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Gastrointestinal cancer is a worldwide health challenge due to its dramatically increasing prevalence and as a leading cause of cancer-related mortality. Increasing evidence has illustrated the vital role of gut microbes-derived metabolites in gastrointestinal cancer progression and treatment. Microbial metabolites are produced by the gut microbiota that utilizes both extrinsic dietary components and intrinsic host-generated compounds. Meanwhile, certain categories of metabolites such as short-chain fatty acids, bile acids, tryptophan, and indole derivatives, are linked to gastrointestinal malignancy. In this review, the major classes of microbial metabolites and their impacts on various gastrointestinal cancers including colorectal cancer, gastric cancer, and hepatocellular carcinoma, have been introduced. The application of microbial metabolites as predictive biomarkers for early diagnosis and prognosis of gastrointestinal cancer has also been explored. In addition, therapeutic potential of strategies that target microbial metabolites against gastrointestinal cancer is further evaluated.

Background: Adverse effects of proton pump inhibitors (PPIs) have raised wide concerns. The association of PPIs with influenza is unexplored, while that with pneumonia or COVID-19 remains controversial. Our study aims to evaluate whether PPI use increases the risks of these respiratory infections. Methods: The current study included 160,923 eligible participants at baseline who completed questionnaires on medication use, which included PPI or histamine-2 receptor antagonist (H2RA), from the UK Biobank. Cox proportional hazards regression and propensity score-matching analyses were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Comparisons with H2RA users were tested. PPI use was associated with increased risks of developing influenza (HR 1.32, 95% CI 1.12–1.56) and pneumonia (hazard ratio [HR] 1.42, 95% confidence interval [CI] 1.26–1.59). In contrast, the risk of COVID-19 infection was not significant with regular PPI use (HR 1.08, 95% CI 0.99–1.17), while the risks of severe COVID-19 (HR 1.19. 95% CI 1.11–1.27) and mortality (HR 1.37. 95% CI 1.29–1.46) were increased. However, when compared with H2RA users, PPI users were associated with a higher risk of influenza (HR 1.74, 95% CI 1.19–2.54), but the risks with pneumonia or COVID-19-related outcomes were not evident. Conclusions: PPI users are associated with increased risks of influenza, pneumonia, as well as COVID-19 severity and mortality compared to non-users, while the effects on pneumonia or COVID-19-related outcomes under PPI use were attenuated when compared to the use of H2RAs. Appropriate use of PPIs based on comprehensive evaluation is required. Funding: This work is supported by the National Natural Science Foundation of China (82171698, 82170561, 81300279, 81741067, 82100238), the Program for High-level Foreign Expert Introduction of China (G2022030047L), the Natural Science Foundation for Distinguished Young Scholars of Guangdong Province (2021B1515020003), the Guangdong Basic and Applied Basic Research Foundation (2022A1515012081), the Foreign Distinguished Teacher Program of Guangdong Science and Technology Department (KD0120220129), the Climbing Program of Introduced Talents and High-level Hospital Construction Project of Guangdong Provincial People’s Hospital (DFJH201923, DFJH201803, KJ012019099, KJ012021143, KY012021183), and in part by VA Clinical Merit and ASGE clinical research funds (FWL).

Background & Aims: Inflammatory bowel disease (IBD) is commonly associated with extraintestinal complications, including autoimmune liver disease. The co-occurrence of IBD and primary biliary cholangitis (PBC) has been increasingly observed, but the underlying relationship between these conditions remains unclear. Methods: Using summary statistics from genome-wide association studies (GWAS), we investigated the causal effects between PBC and IBD, including Crohn’s disease (CD) and ulcerative colitis (UC). We also analyzed the shared genetic architecture between IBD and PBC using data from GWAS, bulk-tissue RNA sequencing, and single cell RNA sequencing, and explored potential functional genes. Result: There was a strong positive genetic correlation between PBC and IBD (linkage disequilibrium score regression: rg = 0.2249, p = 3.38 × 10-5). Cross-trait analysis yielded 10 shared-risk single nucleotide polymorphisms (SNPs), as well as nine novel SNPs, which were associated with both traits. Using Mendelian randomization, a stable causal effect was established of PBC on IBD. Genetically predicted PBC was found to have a risk effect on IBD (1.105; 95% CI: 1.058–1.15; p = 1.16 × 10-10), but not vice versa. Shared tissue-specific heritability enrichment was identified for PBC and IBD (including CD and UC) in lung, spleen, and whole-blood samples. Furthermore, shared enrichment was observed of specific cell types (T cells, B cells, and natural killer cells) and their subtypes. Nine functional genes were identified based on summary statistics-based Mendelian randomization. Conclusions: This study detected shared genetic architecture between IBD and PBC and demonstrated a stable causal relationship of genetically predicted PBC on the risk of IBD. These findings shed light on the biological basis of comorbidity between IBD and PBC, and have important implications for intervention and treatment targets of these two diseases simultaneously. Impact and Implications: The discovery of novel shared single nucleotide polymorphisms (SNPs) and functional genes provides insights into the common targets between inflammatory bowel disease (IBD) and primary biliary cholangitis (PBC), serving as a basis for new drug development and contributing to the study of disease pathogenesis. Additionally, the established significant causality and genetic correlation underscore the importance of clinical intervention in preventing the comorbidity of IBD and PBC. The enrichment of SNP heritability in specific tissues and cell types reveals the role of immune factors in the potential disease mechanisms shared between IBD and PBC. This stimulates further research on potential interventions and could lead to the development of new targets for immune-based therapies.

Abstract Background In the post-pandemic era, a wide range of COVID-19 sequelae is of growing health concern. However, the risks of digestive diseases in long COVID have not been comprehensively understood. To investigate the long-term risk of digestive diseases among COVID patients. Methods In this large-scale retrospective cohort study with up to 2.6 years follow-up (median follow-up: 0.7 years), the COVID-19 group (n = 112,311), the contemporary comparison group (n = 359,671) and the historical comparison group (n = 370,979) predated the COVID-19 outbreak were built using UK Biobank database. Each digestive outcome was defined as the diagnosis 30 days or more after the onset of COVID-19 infection or the index date. Hazard ratios (HRs) and corresponding 95% confidence intervals (CI) were computed utilizing the Cox regression models after inverse probability weighting. Results Compared with the contemporary comparison group, patients with previous COVID-19 infection had higher risks of digestive diseases, including gastrointestinal (GI) dysfunction (HR 1.38 (95% CI 1.26 to 1.51)); peptic ulcer disease (HR 1.23 (1.00 to 1.52)); gastroesophageal reflux disease (GERD) (HR 1.41 (1.30 to 1.53)); gallbladder disease (HR 1.21 (1.06 to 1.38)); severe liver disease (HR 1.35 (1.03 to 1.76)); non-alcoholic liver disease (HR 1.27 (1.09 to 1.47)); and pancreatic disease (HR 1.36 (1.11 to 1.66)). The risks of GERD were increased stepwise with the severity of the acute phase of COVID-19 infection. Even after 1-year follow-up, GERD (HR 1.64 (1.30 to 2.07)) and GI dysfunction (HR 1.35 (1.04 to 1.75)) continued to pose risks to COVID-19 patients. Compared to those with one SARS-CoV-2 infection, reinfected patients were at a higher risk of pancreatic diseases (HR 2.57 (1.23 to 5.38)). The results were consistent when the historical cohort was used as the comparison group. Conclusions Our study provides insights into the association between COVID-19 and the long-term risk of digestive system disorders. COVID-19 patients are at a higher risk of developing digestive diseases. The risks exhibited a stepwise escalation with the severity of COVID-19, were noted in cases of reinfection, and persisted even after 1-year follow-up. This highlights the need to understand the varying risks of digestive outcomes in COVID-19 patients over time, particularly those who experienced reinfection, and develop appropriate follow-up strategies.

Summary: Background: In the post-pandemic era, growing apprehension exists regarding the potential sequelae of COVID-19. However, the risks of respiratory diseases following SARS-CoV-2 infection have not been comprehensively understood. This study aimed to investigate whether COVID-19 increases the long-term risk of respiratory illness in patients with COVID-19. Methods: In this longitudinal, population-based cohort study, we built three distinct cohorts age 37–73 years using the UK Biobank database; a COVID-19 group diagnosed in medical records between January 30th, 2020 and October 30th, 2022, and two control groups, a contemporary control group and a historical control group, with cutoff dates of October 30th, 2022 and October 30th, 2019, respectively. The follow-up period of all three groups was 2.7 years (the median (IQR) follow-up time was 0.8 years). Respiratory outcomes diagnosed in medical records included common chronic pulmonary diseases (asthma, bronchiectasis, chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), pulmonary vascular disease (PVD), and lung cancer. For the data analysis, we calculated hazard ratios (HRs) along with their 95% CIs using Cox regression models, following the application of inverse probability weights (IPTW). Findings: A total of 3 cohorts were included in this study; 112,311 individuals in the COVID-19 group with a mean age (±SDs) of 56.2 (8.1) years, 359,671 in the contemporary control group, and 370,979 in the historical control group. Compared with the contemporary control group, those infected with SARS-CoV-2 exhibited elevated risks for developing respiratory diseases. This includes asthma, with a HR of 1.49 and a 95% CI 1.28–1.74; bronchiectasis (1.30; 1.06–1.61); COPD (1.59; 1.41–1.81); ILD (1.81; 1.38–2.21); PVD (1.59; 1.39–1.82); and lung cancer (1.39; 1.13–1.71). With the severity of the acute phase of COVID-19, the risk of pre-described respiratory outcomes increases progressively. Besides, during the 24-months follow-up, we observed an increasing trend in the risks of asthma and bronchiectasis over time. Additionally, the HR of lung cancer for 0–6 month follow-up was 3.07 (CI 1.73–5.44), and the association of lung cancer with COVID-19 disease disappeared at 6–12 month follow-up (1.06; 0.43–2.64) and at 12–24 months (1.02; 0.45–2.34). Compared to those with one SARS-CoV-2 infection, reinfected patients were at a higher risk of asthma (3.0; 1.32–6.84), COPD (3.07; 1.42–6.65), ILD (3.61; 1.11–11.8), and lung cancer (3.20; 1.59–6.45). Similar findings were noted when comparing with a historical cohort serving as a control group, including asthma (1.31; 1.13–1.52); bronchiectasis (1.53; 1.23–1.89); COPD (1.41; 1.24–1.59); ILD (2.53; 2.05–3.13); PVD (2.30; 1.98–2.66); and lung cancer (2.23; 1.78–2.79). Interpretation: Our research suggests that patients with COVID-19 may have an increased risk of developing respiratory diseases, and the risk increases with the severity of infection and reinfection. Even during the 24-month follow-up, the risk of asthma and bronchiectasis continued to increase. Hence, implementing appropriate follow-up strategies for these individuals is crucial to monitor and manage potential long-term respiratory health issues. Additionally, the increased risk in lung cancer in the COVID-19 individuals was probably due to the diagnostic tests conducted and incidental diagnoses. Funding: The National Natural Science Foundation of China of China Regional Innovation and Development Joint Foundation; National Natural Science Foundation of China; Program for High-level Foreign Expert Introduction of China; Natural Science Foundation for Distinguished Young Scholars of Guangdong Province; Guangdong Basic and Applied Basic Research Foundation; Climbing Program of Introduced Talents and High-level Hospital Construction Project of Guangdong Provincial People’s Hospital; VA Clinical Merit and ASGE clinical research funds.

Accurately simulating glacier mass balance (GMB) data is crucial for assessing the impacts of climate change on glacier dynamics. Since physical models often face challenges in comprehensively accounting for factors influencing glacial melt and uncertainties in inputs, machine learning (ML) offers a viable alternative due to its robust flexibility and nonlinear fitting capability. However, the effectiveness of ML in modeling GMB data across diverse glacier types within High Mountain Asia has not yet been thoroughly explored. This study addresses this research gap by evaluating ML models used for the simulation of annual glacier-wide GMB data, with a specific focus on comparing maritime glaciers in the Niyang River basin and continental glaciers in the Manas River basin. For this purpose, meteorological predictive factors derived from monthly ERA5-Land datasets, and topographical predictive factors obtained from the Randolph Glacier Inventory, along with target GMB data rooted in geodetic mass balance observations, were employed to drive four selective ML models: the random forest model, the gradient boosting decision tree (GBDT) model, the deep neural network model, and the ordinary least-square linear regression model. The results highlighted that ML models generally exhibit superior performance in the simulation of GMB data for continental glaciers compared to maritime ones. Moreover, among the four ML models, the GBDT model was found to consistently exhibit superior performance with coefficient of determination (R2) values of 0.72 and 0.67 and root mean squared error (RMSE) values of 0.21 m w.e. and 0.30 m w.e. for glaciers within Manas and Niyang river basins, respectively. Furthermore, this study reveals that topographical and climatic factors differentially influence GMB simulations in maritime and continental glaciers, providing key insights into glacier dynamics in response to climate change. In summary, ML, particularly the GBDT model, demonstrates significant potential in GMB simulation. Moreover, the application of ML can enhance the accuracy of GMB modeling, providing a promising approach to assess the impacts of climate change on glacier dynamics.

Background Psychiatric disorders have serious harm to individuals’ lives with high disease burden. Observational studies reported inconsistent associations between periodontitis and some psychiatric disorders, and the causal correlations between them remain unknown.Objective This study aims to explore the causal associations between periodontitis and psychiatric disorders.Methods A series of two-sample Mendelian randomisation (MR) analyses were employed using genome-wide association study summary statistics for periodontitis in adults from Gene-Lifestyle Interactions in Dental Endpoints Consortium and 10 psychiatric disorders from Psychiatric Genomics Consortium. Causal effects were primarily estimated using the inverse-variance weighted (IVW) method. Various sensitivity analyses were also conducted to assess the robustness of our results.Findings The MR analysis suggested that genetically determined periodontitis was not causally associated with 10 psychiatric disorders (IVW, all p>0.089). Furthermore, the reverse MR analysis revealed that 10 psychiatric disorders had no causal effect on periodontitis (IVW, all p>0.068). We discovered that all the results were consistent in the four MR analytical methods, including the IVW, MR-Egger, weighted median and weighted mode. Besides, we did not identify any heterogeneity or horizontal pleiotropy in the sensitivity analysis.Conclusions These results do not support bidirectional causal associations between genetically predicted periodontitis and 10 common psychiatric disorders. Potential confounders might contribute to the previously observed associations.Clinical implications Our findings might alleviate the concerns of patients with periodontitis or psychiatric disorders. However, further research was warranted to delve into the intricate relationship between dental health and mental illnesses.

Summary: Background: The treatment of esophageal cancer has entered a new phase with the development of immunotherapy. The current investigation purpose is to investigate and contrast the efficacy and safety of immunotherapy, immunochemotherapy, chemotherapy, and targeted therapy as first-line treatment for individuals suffering from advanced and metastatic esophageal cancer. Methods: Within the framework of this systematic review and network meta-analysis, clinical trials published or reported in English up until 01 May, 2022, were retrieved from Embase, PubMed, Cochrane Central Register of Controlled Trials, the ClinicalTrials.gov databases, ESMO, and ASCO. The analysis incorporated randomized controlled trials (RCTs) from phase 2 to 3 that evaluated a minimum of two first-line therapeutic regimens for metastatic esophageal cancer were included in the analysis. The primary outcomes were overall survival (OS) and progression-free survival (PFS). Secondary clinical outcomes included the incidence of objective response rate (ORR), and adverse events (AEs) of any grade and ≥3 grade. Relative summary data were extracted from included studies by GZ, HS, WS, and TD. For clear statistical analysis, chemotherapy was divided into two categories of fluorouracil-based chemotherapy (FbCT) and fluorouracil-free chemotherapy (FfCT). Bayesian frequentist approach was employed to conduct the network meta-analysis. The indirect intercomparison between regimens was presented with league tables (HRs and 95% CI for OS and PFS, ORs and 95% CI for ORR and AEs). A greater surface value under the cumulative ranking (SUCRA) indicates a higher potential ranking for the corresponding treatment. A further calculation of relative results about esophageal squamous cell cancer was performed in the subgroup analysis. The current protocol for the systematic review has been properly registered on PROSPERO (registration number: CRD42021241145). Findings: The final analysis comprised 17 trials that involved 9128 patients and 19 distinct treatment regimens. Within the scope of investigated immunotherapy (IO) combinations, toripalimab + FfCT (tori + FfCT) demonstrated the best OS advantages (tori + FfCT vs. FbCT, HR 0.57, 95% CI 0.38–0.85; tori + FfCT vs. FfCT, HR 0.58, 95% CI 0.43–0.78). In terms of PFS, camrelizumab + FfCT (cam + FfCT) demonstrated the best PFS advantages (FbCT vs. cam + FfCT, HR 1.79, 95% CI 1.22–2.63; FfCT vs. cam + FfCT, HR 1.79, 95% CI 1.47–2.17). Nivolumab + FbCT (nivo + FbCT vs. FfCT, OR 3.29, 95% CI 1.43–7.56) showed the best objective responses. Compared to the conventional chemotherapy regimen, the toxicity was observed to be the slightest for the tori + FfCT (FbCT vs. tori + FfCT, OR 3.07, 95% CI 1.22–7.7) and sintilimab + FfCT (FbCT vs. sin + FfCT, OR 2.93, 95% CI 1.16–7.37). The results in this study were evaluated as having a low heterogeneity since the I2 value was ≤25% in all analyses. Interpretation: Compared to foreign IO combinations, sin + FfCT, tori + FfCT, cam + FfCT, and tisle + FbCT are superior first-line treatment options for patients with advanced and metastatic esophageal cancer. Although foreign IO combinations, such as pembro + FbCT and nivo + FbCT obtained better objective response rates than other IO combinations, the addition of chemotherapy to IO worsens the safety profiles. Our findings could provide complementary evidence for current guideline recommendations. Funding: This work was supported by a grant from the Science and Technology Program of Guangzhou, China (202206010103); and Natural Science Foundation of Guangdong Province (2022A1515012469).

The exacerbated thermal environment in cities, with the urban heat island (UHI) effect as a prominent example, has been the source of many adverse urban environmental issues, including the increase of health risks, degradation of air quality and ecosystem services, and reduced resiliency of engineering infrastructure. Last decades have witnessed tremendous efforts and resources being invested to find sustainable solutions for urban heat mitigation, whereas the relative contributions of different UHI attributes and their patterns of spatio-temporal variability remain obscure. In this study, we employed the random forest (RF) method to quantify the relative importance of four categories of urban surface characteristics that regulate the surface UHI, namely the urban greenery fraction, land surface albedo, urban morphology, and level of human activities. We selected seventeen major cities from six megaregions in China as our study areas, with the RF training and test sets obtained from multi-sourced remote sensing and observational data products. It is found that the urban greenery coverage manifests as the most important environmental determinants of UHI, followed by surface albedo. The results are informative for urban planners, policymakers, and engineering practitioners to design and implement sustainable strategies for urban heat mitigation.

Summary: Background: Observational studies have associated obesity with an increased risk of multiple sclerosis (MS). However, the role of genetic factors in their comorbidity remains largely unknown. Our study aimed to investigate the shared genetic architecture underlying obesity and MS. Methods: By leveraging data from genome-wide association studies, we investigated the genetic correlation of body mass index (BMI) and MS by linkage disequilibrium score regression and genetic covariance analyser. The casualty was identified by bidirectional Mendelian randomisation. Linkage disequilibrium score regression in specifically expressed genes and multimarker analysis of GenoMic annotation was utilised to explore single-nucleotide polymorphism (SNP) enrichment at the tissue and cell-type levels. Shared risk SNPs were derived using cross-trait meta-analyses and Heritability Estimation from Summary Statistics. We explored the potential functional genes using summary-data-based Mendelian randomization (SMR). The expression profiles of the risk gene in tissues were further examined. Findings: We found a significantly positive genetic correlation between BMI and MS, and the causal association of BMI with MS was supported (β = 0.22, P = 8.03E-05). Cross-trait analysis yielded 39 shared risk SNPs, and the risk gene GGNBP2 was consistently identified in SMR. We observed tissue-specific level SNP heritability enrichment for BMI mainly in brain tissues for MS in immune-related tissues, and cell-type-specific level SNP heritability enrichment in 12 different immune cell types in brain, spleen, lung, and whole blood. The expressions of GGNBP2 were significantly altered in the tissues of patients with obesity or MS compared to those of control subjects. Interpretation: Our study indicates the genetic correlation and shared risk genes between obesity and MS. These findings provide insights into the potential mechanisms behind their comorbidity and the future development of therapeutics. Funding: This work was funded by the National Natural Science Foundation of China (82171698, 82170561, 81300279, and 81741067), the Program for High-level Foreign Expert Introduction of China (G2022030047L), the Natural Science Foundation for Distinguished Young Scholars of Guangdong Province (2021B1515020003), Natural Science Foundation of Guangdong Province (2022A1515012081), the Foreign Distinguished Teacher Program of Guangdong Science and Technology Department (KD0120220129), the Climbing Programme of Introduced Talents and High-level Hospital Construction Project of Guangdong Provincial People's Hospital (DFJH201803, KJ012019099, KJ012021143, and KY012021183), and in part by VA Clinical Merit and ASGE clinical research funds (FWL).

Reservoirs are designed and operated to mitigate hydroclimatic variability and extremes to fulfill various beneficial purposes. Existing reservoir infrastructure capacity and operation policies derived from historical records are challenged by hydrologic regime change and storage reduction from sedimentation. Furthermore, climate change could amplify the water footprint of reservoir operation (i.e. non-beneficial evaporative loss), further influencing the complex interactions among hydrologic variability, reservoir characteristics, and operation decisions. Disentangling and quantifying these impacts is essential to assess the effectiveness of reservoir operation under future climate and identify the opportunities for adaptive reservoir management (e.g. storage reallocation). Using reservoirs in Texas as a testing case, this study develops data-driven models to represent the current reservoir operation policies and assesses the challenges and opportunities in flood control and water supply under dynamically downscaled climate projections from the Coupled Model Intercomparison Project Phase 6. We find that current policies are robust in reducing future flood risks by eliminating small floods, reducing peak magnitude, and extending the duration for large floods. Current operation strategies can effectively reduce the risk of storage shortage for many reservoirs investigated, but reservoir evaporation and sedimentation pose urgent needs for revisions in the current guidelines to enhance system resilience. We also identify the opportunities for reservoir storage reallocation through seasonal-varying conservation pool levels to improve water supply reliability with negligible flood risk increase. This study provides a framework for stakeholders to evaluate the effectiveness of the current reservoir operation policy under future climate through the interactions among hydroclimatology, reservoir infrastructure, and operation policy.

Abstract Background Glioblastoma multiforme (GBM) is one of the most malignant tumors in brain with high morbidity and mortality. Mitophagy plays a significant role in carcinogenesis, metastasis, and invasion. In our study, we aim to construct a mitophagy-related risk model to predict prognosis in GBM. Methods RNA-seq data combined with clinical information were downloaded from TCGA. The 4-gene risk model and nomograph was then constructed and validated in external cohort. Evaluation of immune infiltration, functional enrichment and tumor microenvironment (TME) were then performed. Result A mitophagy-related risk model was established and patients in TCGA and CGGA were classified into low-risk and high-risk groups. In both cohorts, patients in low-risk group had improved survival, while high-risk group had poor prognosis. Also, the risk model was identified as an independent factor for predicting overall survival via Cox regression. Furthermore, a prognostic nomogram including mitophagy signatures was established with excellent predictive performance. In addition, the risk model was closely associated with regulation of immune infiltration as well as TME. Conclusion In conclusion, our study constructed a mitophagy-related risk model, which can be utilized for the clinical prognostic prediction in GBM.

Due to the scarcity of observational data and the intricate precipitation–runoff relationship, individually applying physically based hydrological models and machine learning (ML) techniques presents challenges in accurately predicting floods within data-scarce glacial river basins. To address this challenge, this study introduces an innovative hybrid model that synergistically harnesses the strengths of multi-source remote sensing data, a physically based hydrological model (i.e., Spatial Processes in Hydrology (SPHY)), and ML techniques. This novel approach employs MODIS snow cover data and remote sensing-derived glacier mass balance data to calibrate the SPHY model. The SPHY model primarily generates baseflow, rain runoff, snowmelt runoff, and glacier melt runoff. These outputs are then utilized as extra inputs for the ML models, which consist of Random Forest (RF), Gradient Boosting (GDBT), Long Short-Term Memory (LSTM), Deep Neural Network (DNN), Support Vector Machine (SVM) and Transformer (TF). These ML models reconstruct the intricate relationship between inputs and streamflow. The performance of these six hybrid models and SPHY model is comprehensively explored in the Manas River basin in Central Asia. The findings underscore that the SPHY-RF model performs better in simulating and predicting daily streamflow and flood events than the SPHY model and the other five hybrid models. Compared to the SPHY model, SPHY-RF significantly reduces RMSE (55.6%) and PBIAS (62.5%) for streamflow, as well as reduces RMSE (65.8%) and PBIAS (73.51%) for floods. By utilizing bootstrap sampling, the 95% uncertainty interval for SPHY-RF is established, effectively covering 87.65% of flood events. Significantly, the SPHY-RF model substantially improves the simulation of streamflow and flood events that the SPHY model struggles to capture, indicating its potential to enhance the accuracy of flood prediction within data-scarce glacial river basins. This study offers a framework for robust flood simulation and forecasting within glacial river basins, offering opportunities to explore extreme hydrological events in a warming climate.

IntroductionCrohn’s disease is characterized of dysregulated inflammatory and immune reactions. The role of the NOD-like receptor family, pyrin domain-containing 3 (NLRP3) inflammasome in Crohn’s disease remains largely unknown.MethodsThe microarray-based transcriptomic data and corresponding clinical information of GSE100833 and GSE16879 were obtained from the Gene Expression Omnibus (GEO) database. Identification of in the NLRP3 inflammasome-related genes and construction of LASSO regression model. Immune landscape analysis was evaluated with ssGSEA. Classification of Crohn’s-disease samples based on NLRP3 inflammasome-related genes with ConsensusClusterPlus. Functional enrichment analysis, gene set variation analysis (GSVA) and drug-gene interaction network.ResultsThe expressions of NLRP3 inflammasome-related genes were increased in diseased tissues, and higher expressions of NLRP3 inflammasome-related genes were correlated with generally enhanced immune cell infiltration, immune-related pathways and human leukocyte antigen (HLA)-gene expressions. The gene-based signature showed well performance in the diagnosis of Crohn’s disease. Moreover, consensus clustering identified two Crohn’s disease clusters based on NLRP3 inflammasome-related genes, and cluster 2 was with higher expressions of the genes. Cluster 2 demonstrated upregulated activities of immune environment in Crohn’s disease. Furthermore, four key hub genes were identified and potential drugs were explored for the treatment of Crohn’s disease.ConclusionsOur findings indicate that NLRP3 inflammasome and its related genes could regulate immune cells and responses, as well as involve in the pathogenesis of Crohn’s disease from transcriptomic aspects. These findings provide in silico insights into the diagnosis and treatment of Crohn’s disease and might assist in the clinical decision-making process.

ObjectiveEnergy metabolism plays a crucial role in the improvement of heart dysfunction as well as the development of heart failure (HF). The current study is designed to identify energy metabolism-related diagnostic biomarkers for predicting the risk of HF due to myocardial infarction.MethodsTranscriptome sequencing data of HF patients and non-heart failure (NF) people (GSE66360 and GSE59867) were obtained from gene expression omnibus (GEO) database. Energy metabolism-related differentially expressed genes (DEGs) were screened between HF and NF samples. The subtyping consistency analysis was performed to enable the samples to be grouped. The immune infiltration level among subtypes was assessed by single sample gene set enrichment analysis (ssGSEA). Random forest algorithm (RF) and support vector machine (SVM) were applied to identify diagnostic biomarkers, and the receiver operating characteristic curves (ROC) was plotted to validate the accuracy. Predictive nomogram was constructed and validated based on the result of the RF. Drug screening and gene-miRNA network were analyzed to predict the energy metabolism-related drugs and potential molecular mechanism.ResultsA total of 22 energy metabolism-related DEGs were identified between HF and NF patients. The clustering analysis showed that HF patients could be classified into two subtypes based on the energy metabolism-related genes, and functional analyses demonstrated that the identified DEGs among two clusters were mainly involved in immune response regulating signaling pathway and lipid and atherosclerosis. ssGSEA analysis revealed that there were significant differences in the infiltration levels of immune cells between two subtypes of HF patients. Random-forest and support vector machine algorithm eventually identified ten diagnostic markers (MEF2D, RXRA, PPARA, FOXO1, PPARD, PPP3CB, MAPK14, CREB1, MEF2A, PRMT1) for risk prediction of HF patients, and the proposed nomogram resulted in good predictive performance (GSE66360, AUC = 0.91; GSE59867, AUC = 0.84) and the clinical usefulness in HF patients. More importantly, 10 drugs and 15 miRNA were predicted as drug target and hub miRNA that associated with energy metabolism-related genes, providing further information on clinical HF treatment.ConclusionThis study identified ten energy metabolism-related diagnostic markers using random forest algorithm, which may help optimize risk stratification and clinical treatment in HF patients.

Abstract Necrotizing enterocolitis (NEC) is a devastating disease predominately affecting neonates. Despite therapeutic advances, NEC remains the leading cause of mortality due to gastrointestinal conditions in neonates. Stem cells have been exploited in various diseases, and the application of different types of stem cells in the NEC therapy is explored in the past decade. However, stem cell transplantation possesses several deficiencies, and exosomes are considered potent alternatives. Exosomes, especially those derived from stem cells and breast milk, demonstrate beneficial effects for NEC both in vivo and in vitro and emerge as promising options for clinical practice. In this review, the function and therapeutic effects of stem cells and exosomes for NEC are investigated and summarized, which provide insights for the development and application of novel therapeutic strategies in pediatric diseases. Further elucidation of mechanisms, improvement in preparation, bioengineering, and administration, as well as rigorous clinical trials are warranted.

Necrotizing enterocolitis (NEC) is one of the most prevalent neonatal gastrointestinal disorders. Despite ongoing breakthroughs in its treatment and prevention, the incidence and mortality associated with NEC remain high. New therapeutic approaches, such as breast milk composition administration, stem cell therapy, immunotherapy, and fecal microbiota transplantation (FMT) have recently evolved the prevention and the treatment of NEC. This study investigated the most recent advances in NEC therapeutic approaches and discussed their applicability to bring new insight to NEC treatment.

Esophageal carcinoma is one of the most aggressive malignant diseases. At present, neoadjuvant chemotherapy and neoadjuvant chemoradiotherapy are regarded as the standard modalities for the treatments of locally advanced esophageal cancers based on several landmark trials. However, the optimal regimen, radiation dose, and surgical intervals are uncertain and the rate of recurrence after neoadjuvant therapy is high. Patients receiving neoadjuvant therapy and reaching a pathological complete response have been reported to have a better survival benefit and a fewer recurrence risk than those non-pathological complete responses. Nevertheless, less than half of patients will reach a pathological complete response after neoadjuvant therapy, and the methods to evaluate the efficacy after neoadjuvant therapy accurately are limited. Immune checkpoint inhibitors have been recommended for the treatments of advanced esophageal cancers. Recently, research has been beginning to evaluate the safety and efficacy of immunotherapy combined with neoadjuvant therapy. Here, we will review and discuss the development of the neoadjuvant therapy of locally advanced esophageal cancers and unsolved clinical problems.

Summary: Rho guanosine triphosphatase (GTPases), as molecular switches, have been identified to be dysregulated and involved in the pathogenesis of various rheumatic diseases, mainly including rheumatoid arthritis, osteoarthritis, systemic sclerosis, and systemic lupus erythematosus. Downstream pathways involving multiple types of cells, such as fibroblasts, chondrocytes, synoviocytes, and immunocytes are mediated by activated Rho GTPases to promote pathogenesis. Targeted therapy via inhibitors of Rho GTPases has been implicated in the treatment of rheumatic diseases, demonstrating promising effects. In this review, the effects of Rho GTPases in the pathogenesis of rheumatic diseases are summarized, and the Rho GTPase-mediated pathways are elucidated. Therapeutic strategies using Rho GTPase inhibitors in rheumatic diseases are also discussed to provide insights for further exploration of targeted therapy in preclinical studies and clinical practice. Future directions on studies of Rho GTPases in rheumatic diseases based on current understandings are provided.

Ulcerative colitis is a chronic inflammatory bowel disorder that is hard to cure once diagnosed. Bisdemethoxycurcumin has shown positive effects on inflammatory diseases. However, the underlying bioactive interaction between bisdemethoxycurcumin and ulcerative colitis is unclear. The objective of this study was to determine the core target and potential mechanism of action of bisdemethoxycurcumin as a therapy for ulcerative colitis. The public databases were used to identify potential targets for bisdemethoxycurcumin and ulcerative colitis. To investigate the potential mechanisms, the protein-protein interaction network, gene ontology analysis, and Kyoto encyclopedia of genes and genomes analysis have been carried out. Subsequently, experimental verification was conducted to confirm the findings. A total of 132 intersecting genes of bisdemethoxycurcumin, as well as ulcerative coli-tis-related targets, were obtained. SRC, EGFR, AKT1, and PIK3R1 were the targets of highest potential, and the PI3K/Akt and MAPK pathways may be essential for the treatment of ulcerative colitis by bisdemethoxycurcumin. Molecular docking demonstrated that bisdemethoxycurcumin combined well with SRC, EGFR, PIK3R1, and AKT1. Moreover, the in vitro experiments suggested that bisdemethoxycurcumin might reduce LPS-induced pro-inflammatory cytokines levels in RAW264.7 cells by suppressing PI3K/Akt and MAPK pathways. Our study provided a comprehensive overview of the potential targets and molecular mechanism of bisdemethoxycurcumin against ulcerative colitis. Furthermore, it also provided a theoretical basis for the clinical treatment of ulcerative colitis, as well as compelling evidence for further study on the mechanism of bisdemethoxycurcumin in the treatment of ulcerative colitis.

Esophageal adenocarcinoma (EAC) is a highly malignant type of digestive tract cancers with a poor prognosis despite therapeutic advances. Pyroptosis is an inflammatory form of programmed cell death, whereas the role of pyroptosis in EAC remains largely unknown. Herein, we identified a pyroptosis-related five-gene signature that was significantly correlated with the survival of EAC patients in The Cancer Genome Atlas (TCGA) cohort and an independent validation dataset. In addition, a nomogram based on the signature was constructed with novel prognostic values. Moreover, the downregulation of GSDMB within the signature is notably correlated with enhanced DNA methylation. The pyroptosis-related signature might be related to the immune response and regulation of the tumor microenvironment. Several inhibitors including GDC-0879 and PD-0325901 are promising in reversing the altered differentially expressed genes in high-risk patients. Our findings provide insights into the involvement of pyroptosis in EAC progression and are promising in the risk assessment as well as the prognosis for EAC patients in clinical practice.

Groundwater-based irrigation has dramatically expanded over the past decades. It has important implications for terrestrial water, energy fluxes, and food production, as well as local to regional climates. However, irrigation water use is hard to monitor at large scales due to various constraints, including the high cost of metering equipment installation and maintenance, privacy issues, and the presence of illegal or unregistered wells. This study estimates irrigation water amounts using machine learning to integrate in situ pumping records, remote sensing products, and climate data in the Kansas High Plains. We use a random forest regression to estimate the annual irrigation water amount at a reprojected spatial resolution of 6 km based on various data, including remotely sensed vegetation indices and evapotranspiration (ET), land cover, near-surface meteorological forcing, and a satellite-derived irrigation map. In addition, we assess the value of ECOSTRESS ET products for irrigation water use estimation and compare with the baseline results by using MODIS ET. The random forest regression model can capture the temporal and spatial variability of irrigation amounts with a satisfactory accuracy (R2 = 0.82). It performs reasonably well when it is calibrated on the western portion of the study area and tested on the eastern portion that receives more rain than the western one, suggesting its potential transferability to other regions. ECSOTRESS ET and MODIS ET yield a similar irrigation estimation accuracy.

Background: Emerging data have suggested colorectal cancer (CRC) often coexists with cardiovascular diseases, but whether cardiovascular risk factors play a role in CRC remains unclear. We performed a systematic review and meta-analysis to better illustrate the associations between cardiovascular risk factors and CRC. Methods: We searched EMBASE, MEDLINE and Web of Science databases from inception up to June 14, 2020. Prospective cohort studies were included if they evaluated the association between at least one of cardiovascular risk factors and CRC incidence, containing sufficient data to obtain relative risk (RR) and 95% confidence interval (CI). We performed separate meta-analyses for each cardiovascular risk factor using random-effect model. PROSPERO registration number: CRD42020175537. Findings: Data from 84 studies, reporting 52, 348, 827 individuals and 384, 973 incident cases were included in the analysis. Overall, the risk of CRC was 1.31(95% CI, 1.21–1.42) for obesity, 1.14 (95% CI, 1.09–1.20) for per 5 kg/m2 increase in body mass index, 1.18 (95% CI, 1.14–1.23) for former smoker, 1.20 (95% CI, 1.11–1.30) for current smoker, 1.25 (95% CI, 1.16–1.35) for diabetes, 1.07 (95% CI, 1.02–1.12) for hypertension. The summary RRs of CRC for the highest versus lowest quartiles of total cholesterol, triglyceride, low-density lipoprotein were 1.12 (95% CI, 1.03–1.22), 1.18 (95% CI, 1.04–1.35), 0.85 (95% CI, 0.62–1.17) respectively and the pooled RR for the lowest versus highest quartile of high-density lipoprotein was 1.14 (95% CI, 1.02–1.28). Interpretation: Unfavorable cardiovascular risk factors are associated with increased risk of CRC, which may provide novel insight into the screening strategies of CRC in patient with these risk factors.

Background: Esophagogastric junction adenocarcinoma (EJA) is one of the most common malignant tumors of digestive tract with high mortality worldwide. Given a lack of early diagnosis biomarkers, the prognosis of EJA is poor. Non-invasive biomarkers for early-stage EJA are urgently required. Objective: We aimed at evaluating the early diagnostic value of serum interleukin-8 (IL-8) level in EJA patients. Methods: The IL-8 mRNA expression data were analyzed based on the stomach cardia adenocarcinoma samples of The Cancer Genome Atlas (TCGA) database. Enzyme-linked immunosorbent assay (ELISA) was used to measure the concentration of serum IL-8 in 95 EJA patients and 95 normal controls enrolled from 2 different cancer hospitals. The diagnostic accuracy of serum IL-8 was evaluated by applying Mann-Whitney U test and receiver operating characteristic (ROC) curve. Results: The mRNA expression levels and serum levels of IL-8 in EJA group were significantly higher than those in the normal group (all P < 0.001). The areas under the ROC curve (AUC) were 0.661 (95% CI, 0.583-0.740) and 0.745 (95% CI, 0.606-0.885), with the sensitivities of 43.2% (95% CI, 33.2%-53.7%) and 66.7% (95% CI, 46.0%-82.8%) and the specificities of 87.4% (95% CI, 78.6%-93.1%) in EJA group and early-EJA group, respectively, when the optimal cutoff value was 109.086 pg/mL. The clinical data analysis showed there were significant correlations between patient genders, depth of invasion, lymph node metastasis, TNM stage and the serum level of IL-8 (all P < 0.05). Conclusions: Serum IL-8 represents a potential diagnostic biomarker to identify early-stage EJA.

Rac1 is a small signaling protein, which belongs to the Rho subfamily of Ras superfamily. It is activated by binding GTP and inactivated by exchanging GDP for GTP. The ability of nucleotide exchange depends on guanine nucleotide exchange factors (GEFs) family proteins. T-lymphoma invasion and metastasis factor 1 (Tiam1) is a member of GEFs. Rac1 participates in multiple signaling pathways and regulates various cellular events by interacting with GEFs. Particularly, it is involved in the development and progression of various kinds of tumors. In this paper, we have studied the detailed interaction between Rac1 and Tiam1. Seven residues on Rac1 are predicted to be important for the interaction with Tiam1, i.e. E31, Y32, D38, N39, Y64, D65 and W56. All these residues are located on the switch 1 and 2 domains which are the interface between Rac1 and Tiam1, except W56. In addition, we analyzed how inhibitor NSC23766 interacts with Rac1. Our docking results show that NSC23766 binds to the same region as Tiam1. Several residues, i.e. F37, D38, N39, W56, Y64, L67, L70 and S71, contribute much to binding free energy. These findings are very useful for the structure-based design of inhibitors toward Rac1.

Irrigation has enhanced food security and biofuel production throughout the world. However, the sustainability of irrigation faces challenges from climate variability and extremes, increasing consumption from irrigated cropland expansion, and competing demands from other water use sectors. In this study, we investigated the agricultural water withdrawal landscape of the contiguous United States (CONUS) over 1981–2015, assessed its spatial and temporal changes, and analyzed the factors driving the changes. We introduced the concept of ‘center of mass’ to calculate the spatiotemporal trajectory of water withdrawal, along with climatic and agricultural factors at state, regional and CONUS scales. At the CONUS level, the total agricultural water withdrawal has decreased during 1981–2015, and the centroid of water withdrawal consistently moved toward the east, caused by reduced water withdrawal in the western states and increased withdrawal in the eastern states. While the CONUS irrigation trajectory is not mainly affected by climatologic trends, extreme drought conditions (e.g. the mega droughts in western states since 2000) may interrupt the trend. In the Western US, irrigation withdrawal reduction was mainly achieved by adoption of high-efficiency irrigation technology, while the irrigated acreage remains relatively stable. Under drought conditions, irrigation withdrawal often switched from surface water to groundwater sources, posing challenges on groundwater sustainability under prolonged drought conditions. The Eastern US has experienced accelerating agricultural withdrawal from both surface water and groundwater sources. This was mainly driven by expansion in irrigated acreage in the Midwest and lower Mississippi River, with irrigated croplands supplied by mixed flood irrigation and high-efficiency irrigation methods. At the state level, some states exhibited discrepancy in agricultural withdrawal centroids from surface water and groundwater sources, as results of climate heterogeneity, water availability and infrastructure development. This study provides understanding of the driving forces in the spatiotemporal trends of CONUS agricultural water withdrawal in different regions and implications for predicting future agricultural withdrawal under changing climatic and socioeconomic uncertainties.

Accumulating evidence has suggested a role of the small GTPase Ras homolog gene family member A (RhoA) in DNA damage response (DDR) in addition to its traditional function of regulating cell morphology. In DDR, 2 key components of DNA repair, ataxia telangiectasia-mutated (ATM) and flap structure-specific endonuclease 1 (FEN1), along with intracellular reactive oxygen species (ROS) have been shown to regulate RhoA activation. In addition, Rho-specific guanine exchange factors (GEFs), neuroepithelial transforming gene 1 (Net1) and epithelial cell transforming sequence 2 (Ect2), have specific functions in DDR, and they also participate in Ras-related C3 botulinum toxin substrate 1 (Rac1)/RhoA interaction, a process which is largely unappreciated yet possibly of significance in DDR. Downstream of RhoA, current evidence has highlighted its role in mediating cell cycle arrest, which is an important step in DNA repair. Unraveling the mechanism by which RhoA modulates DDR may provide more insight into DDR itself and may aid in the future development of cancer therapies.

Numerous reservoirs around the world provide multiple flow regulation functions; key among these are hydroelectricity production and water releases for irrigation. These functions contribute to energy and food security at national, regional and global levels. While reservoir operations for hydroelectricity production might support irrigation, there are also well-known cases where hydroelectricity production reduces water availability for irrigated food production. This study assesses these relationships at the global level using machine-learning techniques and multi-source datasets. We find that 54% of global installed hydropower capacity (around 507 thousand Megawatt) competes with irrigation. Regions where such competition exists include the Central United States, northern Europe, India, Central Asia and Oceania. On the other hand, 8% of global installed hydropower capacity (around 79 thousand Megawatt) complements irrigation, particularly in the Yellow and Yangtze River Basins of China, the East and West Coasts of the United States and most river basins of Southeast Asia, Canada and Russia. No significant relationship is found for the rest of the world. We further analyze the impact of climate variables on the relationships between hydropower and irrigation. Reservoir flood control functions that operate under increased precipitation levels appear to constrain hydroelectricity production in various river basins of the United States, South China and most basins in Europe and Oceania. On the other hand, increased reservoir evaporative losses and higher irrigation requirements due to higher potential evaporation levels may lead to increased tradeoffs between irrigation and hydropower due to reduced water availability in regions with warmer climates, such as India, South China, and the Southern United States. With most reservoirs today being built for multiple purposes, it is important for policymakers to understand and plan for growing tradeoffs between key functions. This will be particularly important as climate mitigation calls for an increase in renewable energy while agro-hydrological impacts of climate change, population and economic growth and associated dietary change increase the need for irrigated food production in many regions round the world.

Published observational studies have revealed the connection between neurodegenerative disorders and inflammatory bowel disease (IBD), whereas the causal association remains largely unclear. Our study aims to assess the causality and identify the shared genetic architecture between neurodegenerative disorders and IBD. Two-sample Mendelian randomization analyses were performed to assess the causality between IBD and neurodegenerative disorders (amyotrophic lateral sclerosis [ALS], Alzheimer's disease [AD], Parkinson's disease [PD], and multiple sclerosis [MS]). Shared genetic loci, functional interpretation, and transcriptomic profiles were further investigated in ALS and IBD. We identified that genetic predisposition to IBD was suggestively associated with lower odds of ALS (odds ratio [OR] 0.96, 95% confidence interval [CI] 0.94 to 0.99). In contrast, IBD was not genetically associated with an increased risk of AD, PD, or MS (and vice versa). Two shared genetic loci (rs6571361 and rs7154847) were derived, and SCFD1, G2E3, and HEATR5A were further identified as novel risk genes with enriched functions related to membrane trafficking. G2E3 was differentially expressed and significantly correlated with SCFD1 in patients with ALS or IBD. Our study reveals the suggestively protective role of IBD on ALS, and does not support the causality of AD, PD, or MS on IBD (and vice versa). Our findings indicate possible shared genetic architecture and pathways between ALS and IBD. These results provide insights into the pathogenesis and therapeutics of IBD and neurodegenerative disorders. [ABSTRACT FROM AUTHOR]