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Lung cancer (LC) is among the most prevalent cancers globally, posing a significant threat to human health. This study employed Mendelian randomization (MR) analysis to identify key drug targets for LC treatment. MR results from the inverse variance weighted (IVW) algorithm highlighted 352 expression quantitative trait loci (eQTLs) and 31 protein quantitative trait loci (pQTLs) causally associated with LC. Sensitivity and Steiger analyses confirmed that 305 eQTLs and 28 pQTLs exhibited a robust causal relationship with LC. Colocalization analysis further identified 20 eQTLs as potential drug targets for LC. Predictions were made for 257 drugs and 17 diseases, establishing a target-drug network that included PTGFR-D005557 and IREB2-C004925, among others. The drugs-diseases network revealed associations such as D007213 with Liver Cirrhosis and D013749 with Schizophrenia. Notably, the strongest binding interaction was observed between Valproic acid and eight genes (BRAT1, H2BC11, IREB2, MICAL1, MPHOSPH6, PTGFR, RHNO1, SERPING1), suggesting a significant molecular interaction. Ultimately, seven key drug targets (SERPING1, TDRD9, GBAP1, FAM241A, ZKSCAN4, ZKSCAN3, Z94721.1) were consistently identified across two MR studies and validated. These targets offer new avenues for LC treatment, highlighting their potential in therapeutic development.

Accurate localization of plant growth points is essential for precision agriculture applications, including electro-weeding and laser weeding. While crop and weed detection has been extensively studied, existing methods focus primarily on object-level recognition and often neglect fine-grained growth point localization. To address this limitation, we propose a novel training strategy, epoch-based prior annealing (EPA), which incorporates the excess green minus excess red (ExG-ExR) index as prior knowledge and introduces schedule factor and gain factor to effectively steer keypoint regression. The experimental results show that incorporating EPA improves keypoint localization performance, with mAP50 increasing by 0.024 and mAP50:95 by 0.011, while maintaining bounding box detection performance. The parameter sensitivity experiments confirmed that both excessively strong and weak guidance can hinder training. Furthermore, analysis of parameters and computational cost shows that the additional overhead introduced by the EPA strategy accounts for less than 0.5% of the total, and be considered negligible. In summary, the proposed EPA strategy significantly improves the accuracy, robustness, and generalizability of plant and growth point detection models, offering a practical and scalable solution for precision agricultural applications.

This study aims to develop a machine learning model utilizing Computed Tomography (CT) values to predict systemic inflammatory response syndrome (SIRS) after endoscopic surgery for kidney stones. The goal is to identify high-risk patients early and provide valuable guidance for urologists in the early diagnosis and intervention of post-operative urosepsis. This study included 833 patients who underwent retrograde intrarenal surgery (RIRS) or percutaneous nephrolithotomy (PCNL) for kidney stones. Five machine learning algorithms and ten preoperative or intraoperative variables were used to develop a predictive model for SIRS. The SHapley Additive exPlanations (SHAP) method was used to explain the distribution of feature importance in the model’s predictions. Among the 833 patients, 126 (15.1%) developed SIRS postoperatively. All five machine learning models demonstrated strong discrimination on the validation set (AUC: 0.690–0.858). The eXtreme Gradient Boosting (XGBoost) model was the best performer [AUC: 0.858; sensitivity: 0.877; specificity: 0.981; accuracy: 0.841; positive predictive value: 0.629; negative predictive value: 0.851]. The characteristic importance of the Machine Learning model (ML model) and SHAP results indicated Hounsfield Unit (HU), Urinary protein, Stone burden, and Serum uric acid as important predictors for the model. A machine learning model utilizing CT values was developed to predict postoperative SIRS in endoscopic kidney stone surgery. The model demonstrates strong predictive performance and can assist in assessing the risk of urosepsis in postoperative patients.

Freeform off-axis reflective systems are significantly more difficult to align and assemble owing to their asymmetric surface shapes and system structures. In this study, a freeform surface system design method with low coupling position error sensitivity (FCPESM) was proposed. First, we established a mathematical model of a reflective system when it was perturbed by coupling position errors and used the clustering-microelement method to establish the coupling error sensitivity evaluation function. The evaluation function was then applied to the design process of a freeform surface off-axis three-mirror optical system. The results showed that the FCPESM optical design method can significantly relax the assembly tolerance requirements of optical systems on the basis of ensuring image performance. In this study, the reflective system was perturbed by tilt and decenter simultaneously, and the disturbance mechanism of position errors on optical systems was further improved. Through this research, freeform surface systems with both image performance and error sensitivity can be obtained, which makes freeform off-axis reflective systems with better engineering realizability.

Circular RNAs (circRNAs) are linked to cancer, but it's still not clear what role they play in prostatic cancer. Through high-throughput sequencing, the goal of this study was to compare how circRNAs are expressed at different stages of prostate cancer. 12 patients attending the Department of Urology at the Second Affiliated Hospital of Nanchang University between June 2020 and October 2021 were used for RNA sequencing, and 14 patients were used for real-time fluorescent quantitative PCR (qRT-PCR). The expression profiles of prostate cancer circRNAs were constructed by sequencing with the help of next-generation high-throughput sequencing technology, and the differentially expressed circRNAs were analyzed by targeting microRNA (miRNA) loci and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the genes from which circRNAs originated. Finally, the expression of target circRNAs in two prostate tissues was verified by qRT-PCR. Following high-throughput sequencing, 13,047 circRNAs were identified, and 605 circRNAs with significant differential expression were identified, of which 361 circRNAs were up-regulated, and 244 circRNAs were down-regulated. Analysis of circRNA-originated genes using GO and the KEGG enrichment analysis showed that circRNA host genes can regulate and influence multiple signaling pathways in prostate cancer with important biological functions. And the circRNA–miRNA network was constructed. The highest number of differentially expressed circRNA-binding miRNAs were: hsa_circ_000 7582 (52), hsa_circ_000 6198 (37), hsa_circ_000 6759 (28), hsa_circ_000 5675 (25), and hsa_circ_000 2172 (22). Moreover, we further screened out the circRNA (hsa_circ_0005692) that was significantly differentially expressed and common to all groups and verified by qRT-PCR that the expression of the target circRNA (hsa_circ_0005692) was significantly downregulated in prostate cancer compared with benign prostatic hyperplasia (BPH) tissues.

Bladder cancer (BC) is the most common malignant tumour of the urinary system and one of the leading causes of cancer-related death. Cuproptosis is a novel form of programmed cell death, and its mechanism in tumours remains unclear. This study aimed to establish the prognostic signatures of cuproptosis-related lncRNAs and determine their clinical prognostic value. RNA sequencing data from The Cancer Genome Atlas were used to detect the expression levels of cuproptosis-related genes in BC. Cuproptosis-related lncRNAs linked to survival were identified using co-expression and univariate Cox regression. Furthermore, consensus cluster analysis divided the lncRNAs into two subtypes. Subsequently, we established a signature model consisting of seven cuproptosis-related lncRNAs (AC073534.2, AC021321.1, HYI-AS1, PPP1R26-AS1, AC010328.1, AC012568.1 and MIR4435-2Hg) using least absolute shrinkage and selection operator regression. Survival analysis based on risk score showed that the overall survival and progression-free survival of patients in the high-risk group were worse than those in the low-risk group. Multivariate Cox analysis demonstrated the independent prognostic potential of this signature model for patients with BC. Moreover, age and clinical stage were also significantly correlated with prognosis. The constructed nomogram plots revealed good predictive power for the prognosis of patients with BC and were validated using calibration plots. Additionally, enrichment analysis, Single sample gene set enrichment analysis and immune infiltration abundance analysis revealed significant differences in immune infiltration between the two risk groups, with high levels of immune cell subset infiltrations observed in the high-risk group accompanied by various immune pathway activation. Moreover, almost all the immune checkpoint genes showed high expression levels in the high-risk group. Moreover, TIDE analysis suggested that the high-risk group was more responsive to immunotherapy. Finally, eight drugs with low IC50 values were screened, which may prove to be beneficial for patients in the high-risk group.

Conventional therapy for kidney renal clear cell carcinoma (KIRC) is unpromising. The tumor microenvironment (TME) is intimately linked to the invasiveness of a variety of tumor forms, including KIRC. The purpose of this research is to establish the prognostic and immune-related significance of dihydrolipoamide branched chain transacylase E2 (DBT) in individuals with KIRC. In this investigation, we discovered that DBT expression was down-regulated in a range of human malignancies, and low DBT expression in KIRC was linked to higher-level clinicopathological characteristics as well as a poor prognosis for KIRC patients. Based on the findings of univariate and multivariate Cox regression analyses, DBT might be employed as an independent prognostic factor in KIRC patients. Furthermore, we developed a nomogram to better investigate DBT’s predictive usefulness. To confirm DBT expression, we examined KIRC cell lines using RT-qPCR and Western blotting. We also examined the role of DBT in KIRC using colony formation, CCK-8, EdU, transwell, and wound healing assays. We discovered that plasmid-mediated overexpression of DBT in KIRC cells slowed cell proliferation and decreased migration and invasion. Multiple enrichment analyses revealed that DBT may be involved in processes and pathways related to immunotherapy and drug metabolism. We computed the immune infiltration score and discovered that the immunological score and the ESTIMATE score were both greater in the DBT low expression group. According to the CIBERSORT algorithm, DBT seems to promote anti-cancer immune responses in KIRC by activating M1 macrophages, mast cells, and dendritic cells while inhibiting regulatory T cells. Finally, in KIRC, DBT expression was found to be highly linked to immunological checkpoints, targeted medicines, and immunotherapeutic agents. Our findings suggest that DBT is a distinct predictive biomarker for KIRC patients, playing a significant role in the TME of KIRC and serving as a reference for the selection of targeted treatment and immunotherapy.

Background Public transportation, including high-speed rail (HSR), exerts a significant influence on people's health and health-related behaviors in various ways around the world. Several studies have investigated the impact of HSR on patients' health-seeking behavior, however, many issues regarding the impact of HSR remain to be investigated in depth. We aim to explore whether the effect of HSR on patients' health-seeking behavior crowds out the market for medical services in county regions based on China's practice. Methods The opening of two important HSR lines connecting two megacities in western China, Xi'an to Chengdu (opened on December 6, 2017) and Yinchuan to Xi'an (opened on December 26, 2020), were considered as quasi-experimental intervention, and Event Study and Synthetic Difference-in-Differences (DID) research design were applied in this study. A monthly report database about county-level hospitals of the health statistical data collection from 2017 to 2018 and 2020 to 2021 was used. Results There is no significant change in the total number of visits (TOV) and the number of bed days occupied by discharged persons (BDODP) in county-level hospitals before and after the opening of two major HSR lines being observed. The estimates of TOV from synthetic DID were 319.38 (95% CI, -761.01, 1399.77) and -915.69 (95% CI, -5079.07, 3247.68) for the two HSR lines, respectively. The estimates of BDODP from synthetic DID were -581.34 (95% CI, -1555.27, 392.59) and -960.62 (95% CI, -3932.40, 2011,17) for the two HSR lines, respectively. The results from the event study DID estimates are in line with the synthetic DID. Conclusions Our findings suggest that the construction of HSR does not substantially modify the utilization of medical services at the county level. Moreover the effect of the construction of HSR on the flow of patients to large hospitals may be an incremental effect. These findings hold important implications for infrastructure policy, suggesting that improvements in transportation can coexist with and perhaps even bolster local healthcare services without compromising their usage.

We report a method for determining the field of view (FOV) of a dawn–dusk sun-synchronous orbit satellite based on an improved observation mode. The target trajectory distribution model in geosynchronous orbit (GEO) is established, the natural rendezvous mode is improved, and the observation mode of the satellite is determined. A scheme for determining the thresholds of cross-orbit field of view (COFOV) and the along-orbit field of view (AOFOV) was developed. The result shows that the coverage of the satellite can reach more than 95% when the improved observation mode is used to observe the GEO target. When the revisit period of the satellite is one day, the threshold of the COFOV is 15°, and the threshold of the AOFOV is 12°.

Unplanned readmissions among patients with mental and behavioural disorders (MBDs) disrupt inpatient recovery and impose financial burdens on families and healthcare systems. To estimate the 31-day unplanned inpatient readmission rates for MBDs in China and identify determinant profiles from the perspective of individual, hospital, and contextual levels. Data from patients with MBDs were collected from the medical records of 99 public hospitals across 10 cities. A total of 49,352 inpatient admissions were analysed based on the proposed conceptual model using multilevel logistic regressions. The 31-day unplanned readmission rate (excluding 0-1-day returns) was 8.6% (95% CI: 8.4-8.9%). Determinant profiles differed across the overall group and subgroups. The number of general practitioners within cities was associated with reduced risk of unplanned readmissions. Hospital factors such as facility type and size, human resources, and revenue size were associated with unplanned readmissions only in specific subgroups. Additionally, individual-level factors, including demographic information (e.g. gender, age, marital status, and occupational status), disease-related factors (e.g. primary diagnostic group, condition at admission, and other diagnoses), and clinical characteristics (e.g. length of stay and medical costs), were associated with unplanned readmissions across all subgroups. The study emphasises collaborative efforts from health systems, hospitals, and patients to reduce unplanned readmissions for MDBs. Health systems should focus on improving access to care, enhancing quality, and ensuring continuity while providing incentives for hospitals. Additionally, hospitals should prioritise the identification and effective management of their high-risk patients.