expression of GhAP1, GhSOC1, GhFT and GhSVP. These findings will provide genetic resources for advanced molecular breeding in the future.

Abstract Colonial cities in Asia and Africa, developed under the dual influence of native and sovereign cultures during the colonial era, exhibit unique urban morphological characteristics and reflect the planning ideologies of diverse cultures. Thus, the morphological study of colonial cities in Asia and Africa is crucial for understanding and identifying the historical and cultural value of these cities, which in turn enables the formulation of precise conservation strategies. In light of this, the study develops an urban morphological analysis methodology comprising "Colonial Background Analysis—Morphological Characteristics Analysis—Driving Factor Extraction" based on the Conzenian Approach, which is used to examine the morphology of 21 typical colonial cities in Asia and Africa across various colonial periods. As a result, "Dual-City" emerges as the core spatial characteristic of colonial cities in Asia and Africa, reflecting the morphological differences in road layouts, urban fabric, and urban cores between native and European zones. Additionally, as native settlement sizes, social structures, and cultural identities differ between cities, three major spatial patterns of the "Dual-City" model can be identified: separated, mediated, and integrated spatial patterns, resulting from the varied planning approaches applied by colonizers. Furthermore, suggestions for the conservation of colonial heritage are proposed based on the driving factors analysis from the morphological study.

Abstract Gliomas represent the most predominant primary malignant tumor in central nervous system. Thymine DNA glycosylase (TDG) is a central component in active DNA demethylation. However, the specific mechanisms of TDG-mediated active DNA demethylation in gliomas remain unclear. This research indicates TDG expression is overexpressed in gliomas and correlated with poor prognosis. TDG knockdown suppressed the malignant phenotype of gliomas both in vitro and vivo. Notably, RNA-seq analysis revealed a strong association between TDG and tenascin-C (TNC). ChIP-qPCR and MeDIP-qPCR assays were undertaken to confirm that TDG participates in TNC active DNA demethylation process, revealing decreased DNA methylation levels and elevated TNC expression as a result. Silencing TNC expression also suppressed the tumor malignant phenotype in both in vitro and in vivo experiments. Additionally, simultaneous silencing of TNC reduced or even reversed the glioma promotion caused by TDG overexpression. Based on our findings, we conclude that TDG exerts an indispensable role in TNC active DNA demethylation in gliomas. The DNA demethylation process leads to alternations in TNC methylation levels and promotes its expression, thereby contributing to the development of gliomas. These results suggest a novel epigenetic therapeutic strategy targeting active DNA demethylation in gliomas.

Myopia is becoming more and more common all over the world, and the incidence of myopia is gradually increasing. Many treatments have been used to prevent and control myopia, including optics, drugs, environment or behavior, but the results are different and lack standardization. At present, many experiments have proved that peripheral defocus technology has a certain effect on myopia control. Based on this technology, three kinds of framed eyeglass lenses with peripheral defocus design, namely defocus incorporated multiple segments(DIMS), highly aspherical lenslets(HAL)and cylindrical annular reactive elements(CARE), are commonly used in medical and optometry institutions in China. These lenses provide not only clear vision in the central area, but also a certain amount of myopic defocus in the periphery to control the progression of myopia. This paper aims to focus on the design principle and myopia prevention and control effect of the above three peripheral defocus lenses, and evaluate their effectiveness in clinical practice.

Abstract Background Lung adenocarcinoma is a high-mortality rate cancer. Within this category, Lung mucinous adenocarcinoma (LMAC) is a rare and distinct subtype of lung adenocarcinoma necessitating further investigation. The study was launched to compare the difference of survival features between LMAC and lung non-mucinous adenocarcinoma (LNMAC) and to investigate the significance and demand for developing a new staging system tailored to LMAC. Methods This retrospective study assessed the suitableness of the current staging system for LMAC. It compared the overall survival (OS) between LMAC and LNMAC from 2004 to 2020 (LNMAC: 160,387; LMAC: 6,341) and instituted a novel classification framework for LMAC based on US population. Verification group consisting of patients from two Chinese medical centers from 2010 to 2018 (n = 392) was set to ascertain the applicability of this novel system. The primary endpoint was OS. To minimize the bias, propensity score match (PSM) was employed. Survival analysis and Log-rank test were executed to explore the survival features of LMAC. Results The results indicated that the existed staging system was not suitable for LMAC. Patients diagnosed with LMAC exhibited a superior OS compared to those with LNMAC in stage IA2 (P

Abstract As a stress hormone existing in the human body, cortisol can reflect the psychological stress and health status in daily life, and is a potential biomarker of the body’s stress response. To effectively collect sweat and accurately identify the target, this paper reports a flexible wearable cortisol detection device with outstanding reliability and sensitivity. Molecular imprinted polymer (MIP) ensures cortisol specificity. And carbon nanotubes (CNT) on electrodes increase sensitivity, expanding the detection range to 10−3 to 104 nM, with sensitivity at 189.2 nA/lg(nM). In addition, porous chitosan hydrogel (PCSH) collects sweat effectively, its adhesive properties and 80% swelling rate offer a low-cost alternative to microfluidics. Flexible printed circuit board (FPCB) and serpentine electrode (SE) ensure device durability. This non-invasive, highly sensitive device offers a novel method for mental stress monitoring and clinical diagnosis, advancing human physiological state monitoring.

Abstract Diabetes accelerates vascular senescence, which is the basis for atherosclerosis and stiffness. The activation of NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome and oxidative stress are closely associated with the deteriorative senescence in endothelial cells (ECs) and vascular smooth muscle cells (VSMCs). For decades, Sodium Tanshinone IIA Sulfonate (STS) has been utilized as a cardiovascular medicine with acknowledged anti-inflammatory and anti-oxidative properties. Nevertheless, the impact of STS on vascular senescence remains unexplored in diabetes. Diabetic mice, primary ECs and VSMCs were transfected with the NLRP3 overexpression/knockout plasmid, the tumor necrosis factor alpha-induced protein 3 (TNFAIP3/A20) overexpression/knockout plasmid, and treated with STS to detect senescence-associated markers. In diabetic mice, STS treatment maintained catalase (CAT) level and vascular relaxation, reduced hydrogen peroxide probe (ROSgreen) fluorescence, p21 immunofluorescence, Senescence β-Galactosidase Staining (SA-β-gal) staining area, and collagen deposition in aortas. Mechanistically, STS inhibited NLRP3 phosphorylation (serine 194), NLRP3 dimer formation, NLRP3 expression, and NLRP3-PYCARD (ASC) colocalization. It also suppressed the phosphorylation of IkappaB alpha (IκBα) and NFκB, preserved A20 and CAT levels, reduced ROSgreen density, and decreased the expression of p21 and SA-β-gal staining in ECs and VSMCs under HG culture. Our findings indicate that STS mitigates vascular senescence by modulating the A20-NFκB-NLRP3 inflammasome-CAT pathway in hyperglycemia conditions, offering novel insights into NLRP3 inflammasome activation and ECs and VSMCs senescence under HG culture. This study highlights the potential mechanism of STS in alleviating senescence in diabetic blood vessels, and provides essential evidence for its future clinical application.

Abstract Quasi-two-dimensional (Q-2D) perovskite exhibits exceptional photoelectric properties and demonstrates reduced ion migration compared to 3D perovskite, making it a promising material for the fabrication of highly sensitive and stable X-ray detectors. However, achieving high-quality perovskite films with sufficient thickness for efficient X-ray absorption remains challenging. Herein, we present a novel approach to regulate the growth of Q-2D perovskite crystals in a mixed atmosphere comprising methylamine (CH3NH2, MA) and ammonia (NH3), resulting in the successful fabrication of high-quality films with a thickness of hundreds of micrometers. Subsequently, we build a heterojunction X-ray detector by incorporating the perovskite layer with titanium dioxide (TiO2). The precise regulation of perovskite crystal growth and the meticulous design of the device structure synergistically enhance the resistivity and carrier transport properties of the X-ray detector, resulting in an ultrahigh sensitivity (29721.4 μC Gyair −1 cm−2) for low-dimensional perovskite X-ray detectors and a low detection limit of 20.9 nGyair s−1. We have further demonstrated a flat panel X-ray imager (FPXI) showing a high spatial resolution of 3.6 lp mm−1 and outstanding X-ray imaging capability under low X-ray doses. This work presents an effective methodology for achieving high-performance Q-2D perovskite FPXIs that holds great promise for various applications in imaging technology.

Objective: This study aimed to explore the determinants influencing training transfer and evaluate how those factors change over time among nurses who graduated from clinical nurse specialist training to provide a theoretical basis for improving the training transfer of clinical nurse specialists (CNSs). Methods: A quantitative longitudinal survey with four rounds of data collection was utilized to measure the influencing aspects of training transfer from June 2018 to December 2019. A total of 46 new CNSs participated in this study, including 30 and 16 nurses receiving training programs for CNSs in Infusion, Wound and Ostomy. The factor influencing training transfer (FITT) questionnaire was used to collect data for the first month (time 1), the third month (time 2), the sixth month (time 3), and the first year (time 4) after training. This questionnaire contains 53 items divided into five dimensions, including managerial support (20 items); hindrance in the organization (6 items); the validity of the training program (10 items); organizational and personal facilitators (11 items); and personal attitudes towards training transfer (6 items). Results: The influencing factors of CNSs transfer decreased over time, with managerial support, hindrance in the organization, the validity of the training program, and personal attitudes towards training transfer changing statistically over time (P

Abstract Background Immune checkpoint inhibitors, such as anti-programmed cell death-1 (PD-1) and PD-1 ligand-1 (PD-L1) antibodies, have achieved breakthrough results in improving long-term survival rates in lung cancer. Although high levels of PD-L1 expression and tumor mutational burden have emerged as pivotal biomarkers, not all patients derive lasting benefits, and resistance to immune checkpoint blockade remains a prevalent issue. Comprehending the immunological intricacies of lung cancer is crucial for uncovering the mechanisms that govern responses and resistance to immunomodulatory treatments. This study aimed to explore the potential of peripheral immune markers in predicting treatment efficiency among lung cancer patients undergoing PD-1/PD-L1 checkpoint inhibitors. Methods This study enrolled 71 lung cancer patients undergoing PD-1/PD-L1 inhibitor therapy and 20 healthy controls. Immune cell subsets (CD4 + T cells, CD8 + T cells, B cells, NK cells, and NKT cells), phenotypic analysis of T cells and B cells, and PMA/Ionomycin-stimulated lymphocyte function assay were conducted. Results Lung cancer patients exhibited significant alterations in immune cell subsets, notably an increased percentage of Treg cells. Post-treatment, there were substantial increases in absolute numbers of CD3 + T cells, CD8 + T cells, and NKT cells, along with heightened HLA-DR expression on CD3 + T and CD8 + T cells. Comparison between complete remission and non-complete remission (NCR) groups showed higher Treg cell percentages and HLA-DR + CD4 + T cells in the NCR group. Conclusion The study findings suggest potential predictive roles for immune cell subsets and phenotypes, particularly Treg cells, HLA-DR + CD4 + T cells, and naïve CD4 + T cells, in evaluating short-term PD-1/PD-L1 therapy efficacy for lung cancer patients. These insights offer valuable prospects for personalized treatment strategies and underscore the importance of immune profiling in lung cancer immunotherapy.

Abstract Synthesis of valuable chemicals from CO2 electroreduction in acidic media is highly desirable to overcome carbonation. However, suppressing the hydrogen evolution reaction in such proton-rich environments remains a considerable challenge. The current study demonstrates the use of a hollow fiber silver penetration electrode with hierarchical micro/nanostructures to enable CO2 reduction to CO in strong acids via balanced coordination of CO2 and K+/H+ supplies. Correspondingly, a CO faradaic efficiency of 95% is achieved at a partial current density as high as 4.3 A/cm2 in a pH = 1 solution of H2SO4 and KCl, sustaining 200 h of continuous electrolysis at a current density of 2 A/cm2 with over 85% single-pass conversion of CO2. The experimental results and density functional theory calculations suggest that the controllable CO2 feeding induced by the hollow fiber penetration configuration primarily coordinate the CO2/H+ balance on Ag active sites in strong acids, favoring CO2 activation and key intermediate *COOH formation, resulting in enhanced CO formation.

Abstract Although numerous ambient ionization mass spectroscopy technologies have been developed over the past 20 years to address diverse analytical circumstances, a single-ion source technique that can handle all analyte types is still lacking. Here, a wide-energy programmable microwave plasma-ionization mass spectrometry (WPMPI-MS) system is presented, through which MS analysis can achieve high coverage of substances with various characteristics by digitally regulating the microwave energy. In addition, ionization energy can be rapidly scanned using programmable waveforms, enabling the simultaneous detection of biomolecules, heavy metals, non-polar molecules, etc., in seconds. WPMPI-MS performs well in analyzing real samples, rapidly analyzing nine toxicological standards in one drop of serum, and demonstrating good quantification and liquid chromatography coupling capability. The WPMPI-MS has also been used to detect soil extracts, solid pharmaceuticals, and landfill leachate, further demonstrating its robust analytical capabilities for real samples. The prospective uses of the technology in biological and chemical analysis are extensive, and it is anticipated to emerge as a viable alternative to commercially available ion sources.

Abstract Ethylene regulates plant growth, development, and stress adaptation. However, the early signaling events following ethylene perception, particularly in the regulation of ethylene receptor/CTRs (CONSTITUTIVE TRIPLE RESPONSE) complex, remains less understood. Here, utilizing the rapid phospho-shift of rice OsCTR2 in response to ethylene as a sensitive readout for signal activation, we revealed that MHZ3, previously identified as a stabilizer of ETHYLENE INSENSITIVE 2 (OsEIN2), is crucial for maintaining OsCTR2 phosphorylation. Genetically, both functional MHZ3 and ethylene receptors prove essential for OsCTR2 phosphorylation. MHZ3 physically interacts with both subfamily I and II ethylene receptors, e.g., OsERS2 and OsETR2 respectively, stabilizing their association with OsCTR2 and thereby maintaining OsCTR2 activity. Ethylene treatment disrupts the interactions within the protein complex MHZ3/receptors/OsCTR2, reducing OsCTR2 phosphorylation and initiating downstream signaling. Our study unveils the dual role of MHZ3 in fine-tuning ethylene signaling activation, providing insights into the initial stages of the ethylene signaling cascade.

Abstract The worldwide occurrence of wind droughts challenges the balance of power systems between energy production and consumption. Expanding inter‐day energy storage serves as a strategic solution, yet optimizing its capacity depends on accurately modeling future renewable energy uncertainties to avoid over‐ or under‐investment. Existing approaches that use the historical extreme scenario set (HESS) to represent future conditions are contentious due to potential inadequacies in forecasting future extreme scenarios (ESs), including those on a decadal or centennial scale. This study addresses the issue by proposing an advanced energy storage expansion framework that leverages Extreme Value Theory (EVT) and a novel Deep Generative Model, namely the Diffusion Model. To model the extremes in a principled way, this work leverages EVT to establish a severity‐probability mapping for wind droughts, guiding the training process of the Diffusion Model. This model excels in generating ESs that accurately reflect the distribution of real‐world extremes, thereby significantly enhancing the predictive capacity of HESS. Case studies on a real‐world power system confirm the method's capacity to generate high‐quality ESs, encompassing the most severe historical wind droughts not included in the training dataset, thereby facilitating resilient energy storage expansion against unforeseen extremes.

Abstract Background Hyperlipidemia damages vascular wall and serves as a foundation for diseases such as atherosclerosis, hypertension and stiffness. The NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome is implicated in vascular dysfunction associated with hyperlipidemia-induced vascular injury. Sodium tanshinone IIA sulfonate (STS), a well-established cardiovascular protective drug with recognized anti-inflammatory, antioxidant, and vasodilatory properties, is yet to be thoroughly investigated for its impact on vascular relaxant imbalance induced by hyperlipidemia. Methods In this study, we treated ApoE-knockout (ApoE-/-) mouse with STS and assessed the activation of the NLRP3 inflammasome, expression of MMP2/9, integrity of elastic fibers, and vascular constriction and relaxation. Results Our findings reveal that STS intervention effectively preserves elastic fibers, significantly restores aortic relaxation function in ApoE-/- mice, and reduces their excessive constriction. Furthermore, STS inhibits the phosphorylation of spleen tyrosine kinase (SYK), suppresses NLRP3 inflammasome activation, and reduces MMP2/9 expression. Conclusions These results demonstrate that STS protects vascular relaxation against hyperlipidemia-induced damage through modulation of the SYK-NLRP3 inflammasome-MMP2/9 pathway. This research provides novel insights into the mechanisms underlying vascular relaxation impairment in a hyperlipidemic environment and uncovers a unique mechanism by which STS preserves vascular relaxation, offering valuable foundational research evidence for its clinical application in promoting vascular health.

Abstract Helicobacter pylori (H. pylori) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high prevalence and resistance make it difficult to tackle. A graph neural network-based deep learning model, employing different training sets of 13,638 molecules for pre-training and fine-tuning, was aided in predicting and exploring novel molecules against H. pylori. A positively predicted novel berberine derivative 8 with 3,13-disubstituted alkene exhibited a potency against all tested drug-susceptible and resistant H. pylori strains with minimum inhibitory concentrations (MICs) of 0.25–0.5 μg/mL. Pharmacokinetic studies demonstrated an ideal gastric retention of 8, with the stomach concentration significantly higher than its MIC at 24 h post dose. Oral administration of 8 and omeprazole (OPZ) showed a comparable gastric bacterial reduction (2.2-log reduction) to the triple-therapy, namely OPZ + amoxicillin (AMX) + clarithromycin (CLA) without obvious disturbance on the intestinal flora. A combination of OPZ, AMX, CLA, and 8 could further decrease the bacteria load (2.8-log reduction). More importantly, the mono-therapy of 8 exhibited comparable eradication to both triple-therapy (OPZ + AMX + CLA) and quadruple-therapy (OPZ + AMX + CLA + bismuth citrate) groups. SecA and BamD, playing a major role in outer membrane protein (OMP) transport and assembling, were identified and verified as the direct targets of 8 by employing the chemoproteomics technique. In summary, by targeting the relatively conserved OMPs transport and assembling system, 8 has the potential to be developed as a novel anti-H. pylori candidate, especially for the eradication of drug-resistant strains.

Abstract The outcomes of patients with sepsis are influenced by the contractile function of the right ventricle (RV), but the impact of cardiopulmonary interaction in ICU-mortality of sepsis patients remains unclear. This study aims to investigate the ICU-mortality impact of right ventricular-pulmonary artery (RV-PA) coupling in patients with sepsis. We employed echocardiography to assess patients with sepsis within the initial 24 h of their admission to the ICU. RV-PA coupling was evaluated using the tricuspid annular plane systolic excursion (TAPSE) to pulmonary artery systolic pressure (PASP) ratio. A total of 92 subjects were enrolled, with 55 survivors and 37 non-survivors. TAPSE/PASP ratio assessed mortality with an area under the curve (AUC) of 0.766 (95% CI 0.670–0.862) and the optimal cutoff value was 0.495 mm/mmHg. We constructed a nomogram depicting the TAPSE/PASP in conjunction with IL-6 and Lac for the joint prediction of sepsis prognosis, and demonstrated the highest predictive capability (AUC = 0.878, 95% CI 0.809–0.948). In conclusion, the TAPSE/PASP ratio demonstrated prognostic value for ICU mortality in sepsis patients. The nomogram, which combines the TAPSE/PASP, IL-6, and LAC, demonstrated enhanced predictive efficacy for the prognosis of sepsis patients.