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Abstract Objective This study aimed to explore the application value of three-dimensional (3D) visualization technology in the early surgical repair of bile duct injury during laparoscopic cholecystectomy (LC). Methods A retrospective analysis was conducted on the clinical data of 15 patients who underwent early surgical repair of bile duct injury during LC with the assistance of 3D visualization technology at the Hepatobiliary Surgery Department of Ningxia Hui Autonomous Region People’s Hospital from January 2019 to December 2022. Postoperative efficacy and long-term follow-up outcomes were summarized. Results Before the repair surgery, 15 cases of bile duct injury during LC were evaluated using 3D visualization technology according to the Strasberg-Bismuth classification: 2 cases of type C, 4 of type E1, 3 of type E2, 3 of type E3, and 3 of type E4. Intraoperative findings were consistent with the 3D visualization reconstruction results, and all patients successfully underwent hepaticojejunostomy using Roux-en-Y anastomosis guided by the 3D visualization navigation. The time interval between LC and bile duct repair surgery ranged from 5 to 28 (14.2 ± 9.7) days. The surgical time was between 120 and 190 (156.40 ± 23.92) min, and estimated blood loss ranged from 80 to 250 (119.66 ± 47.60) mL. The length of hospital stay ranged from 12 to 25 days (median: 16 days). One patient experienced mild bile leakage after the operation, which healed with conservative treatment. All patients were followed up for 12–56 months (median: 34 months) without any loss to follow-up. During the follow-up period, no complications, such as anastomotic stricture or stone formation, were observed. Conclusion The application of 3D visualization technology for preoperative evaluation and intraoperative navigation can accurately and effectively facilitate early surgical repair of bile duct injury during LC and has clinical value for promotion and application.

Abstract Background There is currently a lack of comprehensive evidence regarding the correlation between Alternate Mediterranean Diet (AMED) and the survival of patients with ovarian cancer (OC). This prospective cohort study first assessed the association of AMED, not only pre-diagnosis and post-diagnosis but also the change from pre-diagnosis to post-diagnosis with OC survival. Methods A total of 560 OC patients were included in the study, and their dietary intake was assessed using a reliable 111-item food frequency questionnaire. The overall survival (OS) of the patients was monitored through active follow-up and review of medical records until February 16th, 2023. Cox proportional hazard regression models were utilized to compute the hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs). Results Out of the total 560 patients with OC, 211 (37.68%) succumbed during a median follow-up period of 44.40 months (interquartile range: 26.97–61.37). Comparative analysis indicated a significant association between the highest tertiles of pre-diagnosis (HR = 0.59; 95% CI 0.38–0.90; P trend

Abstract Enhancing drought tolerance in crops and understanding the underlying mechanisms have been subject of intense research. The precise function and molecular mechanisms of B-box zinc finger proteins (BBX) remain elusive. Here, we report a natural allele of BBX18 (BBX18 TT ) that encodes a C-terminal truncated protein. While most wild tomato germplasms contain the BBX18 CC allele and show more drought tolerant, modern cultivated tomatoes mostly carry BBX18 TT allele and are more drought sensitive. Knockout of BBX18 leads to improved drought tolerance in transgenic plants of cultivated tomato. Ascorbate peroxidase 1 (APX1) is identified as a BBX18-interacting protein that acts as a positive regulator of drought resistance in tomato. Chromatin immunoprecipitation sequencing analyses reveal that BBX18 binds to a unique cis-acting element of the APX1 promoter and represses its gene expression. This study provides insights into the molecular mechanism underlying drought resistance mediated by the BBX18-APX1 module in plants.

Abstract Background Numerous meta-analyses have explored the association between the triglyceride-glucose (TyG) index and diverse health outcomes, yet the comprehensive assessment of the scope, validity, and quality of this evidence remains incomplete. Our aim was to systematically review and synthesise existing meta-analyses of TyG index and health outcomes and to assess the quality of the evidence. Methods A thorough search of PubMed, EMBASE, and Web of Science databases was conducted from their inception through to 8 April 2024. We assessed the quality of reviews using A Measurement Tool to Assess Systematic Reviews (AMSTAR) and the certainty of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) system. This study was registered with PROSPERO (CRD: 42024518587). Results Overall, a total of 95 associations from 29 meta-analyses were included, investigating associations between TyG index and 30 health outcomes. Of these, 83 (87.4%) associations were statistically significant (P

Abstract Background Numerous studies have been conducted to investigate the relationship between ABO and Rhesus (Rh) blood groups and various health outcomes. However, a comprehensive evaluation of the robustness of these associations is still lacking. Methods We searched PubMed, Web of Science, Embase, Scopus, Cochrane, and several regional databases from their inception until Feb 16, 2024, with the aim of identifying systematic reviews with meta-analyses of observational studies exploring associations between ABO and Rh blood groups and diverse health outcomes. For each association, we calculated the summary effect sizes, corresponding 95% confidence intervals, 95% prediction interval, heterogeneity, small-study effect, and evaluation of excess significance bias. The evidence was evaluated on a grading scale that ranged from convincing (Class I) to weak (Class IV). We assessed the certainty of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation criteria (GRADE). We also evaluated the methodological quality of included studies using the A Measurement Tool to Assess Systematic Reviews (AMSTAR). AMSTAR contains 11 items, which were scored as high (8–11), moderate (4–7), and low (0–3) quality. We have gotten the registration for protocol on the PROSPERO database (CRD42023409547). Results The current umbrella review included 51 systematic reviews with meta-analysis articles with 270 associations. We re-calculated each association and found only one convincing evidence (Class I) for an association between blood group B and type 2 diabetes mellitus risk compared with the non-B blood group. It had a summary odds ratio of 1.28 (95% confidence interval: 1.17, 1.40), was supported by 6870 cases with small heterogeneity (I 2 = 13%) and 95% prediction intervals excluding the null value, and without hints of small-study effects (P for Egger’s test > 0.10, but the largest study effect was not more conservative than the summary effect size) or excess of significance (P

Abstract Background Wrist fracture is one of the common limb fractures. Its incidence rate increases with age and osteoporosis. Nowadays, Sleep health is increasingly valued, but the relationship between wrist fractures and sleep time is not yet clear. Methods Data in this study were collected and screened from the NHANES from 2005 to 2010 and 2013 to 2014. The variables were extracted from interviews and compared between the wrist fractures and the sleep duration. The data was analyzed by weighted multivariate logistic regression. Results After excluding individuals who were not eligible and had invalid data, we finally identified 1835 participants for inclusion in this study. We found a negative association between the sleep duration and the fractured of the wrist (OR = 1.027,95% CI (1.027, 1.028), P

In order to find new potential fungicides and anticancer agents, a series of new coumarin amide derivatives bearing fluorine were synthesized and characterized spectroscopically. Compounds A6, B11, C2 and C7 were confirmed by X-ray diffraction further. The antifungal bioassays against five typical pathogenic fungi showed that compound C5 exhibited more remarkable fungicidal activities against Alternaria alternata (EC50 = 11.5 μg/mL), Colletotrichum gloeosporioides (EC50 = 18.0 μg/mL), Pyricularia grisea (EC50 = 33.8 μg/mL), surpassing kresoxim-methyl. Molecular docking result indicated that C5 displayed high binding affinity to chitinase, which plays crucial role in degradation and remodeling of fungal cell walls. In addition, the anticancer bioassays against three cancer cells demonstrated that compound A4 displayed excellent growth inhibitory effect against Hela cells with IC50 value of 8.13 μM, and low cytotoxicity against human normal cells BEAS-2B. Flow cytometric analysis further demonstrated that A4 significantly arrested cell cycle at the S phase and trigger apoptosis. With the above interesting biological profile, these coumarin derivatives could be used as anfungicides and anticancer candidates.

Summary: Background: Two important questions regarding the genetics of pancreatic adenocarcinoma (PDAC) are 1. Which germline genetic variants influence the incidence of this cancer; and 2. Whether PDAC causally predisposes to associated non-malignant phenotypes, such as type 2 diabetes (T2D) and venous thromboembolism (VTE). Methods: In this study of 8803 patients with PDAC and 67,523 controls, we first performed a large-scale transcriptome-wide association study to investigate the association between genetically determined gene expression in normal pancreas tissue and PDAC risk. Secondly, we used Mendelian Randomization (MR) to analyse the causal relationships among PDAC, T2D (74,124 cases and 824,006 controls) and VTE (30,234 cases and 172,122 controls). Findings: Sixteen genes showed an association with PDAC risk (FDR

Abstract Background Early-onset prostate cancer (EOPC, ≤ 55 years) has a unique clinical entity harboring high genetic risk, but the majority of EOPC patients still substantial opportunity to be early-detected thus suffering an unfavorable prognosis. A refined understanding of age-based polygenic risk score (PRS) for prostate cancer (PCa) would be essential for personalized risk stratification. Methods We included 167,517 male participants [4882 cases including 205 EOPC and 4677 late-onset PCa (LOPC)] from UK Biobank. A General-, an EOPC- and an LOPC-PRS were derived from age-specific genome-wide association studies. Weighted Cox proportional hazard models were applied to estimate the risk of PCa associated with PRSs. The discriminatory capability of PRSs were validated using time-dependent receiver operating characteristic (ROC) curves with additional 4238 males from PLCO and TCGA. Phenome-wide association studies underlying Mendelian Randomization were conducted to discover EOPC linking phenotypes. Results The 269-PRS calculated via well-established risk variants was more strongly associated with risk of EOPC [hazard ratio (HR) = 2.35, 95% confidence interval (CI) 1.99–2.78] than LOPC (HR = 1.95, 95% CI 1.89–2.01; I 2 = 79%). EOPC-PRS was dramatically related to EOPC risk (HR = 4.70, 95% CI 3.98–5.54) but not to LOPC (HR = 0.98, 95% CI 0.96–1.01), while LOPC-PRS had similar risk estimates for EOPC and LOPC (I 2 = 0%). Particularly, EOPC-PRS performed optimal discriminatory capability for EOPC (area under the ROC = 0.613). Among the phenomic factors to PCa deposited in the platform of ProAP (Pro state cancer A ge-based P heWAS; https://mulongdu.shinyapps.io/proap ), EOPC was preferentially associated with PCa family history while LOPC was prone to environmental and lifestyles exposures. Conclusions This study comprehensively profiled the distinct genetic and phenotypic architecture of EOPC. The EOPC-PRS may optimize risk estimate of PCa in young males, particularly those without family history, thus providing guidance for precision population stratification.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Abstract Background The predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters for predicting AIP relapse is currently unknown. This study firstly explored the value of 18F-FDG PET/CT parameters as predictors of type 1 AIP relapse. Methods This multicenter retrospective cohort study analyzed 51 patients who received 18F-FDG PET/CT prior to treatment and did not receive maintenance therapy after remission. The study collected baseline characteristics and clinical data and conducted qualitative and semi-quantitative analysis of pancreatic lesions and extrapancreatic organs. The study used three thresholds to select the boundaries of pancreatic lesions to evaluate metabolic parameters, including the maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), total lesion glycolysis (TLG), metabolic tumor volume (MTV), and tumor-to-normal liver standard uptake value ratio (SUVR). Univariate and multivariate analyses were performed to identify independent predictors and build a recurrence prediction model. The model was internally validated using the bootstrap method and a nomogram was created for clinical application. Results In the univariable analysis, the relapsed group showed higher levels of SUVmax (6.0 ± 1.6 vs. 5.2 ± 1.1; P = 0.047), SUVR (2.3 [2.0–3.0] vs. 2.0 [1.6–2.4]; P = 0.026), and TLG2.5 (234.5 ± 149.1 vs. 139.6 ± 102.5; P = 0.020) among the 18F-FDG PET metabolic parameters compared to the non-relapsed group. In the multivariable analysis, serum IgG4 (OR, 1.001; 95% CI, 1.000–1.002; P = 0.014) and TLG2.5 (OR, 1.007; 95% CI, 1.002–1.013; P = 0.012) were independent predictors associated with relapse of type 1 AIP. A receiver-operating characteristic curve of the predictive model with these two predictors demonstrated an area under the curve of 0.806. Conclusion 18F-FDG PET/CT metabolic parameters, particularly TLG2.5, are potential predictors for relapse in patients with type 1 AIP. A multiparameter model that includes IgG4 and TLG2.5 can enhance the ability to predict AIP relapse.

Abstract Background Specific peripheral proteins have been implicated to play an important role in the development of Alzheimer’s disease (AD). However, the roles of additional novel protein biomarkers in AD etiology remains elusive. The availability of large-scale AD GWAS and plasma proteomic data provide the resources needed for the identification of causally relevant circulating proteins that may serve as risk factors for AD and potential therapeutic targets. Methods We established and validated genetic prediction models for protein levels in plasma as instruments to investigate the associations between genetically predicted protein levels and AD risk. We studied 71,880 (proxy) cases and 383,378 (proxy) controls of European descent. Results We identified 69 proteins with genetically predicted concentrations showing associations with AD risk. The drugs almitrine and ciclopirox targeting ATP1A1 were suggested to have a potential for being repositioned for AD treatment. Conclusions Our study provides additional insights into the underlying mechanisms of AD and potential therapeutic strategies.

Abstract Platinum-based chemotherapy remains one of the major choices for treatment of ovarian cancer (OC). However, primary or acquired drug resistance severely impairs their efficiency, thereby causing chemotherapy failure and poor prognosis. SH3 domain containing ring finger 2 (SH3RF2) has been linked to the development of cancer. Here we find higher levels of SH3RF2 in the tumor tissues from cisplatin-resistant OC patients when compared to those from cisplatin-sensitive patients. Similarly, cisplatin-resistant OC cells also express higher levels of SH3RF2 than normal OC cells. Through in vitro and in vivo loss-of-function experiments, SH3RF2 is identified as a driver of cisplatin resistance, as evidenced by increases in cisplatin-induced cell apoptosis and DNA damage and decreases in cell proliferation induced by SH3RF2 depletion. Mechanistically, SH3RF2 can directly bind to the RNA-binding protein mRNA processing factor (RBPMS). RBPMS has been reported as an inhibitor of cisplatin resistance in OC. As a E3 ligase, SH3RF2 promotes the K48-linked ubiquitination of RBPMS to increase its proteasomal degradation and activator protein 1 (AP-1) transactivation. Impairments in RBPMS function reverse the inhibitory effect of SH3RF2 depletion on cisplatin resistance. Collectively, the SH3RF2-RBPMS-AP-1 axis is an important regulator in cisplatin resistance and inhibition of SH3RF2 may be a potential target in preventing cisplatin resistance.

Abstract The support vector machine (SVM) method is an important basis of the current popular multi-class classification (MCC) methods and requires a sufficient number of samples. In the case of a limited number of samples, the problem of over-learning easily occurs, resulting in unsatisfactory classification. Therefore, this work investigates an MCC method that requires only a small number of samples. During model construction, raw data are converted into two-dimensional form via preprocessing. Via feature extraction, the learning network is measured and the loss function minimization principle is considered to better solve the problem of learning based on a small sample. Finally, three examples are provided to illustrate the feasibility and effectiveness of the proposed method.

Abstract Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR)

CO2 emissions prediction plays a key role in atmospheric environment management and regional sustainable development. Taking the Four Provinces of Mountains and Rivers (Henan, Hebei, Shandong, and Shanxi) in China as an example, the Autoregressive Integrated Moving Average Model (ARIMA) and random forest importance analysis were used to calculate the future trend of the CO2 emission–influencing factors and obtain the main influencing factors. Based on the above, BP neural network (BPNN), support vector machine (SVR), and random forest (RF) models were used to predict the future apparent CO2 emissions of the four provinces. The results show that, in general, population, coal consumption, and per capita GDP are the main factors influencing CO2 emissions. The RF model has the best prediction performance; for instance, RMSE (81.86), R2 (0.905), and MAE (64.69). The prediction results show that the total apparent CO2 emissions of the Four Provinces of Mountains and Rivers will peak in 2028 (with a peak of about 4500 Mt). The apparent CO2 emissions of Henan, Hebei, and Shandong Province peaked in 2011 (with a peak of about 654 Mt), 2013 (with a peak of about 657 Mt), and 2020 (with a peak of about 1273 Mt), respectively. Shanxi is forecast to reach its peak (with a peak of about 2486 Mt) in 2029. The apparent CO2 emissions of all provinces showed an obvious downward trend after reaching their peak. Henan, Hebei Shandong, and Shanxi showed a significant downward trend in 2018, 2023, and 2032, respectively.

Summary: Background: Benefits of Intermittent fasting (IF) on health-related outcomes have been found in a range of randomised controlled trials (RCTs). Our umbrella review aimed to systematically analyze and synthesize the available causal evidence on IF and its impact on specific health-related outcomes while evaluating its evidence quality. Methods: We comprehensively searched the PubMed, Embase, Web of Science, and Cochrane databases (from inception up to 8 January 2024) to identify related systematic reviews and meta-analyses of RCTs investigating the association between IF and human health outcomes. We recalculated the effect sizes for each meta-analysis as mean difference (MD) or standardized mean difference (SMD) with corresponding 95% confidence intervals (CIs). Subgroup analyses were performed for populations based on three specific status: diabetes, overweight or obesity, and metabolic syndrome. The quality of systematic reviews was evaluated using A Measurement Tool to Assess Systematic Reviews (AMSTAR), and the certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. This study is registered with PROSPERO (CRD42023382004). Findings: A total of 351 associations from 23 meta-analyses with 34 health outcomes were included in the study. A wide range of outcomes were investigated, including anthropometric measures (n = 155), lipid profiles (n = 83), glycemic profiles (n = 57), circulatory system index (n = 41), appetite (n = 9), and others (n = 6). Twenty-one (91%) meta-analyses with 346 associations were rated as high confidence according to the AMSTAR criteria. The summary effects estimates were significant at p

Metal–oxide–semiconductor (MOS) gas sensors are widely used for gas detection and monitoring. However, MOS gas sensors have always suffered from instability in the link between gas sensor data and the measured gas concentration. In this paper, we propose a novel deep learning approach that combines the surface state model and a Gated Recurrent Unit (GRU)-based regression to enhance the analysis of gas sensor data. The surface state model provides valuable insights into the microscopic surface processes underlying the conductivity response to pulse heating, while the GRU model effectively captures the temporal dependencies present in time-series data. The experimental results demonstrate that the theory guided model GRU+β outperforms the elementary GRU algorithm in terms of accuracy and astringent speed. The incorporation of the surface state model and the parameter rate enhances the model’s accuracy and provides valuable information for learning pulse-heated regression tasks with better generalization. This research exhibits superiority of integrating domain knowledge and deep learning techniques in the field of gas sensor data analysis. The proposed approach offers a practical framework for improving the understanding and prediction of gas concentrations, facilitating better decision-making in various practical applications.

Abstract Background Mutations in one or more genes responsible for encoding subunits within the SWItch/Sucrose Non‐Fermentable (SWI/SNF) chromatin‐remodelling complexes are found in approximately 25% of cancer patients. Bromodomain containing 9 (BRD9) is a more recently identified protein coding gene, which can encode SWI/SNF chromatin‐remodelling complexes subunits. Although initial evaluations of the potential of BRD9‐based targeted therapy have been explored in the clinical application of a small number of cancer types, more detailed study of the diagnostic and prognostic potential, as well as the detailed biological mechanism of BRD9 remains unreported. Methods We used various bioinformatics tools to generate a comprehensive, pan‐cancer analyses of BRD9 expression in multiple disease types described in The Cancer Genome Atlas (TCGA). Experimental validation was conducted in tissue microarrays and cell lines derived from lung and colon cancers. Results Our study revealed that BRD9 exhibited elevated expression in a wide range of tumours. Analysis of survival data and DNA methylation for BRD9 indicated distinct conclusions for multiple tumours. mRNA splicing and molecular binding were involved in the functional mechanism of BRD9. BRD9 may affect cancer progression through different phosphorylation sites or N6‐methyladenosine site modifications. BRD9 could potentially serve as a novel biomarker for diagnosing different cancer types, especially could accurately forecast the prognosis of melanoma patients receiving anti‐programmed cell death 1 immunotherapy. BRD9 has the potential to serve as a therapeutic target, when pairing with etoposide in patients with melanoma. The BRD9/SMARCD1 axis exhibited promising discriminative performance in forecasting the prognosis of patients afflicted with liver hepatocellular carcinoma (LIHC) and mesothelioma. Additionally, this axis appears to potentially influence the immune response in LIHC by regulating the programmed death‐ligand 1 immune checkpoint. For experimental validation, high expression levels of BRD9 were observed in tumour tissue samples from both lung and colon cancer patients. Knocking down BRD9 led to the inhibition of lung and colon cancer development, likely via the Wnt/β‐catenin signalling pathway. Conclusions These pan‐cancer study revealed the diagnostic and prognostic potential, along with the biological mechanism of BRD9 as a novel therapeutic target in human tumours.

Abstract Background and objective For high-risk elderly patients with chronic diseases, endoscopic stone removal for large common bile duct stones is associated with a high risk of adverse events and incomplete stone removal. The aim of this study was to investigate whether the treatment strategy of short-term biliary plastic stent placement followed by elective endoscopic stone removal is more effective and safer than immediate endoscopic stone removal. Methods The data of 262 high-risk elderly patients who received endoscopic retrograde cholangiopancreatography (ERCP) for large common bile duct (CBD) stones from 2017 to 2022 were retrospectively analyzed. The patients were divided into group A (immediate stone removal) and group B (stent drainage + elective stone removal). The baseline data of the 2 groups were matched 1:1 by propensity score matching. The stone clearance rate, ERCP procedure time, total hospital stay, and procedure-related adverse events were compared between the matched groups. In group B, stone size before and after stent placement, hospital stay, procedure time and adverse events of two ERCPs were compared. Results A total of 57 pairs of patients were successfully matched between the 2 groups. The stone clearance rate in group B was higher than that in group A (89.5% vs. 75.3, P = 0.049). The total hospital stay in group B was longer than that in group A (11.86 ± 3.912 d vs. 19.14 ± 3.176 d, P

Abstract The binding of small molecules to the double helical structure of DNA, through either intercalation or minor groove binding, may significantly alter the stability and functionality of DNA, which is a fundamental basis for many therapeutic and sensing applications. Here, we report that small-molecule DNA binders can also be used to program reaction pathways of a dynamic DNA reaction, where DNA strand displacement can be tuned quantitatively according to the affinity, charge, and concentrations of a given DNA binder. The binder-induced nucleic acid strand displacement (BIND) thus enables innovative technologies to accelerate the discovery and characterization of bioactive small molecules. Specifically, we demonstrate the comprehensive characterization of existing and newly discovered DNA binders, where critical parameters for binding affinity and sequence selectivity can be obtained in a single, unbiased molecular platform without the need for any specialized equipment. We also engineer a tandem BIND system as a high-throughput screening assay for discovering DNA binders, through which 8 DNA binders were successfully discovered from a library of 700 compounds.

Health Canada approved pembrolizumab in the first-line setting for advanced non-small-cell lung cancer with PD-L1 ≥ 50% and no EGFR/ALK aberration. The keynote 024 trial showed 55% of such patients progress with pembrolizumab monotherapy. We propose that the combination of baseline CT and clinical factors can help identify those patients who may progress. In 138 eligible patients from our institution, we retrospectively collected their baseline variables, including baseline CT findings (primary lung tumor size and metastatic site), smoking pack years, performance status, tumor pathology, and demographics. The treatment response was assessed via RECIST 1.1 using the baseline and first follow-up CT. Associations between the baseline variables and progressive disease (PD) were tested by logistic regression analyses. The results showed 46/138 patients had PD. The baseline CT “number of involved organs” by metastasis and smoking pack years were independently associated with PD (p < 0.05), and the ROC analysis showed a good performance of the model that integrated these variables in predicting PD (AUC: 0.79). This pilot study suggests that the combination of baseline CT disease and smoking PY can identify who may progress on pembrolizumab monotherapy and can potentially facilitate decision-making for the optimal first-line treatment in the high PD-L1 cohort.

Objectives: Previous studies have suggested a potential link between glycan levels and pancreatic cancer. To better characterize this relationship, we performed a study to evaluate the association between genetically predicted N-glycan levels in plasma and pancreatic cancer risk. Methods: Using genetic variants identified to be associated with plasma N-glycan levels in large genome-wide association studies (GWAS) as instruments, we evaluated the associations between plasma N-glycans and pancreatic cancer risk by analyzing data from 8275 pancreatic cancer cases and 6723 controls. Results: We observed that lower predicted PGP110 levels were significantly associated with an increased risk of pancreatic cancer after adjusting for multiple comparisons. Conclusions: Our study did not support strong associations between human plasma N-glycans and the risk of pancreatic cancer, although the observed association with PGP110 warrants further investigation. Simple summary Objectives: Pancreatic cancer is a fatal malignancy. Therefore, there is an urgent need to better understand its risk factors and identify markers for better predicting individual risk of developing this cancer. Previous research has suggested that glycans may play a role in the development of pancreatic cancer. To better understand their relationship, we conducted a study to assess the associations between N-glycan levels predicted by genetic factors and pancreatic cancer risk. Methods: We used genetic factors related to blood N-glycan levels as instruments. We further evaluated the associations between plasma N-glycans and pancreatic cancer risk by analyzing data from 8275 pancreatic cancer patients and 6723 controls. Results: We only observed one association between predicted levels of PGP110 and pancreatic cancer risk. Conclusions: Our study did not support strong associations between N-glycan levels and pancreatic cancer risk, although the observed association with PGP110 can be further studied.

This paper proposes a method to optimize reinforcement layout of three-dimensional members under a state of complex stress and multiple load cases (MLCs). To simulate three-dimensional members, the spatial truss-like material model is adopted. Three families of truss-like members along orthotropic directions are embedded continuously in concrete. The optimal reinforcement layout design is obtained by optimizing the member densities and orientations. The optimal design of three-dimensional member is carried out by solving the problem of minimum volume of reinforcing bars with stress constraints. Firstly, the optimized reinforcement layout under each single load case (SLC) is obtained as per the fully stressed criterion. Second, on the basis of the previous results, an equivalent multi-case optimization is proposed by introducing the idea of stiffness envelope. Finally, according to the characteristics of the truss-like material, a closed and symmetrical surface is adopted to fit the maximum directional stiffness under all SLCs. It can be proved that the densities and orientations of truss-like members are the eigenvalues and eigenvectors of the surface coefficient matrix, respectively. Several three-dimensional members are used as examples to demonstrate the capability of the proposed method in finding the best reinforcement layout design of each reinforced concrete (RC) member and to verify its efficiency in application to real design problems.

Background: Clinical decision support tools (CDSs) have been demonstrated to enhance the accuracy of antibiotic prescribing among physicians. However, their effectiveness in reducing inappropriate antibiotic use for respiratory tract infections (RTI) is controversial.Methods: A literature search in 3 international databases (Medline, Web of science and Embase) was conducted before 31 May 2023. Relative risk (RR) and corresponding 95% confidence intervals (CI) were pooled to evaluate the effectiveness of intervention. Summary effect sizes were calculated using a random-effects model due to the expected heterogeneity (I2 over 50%).Results: A total of 11 cluster randomized clinical trials (RCTs) and 5 before-after studies were included in this meta-analysis, involving 900,804 patients met full inclusion criteria. Among these studies, 11 reported positive effects, 1 reported negative results, and 4 reported non-significant findings. Overall, the pooled effect size revealed that CDSs significantly reduced antibiotic use for RTIs (RR = 0.90, 95% CI = 0.85 to 0.95, I2 = 96.10%). Subgroup analysis indicated that the intervention duration may serve as a potential source of heterogeneity. Studies with interventions duration more than 2 years were found to have non-significant effects (RR = 1.00, 95% CI = 0.96 to 1.04, I2 = 0.00%). Egger’s test results indicated no evidence of potential publication bias (p = 0.287).Conclusion: This study suggests that CDSs effectively reduce inappropriate antibiotic use for RTIs among physicians. However, subgroup analysis revealed that interventions lasting more than 2 years did not yield significant effects. These findings highlight the importance of considering intervention duration when implementing CDSs.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023432584, Identifier: PROSPERO (CRD42023432584).

Oral mucosal infection, especially oral candidiasis, is currently the most common oral mucosal disease. Traditional drug treatment regimens have difficulty adhering to mucous membranes, coupled with the unique anatomical and physiological characteristics of the oral cavity, thus reducing drug availability and limiting the effective time of drug action. Inspired by cell membrane-coated nanoparticles, this study aimed to construct a bionic adherent oral mucosal drug delivery system and investigated its therapeutic potential for oral candidiasis. The system was obtained by encapsulating Streptococcus salivarius K12 membranes on triclosan-loaded PLGA nanoparticles using an extrusion method. The constructed nanocomplexes (K12/TCS@PLGA-NPs) inherited the properties of the source cell membrane, bionically adhering to the oral mucosa and binding to the candida albicans hypha. Our in vitro and in vivo experiments have confirmed that K12/TCS@PLGA-NPs nanocomplexes significantly inhibits the formation of C. albicans biofilms and the development of oral candidiasis by enhancing the accumulation of drugs in lesions, optimizing drug efficacy. Furthermore, the biomimetic nanocomplexes could be considered safe and effective drug delivery systems, which hold considerable therapeutic promise for oral mucosal infections including candidiasis.

Alzheimer's disease (AD) is a common neurodegenerative disease in aging individuals. Alternative splicing is reported to be relevant to AD development while their roles in etiology of AD remain largely elusive. We performed a comprehensive splicing transcriptome-wide association study (spTWAS) using intronic excision expression genetic prediction models of 12 brain tissues developed through three modelling strategies, to identify candidate susceptibility splicing introns for AD risk. A total of 111,326 (46,828 proxy) cases and 677,663 controls of European ancestry were studied. We identified 343 associations of 233 splicing introns (143 genes) with AD risk after Bonferroni correction (0.05/136,884 = 3.65 × 10−7). Fine-mapping analyses supported 155 likely causal associations corresponding to 83 splicing introns of 55 genes. Eighteen causal splicing introns of 15 novel genes (EIF2D, WDR33, SAP130, BYSL, EPHB6, MRPL43, VEGFB, PPP1R13B, TLN2, CLUHP3, LRRC37A4P, CRHR1, LINC02210, ZNF45-AS1, and XPNPEP3) were identified for the first time to be related to AD susceptibility. Our study identified novel genes and splicing introns associated with AD risk, which can improve our understanding of the etiology of AD.

Abstract Background Noninvasively urine-based diagnostic modalities for upper urinary tract urothelial carcinoma (UTUC) were still lacking. We evaluated the diagnostic value of our previously developed urine-based assay (UTC assay) in UTUC. Methods We retrospectively analyzed 90 patients with suspected UTUC and 40 donors without UTUC. Voided urine specimens were analyzed by UTC assay and fluorescence in situ hybridization (FISH). The performance of UTC assay and FISH was compared among the 60 histologically proven UTUC patients and the 40 donors with benign disease. Results Of the 60 UTUCs, there were 8 low-grade and 52 high-grade cases. Overall sensitivity for UTC assay and FISH were 85% and 73.3%, respectively (P = 0.116). Specificities for UTC assay and FISH were 92.5% and 95%, respectively (P = ns.). By grade, sensitivities of UTC assay and FISH were 87.5% vs. 37.5% for low-grade (P = 0.119), and 84.6% vs. 78.8% for high- grade UTUC (P = 0.446), respectively. By stage, UTC assay showed significantly higher sensitivity than FISH for detecting non-muscle-invasive UTUC, which were 88.5% vs. 61.5%, respectively (P = 0.025). Conclusion UTC assay has good performance for the non-invasive diagnosis of UTUC. UTC assay may improve the diagnosis and surveillance of low-grade or superficial UTUC.

Abstract Background The value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. Methods An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case–control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold. Results In the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634–0.646), 0.718 (95% CI, 0.713–0.723), and 0.753 (95% CI, 0.748–0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and − 0.023 (95% CI, − 0.025 to − 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category. Conclusions Addition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.

Genes with moderate-low expression heritability cannot be sufficiently captured with conventional TWAS. This study introduces a new method, Summary-level Unified Method for Modeling Integrated Transcriptome (SUMMIT), to improve the expression prediction of TWAS by using eQTL summary-level data.

Abstract Background Due to their prevalence, dental caries ranks first among all diseases endangering human health. Therefore, the prevention of caries is of great significance, as caries have become a serious public health problem worldwide. Currently, using nanoscale drug delivery systems to prevent caries has received increased attention. However, the preventive efficacy of these systems is substantially limited due to the unique physiological structure of cariogenic biofilms. Thus, novel strategies aimed at combating cariogenic biofilms to improve preventive efficiency against caries are meaningful and very necessary. Herein, inspired by cell membrane coating technology and Lactobacillus strains, we coated triclosan (TCS)-loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles (TCS@PLGA-NPs) with an envelope of Lactobacillus (LA/TCS@PLGA-NPs) and investigated their potential as a nanoparticle delivery system against cariogenic biofilms and dental caries. Results LA/TCS@PLGA-NPs were successfully prepared with favorable properties, including a coated envelope, controllable size, negative charge, sustained drug-release kinetics and so on. The LA/TCS@PLGA-NPs inherited native properties from the source cell surface, thus the LA/TCS@PLGA-NPs adhered to S. mutans, integrated into the S. mutans biofilm, and interfered with the biofilm formation of S. mutans. The nanoparticles significantly inhibited the activity, biomass and virulence gene expression of S. mutans biofilms in vitro. Additionally, LA/TCS@PLGA-NPs exhibited a long-lasting inhibitory effect on the progression of caries in vivo. The safety performance of the nanoparticles is also favorable. Conclusions Our findings reveal that the antibiofilm effect of LA/TCS@PLGA-NPs relies not only on the inheritance of native properties from the Lactobacillus cell surface but also on the inhibitory effect on the activity, biomass and virulence of S. mutans biofilms. Thus, these nanoparticles could be considered feasible candidates for a new class of effective drug delivery systems for the prevention of caries. Furthermore, this work provides new insights into cell membrane coating technology and presents a novel strategy to combat bacterial biofilms and associated infections. Graphical Abstract

Summary: Background: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. Methods: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. Findings: Genetically elevated PUFA desaturase activity was associated (P

Federated learning (FL) and blockchains exhibit significant commonality, complementarity, and alignment in various aspects, such as application domains, architectural features, and privacy protection mechanisms. In recent years, there have been notable advancements in combining these two technologies, particularly in data privacy protection, data sharing incentives, and computational performance. Although there are some surveys on blockchain-based federated learning (BFL), these surveys predominantly focus on the BFL framework and its classifications, yet lack in-depth analyses of the pivotal issues addressed by BFL. This work aims to assist researchers in understanding the latest research achievements and development directions in the integration of FL with blockchains. Firstly, we introduced the relevant research in FL and blockchain technology and highlighted the existing shortcomings of FL. Next, we conducted a comparative analysis of existing BFL frameworks, delving into the significant problems in the realm of FL that the combination of blockchain and FL addresses. Finally, we summarized the application prospects of BFL technology in various domains such as the Internet of Things, Industrial Internet of Things, Internet of Vehicles, and healthcare services, as well as the challenges that need to be addressed and future research directions.

BackgroundThe outbreak of COVID-19 in early 2020 presented a major challenge to the healthcare system in China. This study aimed to quantitatively evaluate the impact of COVID-19 on health services utilization in China in 2020.MethodsHealth service-related data for this study were extracted from the China Health Statistical Yearbook. The Auto-Regressive Integrated Moving Average model (ARIMA) was used to forecast the data for the year 2020 based on trends observed between 2010 and 2019. The differences between the actual 2020 values reported in the statistical yearbook and the forecast values from the ARIMA model were used to assess the impact of COVID-19 on health services utilization.ResultsIn 2020, the number of admissions and outpatient visits in China declined by 17.74 and 14.37%, respectively, compared to the ARIMA model’s forecast values. Notably, public hospitals experienced the largest decrease in outpatient visits and admissions, of 18.55 and 19.64%, respectively. Among all departments, the pediatrics department had the greatest decrease in outpatient visits (35.15%). Regarding geographical distribution, Beijing and Heilongjiang were the regions most affected by the decline in outpatient visits (29.96%) and admissions (43.20%) respectively.ConclusionThe study’s findings suggest that during the first year of the COVID-19 pandemic, one in seven outpatient services and one in six admissions were affected in China. Therefore, there is an urgent need to establish a green channel for seeking medical treatment without spatial and institutional barriers during epidemic prevention and control periods.

Laoheba phosphate mineral resources are rich in Mabian region, and mining activities are frequent. The impact on the soil and water environment is unclear in the mining area. In order to find out the pollution degree of heavy metals in the mine environment, water body and soil in the Laoheba phosphate ore area, the content and distribution characteristics of heavy metals (Cd, As, Cu, Cr, Pb, Zn) in the surface water and surface soil were evaluated by taking the soil and water environment in the Laoheba phosphate ore area as the research object. The results indicate that the water quality in the study area is good, and the pollution degree of heavy metals and phosphorus is low, which conforms to the relevant indexes of the Environmental Quality Standard for Surface Water (GB3838-2002)Ⅲ. Compared with the background value of soil elements in Sichuan Province, the mean value of metal elements in the soil is 8.75 times, 3.36 times, 1.94 times, 1.48 times, 1.36 times, and 7.47 times of Cd, Pb, Zn, Cu and P. Compared with the background values of soil elements in China, Cd exceeds the standard by 10 times, Pb 4.40 times, Zn 2.48 times, As 1.88 times, Cu 2.12 times and Cr 1.42 times. The potential ecological hazard index method showed that the pollution degree of heavy metals in the surface soil of Laoheba phosphate mine was Cd> As > Pb > Cu> Zn>Cr, followed by Cd element, followed by As, Pb and Zn, which was a moderate ecological pollution risk. The accumulation index method showed that the pollution degree of heavy metals in the surface soil of Mabian Laoheba phosphate mine was Cd>Pb>As>Zn>Cu>Cr, and the pollution degree of Cd and Pb was moderate. In conclusion, the heavy metal pollution of phosphate ore has little influence on water body, while the heavy metal pollution of soil cannot be ignored in Laoheba, Mabian.

Abstract Background DNA methylation and gene expression are known to play important roles in the etiology of human diseases such as prostate cancer (PCa). However, it has not yet been possible to incorporate information of DNA methylation and gene expression into polygenic risk scores (PRSs). Here, we aimed to develop and validate an improved PRS for PCa risk by incorporating genetically predicted gene expression and DNA methylation, and other genomic information using an integrative method. Methods Using data from the PRACTICAL consortium, we derived multiple sets of genetic scores, including those based on available single‐nucleotide polymorphisms through widely used methods of pruning and thresholding, LDpred, LDpred‐funt, AnnoPred, and EBPRS, as well as PRS constructed using the genetically predicted gene expression and DNA methylation through a revised pruning and thresholding strategy. In the tuning step, using the UK Biobank data (1458 prevalent cases and 1467 controls), we selected PRSs with the best performance. Using an independent set of data from the UK Biobank, we developed an integrative PRS combining information from individual scores. Furthermore, in the testing step, we tested the performance of the integrative PRS in another independent set of UK Biobank data of incident cases and controls. Results Our constructed PRS had improved performance (C statistics: 76.1%) over PRSs constructed by individual benchmark methods (from 69.6% to 74.7%). Furthermore, our new PRS had much higher risk assessment power than family history. The overall net reclassification improvement was 69.0% by adding PRS to the baseline model compared with 12.5% by adding family history. Conclusions We developed and validated a new PRS which may improve the utility in predicting the risk of developing PCa. Our innovative method can also be applied to other human diseases to improve risk prediction across multiple outcomes.

Abstract Background Genome-wide association studies (GWAS) have identified over 56 susceptibility loci associated with Alzheimer’s disease (AD), but the genes responsible for these associations remain largely unknown. Methods We performed a large transcriptome-wide association study (TWAS) leveraging modified UTMOST (Unified Test for MOlecular SignaTures) prediction models of ten brain tissues that are potentially related to AD to discover novel AD genetic loci and putative target genes in 71,880 (proxy) cases and 383,378 (proxy) controls of European ancestry. Results We identified 53 genes with predicted expression associations with AD risk at Bonferroni correction threshold (P value < 3.38 × 10−6). Based on fine-mapping analyses, 21 genes at nine loci showed strong support for being causal. Conclusions Our study provides new insights into the etiology and underlying genetic architecture of AD.

Background: Repetitive transcranial magnetic stimulation (rTMS) is an efficacious and well-tolerated intervention for treatment-resistant depression (TRD). A novel rTMS protocol, intermittent theta burst stimulation (iTBS) has been recently implemented in clinical practice, and it is essential to characterize the factors associated to pain and the trajectory of pain of iTBS compared to standard rTMS protocols. Objective: We aimed to characterize the side effect profile and the pain trajectories of High-Frequency Left (HFL) and iTBS in TRD patients in the THREE-D trial. We also investigated factors associated to pain and the relationship between pain and clinical outcomes. Methods: 414 patients were randomized to either HFL or iTBS. Severity of pain was measured after every treatment. General Estimating Equation was used to investigate factors associated with pain. Latent class linear mixed model was used to investigate latent classes of pain trajectories over the course of rTMS. Results: Higher level of pain was associated with older age, higher stimulation intensity, higher anxiety, female, and non-response. The severity of pain significantly declined over the course of treatments with a steeper decrease early on in the course of the treatment in both protocols, and four latent pain trajectories were identified. The less favorable pain trajectories were associated with non-response and higher stimulation intensity. Conclusions: HFL and iTBS were associated with similar factors and pain trajectories, although iTBS was more uncomfortable. Response to rTMS was associated with less pain and more favorable pain trajectories furthering the evince base of overlapping neurobiological underpinnings of mood and pain. We translated these results into patient-oriented information to aid in the decision-making process when considering rTMS.

Background and aimThe number of elderly patients with biliary stones is increasing. Endoscopic retrograde cholangiography (ERCP) is considered to be an effective treatment for biliary stones. Having a sound knowledge of the risk factors can help reduce the incidence and severity of complications for ERCP. Furthermore, limited research has been published on patients aged over 85 years undergoing endoscopic biliary stone removal. This study aims to determine the risk factors that lead to complications of ERCP in patients over 85 years of age.MethodsThis was a single-center retrospective study. We analyzed 156 patients aged ≥ 85 years with biliary stones who underwent their first ERCP at Chinese PLA General Hospital from February 2002 to March 2021. Logistic regression models were employed to identify the independent risk factors for complications.ResultsA total of 13 patients (8.3%) had complications. Thereinto, pancreatitis, cholangitis, bleeding, and other complications occurred in 4 cases (2.6%), 1 cases (0.6%), 4 cases (2.6%), and 4 cases (2.6%), respectively. There was no perforation or death related to ERCP. Independent risk factors for complications were acute biliary pancreatitis (ABP) (P = 0.017) and Charlson Comorbidity Index (CCI) (P = 0.019). Significantly, reasons for incomplete stone removal at once were large stone (>10 mm) (P

Genome wide association studies have identified multiple loci associated with risk of developing prostate cancer but the functional significance of many of these are unknown. Here, after generating models to predict methylation, the authors identify CpG methylation sites associated with prostate cancer.

Nuclear accidents and decommissioning in the nuclear industry would release a large number of radioactive aerosols which endangers the natural environment and the health of workers. Therefore, there is an urgent need for environment-friendly aerosol suppressants to control and handle environmental pollution problems caused by radioactive aerosols. In this paper, sodium alginate (SA), a type of polyphenol material (TP), and alkyl glycosides (APGs) were selected as the components of the compound aerosol suppressant and the optimal proportion was generated via the method of D-optimal mixture design. Furthermore, the cesium aerosol sedimentation effect of the optimized compound aerosol suppressants was evaluated via sedimentation efficiency, the change in particle concentration cumulative concentration fraction of the cesium aerosol sedimentation process. The results showed that the aerosol sedimentation efficiency was 99.82% which was much higher than nature settlement, 18.6% and water spraying sedimentation, 43.3%. Moreover, after spraying the compound suppressant, it displayed a good effect on settling the cesium aerosol particles with a diameter of less than 1 µm, as the concentration of particles was reduced from 55.49% to 44.53%. Finally, the sedimentation mechanism of the compound aerosol suppressant and cesium aerosol particles, such as the coagulation effect, was analyzed using the particle size distribution.

It can be challenging to learn algorithms due to the research of business-related few-shot classification problems. Therefore, in this paper, we evaluate the classification of few-shot learning in the commercial field. To accurately identify the categories of few-shot learning problems, we proposed a probabilistic network (PN) method based on few-shot and one-shot learning problems. The enhancement of the original data was followed by the subsequent development of the PN method based on feature extraction, category comparison, and loss function analysis. The effectiveness of the method was validated using two examples (absenteeism at work and Las Vegas Strip hotels). Experimental results demonstrate the ability of the PN method to effectively identify the categories of commercial few-shot learning problems. Therefore, the proposed method can be applied to business-related few-shot classification problems.

Abstract Introduction Several Mendelian randomization studies have been conducted that identified multiple risk factors for Alzheimer's disease (AD). However, they typically focus on a few pre‐selected risk factors. Methods A two‐sample Mendelian randomization (MR) study was used to systematically examine the potential causal associations of 1037 risk factors/medical conditions and 31 drugs with the risk of late‐onset AD. To correct for multiple comparisons, the false discovery rate was set at

A novel cobalt ion-imprinted polymer (Co(II)-MIIP) based on magnetic Fe3O4 nanoparticles was prepared by using Co(II) as the template ion, and bis(2-methacryloxyethyl) phosphate and glycylglycine as dual functional monomers. The fabricated material was analyzed by Fourier transform infrared spectroscopy, thermogravimetric analysis, field emission scanning electron microscopy, energy dispersive X-ray spectroscopy, Brunauer–Emmett–Teller, X-ray diffraction, and vibrating sample magnetometer. The adsorption experiments with Co(II)-MIIP, found that the maximum adsorption capacity could reach 33.4 mg·g−1, while that of the non-imprinted polymer (Co(II)-NIP) was found to reach 15.7 mg·g−1. The adsorption equilibriums of Co(II)-MIIP and Co(II)-NIP was established within 20 min and 30 min, respectively. The adsorption process could be suitably described by the Langmuir isotherm model and the pseudo-second-order kinetics model. In binary mixtures of Co(II)/Fe(II), Co(II)/Cu(II), Co(II)/Mg(II), Co(II)/Zn(II), and Co(II)/Ni(II), the relative selectivity coefficients of Co(II)-MIIP toward Co(II)-NIP were 5.25, 4.05, 6.06, 11.81, and 4.48, respectively. The regeneration experiments indicated that through six adsorption–desorption cycles, the adsorption capacity of Co(II)-MIIP remained nearly 90%.

Abstract Background The burden of HCV among those living with HIV remains a major public health challenge. We aimed to characterize trends in healthcare-related visits (HRV) of people living with HIV (PLW-HIV) and those living with HIV and HCV (PLW-HIV/HCV), in British Columbia (BC), and to identify risk factors associated with the highest HRV rates over time. Methods Eligible individuals, recruited from the BC Seek and Treat for Optimal Prevention of HIV/AIDS population-based retrospective cohort (N = 3955), were ≥ 18 years old, first started combination antiretroviral therapy (ART) between 01/01/2000–31/12/2013, and were followed for ≥6 months until 31/12/2014. The main outcome was HRV rate. The main exposure was HIV/HCV co-infection status. We built a confounder non-linear mixed effects model, adjusting for several demographic and time-dependent factors. Results HRV rates have decreased since 2000 in both groups. The overall age-sex standardized HRV rate (per person-year) among PLW-HIV and PLW-HIV/HCV was 21.11 (95% CI 20.96–21.25) and 41.69 (95% CI 41.51–41.88), respectively. The excess in HRV in the co-infected group was associated with late presentation for ART, history of injection drug use, sub-optimal ART adherence and a higher number of comorbidities. The adjusted HRV rate ratio for PLW-HIV/HCV in comparison to PLW-HIV was 1.18 (95% CI 1.13–1.24). Conclusions Although HRV rates have decreased over time in both groups, PLW-HIV/HCV had 18% higher HRV than those only living with HIV. Our results highlight several modifiable risk factors that could be targeted as potential means to minimize the disease burden of this population and of the healthcare system.

Three-dimensional feature description for a local surface is a core technology in 3D computer vision. Existing descriptors perform poorly in terms of distinctiveness and robustness owing to noise, mesh decimation, clutter, and occlusion in real scenes. In this paper, we propose a 3D local surface descriptor using point-pair transformation feature histograms (PPTFHs) to address these challenges. The generation process of the PPTFH descriptor consists of three steps. First, a simple but efficient strategy is introduced to partition the point-pair sets on the local surface into four subsets. Then, three feature histograms corresponding to each point-pair subset are generated by the point-pair transformation features, which are computed using the proposed Darboux frame. Finally, all the feature histograms of the four subsets are concatenated into a vector to generate the overall PPTFH descriptor. The performance of the PPTFH descriptor is evaluated on several popular benchmark datasets, and the results demonstrate that the PPTFH descriptor achieves superior performance in terms of descriptiveness and robustness compared with state-of-the-art algorithms. The benefits of the PPTFH descriptor for 3D surface matching are demonstrated by the results obtained from five benchmark datasets.

The microbial communities in freshwater have raised concerns about the ecosystem and human health. Many ecological environmental problems have been found in urban river because of the unreasonable use and long-term wastewater discharge. In this study, we explored the bacterial community composition, abundance of 14 antibiotics and 21 antibiotic resistance genes (ARGs), and water environment features in seven water samples and seven sediment samples from Ba River in Xi’an, China. Results showed Proteobacteria and Bacteroidetes were the dominant phyla in all samples, and sediment samples had a higher bacterial diversity and richness than it in water. Bacterial communities of site 5 and 6 were clustered in discrepant patterns compared to those at remaining sites from other samples. It might be influenced by nutrients, heavy metals and antibiotics. Antibiotics concentrations ranged from 1.26 to 1.61 × 103 ng L-1 in water samples and 1.55 to 4.05 × 102 μg kg-1 in sediment samples. Sulfamerazine (SM1) and erythromycin (ERY) were the chief antibiotics in water samples, while the level of oxytetracycline (OTC) and cefazolin (CFZ) were higher in sediment samples. Canonical correspondence analysis showed that trimethoprim (TMP) was significantly related to Acinetobacter in W6, and that SM1 and OTC had positive correlation with Arcobacter in W5. The tetC, blaTEM,ermF and sul1 had higher pollution abundance ranging from 10-4 to 100 copies/16S rRNA gene copies in all samples. Significant correlations were observed between ARGs and matching antibiotics, suggesting that antibiotics can pose the selective pressure on ARGs in this river. In summary, these finding might provide some new data to the limited information available on the bacterial community characteristics, abundance of antibiotics and ARGs in urban river of China.

Sn63Pb37/SAC305 mixed solder joint is inevitably in the electronic device requiring high reliability, such as health care, aerospace etc. However, the usage history of mixed solder joint is relatively short and as such their interfacial behaviour and reliability in service has not been completely figure out. Herein, the evolution of microstructures in fully mixed Sn63Pb37/SAC305 BGA solder joints during high-temperature storage were systematically studied. After reflow soldering process, the Pb-rich phases uniformly distributed in the fully mixed joint. During the thermal aging test, the size of Pb-rich phases gradually coarsened. The intermetallic compound (IMC) layers thickness at the two-side interface (upper interface: between the pad on substrate and solder; lower interface: between the pad on PCB and solder) were also increased. Moreover, the growth kinetics models of two-side IMC layer were successfully established according to the Arrhenius equation. IMC layer grows faster at higher temperature, because of higher diffusion coefficient. With the increasing of aging time, the fracture position partially moved from the interface between Ni layer and IMC layer into IMC internal. These results may provide support for the reliable applications of mixed Sn63Pb37/SAC305 solder joints.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with deficits in social communication ability and repetitive behavior. The pathophysiological events involved in the brain of this complex disease are still unclear. Methods: In this study, we aimed to profile the gene expression signatures of brain cortex of ASD patients, by using two publicly available RNA-seq studies, in order to discover new ASD-related genes. Results: We detected 1567 differentially expressed genes (DEGs) by meta-analysis, where 1194 were upregulated and 373 were downregulated genes. Several ASD-related genes previously reported were also identified. Our meta-analysis identified 235 new DEGs that were not detected using the individual RNA-seq studies used. Some of those genes, including seven DEGs (PAK1, DNAH17, DOCK8, DAPP1, PCDHAC2, and ERBIN, SLC7A7), have been confirmed in previous reports to be associated with ASD. Gene Ontology (GO) and pathways analysis showed several molecular pathways enriched by the DEGs, namely, osteoclast differentiation, TNF signaling pathway, complement and coagulation cascade. Topological analysis of protein–protein interaction of the ASD brain cortex revealed proteomics hub gene signatures: MYC, TP53, HDAC1, CDK2, BAG3, CDKN1A, GABARAPL1, EZH2, VIM, and TRAF1. We also identified the transcriptional factors (TFs) regulating DEGs, namely, FOXC1, GATA2, YY1, FOXL1, USF2, NFIC, NFKB1, E2F1, TFAP2A, HINFP. Conclusion: Novel core genes and molecular signatures involved with ASD were identified by our meta-analysis.