Search

Abstract Immune checkpoint blockade (ICB) therapy has emerged as a new therapeutic paradigm for a variety of advanced cancers, but wide clinical application is hindered by low response rate. Here we use a peptide-based, biomimetic, self-assembly strategy to generate a nanoparticle, TPM1, for binding PD-L1 on tumour cell surface. Upon binding with PD-L1, TPM1 transforms into fibrillar networks in situ to facilitate the aggregation of both bound and unbound PD-L1, thereby resulting in the blockade of the PD-1/PD-L1 pathway. Characterizations of TPM1 manifest a prolonged retention in tumour ( > 7 days) and anti-cancer effects associated with reinvigorating CD8+ T cells in multiple mice tumour models. Our results thus hint TPM1 as a potential strategy for enhancing the ICB efficacy.

Abstract Background Asthma and allergic diseases (such as allergic rhinitis) are multifactorial chronic respiratory diseases, and have many common pathogenic mechanisms. This study aimed to assess the joint effects of breastfeeding and genetic susceptibility on asthma, allergic disease in children and adolescents and sought to examine whether the effect of breastfeeding was consistent under distinct levels of genetic risk. Methods A total of 351,931 UK Biobank participants were analyzed. Firstly, Cox proportional hazards model was used to evaluate the relation between breastfeeding and asthma, allergic disease and their comorbidity. Next, we incorporated the polygenic risk score as an additional covariate into the model. Then, we explored the role of breastfeeding at each stage of asthma and allergic disease through a multi-state model. Meanwhile, several sensitivity analyses were conducted to evaluate the robustness of our results. Finally, we calculated the attributable protection and population attributable protection of breastfeeding. Results Breastfeeding was related to a reduced risk of occurring asthma (adjusted hazard ratio [HR] = 0.89, 95% confidence interval [CI] 0.86 ~ 0.93), allergic disease (HR = 0.89, 95%CI 0.87 ~ 0.91) and comorbidity (HR = 0.89, 95%CI 0.83 ~ 0.94). The effect of breastfeeding was almost unchanged after considering PRS and did not substantially differ across distinct genetic risk levels. Breastfeeding showed a stronger risk-decreased impact on individuals who developed from allergic rhinitis to comorbidity (HR = 0.83, 95%CI 0.73 ~ 0.93). Further, the influence of breastfeeding was robust against covariates considered and the confounding influence of adolescent smoking. Finally, due to breastfeeding, 12.0%, 13.0% or 13.0% of the exposed population would not suffer from asthma, allergic diseases and the comorbidity, while 7.1%, 7.6% or 7.6% of the general population would not suffer from these diseases. Conclusions This study provided supportive evidence for the risk-reduced effect of breastfeeding on asthma, allergic diseases, and the comorbidity in children and adolescents, and further revealed that such an influence was consistent across distinct genetic risk levels.

Abstract Purposes T cells play a crucial role as regulators of anti-tumor activity within the tumor microenvironment (TME) and are closely associated with the progression of osteosarcoma (OS). Nevertheless, the specific role of T cell-related genes (TCRGs) in the pathogenesis of OS remains unclear. Methods First, we processed single-cell RNA sequencing (scRNA-seq) data of OS from the public databases and performed cell annotation. We identified highly variable genes in each cell type using the "FindAllMarkers" function, explored the distribution of different clusters, and investigated inter-cellular communication patterns via the "CellChat" framework. Then, we used multivariate Cox analysis to construct a TCRG and developed a nomogram to predict survival probabilities for OS patients. Finally, we validated the aforementioned results using various cell lines and investigated the immune cell infiltration, expression of immune checkpoints, chemotherapy sensitivity, and the efficacy of targeted therapies across different risk groups. Results From the scRNA-seq data, we identified 3,000 highly variable genes, presented the top 10 genes, and validated the expression of core genes across different cell lines.Moreover, our analysis delved into interactions between T cells and other cell types. Our analyses constructed a predictive T cell-related signature (TCRS) that incorporated these prognostic TCRGs, showing a clear prognostic separation between the high-risk and low-risk OS patient groups in multiple cohorts. Survival analysis indicated better outcomes for patients classified in the high-risk group. The low-risk group exhibited elevated levels of CD4 memory resting T cells, contrasting with the higher levels of macrophage M0 observed in the high-risk group via the CIBERSORT algorithm. Furthermore, we observed that the low-risk group exhibitedAQ1 significant up-regulation of immune checkpoint genes (ICGs) and lower Tumour Immune Dysfunction and Exclusion (TIDE) scores, suggesting that they may be suitable for immunotherapy. Conversely, the high-risk group appeared more responsive to chemotherapy and targeted therapies, according to our drug sensitivity analysis. Conclusion In conclusion, our study identified TCRGs, constructed and validated a TCRS for OS, and assessed immune response and drug sensitivity in different risk groups of OS patients. These findings provide novel insights into personalized treatment strategies for OS, potentially guiding more effective therapeutic interventions.

Abstract Background To investigate the association between cigarette smoking, smoking cessation and the trajectory of cardiometabolic multimorbidity (CMM), and further to examine the association of age at smoking initiation and smoking cessation with CMM. Methods This study included 298,984 UK Biobank participants without cardiometabolic diseases (CMDs) (including type 2 diabetes, coronary heart diseases, stroke, and hypertension) at baseline. Smoking status was categorized into former, current, and never smokers, with age at smoking initiation and smoking cessation as a proxy for current and former smokers. The multi-state model was performed to evaluate the association between cigarette smoking, smoking cessation and CMM. Results During a median follow-up of 13.2 years, 59,193 participants developed first cardiometabolic disease (FCMD), 14,090 further developed CMM, and 16,487 died. Compared to former smokers, current smokers had higher risk at all transitions, with hazard ratio (95% confidence interval) = 1.59 (1.55 ∼ 1.63) vs. 1.18 (1.16 ∼ 1.21) (P = 1.48 × 10− 118) from health to FCMD, 1.40 (1.33 ∼ 1.47) vs. 1.09 (1.05 ∼ 1.14) (P = 1.50 × 10− 18) from FCMD to CMM, and 2.87 (2.72 ∼ 3.03) vs. 1.38 (1.32 ∼ 1.45) (P

Abstract Background Researches have found that alteration of intestinal flora may be closely related to the development of autism spectrum disorder (ASD). However, whether probiotics supplementation has a protective effect on ASD remains controversial. This meta-analysis aimed to analyze the outcome of probiotics in the treatment of ASD children. Methods The Pubmed, Cochrane Library, Web of Science and Embase were searched until Sep 2022. Randomized controlled trials (RCTs) relevant to the probiotics and placebo treatment on ASD children were screened. Quality assessment of the included RCTs was evaluated by the Cochrane collaboration’s tool. The primary outcomes were ASD assessment scales, including ABC (aberrant behavior checklist) and CBCL (child behavior checklist) for evaluating the behavior improvement, SRS (social responsiveness scale) for social assessment, DQ (developmental quotient) for physical and mental development and CGI-I (clinical global impression improvement) for overall improvement. The secondary outcome was total 6-GSI (gastrointestinal severity index). Results In total, 6 RCTs from 6 studies with 302 children were included in the systemic review. Total 6-GSI (MD=-0.59, 95%CI [-1.02,-0.17], P

Abstract Background Globally increasing atmospheric nitrogen (N) deposition has altered soil phosphorus (P) transformations and availability, and thereby influenced structure and function of terrestrial ecosystems. Edaphic characteristics and chemical form of deposited N could be important factors determining impacts of N deposition on soil P transformations, yet the underlying mechanisms remain largely unknown. Objectives of this study were to examine how mineral-N and amino N differently affect P fractions, and identify key soil properties determining N addition impacts on soil P transformations. Considering that amino N is an important component of deposited N and forest soils vary greatly in different regions, the results of present study can guide the management of forests across different soils under ongoing N deposition scenarios. Methods We conducted a 60-day laboratory experiment to investigate the effects of N addition (NH4NO3 and glycine) on soil P fractions and related biochemical properties in four representative forest soils (brown, yellow brown, aeolian sandy, and red soils) in China. Glycine and NH4NO3 were separately added at three rates (5, 10 and 20 g N m–2 yr–1). Results Firstly, the percent changes in organic P fractions with N addition were significantly greater than changes in inorganic P fractions across all soils. Secondly, the percent changes in P fractions with glycine and NH4NO3 additions were significantly correlated across all soils and treatments. However, glycine addition had significantly greater impacts on organic P fractions than NH4NO3 addition in the aeolian sandy and red soils with low organic carbon content. Thirdly, P fractions responded differently to N addition among the four soils. N-induced changes in microbial biomass and phosphatase activities, pH, exchangeable Ca2+ and Mg2+ contributed differently to the changes in P fractions with N addition in the four soils. Conclusions The different responses of P fractions to N addition in the four soils were mainly generated by the differences in extent of microbial N limitation, acid buffering capacity, and cation exchange capacity among the soils. The different impacts of mineral and amino N on soil P fractions can be ascribed to their divergent effects on soil pH, microbial biomass and activities.

Abstract Background The term eGene has been applied to define a gene whose expression level is affected by at least one independent expression quantitative trait locus (eQTL). It is both theoretically and empirically important to identify eQTLs and eGenes in genomic studies. However, standard eGene detection methods generally focus on individual cis-variants and cannot efficiently leverage useful knowledge acquired from auxiliary samples into target studies. Methods We propose a multilocus-based eGene identification method called TLegene by integrating shared genetic similarity information available from auxiliary studies under the statistical framework of transfer learning. We apply TLegene to eGene identification in ten TCGA cancers which have an explicit relevant tissue in the GTEx project, and learn genetic effect of variant in TCGA from GTEx. We also adopt TLegene to the Geuvadis project to evaluate its usefulness in non-cancer studies. Results We observed substantial genetic effect correlation of cis-variants between TCGA and GTEx for a larger number of genes. Furthermore, consistent with the results of our simulations, we found that TLegene was more powerful than existing methods and thus identified 169 distinct candidate eGenes, which was much larger than the approach that did not consider knowledge transfer across target and auxiliary studies. Previous studies and functional enrichment analyses provided empirical evidence supporting the associations of discovered eGenes, and it also showed evidence of allelic heterogeneity of gene expression. Furthermore, TLegene identified more eGenes in Geuvadis and revealed that these eGenes were mainly enriched in cells EBV transformed lymphocytes tissue. Conclusion Overall, TLegene represents a flexible and powerful statistical method for eGene identification through transfer learning of genetic similarity shared across auxiliary and target studies.

ObjectiveRheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy.MethodsscRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features.ResultsBy analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients.ConclusionOur findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

BackgroundGastric cancer (GC) and type 2 diabetes (T2D) contribute to each other, but the interaction mechanisms remain undiscovered. The goal of this research was to explore shared genes as well as crosstalk mechanisms between GC and T2D.MethodsThe Gene Expression Omnibus (GEO) database served as the source of the GC and T2D datasets. The differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were utilized to identify representative genes. In addition, overlapping genes between the representative genes of the two diseases were used for functional enrichment analysis and protein–protein interaction (PPI) network. Next, hub genes were filtered through two machine learning algorithms. Finally, external validation was undertaken with data from the Cancer Genome Atlas (TCGA) database.ResultsA total of 292 and 541 DEGs were obtained from the GC (GSE29272) and T2D (GSE164416) datasets, respectively. In addition, 2,704 and 336 module genes were identified in GC and T2D. Following their intersection, 104 crosstalk genes were identified. Enrichment analysis indicated that “ECM-receptor interaction,” “AGE-RAGE signaling pathway in diabetic complications,” “aging,” and “cellular response to copper ion” were mutual pathways. Through the PPI network, 10 genes were identified as candidate hub genes. Machine learning further selected BGN, VCAN, FN1, FBLN1, COL4A5, COL1A1, and COL6A3 as hub genes.Conclusion“ECM-receptor interaction,” “AGE-RAGE signaling pathway in diabetic complications,” “aging,” and “cellular response to copper ion” were revealed as possible crosstalk mechanisms. BGN, VCAN, FN1, FBLN1, COL4A5, COL1A1, and COL6A3 were identified as shared genes and potential therapeutic targets for people suffering from GC and T2D.

Purposes A load feature extraction method based on a combination of event monitoring and Gaussian mixture model clustering is proposed to explore the potential of energy saving and emission reduction at the customer side, to finely analyze and manage the customers’ electricity consumption behavior, and to improve the efficiency of electricity utilization. Methods First, the active power fluctuation of each appliance during a single operation is extracted by the event monitoring algorithm based on sliding window, and the start-up time, number of times, and operation duration of the appliance can be obtained by the event monitoring algorithm. Second, to address the problem that the same appliance often has similar power but inconsistent operation status, the Gaussian mixture model clustering algorithm with the advantages of “soft classification” and flexible class clusters is adopted to finely classify the load operating status and form a load status feature library that is consistent with the actual operation of power-using equipment. Finally, with the public data set AMPds2 as the research object, the method proposed in this paper is applied to study the energy consumption habits of residential customers, and the validation analysis is carried out. Findings The results show that the proposed method can extract load features better than other models.

Abstract Background The World Health Organization (WHO) has established recommended daily intakes for sodium and potassium. However, there is currently some controversy regarding the association between sodium intake, potassium intake, the sodium-to-potassium ratio, and overall mortality. To assess the correlations between sodium intake, potassium intake, the sodium-to-potassium ratio, and overall mortality, as well as the potential differences in sodium and potassium intake thresholds among different population groups, we analyzed data from NHANES 2003–2018. Methods NHANES is an observational cohort study that estimates sodium and potassium intake through one or two 24-h dietary recalls. Hazard ratios (HR) for overall mortality were calculated using multivariable adjusted Cox models accounting for sampling design. A total of 13855 out of 26288 participants were included in the final analysis. Restricted cubic spline analyses were used to examine the relationship between sodium intake, potassium intake, and overall mortality. If non-linearity was detected, we employed a recursive algorithm to calculate inflection points. Results Based on one or two 24-h dietary recalls, the sample consisted of 13,855 participants, representing a non-institutionalized population aged 40–80 years, totaling 11,348,771 person-months of mean follow-up 99.395 months. Daily sodium intake and daily potassium intake were inversely associated with all-cause mortality. Restrictive cubic spline analysis showed non-linear relationships between daily sodium intake, potassium intake, sodium–potassium ratio, and total mortality. The inflection point for daily sodium intake was 3133 mg/d, and the inflection point for daily potassium intake was 3501 mg/d, and the inflection point for daily sodium–potassium ratio intake was 1.203 mg/mg/d. In subgroup analyses, a significant interaction was found between age and high sodium intake, which was further confirmed by the smooth curves that showed a U-shaped relationship between sodium intake and all-cause mortality in the elderly population, with a inflection point of 3634 mg/d. Conclusion Nonlinear associations of daily sodium intake, daily potassium intake and daily sodium–potassium ratio intake with all-cause mortality were observed in American individuals. The inflection point for daily sodium intake was 3133 mg/d. And the inflection point for daily sodium intake was 3634 mg/d in elderly population. The inflection point for daily potassium intake was 3501 mg/d. The inflection point for daily sodium–potassium ratio intake was 1.203 mg/mg/d, respectively, A healthy diet should be based on reasonable sodium intake and include an appropriate sodium-to-potassium ratio.

Background: The systemic immune-inflammation index (SII) is a proven, reliable inflammatory marker of the atherosclerotic process. Additionally, inflammation is one of the most important mechanisms of heart failure (HF) after myocardial infarction (MI). However, it is not clear whether SII is related to the risk of in-hospital HF in patients with MI. Thus, we aimed to explore the relationship between SII and the risk of new-onset in-hospital HF in ST-segment elevation myocardial infarction (STEMI) patients treated with primary percutaneous coronary intervention (pPCI). Methods: A total of 5586 patients with STEMI underwent pPCI at seven clinical sites in China from January 2015 to August 2021. The patients were divided into two groups based on the SII values. The association between SII and new-onset in-hospital HF in STEMI patients was assessed using logistic regression analysis. Results: Ultimately, 3808 STEMI patients with Killip class I who were treated with pPCI were included. All included patients were divided into two groups based on the calculated SII (Q1 SII:

Background: Although extensive discussions on the influence of maternal educational attainment on offspring birthweight, the conclusion remains controversial, and it is challenging to comprehensively assess the causal association between them. Methods: To estimate effect of maternal educational attainment on the birthweight of first child, we first conducted an individual-level analysis with UK Biobank participants of white ancestry (n = 208,162). We then implemented Mendelian randomization (MR) methods including inverse variance weighted (IVW) MR and multivariable MR to assess the causal relation between maternal education and maternal-specific birthweight. Finally, using the UK Biobank parent-offspring trio data (n = 618), we performed a polygenic score based MR to simultaneously adjust for confounding effects of fetal-specific birthweight and paternal educational attainment. We also conducted simulations for power evaluation and sensitivity analyses for horizontal pleiotropy of instruments. Results: We observed that birthweight of first child was positively influenced by maternal education, with 7 years of maternal education as the reference, adjusted effect = 44.8 (95%CIs 38.0–51.6, P = 6.15 × 10−38), 54.9 (95%CIs 47.6–62.2, P = 4.21 × 10−128), and 89.4 (95%CIs 82.1–96.7, P = 4.28 × 10−34) for 10, 15 and 20 years of maternal educational attainment, respectively. A causal relation between maternal education and offspring birthweight was revealed by IVW MR (estimated effect = 0.074 for one standard deviation increase in maternal education years, 95%CIs 0.054–0.093, P = 2.56 × 10−13) and by complementary MR methods. This connection was not substantially affected by paternal education or horizontal pleiotropy. Further, we found a positive but insignificant causal association (adjusted effect = 24.0, 95%CIs −150.1–198.1, P = 0.787) between maternal education and offspring birthweight after simultaneously controlling for fetal genome and paternal education; this null causality was largely due to limited power of small sample sizes of parent-offspring trios. Conclusion: This study offers supportive evidence for a causal association between maternal education and offspring birthweight, highlighting the significance of enhancing maternal education to prevent low birthweight.

Abstract Background The relation of social deprivation with single cardiometabolic disease (CMD) was widely investigated, whereas the association with cardiometabolic multi-morbidity (CMM), defined as experiencing more than two CMDs during the lifetime, is poorly understood. Methods We analyzed 345,417 UK Biobank participants without any CMDs at recruitment to study the relation between social deprivation and four CMDs including type II diabetes (T2D), coronary artery disease (CAD), stroke and hypertension. Social deprivation was measured by Townsend deprivation index (TDI), and CMM was defined as occurrence of two or more of the above four diseases. Multivariable Cox models were performed to estimate hazard ratios (HRs) per one standard deviation (SD) change and in quartile (Q1-Q4, with Q1 as reference), as well as 95% confidence intervals (95% CIs). Results During the follow up, 68,338 participants developed at least one CMD (median follow up of 13.2 years), 16,225 further developed CMM (median follow up of 13.4 years), and 18,876 ultimately died from all causes (median follow up of 13.4 years). Compared to Q1 of TDI (lowest deprivation), the multivariable adjusted HR (95%CIs) of Q4 (highest deprivation) among participants free of any CMDs was 1.23 (1.20 ~ 1.26) for developing one CMD, 1.42 (1.35 ~ 1.48) for developing CMM, and 1.34 (1.27 ~ 1.41) for all-cause mortality. Among participants with one CMD, the adjusted HR (95%CIs) of Q4 was 1.30 (1.27 ~ 1.33) for developing CMM and 1.34 (1.27 ~ 1.41) for all-cause mortality, with HR (95%CIs) = 1.11 (1.06 ~ 1.16) for T2D patients, 1.07 (1.03 ~ 1.11) for CAD patients, 1.07 (1.00 ~ 1.15) for stroke patients, and 1.24 (1.21 ~ 1.28) for hypertension patients. Among participants with CMM, TDI was also related to the risk of all-cause mortality (HR of Q4 = 1.35, 95%CIs 1.28 ~ 1.43). Conclusions We revealed that people living with high deprived conditions would suffer from higher hazard of CMD, CMM and all-cause mortality.

Abstract Background Epidemiologic evidence suggested that remnant cholesterol (RC) is associated with the occurrence of cardiovascular disease (CVD). In recent years, RC has been connected with different types of cardiometabolic disorders. We aim to clarify the relationship among RC, metabolic syndrome (MetS) and subsequent CVD. Methods We enrolled 7471 individuals into our study from China Health and Nutrition Survey in 2009 and followed participants till 2015. RC was calculated as total cholesterol minus low-density lipoprotein cholesterol minus high-density lipoprotein cholesterol. CVD was defined as myocardial infarction and stroke. Multivariate logistic regression and Cox regression models were used to evaluate the association between RC and MetS as well as CVD. We further investigated whether the association between RC and CVD was mediated by MetS. Results Of all subjects, 24.73% were diagnosed with MetS and 2.74% developed CVD. Multivariate logistic regression analysis elucidated that per-tertile-increase in RC was associated with MetS after adjusting all the confounder factors, (odds ratio: 3.49, 95% confidence interval CI 3.21–3.79, P for trend

Abstract Background Social frailty has not been comprehensively studied in China. Our objective is to investigate the prevalence of social frailty among the older population in China, as well as identify relevant factors and urban-rural differences. Methods We obtained data from the Fourth Sample Survey of the Aged Population in Urban and Rural China (SSAPUR) database. The study employed a multistage, stratified, cluster-sampling method, recruiting a total of 224,142 adults aged 60 years or older. Participants were interviewed to gather demographic data and information on family, health and medical conditions, health care service status, living environment conditions, social participation, protected rights status, spiritual and cultural life, and health. Social frailty was assessed using the HALFE Social Frailty Index. A score of three or above indicated social frailty. Results We analyzed a total of 222,179 cases, and the overall prevalence of social frailty was found to be 15.2%. The highest prevalence was observed among participants aged 75–79 years (18.0%). The prevalence of social frailty was higher in rural older populations compared to urban older populations (19.9% in rural vs. 10.9% in urban, P

Abstract In this multicenter, single-arm phase 2 trial (ChiCTR1900024428), patients with locally advanced gastric/gastroesophageal junction cancers receive one cycle of sintilimab (anti-PD1) and chemotherapy (S-1 and nab-paclitaxel), followed by 5 weeks of concurrent chemoradiotherapy and sintilimab, and another cycle of sintilimab and chemotherapy thereafter. Surgery is preferably scheduled within one to three weeks, and three cycles of adjuvant sintilimab and chemotherapy are administrated. The primary endpoint is the pathological complete response. Our results meet the pre-specified primary endpoint. Thirteen of 34 (38.2%) enrolled patients achieve pathological complete response (95% CI: 22.2-56.4). The secondary objectives include disease-free survival (DFS), major pathological response, R0 resection rate, overall survival (OS), event-free survival (EFS), and safety profile. The median DFS and EFS were 17.0 (95%CI: 11.1-20.9) and 21.1 (95%CI: 14.7-26.1) months, respectively, while the median OS was not reached, and the 1-year OS rate was 92.6% (95%CI: 50.1-99.5%). Seventeen patients (50.0%) have grade ≥3 adverse events during preoperative therapy. In prespecified exploratory biomarker analysis, CD3+ T cells, CD56+ NK cells, and the M1/M1 + M2-like macrophage infiltration at baseline are associated with pathological complete response. Here, we show the promising efficacy and manageable safety profile of sintilimab in combination with concurrent chemoradiotherapy for the perioperative treatment of locally advanced gastric/gastroesophageal junction adenocarcinoma.

Abstract The Wide-Lane (WL) and Narrow-Lane (NL) Uncalibrated Phase Delays (UPDs) are the prerequisites in the traditional Precise Point Positioning (PPP) Ambiguity Resolution (AR). As the generation mechanism of various biases becomes more complex, we systematically studied the impact factors of four satellite systems WL and NL UPDs from the perspective of parameter estimation. Approximately 100 stations in a global network are used to generate the UPDs. The results of different satellite systems show that the estimation method, update frequency, and solution mode need to be treated differently. Two regional networks with different receiver types, JAVAD, and Trimble, are also adopted. The results indicate that the receiver-dependent bias has an influence on UPD estimation. Also, the hardware delays can inhibit the satellite-side UPDs if these receiver-specific errors are not fully deployed or even misused. Furthermore, the temporal stability and residual distribution of NL UPDs are significantly enhanced by utilizing a regional network, with the improvements by over 68% and 40%, respectively. It demonstrates that different network scales exhibit the different implication of unmodeled errors, and the unmodeled errors cannot be ignored and must be handled in UPD estimation.

Abstract Objective Sjögren’s syndrome (SS) is an inflammatory autoimmune disease characterized by high levels of chronic lymphocyte infiltration. Differences and dysfunction in the gut microbiota and metabolites may be closely related to the pathogenesis of SS. The purpose of this study was to reveal the relationship between the gut microbiota and metabolome in NOD mice as a model of SS and the role of FuFang Runzaoling (FRZ), which is a clinically effective in treating SS. Methods NOD mice were gavaged with FRZ for 10 weeks. The ingested volume of drinking water, submandibular gland index, pathologic changes of the submandibular glands, and serum cytokines interleukin (IL)-6, IL-10, IL-17 A, and tumor necrosis factor-alpha (TNF-α) were determined. The roles of FRZ on gut microbiota and fecal metabolites were explored by 16 S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC-MC), respectively. The correlation between them was determined by Pearson correlation analysis. Results Compared with the model group, the drinking water volume of NOD mice treated with FRZ increased and the submandibular gland index decreased. FRZ effectively ameliorated lymphocyte infiltration in the small submandibular glands in mice. Serum levels of IL-6, TNF-α, and IL-17 A decreased, and IL-10 increased. The Firmicutes/Bacteroidetes ratio in the FRZ treatment group was higher. FRZ significantly downregulated the relative abundance of the family Bacteroidaceae and genus Bacteroides, and significantly upregulated the relative abundance of genus Lachnospiraceae_UCG-001. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) revealed the significant change in fecal metabolites after FRZ treatment. Based on criteria of OPLS-DA variable influence on projection > 1, P 50, a total of 109 metabolites in the FRZ-H group were differentially regulated (47 downregulated and 62 upregulated) compared to their expressions in the model group. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed enriched metabolic of sphingolipid metabolism, retrograde endocannabinoid signaling, GABAergic synapse, necroptosis, arginine biosynthesis, and metabolism of histidine, alanine, aspartate, and glutamate. Correlation analysis between gut microbiota and fecal metabolites suggested that the enriched bacteria were related to many key metabolites. Conclusions Taken together, we found FRZ could reduce the inflammatory responses in NOD mice by regulating the gut microbiota, fecal metabolites, and their correlation to emerge a therapeutic effect on mice with SS. This will lay the foundation for the further studies and applications of FRZ, and the use of gut microbiotas as drug targets to treat SS. Graphical Abstract

Abstract Background Genome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently. Results By leveraging summary statistics of 37 traits from East Asian (N max=254,373) or European (N max=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρ g ) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with $${\widehat{\rho }}_{g}$$ ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs. Conclusions Our study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

Abstract Background Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear. Results By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection. Conclusions Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

Objectives: This study aimed to evaluate the joint effects of multiple air pollutants including PM2.5, PM10, NO2, and NOx with dementia and examined the modifying effects of genetic susceptibility.Methods: This study included 220,963 UK Biobank participants without dementia at baseline. Weighted air pollution score reflecting the joint exposure to multiple air pollutants were constructed by cross-validation analyses, and inverse-variance weighted meta-analyses were performed to create a pooled effect. The modifying effect of genetic susceptibility on air pollution score was assessed by genetic risk score and APOE ε4 genotype.Results: The HR (95% CI) of dementia for per interquartile range increase of air pollution score was 1.13 (1.07∼1.18). Compared with the lowest quartile (Q1) of air pollution score, the HR (95% CI) of Q4 was 1.26 (1.13∼1.40) (Ptrend = 2.17 × 10−5). Participants with high air pollution score and high genetic susceptibility had higher risk of dementia compared to those with low air pollution score and low genetic susceptibility.Conclusion: Our study provides evidence that joint exposure to multiple air pollutants substantially increases the risk of dementia, especially among individuals with high genetic susceptibility.

ObjectivesAdverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs.MethodsSeven categories of ACE and four classifications of psychiatric disorders were defined in a sample of 126,064 participants identified by the UK Biobank from 2006–2022, and correlations were investigated using logistic regression models. Then, to explore nonlinear relationships, restricted spline models were developed to examine differences in sex and age across cohorts (n = 126,064 for the full cohort and n = 121,934 for the European cohort). Finally, the impact of the category of ACEs on psychiatric disorders was examined.ResultsAfter controlling for confounders, ACEs scores showed dose-dependent relationships with depression, anxiety, anxiety-depression co-morbidity, and at least one (any of the first three outcomes) in all models. ACEs with different scores were significantly positively correlated with the four psychiatric disorders classifications, with the highest odds of anxiety-depression co-morbidity (odds ratio [OR] = 4.87, 95% confidence intervals [CI]: 4.37 ~ 5.43), p = 6.08 × 10−178. In the restricted cubic spline models, the risk was relatively flat for females at ACEs = 0–1 and males at ACEs = 0–2/3 (except in males, where ACEs were associated with a lower risk of anxiety, all other psychiatric disorders had an increased risk of morbidity after risk smoothing). In addition, the risk of having anxiety, depression, anxiety-depression co-morbidity, and at least one of these disorders varies with each category of ACEs.ConclusionThe prevalence of anxiety-depression comorbidity was highest across ACE scores after controlling for confounding factors and had a significant effect on each category of ACEs.

Background: To explore the long-term relationship between maternal smoking during pregnancy and early childhood growth in the UK Biobank cohort. Methods: To estimate the effect of maternal smoking during pregnancy on offspring height and body size at ten years old, we performed binary logistic analyses and reported odds ratios (OR) as well as 95% confidence intervals (95%CIs). We also implemented the cross-contextual comparison study to examine whether such influence could be repeatedly observed among three different ethnicities in the UK Biobank cohort (n = 22,140 for White, n = 7094 for South Asian, and n = 5000 for Black). In particular, we conducted the sibling cohort study in White sibling cohort (n = 9953 for height and n = 7239 for body size) to control for unmeasured familial confounders. Results: We discovered that children whose mothers smoked during pregnancy had greater risk of being shorter or plumper at age ten in the full UK Biobank White cohort, with 15.3% (95% CIs: 13.0%∼17.7%) higher risk for height and 32.4% (95%CIs: 29.5%∼35.4%) larger risk for body size. Similar associations were identified in the South Asian and Black ethnicities. These associations were robust and remained significant in the White sibling cohort (12.6% [95%CIs: 5.0%∼20.3%] for height and 36.1% [95%CIs: 26.3%∼45.9%] for body size) after controlling for family factors. Conclusion: This study robustly confirms that maternal smoking during pregnancy can promote height deficit and obesity for offspring at ten years old. Our findings strongly encourage mothers to quit smoking during pregnancy for improving growth and development of offspring.

Background and objectivesNationwide data were used to explore factors associated with physical function in order to identify interventions that could improve and maintain physical function in the older people.MethodsThe physical function was assessed by gait speed (GS). We selected 2,677 male and 2,668 female older adults (aged ≥60) who could perform the GS test as study subjects. GS was measured by having subjects walk across and back a 10-m course. A gait speed less than 20% that of a reference population (

ABSTRACT Albofungin is a promising broad-spectrum antimicrobial compound against multidrug-resistant bacteria. In the present study, we further investigated albofungin’s biofilm eradication activity and its potential mode of action against drug-resistant Vibrio parahaemolyticus. Among all derivatives, albofungin exhibited the best antibiofilm and antibacterial activity with rapid killing effects at 0.12 µg mL−1. Confocal microscopy observation exhibited that albofungin disrupted V. parahaemolyticus biofilms by killing or dispersing biofilm cells. Meanwhile, scanning electron microscope and fluorescent staining experiments demonstrated that albofungin rapidly destroyed the integrity and permeability of the bacterial cell membrane. Moreover, this study revealed an antibiofilm mechanism of albofungin involving inhibition of peptidoglycan biosynthesis, flagella assembly pathways, and secretion system proteins in V. parahaemolyticus by quantitative proteomics and validation experiments. Our results highlighted albofungin’s mechanism of action in planktonic cells and biofilms and suggested further development and potential applications of albofungin for treating infections caused by penicillins-and-cephalosporins-resistant V. parahaemolyticus. IMPORTANCE Infections caused by multidrug-resistant bacteria, as well as a scarcity of new antibiotics, have become a major health threat worldwide. To tackle the demand for new and effective treatments, we investigated the mechanism of action of albofungin, a natural product derived from Streptomyces, which exhibits potent antimicrobial activity against multidrug-resistant bacteria. Albofungin showed potent biofilm eradication activity against penicillins-and-cephalosporins-resistant Vibrio parahaemolyticus, which expresses a novel metallo-β-lactamase and, thus, reduces their sensitivity to various antibiotics. We observed membrane disruption and permeation mechanisms in planktonic cells and biofilms after albofungin treatment, while albofungin had a weak interaction with bacterial DNA. Moreover, the antibiofilm mechanism of albofungin included inhibition of peptidoglycan biosynthesis, flagellar assembly pathways, and secretion system proteins. Our finding suggested potential applications of albofungin as an antibacterial and antibiofilm therapeutic agent.

Current electronic voting systems mostly relied on central server and the trusted third party, this kind system architecture increases the security risks of voting, and even makes voting fail.In order to solve this issue, an electronic voting system BFV-blockchainvoting that supported BFV homomorphic encryption was proposed, and this system applied the blockchain technology to the electronic voting system to replace the trusted third party.Firstly, an open and transparent bulletin board was used to record the vote information, and an intelligent contract was used to realize the functions of verification and self counting.Secondly, in order to further improve the security and reliability of the voting process, the voter’s registration information was signed by SM2 signature algorithm, the ballot was managed by both parties that can supervise each other, and the counting data was encrypted by the BFV full homomorphic encryption algorithm.Finally, the evaluation of performance shows that it only costs 1.69 ms to complete one ballot in the proposed electronic voting system.This electronic voting scheme based on the BFV full homomorphic encryption and blockchain has better security attributes such as manipulation-resistance, anonymity, verifiability, double-voting resistance, coercion-resistance and resistance to quantum attacks.The scheme is suitable for a variety of voting scenarios and can meet the efficiency requirements in large voting scenarios.

Abstract Background Detecting trans-ethnic common associated genetic loci can offer important insights into shared genetic components underlying complex diseases/traits across diverse continental populations. However, effective statistical methods for such a goal are currently lacking. Methods By leveraging summary statistics available from global-scale genome-wide association studies, we herein proposed a novel genetic overlap detection method called CONTO (COmposite Null hypothesis test for Trans-ethnic genetic Overlap) from the perspective of high-dimensional composite null hypothesis testing. Unlike previous studies which generally analyzed individual genetic variants, CONTO is a gene-centric method which focuses on a set of genetic variants located within a gene simultaneously and assesses their joint significance with the trait of interest. By borrowing the similar principle of joint significance test (JST), CONTO takes the maximum P value of multiple associations as the significance measurement. Results Compared to JST which is often overly conservative, CONTO is improved in two aspects, including the construction of three-component mixture null distribution and the adjustment of trans-ethnic genetic correlation. Consequently, CONTO corrects the conservativeness of JST with well-calibrated P values and is much more powerful validated by extensive simulation studies. We applied CONTO to discover common associated genes for 31 complex diseases/traits between the East Asian and European populations, and identified many shared trait-associated genes that had otherwise been missed by JST. We further revealed that population-common genes were generally more evolutionarily conserved than population-specific or null ones. Conclusion Overall, CONTO represents a powerful method for detecting common associated genes across diverse ancestral groups; our results provide important implications on the transferability of GWAS discoveries in one population to others.

With the advancement in membrane technology, membrane separation technology has been found increasingly widespread applications in the pharmaceutical industry. It is utilized in drug separation and purification, wastewater treatment, and the recycling of wastewater resources. This study summarizes the application history of membrane technology in the pharmaceutical industry, presents practical engineering examples of its applications, analyzes the various types of membrane technologies employed in the pharmaceutical sector, and finally, highlights the application cases of renowned international and Chinese membrane technology companies in the pharmaceutical field.

Abstract Background Multilocus analysis on a set of single nucleotide polymorphisms (SNPs) pre-assigned within a gene constitutes a valuable complement to single-marker analysis by aggregating data on complex traits in a biologically meaningful way. However, despite the existence of a wide variety of SNP-set methods, few comprehensive comparison studies have been previously performed to evaluate the effectiveness of these methods. Results We herein sought to fill this knowledge gap by conducting a comprehensive empirical comparison for 22 commonly-used summary-statistics based SNP-set methods. We showed that only seven methods could effectively control the type I error, and that these well-calibrated approaches had varying power performance under the simulation scenarios. Overall, we confirmed that the burden test was generally underpowered and score-based variance component tests (e.g., sequence kernel association test) were much powerful under the polygenic genetic architecture in both common and rare variant association analyses. We further revealed that two linkage-disequilibrium-free P value combination methods (e.g., harmonic mean P value method and aggregated Cauchy association test) behaved very well under the sparse genetic architecture in simulations and real-data applications to common and rare variant association analyses as well as in expression quantitative trait loci weighted integrative analysis. We also assessed the scalability of these approaches by recording computational time and found that all these methods can be scalable to biobank-scale data although some might be relatively slow. Conclusion In conclusion, we hope that our findings can offer an important guidance on how to choose appropriate multilocus association analysis methods in post-GWAS era. All the SNP-set methods are implemented in the R package called MCA, which is freely available at https://github.com/biostatpzeng/ .

Abstract Breast cancer (BRCA) is the primary cause of mortality among females globally. The combination of advanced genomic analysis with proteomics characterization to construct a protein prognostic model will help to screen effective biomarkers and find new therapeutic directions. This study obtained proteomics data from The Cancer Proteome Atlas (TCPA) dataset and clinical data from The Cancer Genome Atlas (TCGA) dataset. Kaplan–Meier and Cox regression analyses were used to construct a prognostic risk model, which was consisted of 6 proteins (CASPASE7CLEAVEDD198, NFKBP65-pS536, PCADHERIN, P27, X4EBP1-pT70, and EIF4G). Based on risk curves, survival curves, receiver operating characteristic curves, and independent prognostic analysis, the protein prognostic model could be viewed as an independent factor to accurately predict the survival time of BRCA patients. We further validated that this prognostic model had good predictive performance in the GSE88770 dataset. The expression of 6 proteins was significantly associated with the overall survival of BRCA patients. The 6 proteins and encoding genes were differentially expressed in normal and primary tumor tissues and in different BRCA stages. In addition, we verified the expression of 3 differential proteins by immunohistochemistry and found that CDH3 and EIF4G1 were significantly higher in breast cancer tissues. Functional enrichment analysis indicated that the 6 genes were mainly related to the HIF-1 signaling pathway and the PI3K-AKT signaling pathway. This study suggested that the prognosis-related proteins might serve as new biomarkers for BRCA diagnosis, and that the risk model could be used to predict the prognosis of BRCA patients.

The drug otilonium bromide restores the activity of colistin against colistinresistant Gram-negative bacteria in vitro and in a mouse infection model, suggesting that this combination may restore the value of colistin in treatment of antibiotic resistant disease.

BackgroundSocial frailty is one type of frailty. Physical frailty with cardiovascular and cerebrovascular diseases (CCVD) have been studied a lot, but less research on social frailty.ObjectivesTo study the prevalence, related risk factors and regional differences of social frailty with CCVD in Chinese older adults.MethodsSSAPUR was a national cross-sectional survey. Participants aged 60 years or older were recruited in August 2015. Demographic data and information regarding family, health and medical conditions, living environment conditions, social participation, spiritual and cultural life, and health condition were obtained. Social frailty was assessed in five areas (HALFE Social Frailty Index) including inability to help others, limited social participation, loneliness, financial difficulty, and living alone. The prevalence of CCVD with social frailty, related risk factors and regional differences in CCVD with social frailty were studied.ResultsA total of 222,179 participants were enrolled. 28.4% of them had CCVD history. The prevalence of social frailty in the CCVD group was 16.03%. In CCVD participants, compared with the group without social frailty, there were significant differences in gender, age, urban–rural distribution, ethnicity, marital status, and education levels in the social frailty group. Significant differences were also found in physical exercise participation, health status, cataract, hypertension, diabetes mellitus, hospitalization within 1 year, self-assessed health status, crutch or wheelchair usage, urinary and fecal incontinence, need for care from others, fall history, housing satisfaction, and self-assessed happiness in the social frailty group. Women with CCVD had a higher prevalence of social frailty than men. By age in CCVD with social frailty, the highest prevalence was found in participants 75–79 years old. The prevalence of CCVD was significant difference between social frailty in urban and rural group. The prevalence of social frailty with CCVD was significantly different in different regions. The highest prevalence was 20.4% in southwest area, and the lowest prevalence was 12.5% in northeast with area.ConclusionThe prevalence of social frailty among the CCVD older adults is high. Factors such as gender, age, region, urban–rural residence, and the state of the disease may be associated with social frailty.

BackgroundThis study aimed to examine depressive symptoms associated with interpersonal sensitivity, sleep quality, and psychological capital among postgraduate students during static campus management after the COVID-19 pandemic in China.MethodsResearch data were obtained during static campus management (10–19 April 2022) after the reappearance of COVID-19 in cities in eastern China. We collected data through an online questionnaire, and the anonymous self-reported questionnaire included the Patient Health Questionnaire, the interpersonal sensitivity subscale of Symptom Checklist-90, the Psychological Capital Questionnaire, and the Pittsburgh Sleep Quality Index. analysis of variance was performed using t-test and ANOVA. The PROCESS macro was used to determine the relationship between interpersonal sensitivity and depression, together with the independent and serial mediating role of psychological capital and sleep quality.ResultsA total of 2,554 postgraduate students were included in this study. The prevalence of mild, moderate, and severe depressive symptoms was 30.97, 6.58, and 1.45%, respectively. Interpersonal sensitivity was significantly associated with depressive symptoms (direct effect = 0.183, p < 0.001). Between interpersonal sensitivity and depressive symptoms, psychological capital and sleep quality played a single mediating role (indirect effect = 0.136 and 0.100, p < 0.001, respectively) and a chain mediating role together (indirect effect = 0.066, p < 0.001).ConclusionInterpersonal sensitivity has a significant influence on depression among Chinese graduate students. Psychological capital and sleep quality may not only independently mediate the relationship between interpersonal sensitivity and depression, but also co-play a chain-mediating role in the pathway from interpersonal sensitivity to depression. Positive psychological interventions and sleep guidance may be beneficial in alleviating depressive symptoms.

BackgroundA greatly growing body of literature has revealed the mediating role of DNA methylation in the influence path from childhood maltreatment to psychiatric disorders such as post-traumatic stress disorder (PTSD) in adult. However, the statistical method is challenging and powerful mediation analyses regarding this issue are lacking.MethodsTo study how the maltreatment in childhood alters long-lasting DNA methylation changes which further affect PTSD in adult, we here carried out a gene-based mediation analysis from a perspective of composite null hypothesis in the Grady Trauma Project (352 participants and 16,565 genes) with childhood maltreatment as exposure, multiple DNA methylation sites as mediators, and PTSD or its relevant scores as outcome. We effectively addressed the challenging issue of gene-based mediation analysis by taking its composite null hypothesis testing nature into consideration and fitting a weighted test statistic.ResultsWe discovered that childhood maltreatment could substantially affected PTSD or PTSD-related scores, and that childhood maltreatment was associated with DNA methylation which further had significant roles in PTSD and these scores. Furthermore, using the proposed mediation method, we identified multiple genes within which DNA methylation sites exhibited mediating roles in the influence path from childhood maltreatment to PTSD-relevant scores in adult, with 13 for Beck Depression Inventory and 6 for modified PTSD Symptom Scale, respectively.ConclusionOur results have the potential to confer meaningful insights into the biological mechanism for the impact of early adverse experience on adult diseases; and our proposed mediation methods can be applied to other similar analysis settings.

Abstract Background Previous studies demonstrated a positive relationship between birthweight and breast cancer; however, inconsistent, sometimes even controversial, observations also emerged, and the nature of such relationship remains unknown. Methods Using summary statistics of birthweight and breast cancer, we assessed the fetal/maternal-specific genetic correlation between them via LDSC and prioritized fetal/maternal-specific pleiotropic genes through MAIUP. Relying on summary statistics we conducted Mendelian randomization (MR) to evaluate the fetal/maternal-specific origin of causal relationship between birthweight, age of menarche, age at menopause and breast cancer. Results With summary statistics we identified a positive genetic correlation between fetal-specific birthweight and breast cancer (r g = 0.123 and P = 0.013) as well as a negative but insignificant correlation between maternal-specific birthweight and breast cancer (r g = − 0.068, P = 0.206); and detected 84 pleiotropic genes shared by fetal-specific birthweight and breast cancer, 49 shared by maternal-specific birthweight and breast cancer. We also revealed fetal-specific birthweight indirectly influenced breast cancer risk in adulthood via the path of age of menarche or age at menopause in terms of MR-based mediation analysis. Conclusion This study reveals that shared genetic foundation and causal mediation commonly drive the connection between the two traits, and that fetal/maternal-specific birthweight plays substantially distinct roles in such relationship. However, our work offers little supportive evidence for the fetal origins hypothesis of breast cancer originating in utero.

ObjectiveThe purpose of the study was to identify the latent body mass index (BMI) z-score trajectories of children from birth to 5 years of age and evaluate their sex-specific association with prepregnant BMI and gestational weight gain (GWG).MethodsThis was a retrospective longitudinal cohort study performed in China. In total, three distinct BMI-z trajectories from birth to 5 years of age were determined for both genders using the latent class growth modeling. The logistic regression model was used to assess the associations of maternal prepregnant BMI and GWG with childhood BMI-z growth trajectories.ResultsExcessive GWG increased the risks of children falling into high-BMI-z trajectory relative to adequate GWG (OR = 2.04, 95% CI: 1.29, 3.20) in boys; girls born to mothers with prepregnancy underweight had a higher risk of low-BMI-z trajectory than girls born to mothers with prepregnancy adequate weight (OR = 1.85, 95% CI: 1.22, 2.79).ConclusionBMI-z growth trajectories of children from 0 to 5 years of age have population heterogeneity. Prepregnant BMI and GWG are associated with child BMI-z trajectories. It is necessary to monitor weight status before and during pregnancy to promote maternal and child health.

ObjectiveWe aimed to describe the trends and influence factors in the prevalence, awareness, treatment, and control of hypertension among US Adults from 1999 to 2018.MethodsWe utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning ten survey cycles (n = 53,496). Prevalence, awareness, treatment, and control of hypertension were calculated using survey weights. Joinpoint regression and survey-weighted generalized linear models were used to analyze trends and influence factors, respectively.ResultsThe estimated prevalence of hypertension increased significantly from 33.53% to 40.58% (AAPC = 0.896, P = 0.002) during 1999-2018 with dropping rate of newly diagnosed hypertension from 8.62% to 4.82% before 2014 (APC = -4.075, P = 0.001), and then rose to 7.51% in 2018 (APC = 12.302, P = 0.126). Despite modest improvements or stability in the awareness, treatment, and control since 1999, the latter two remained inadequate in 2018 at 59.52% and 51.71%. There was an uptrend in the use of angiotensin-converting enzyme inhibitors (from 24.02% to 45.71%) and angiotensin receptor blockers (from 20.22% to 38.38%), and downtrend in β-blocker (from 12.71% to 4.21%). Men were at higher risk of incidence, un-awareness, un-treatment, and un-control for hypertension. Lower income and education were associated with susceptibility to hypertension, while being married was favorable for treatment and control. Optimal health reduced the incidence of hypertension, and increased the awareness and treatment.ConclusionAlthough the rate of newly diagnosed hypertension has declined slightly since 2010 in the US, the prevalence of hypertension is increasing, and treatment and control rates remain inadequate. To manage hypertension effectively, we need to focus on screening and prevention for high-risk populations, while advocating for optimal health to improve the burden of hypertension.

Both schizophrenia (SZ) and multiple sclerosis (MS) affect millions of people worldwide and impose a great burden on society. Recent studies indicated that MS elevated the risk of SZ and vice versa, whereas the underlying pathological mechanisms are still obscure. Considering that fecal microbiota played a vital role in regulating brain functions, the fecal microbiota and serum cytokines from 90 SZ patients and 71 age-, gender-, and BMI-matched cognitively normal subjects (referred as SZC), 22 MS patients and 33 age-, gender-, and BMI-matched healthy subjects (referred as MSC) were analyzed. We found that both diseases demonstrated similar microbial diversity and shared three differential genera, including the down-regulated Faecalibacterium, Roseburia, and the up-regulated Streptococcus. Functional analysis indicated that the three genera were involved in pathways such as “carbohydrate metabolism” and “amino acid metabolism.” Moreover, the variation patterns of serum cytokines associated with MS and SZ patients were a bit different. Among the six cytokines perturbed in both diseases, TNF-α increased, while IL-8 and MIP-1α decreased in both diseases. IL-1ra, PDGF-bb, and RANTES were downregulated in MS patients but upregulated in SZ patients. Association analyses showed that Faecalibacterium demonstrated extensive correlations with cytokines in both diseases. Most notably, Faecalibacterium correlated negatively with TNF-α. In other words, fecal microbiota such as Faecalibacterium may contribute to the coexistence of MS and SZ by regulating serum cytokines. Our study revealed the potential roles of fecal microbiota in linking MS and SZ, which paves the way for developing gut microbiota-targeted therapies that can manage two diseases with a single treat.

Rheumatoid arthritis (RA) is a chronic progressive autoimmune disease characterized with high recurrence, high disability, poor prognosis, and long treatment cycles. Versus western medicine, traditional Chinese medicine has the traits of definite efficacy, low toxicity, and side effects in the treatment of RA. Moreover, traditional Chinese medicine also has the advantages of multiple targets, multiple links, and multiple approaches. This study was committed to exploring the effect of Jinwujiangu prescription on peripheral blood osteoclasts in those patients with RA and relevant molecular mechanisms. We first identified 159 common targets by online pharmacology, and there were correlations among these targets; besides, the main signaling pathways involved were inclusive TNF signaling pathway, rheumatoid arthritis, IL-17 signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, etc. Through experimental verification, we found that PBMC cells extracted from human peripheral blood could be successfully induced into osteoclasts, and Jinwujiangu prescription inhibited the generation of osteoclasts from PBMCs of RA patients. CCK-8 and flow cytometry showed that osteoclast viability was significantly decreased and osteoclast apoptosis was significantly increased in the HIF-1α interference group; low-, medium-, and high-dose Jinwujiangu prescription groups; sinapine group; and hydroxychloroquine control group. Moreover, Jinwujiangu prescription and sinapine could inhibit the production of cytokines in peripheral blood osteoclasts and inhibit autophagy in RA patients. The expression level of mTOR was significantly increased in both Jinwu middle- and high-dose groups. In conclusion, this study demonstrated that sinapine, the active target in Jinwujiangu prescription, can act as a HIF-1α inhibitor; activate the mTOR pathway; downregulate the level of autophagy rate, ATG5, beclin-1, and LC3 expression; and inhibit the occurrence of autophagy. The trial registration number of the study is KYW2021010.

Abstract Background Cetuximab is used for colorectal cancer (CRC) treatment. However, the early biomarker of treatment efficacy of cetuximab has not been identified. Methods After 1 year of cetuximab treatment, patients were divided into an effective group and an ineffective group. The interleukin‐33 (IL‐33) level and the distribution of lymphatic cells in patients were investigated by analyzing the peripheral blood mononuclear cells via flow cytometry analysis and ELISA. The correlation between IL‐33 immunomodulatory effect and cetuximab treatment efficacy was determined through experiments in vivo and in vitro. Results The IL‐33 level in the peripheral blood was increased at 4 weeks after cetuximab administration of effective group, meanwhile, the osteopontin (OPN) was reduced. Whereas neither IL‐33 level nor OPN level of ineffective patients changed. In the effective group, the number of natural killer (NK) and CD8+ T cells were increased. Moreover, CD137 and CD107a expression on NK cells were higher in the effective group compared to the ineffective group. In vitro cetuximab treatment also increased the number of NK and CD8+ T cells as well as CD137 and CD107a expression upon IL‐33 stimulation. Moreover, the secretion of OPN was inhibited by IL‐33 administration in cetuximab‐treated PBMCs from the effective group patients. IL‐33 upregulated the cytotoxicity of NK cells and inhibited tumor cells growth in the effective cetuximab treatment mice. Conclusion Effective cetuximab treatment induced a change of IL‐33 and OPN at the early stage and triggered the NK cells antitumor activity. Consequently, significantly increased IL‐33 level and decreased OPN level in the peripheral blood at the early treatment are proposed as potential predictors of cetuximab treatment efficacy.

Abstract Background Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear. Methods We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders. Results We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders. Conclusions Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.

ABSTRACT The gut microbiome is involved in metabolic disorders. Osteopontin (OPN), as a key cytokine, contributes to various inflammation-related diseases. The underlying role of OPN in the microbiome remains poorly understood. Here, we investigated whether OPN could modulate metabolic disorders by affecting gut microbiota. In our present study, we found that the expression of OPN was elevated in individuals with obesity compared to that observed in healthy controls. There was a positive correlation between plasma OPN levels and body mass index (BMI) in humans. Moreover, OPN significantly exacerbated lipid accumulation and metabolic disorders in high-fat diet (HFD)-fed mice. Importantly, OPN significantly aggravated HFD-induced gut dysbiosis with a key signature profile. Fecal microbiota transplantation also supported the role of OPN in HFD-induced metabolic disorders in a microbiota-dependent manner. Moreover, the microbiome shift of OPN-deficient mice would be compensated to resemble those of wild-type mice by feeding with either OPN-containing milk or recombinant OPN protein in vivo. Furthermore, metagenomic analysis showed that OPN induced a higher abundance of Dorea and a lower abundance of Lactobacillus, which were positively and negatively correlated with body weight, respectively. Indeed, the abundance of Dorea was significantly decreased after Lactobacillus administration, suggesting that OPN may regulate the intestinal abundance of Dorea by reducing the colonization of Lactobacillus. We further confirmed that OPN decreased the adhesion of Lactobacillus to intestinal epithelial cells through the Notch signaling pathway. This study suggested that OPN could exacerbate HFD-induced metabolic dysfunctions through the OPN-induced alteration of the gut microbiome. Therefore, OPN could be a potential therapeutic target for metabolic syndrome. IMPORTANCE Gut microbiota are involved in metabolic disorders. However, microbiome-based therapeutic interventions are not always effective, which might be due to interference of the host factors. Here, we identified a strong positive correlation between OPN levels and BMI in humans. Next, we confirmed that OPN could aggravate high-fat diet-induced metabolic disorders in mice. Importantly, we found that fecal microbiota transplantation from OPN-deficient mice significantly alleviated metabolic disorders in WT mice. OPN directly induces the remodeling of the gut microbiota both in vitro and in vivo. These findings indicate that OPN could contribute to metabolic disorders by inducing an alteration of gut microbiota. OPN regulated the relative abundance of Lactobacillus by decreasing the adhesion of Lactobacillus to intestinal epithelial cells through the Notch signaling pathway. These data identify OPN as a potential pharmaceutical target for weight control and for the treatment of metabolic disorders.

Abstract Background Integrating functional annotations into SNP-set association studies has been proven a powerful analysis strategy. Statistical methods for such integration have been developed for continuous and binary phenotypes; however, the SNP-set integrative approaches for time-to-event or survival outcomes are lacking. Methods We here propose IEHC, an integrative eQTL (expression quantitative trait loci) hierarchical Cox regression, for SNP-set based survival association analysis by modeling effect sizes of genetic variants as a function of eQTL via a hierarchical manner. Three p-values combination tests are developed to examine the joint effects of eQTL and genetic variants after a novel decorrelated modification of statistics for the two components. An omnibus test (IEHC-ACAT) is further adapted to aggregate the strengths of all available tests. Results Simulations demonstrated that the IEHC joint tests were more powerful if both eQTL and genetic variants contributed to association signal, while IEHC-ACAT was robust and often outperformed other approaches across various simulation scenarios. When applying IEHC to ten TCGA cancers by incorporating eQTL from relevant tissues of GTEx, we revealed that substantial correlations existed between the two types of effect sizes of genetic variants from TCGA and GTEx, and identified 21 (9 unique) cancer-associated genes which would otherwise be missed by approaches not incorporating eQTL. Conclusion IEHC represents a flexible, robust, and powerful approach to integrate functional omics information to enhance the power of identifying association signals for the survival risk of complex human cancers.

Abstract Since the COVID‐19 pandemic, physicians concerned about the potential adverse effects of angiotensin converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs). To explore the relationship between ACEIs/ARBs and the risk of mortality and other clinical outcomes in COVID‐19 patients, the authors conducted a systemic review and meta‐analysis. An electronic search was performed from inception to November 12, 2020 in PubMed, Medline, EMBASE, ClinicalTrials, TRIP, the Cochrane Library, CNKI, Wanfang, and CBM database. Risk of bias was assessed using the Risk Of Bias In Non‐randomized Studies of Interventions tool. The primary outcome was in‐hospital all‐cause mortality. Secondary outcomes included all‐cause mortality measured at 30‐day or longer term, mechanical ventilation, length of hospital stay, readmission, and cardiac adverse events. A total of 28 studies with 73 465 patients was included. Twenty‐two studies with 19 871 patients reported the incidence of all‐cause mortality. Results showed no association between using ACEIs/ARBs and risk of mortality crude odds ratio （OR） of 1.02, 95% CI 0.71–1.46, p = .90, I2 = 88%, adjusted OR in 6260 patients of 0.96, 95% CI 0.77–1.18, p = .68, I2 = 0%. While six studies with 10 030 patients reported a lower risk of mortality in ACEIs/ARBs group hazard ratio (HR) of 0.53, 95% CI 0.34–0.84, p = .007, I2 = 68%. Similar association (for HR) was found in hypertension subgroup. There was no significant association for the secondary outcomes. Based on the available data, we concluded that ACEIs/ARBs is not associated with the risk of in‐hospital all‐cause mortality in COVID‐19 patients, but may be associated with a decreased risk of 30‐day all‐cause mortality. Patients with hypertension may benefit from using ACEIs/ARBs.

To investigate the prevalence of interpersonal sensitivity, anxiety, depression symptoms and associated risk factors among a large-scale sample of college students in China during the COVID-19 campus lockdown. The survey was conducted among undergraduate students at a university in eastern part of China in April 2022. The Chi-square test was used to compare the different variable groups and multivariable analysis was performed for the risk factors associated with interpersonal sensitivity, anxiety, and depression symptoms. A total of 12,922 college students were included, with an average age of (20.96 ± 1.66) years. The prevalence of interpersonal sensitivity, anxiety and depression symptoms in this study was 58.1, 22.7, and 46.8%, respectively. Male (OR = 1.16, p

BackgroundChildhood-onset asthma (COA) has become a major and growing problem worldwide and imposes a heavy socioeconomic burden on individuals and families; therefore, understanding the influence of early-life experiences such as breastfeeding on COA is of great importance for early prevention.ObjectivesTo investigate the impact of breastfeeding on asthma in children under 12 years of age and explore its role at two different stages of age in the UK Biobank cohort.MethodsA total of 7,157 COA cases and 158,253 controls were obtained, with information regarding breastfeeding, COA, and other important variables available through questionnaires. The relationship between breastfeeding and COA were examined with the logistic regression while adjusting for available covariates. In addition, a sibling analysis was performed on 398 pairs of siblings to explain unmeasured family factors, and a genetic risk score analysis was performed to control for genetic confounding impact. Finally, a power evaluation was conducted in the sibling data.ResultsIn the full cohort, it was identified that breastfeeding had a protective effect on COA (the adjusted odds ratio (OR)=0.875, 95% confidence intervals (CIs): 0.831~0.922; P=5.75×10-7). The impact was slightly pronounced in children aged 6-12 years (OR=0.852, 95%CIs: 0.794~0.914, P=7.41×10-6) compared to those aged under six years (OR=0.904, 95%CIs: 0.837~0.975, P=9.39×10-3), although such difference was not substantial (P=0.266). However, in the sibling cohort these protective effects were no longer significant largely due to inadequate samples as it was demonstrated that the power was only 23.8% for all children in the sibling cohort under our current setting. The protective effect of breastfeeding on COA was nearly unchanged after incorporating the genetic risk score into both the full and sibling cohorts.ConclusionsOur study offered supportive evidence for the protective effect of breastfeeding against asthma in children less than 12 years of age; however, sibling studies with larger samples were warranted to further validate the robustness our results against unmeasured family confounders. Our findings had the potential to encourage mothers to initiate and prolong breastfeeding.

Abstract Elderly people and patients with comorbidities are at higher risk of COVID-19 infection, resulting in severe complications and high mortality. However, the underlying mechanisms are unclear. In this study, we investigate whether miRNAs in serum exosomes can exert antiviral functions and affect the response to COVID-19 in the elderly and people with diabetes. First, we identified four miRNAs (miR-7-5p, miR-24-3p, miR-145-5p and miR-223-3p) through high-throughput sequencing and quantitative real-time PCR analysis, that are remarkably decreased in the elderly and diabetic groups. We further demonstrated that these miRNAs, either in the exosome or in the free form, can directly inhibit S protein expression and SARS-CoV-2 replication. Serum exosomes from young people can inhibit SARS-CoV-2 replication and S protein expression, while the inhibitory effect is markedly decreased in the elderly and diabetic patients. Moreover, three out of the four circulating miRNAs are significantly increased in the serum of healthy volunteers after 8-weeks’ continuous physical exercise. Serum exosomes isolated from these volunteers also showed stronger inhibitory effects on S protein expression and SARS-CoV-2 replication. Our study demonstrates for the first time that circulating exosomal miRNAs can directly inhibit SARS-CoV-2 replication and may provide a possible explanation for the difference in response to COVID-19 between young people and the elderly or people with comorbidities.