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ABSTRACT Recent guidelines have recognized several factors, including blood pressure (BP), body mass index (BMI), low‐density lipoprotein cholesterol (LDL‐C), hemoglobin A1c (HbA1c), smoking, and physical activity, as key contributors to stroke risk. However, the impact of simultaneous management of these risk factors on stroke susceptibility in individuals with hypertension remains ambiguous. This study involved 238 388 participants from the UK Biobank, followed up from their recruitment date until April 1, 2023. Cox proportional hazard models with hazard ratios (HRs) and 95% confidence intervals (CIs) were used to illustrate the correlation between the joint modifiable risk factor control and the stroke risk. As the degree of risk factor control increased, a gradual reduction in stroke risk was observed. Hypertensive patients who had the optimal risk factor control (≥5 risk factor controls) had a 14.6% lower stroke risk than those who controlled 2 or fewer (HR: 0.854; 95% CI: 804–0.908; p < 0.001). The excess risk of stroke linked to hypertension slowly diminished as the number of controlled risk factors increased. However, the risk was still 25.1% higher for hypertensive patients with optimal risk factor control as compared to the non‐hypertensive population (HR: 1.251; 95% CI: 1.100–1.422; p < 0.001). The protective effect of joint risk factor control against the stroke risk due to hypertension was stronger in medicated hypertensive patients than in those not medicated. This finding leads to the conclusion that joint risk factor control combined with pharmacological treatment could potentially eliminate the excess risk of stroke associated with hypertension.

Abstract With the backdrop of climate change and human activities, the complex interactions within the social‐ecological system have brought unprecedented challenges to sustainable development. However, there is still a lack of quantitative methods for analyzing the dynamics of the social‐ecological system. Here, we introduced a social‐ecological network approach incorporating supply and demand of ecosystem services (ESs) as bridges and took the Dongting Lake basin in China as the research area. From 2000 to 2020, we discovered that the number of linkages among meteorological elements and ESs supply decreased from 5 to 0. Along with this, the network density (from 26 to 22) and network connectivity (from 43 to 28) showed the decoupling trends of the social‐ecological networks. These results implied the decreasing impacts of meteorological elements and the importance of considering human activities impacts. Based on the average degree analysis of the networks, proportions of cultivated land and forest land were key for ESs supply (both around 0.900), while population density and artificial land proportion were important for the ESs demand (around 0.850 and 0.800, respectively). More management practices are required because these elements have significant impacts on the supply‐demand alignments of multiple ESs. We further illustrated the spatial supply‐demand mismatches of ESs, along with the negative effects of urbanization. This study highlighted the advantage of integrating the ecosystems services approach into the social‐ecological network analysis, and provided policy insights serving for sustainable development of the typical great lake basins.

Abstract Background Intraperitoneal paclitaxel is proved to be efficient for peritoneal metastasis of gastric cancer. It remains uncertain the efficacy and safety of the triplets regimen which combined intraperitoneal high‐dose paclitaxel with systemic SOX in gastric cancer patients with peritoneal metastasis. This study aimed to evaluate the efficacy and safety of intraperitoneal administration of high‐dose paclitaxel, intravenous oxaliplatin and S‐1 in patients with peritoneal metastatic gastric cancer. Methods This single‐center, prospective, single‐arm phase II study was conducted between January 2017 and May 2019 in West China Hospital, Sichuan University. Patients diagnosed with primary gastric cancer by histopathology and confirmed synchronous peritoneal metastasis were enrolled. This study aimed to evaluate efficacy and safety of intraperitoneal administration of high‐dose paclitaxel (80 mg/m2, d1), intravenous oxaliplatin (100 mg/m2, d1), and S‐1 (80 mg/m2, d1‐14) of patients. The primary endpoint was 1‐year overall survival rate, and the second endpoints were progression‐free survival (PFS), overall survival (OS), overall response rate (ORR), disease control rate (DCR) and adverse events. Results In this single‐arm phase II clinical trial, 49 patients received SOX combined intraperitoneal high‐dose paclitaxel treatment. One‐year survival rate was 81.6% (95% CI, 68.6–90.0%). Median PFS and OS were 6.50 months (95% CI, 2.89–10.11) and 16.9 months (95% CI, 13.58 to 20.22), respectively; ORR was 55.3% (95% CI, 41.3–68.6) and DCR was 76.6% (95% CI, 62.8–86.4). Thirteen patients underwent second laparoscopic detection, but only nine ultimately underwent radical gastrectomy. Subgroup analysis showed that sPCI ≤12 was a good index for a favorable prognosis. The most frequent grade 3/4 toxicities were neutropenia (40.8%), anemia (22.4%), leukopenia (18.4%), nausea (14.3%), and vomiting (12.2%). None of the patients had any intraperitoneal catheter‐related complications. Conclusions Intraperitoneal high‐dose paclitaxel with systemic SOX is an effective and tolerable first‐line treatment for patients with peritoneal metastatic gastric cancer and patients with sPCI≤12 scores might be recommended crowd for this regimen as conversion therapy.

Abstract Background Clear‐cell renal cell carcinoma (ccRCC) is stubborn to traditional chemotherapy and radiation treatment, which makes its clinical management a major challenge. Recently, we have made efforts in understanding the etiology of ccRCC. Increasing evidence revealed that the competing endogenous RNA (ceRNA) was involved in the development of varied tumors. However, a comprehensive analysis of the prognostic model based on lncRNA‐miRNA‐mRNA ceRNA regulatory network of ccRCC with large‐scale sample size and RNA‐sequencing expression data is still limited. Methods RNA‐sequencing expression data were taken out from GTEx database and TCGA database, a total of 354 samples with ccRCC and 157 normal controlled samples were included in our study. The ccRCC‐specific genes were obtained by WGCNA and differential expression analysis. Following, the communication of mRNAs and lncRNAs with targeted miRNAs were predicted by MiRcode, starBase, miRTarBase, and TargetScan. A gene signature of eight genes was further constructed by univariate Cox regression, Lasso methods, and multivariate Cox regression analysis. Results A total of 2191 mRNAs and 1377 lncRNAs was identified, and a dysregulated ceRNA network for ccRCC was established using 7 mRNAs, 363 lncRNAs, and 3 miRNAs. Further, a gene signature including eight genes based on this ceRNA was determined followed by the development of a nomogram predicting 1‐, 3‐, and 5‐year survival probability for ccRCC. Conclusion It could contribute to a better understanding of ccRCC tumorigenesis mechanism and guide clinicians to make a more accurate treatment decision.

Background The study was conducted to compare the clinicopathological characteristics, survival outcomes, and metastatic patterns between pulmonary large cell neuroendocrine carcinoma (LCNEC) and other non‐small cell lung cancer (ONSCLC), and to identify the prognostic factors of LCNEC. Methods Data of patients diagnosed with LCNEC and ONSCLC from 2004 to 2014 were obtained from the Surveillance, Epidemiology, and End Results dataset. Pearson’s chi‐square tests were used to compare differences in clinicopathological characteristics. The Kaplan–Meier method was used for survival analysis. A propensity score was used for matching and a Cox proportional hazards model was used for multivariate and subgroup analyses. Results A total of 2368 LCNEC cases and 231 672 ONSCLC cases were identified. LCNEC incidence increased slightly over time. Except for marital status, LCNEC patients had obviously different biological features to ONSCLC patients. Survival analysis showed that LCNEC had poorer outcomes than ONSCLC. Multivariate analysis revealed that female gender, black race, surgery, radiation, and chemotherapy were protective factors for LCNEC. Matched subgroup analysis further demonstrated that most subgroup factors favored ONSCLC, especially in early stage. Early‐stage LCNEC patients had a higher risk of lung cancer‐specific death than early‐stage ONSCLC patients. Moreover, metastatic patterns were different between LCNEC and ONSCLC. LCNEC patients with isolated liver metastasis or combined invasion to other organs had poorer survival rates. Conclusions LCNEC has totally different clinicopathological characteristics and metastatic patterns to ONSCLC. LCNEC also has poorer survival outcomes, primarily because of isolated liver metastasis or combined invasion to other organs. Most subgroup factors are adverse factors for LCNEC.

Abstract Lung cancer is one of the main causes of cancer mortality globally. Most patients received radiotherapy during the course of disease. However, radioresistance generally occurs in the majority of these patients, leading to poor curative effect, and the underlying mechanism remains unclear. In the present study, miR‐18a‐5p expression was downregulated in irradiated lung cancer cells. Overexpression of miR‐18a‐5p increased the radiosensitivity of lung cancer cells and inhibited the growth of A549 xenografts after radiation exposure. Dual luciferase report system and miR‐18a‐5p overexpression identified ataxia telangiectasia mutated (ATM) and hypoxia inducible factor 1 alpha (HIF‐1α) as the targets of miR‐18a‐5p. The mRNA and protein expressions of ATM and HIF‐1α were dramatically downregulated by miR‐18a‐5p in vitro and in vivo. Clinically, plasma miR‐18a‐5p expression was significantly higher in radiosensitive than in radioresistant group (P 2.28 was obtained from receiver operating characteristic (ROC) curve. The objective response rate (ORR) was significantly higher in miR‐18a‐5p‐high group than in miR‐18a‐5p‐low group (P