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Background and Objectives Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural–urban disparities in multimorbidity. Research Design and Methods Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011–2018), linked with the full-coverage particulate matter 2.5 (PM2.5) concentration data set (2000–2018) and temperature records (2000–2018). Air pollution was assessed by the moving average of PM2.5 concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural–urban disparities in multimorbidity related to temperature and PM2.5 exposure. Results We found the higher PM2.5 concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural–urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM2.5-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM2.5 exposure, but PM2.5 exposure or temperature is not associated with the rate of multimorbidity increase with age. Discussion and Implications Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural–urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals. [ABSTRACT FROM AUTHOR]

Background: Systemic chemotherapy or chemoradiation therapy has proven to be effective in treating advanced biliary tract carcinoma (BTC). However, its efficacy in the adjuvant setting remains controversial. Therefore, this study aimed to determine the prognostic significance of genomic biomarkers in resected BTC and their potential role in stratifying patients for adjuvant treatment. Methods: We retrospectively reviewed 113 BTC patients who underwent curative‐intent surgery and had available tumor sequencing data. Disease‐free survival (DFS) was the primary outcome examined and univariate analysis was used to identify gene mutations with prognostic value. Favorable and unfavoratble gene subsets were distinguished from the selected genes through grouping, respectively. Multivariate Cox regression was used to identify independent prognostic factors of DFS. Results: Our results indicated that mutations in ACVR1B, AR, CTNNB1, ERBB3, and LRP2 were favorable mutations, while mutations in ARID1A, CDKN2A, FGFR2, NF1, NF2, PBRM1, PIK3CA, and TGFBR1 were unfavorable mutations. In addition to age, sex, and node positive, favorable genes (HR = 0.15, 95% CI = 0.04–0.48, p = 0.001) and unfavorable genes (HR = 2.86, 95% CI = 1.51–5.29, p = 0.001) were identified as independent prognostic factors for DFS. Out of the 113 patients, only 35 received adjuvant treatment whereas the majority (78) did not. For patients with both favorable and unfavorable mutations undetected, adjuvant treatment showed negative effect on DFS (median DFS: S441 vs. 956 days, p = 0.010), but there was no significant difference in DFS among those in other mutational subgroups. Conclusions: Genomic testing might be useful in guiding the decisions regarding adjuvant treatment in BTC. [ABSTRACT FROM AUTHOR]

Hainan gibbons are among the world's most critically endangered primates, with a remaining population of only 35 individuals distributed across 5 social groups in the Bawangling Branch of the Hainan Tropical Rainforest National Park, China. Habitat conversion and forest fragmentation over the past 40 years have reduced their geographical distribution by 95%. In the absence of a quantitative assessment of the availability of remaining suitable habitat, it is unclear whether this species can survive to the end of this century. We used behavioral observations, ArcGIS, remote sensing, stereo optical imagery, and MaxEnt modeling to identify patterns of Hainan gibbon range use and compare changes in the distribution of suitable forest types and areas of forest fragmentation over the past 20 years (2000–2020). The results indicate that the combined range of the 5 extant Hainan gibbon groups totaled 14.89 km2. The home range of the smallest group (Group E, 3 individuals) was 1.51 km2, which likely represents the minimum home range size for this species. The remaining area of highly suitable and moderately suitable habitat totals 26.9 km2. However, habitat connectivity across the gibbon range is very low (less than 0.5), limiting the ability of Hainan gibbons to move between forest patches. The results of this study indicate that the availability of suitable habitat in Bawangling is insufficient to allow for future Hainan gibbon population growth. Therefore, immediate action must be taken to restore, reforest, and establish ecological corridors to reconnect areas of suitable habitat for these critically endangered gibbons. [ABSTRACT FROM AUTHOR]