Chronic pancreatitis （CP） is a common disease in clinical practice characterized by progressive inflammatory fibrosis of the pancreas. Gut microbiota， known as the “second genome” of humans， bidirectionally modulates the progression of fibrosis in CP via the gut-pancreas axis. This article systematically elaborates on the characteristics of gut microbiota during the progression of CP and its molecular mechanism in mediating pancreatic fibrosis through bacterial translocation， metabolites， immune regulatory networks， and microbe-pancreatic stellate cell interactions， with a focus on the pivotal role of short-chain fatty acids and inflammatory cytokine networks in pancreatic stellate cell activation and extracellular matrix deposition. In addition， this article explores the potential value of gut microbiota-targeted interventions in the prevention and treatment of CP fibrosis， such as probiotics， prebiotics， and fecal microbiota transplantation， and discusses the translational potential of using multi-omics technologies to identify diagnostic biomarkers and novel therapeutic targets for CP， in order to provide new ideas for the precise diagnosis and treatment of CP.

Short-chain fatty acids （SCFA） are the main metabolic products generated by the fermentation of dietary fiber by gut microbiota. Studies have shown that SCFA not only play a role in energy metabolism， but also act as important signaling molecules， exhibiting a significant potential in alleviating liver and pancreatic fibrosis. The core mechanism of SCFA mainly involves the regulation of various key signaling pathways by activating G protein-coupled receptors and inhibiting the activity of histone deacetylase， thereby suppressing the activation and proliferation of hepatic stellate cell （HSC） and pancreatic stellate cell （PSC）， which is a key link in fibrosis formation. In addition， SCFA can effectively alleviate tissue inflammation response， improve intestinal barrier function， and regulate gut microbiota balance， thus indirectly preventing the process of fibrosis mediated by the “gut-liver/pancreas axis”. Compared with the research on SCFA in liver fibrosis， studies on their role in pancreatic fibrosis are limited. Given that HSC and PSC are highly homologous， the transcription factors and proteins that have been confirmed in liver fibrosis-related studies are also similarly expressed in PSC， suggesting that they may also influence the activation of PSC. This article systematically summarizes the recent advances in the research on SCFA in alleviating liver and pancreatic fibrosis， in order to provide new perspectives for exploring the mechanism of pancreatic fibrosis and developing related interventional strategies.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Stroke ranks as the third leading cause of death and the fourth leading cause of disability worldwide. Its high disability rate and prolonged recovery period not only severely impact patients' quality of life but also impose a significant burden on families and society. Primary prevention is the cornerstone of stroke control, as early intervention on risk factors can effectively reduce its incidence. Therefore, the development of predictive models for first-ever stroke risk holds substantial clinical value. In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. Second, there is a need to diversify data types and optimize model architectures to construct more comprehensive and precise predictive models. Lastly, particular attention should be given to the clinical validation of models in real-world settings. This not only enhances the robustness and generalizability of the models but also promotes physicians' understanding of predictive models, which is crucial for their application and dissemination.

In the context of continuously deepening medical and health system reforms and comprehensively promoting the "Healthy China" strategy, Henan Provincial People's Hospital has established a regional collaborative and vertically integrated critical care service structure and network. This initiative aims to enhance information empowerment, strengthen regional collaboration, improve the insufficient primary medical services, and ensure timely and effective treatment for critically ill patients. By establishing a comprehensive dispatch service platform for regional collaborative critical care, building a "top-down" remote medical collaboration network, and forming a cross-regional specialty alliance for critical care, the hospital has improved the efficiency of medical services and enhanced regional capabilities for treating critically ill patients. Simultaneously, for critically serious patients and those with complex diseases at primary medical institutions, a one-stop consultation and referral service has been implemented. This service adopts a "three specialists" approach and a multidisciplinary consultation mechanism within the hospital, constructs a multi-dimensional critical care transfer mode integrating air, ground, and the internet, creates a regional collaborative rescue mode, and implements full-cycle treatment for critically serious patients. The comprehensive, flexible, and efficient service pathway for regional collaborative critical care established by this system ensures timely and safe treatment for critically ill patients, promotes the distribution of high-quality medical resources, and effectively addresses issues such as uneven distribution of high-quality medical resources and varying levels of critical care capabilities. It has facilitated the formation of a new tiered diagnosis and treatment order characterized by "first diagnosis at the primary level, two-way referral, separate treatment for acute and chronic diseases, and vertical integration". This approach has enhanced the diagnostic and comprehensive service capabilities of primary medical institutions. Currently, by strengthening information empowerment and sharing, creating a full-process critical care diagnosis and treatment model, providing medical assistance and cultivating primary-level critical care talent, and promoting appropriate technologies, the hospital has gradually overcome challenges such as barriers to information exchange and sharing between hospitals, overloaded critical care teams, high pressure on patient reception and transfer, and limited critical care capabilities at primary medical institutions. This article summarizes the construction and practical application of this regionally coordinated critical care system, aiming to provide a reference for the management of critical care treatment.
Humans ; China ; Critical Care/organization & administration* ; Delivery of Health Care/organization & administration*

Lingguizhugan Decoction (LGZG) demonstrates significant efficacy in treating various cardiovascular diseases clinically, yet its precise mechanism of action remains elusive. This study aimed to elucidate the potential mechanisms and effects of LGZG on isoproterenol (ISO) continuous stimulation-induced chronic heart failure (CHF) in mice, providing direct experimental evidence for further clinical applications. In vivo, continuous ISO infusion was administered to mice, and ventricular myocytes were utilized to explore LGZG?s potential mechanism of action on the ?1-adrenergic receptor (?1-AR)/Gs/G protein-coupled receptor kinases (GRKs)/?-arrestin signaling deflection system in the heart. The findings reveal that LGZG significantly reduced the messenger ribonucleic acid (mRNA) expression of hypertrophy-related biomarkers [atrial natriuretic peptide (ANP) and B-type natriuretic peptide (BNP)] and improved cardiac remodeling and left ventricular diastolic function in mice with ISO-induced CHF. Furthermore, LGZG inhibited the overactivation of Gs/cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) signaling and downregulated the downstream transcriptional activity of cAMP-response element binding protein (CREB) and the expression of the coactivator CBP/P300. Notably, LGZG downregulated the expression of ?-arrestin1 and GRK 2/3/5 while upregulating the expression of ?1-AR and ?-arrestin2. These results suggest that LGZG inhibits Gs/cAMP/PKA signaling and ?-arrestin/GRK-mediated desensitization and internalization of ?1-AR, potentially exerting cardioprotective effects through the synergistic regulation of the ?1-AR/Gs/GRKs/?-arrestin signaling deflection system via multiple pathways.
Animals ; Heart Failure/genetics* ; Signal Transduction/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Male ; G-Protein-Coupled Receptor Kinases/genetics* ; Mice, Inbred C57BL ; Humans ; Isoproterenol ; Arrestins/genetics* ; Chronic Disease

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To explore the potential causal relationship between childhood obesity and the risk of inflammatory bowel disease(IBD)based on Mendel randomization(MR).Methods The genome-wide association study(GWAS)data for childhood obesity included 5 530 cases and 8 318 controls.The GWAS data for IBD included 5 673 cases and 213 119 controls.The GWAS data for ulcerative colitis included 4 320 cases and 210 300 controls.The GWAS data of Crohn's disease included 2 056 cases and 210 300 controls.The risk association between obesity and the occurrence of IBD was analyzed using the inverse variance weighted meth-od(IVW),general model,weighted model,weighted median,and MR-Egger.Results Fourteen independent single nucleotide polymorphisms(SNP)significantly associated with childhood obesity were screened out as instrumental variables.IVW analysis results showed that no potential causal association was found between childhood obesity and IBD(OR=1.048,95%CI:0.976-1.125),ulcerative colitis(OR=1.026,95%CI:0.946-1.113),and Crohn's disease(OR=1.123,95%CI:0.993-1.269,P>0.05).Conclusion There was no causal relationship between childhood obesity and the risk of IBD.

Objective To explore the relationship between platelet-to-leukocyte ratio(PLR)and neutro-phil-to-lymphocyte ratio(NLR)and fibrinogen(Fib)levels in the peripheral blood of stroke patients and deep vein thrombosis(DVT)of the lower limbs,as well as their predictive value for wether DVT occurred in stroke patients.Methods A total of 106 stroke patients admitted to the hospital from January 1,2022 to January 30,2024 were retrospectively selected as the research subjects.According to the occurrence of DVT in the pa-tients,they were divided into the DVT group(n=38)and the non-DVT group(n=68),and the levels of PLR,NLR and Fib in the two groups were compared.Multivariate Logistic regression was used to analyze the influencing factors of DVT in stroke patients,and the receiver operating characteristic(ROC)curve was used to analyze the predictive value of PLR,NLR and Fib for DVT in stroke patients.Results The proportions of patients in the DVT group with NIHSS score＞14 points,GCS score＞8 points,and dehydrating drug use time＞5 days were higher than those in the non-DVT group(P＜0.05),and the levels of PLR,NLR and Fib were higher than those in the non-DVT group(P＜0.05).The results of Logistic regression analysis showed that the upregulation of PLR,NLR and Fib levels were all risk factors for DVT in stroke patients(P＜0.05).ROC curve analysis showed that the area under the curve(AUC)of the combined prediction of DVT in stroke patients by PLR,NLR and Fib was 0.890,with a sensitivity of 81.62％and a specificity of 88.78％.The com-bined detection AUC was higher than that predicted separately by PLR,NLR and Fib(Z=2.768,3.424,3.657,all P＜0.05).Conclusion Peripheral blood PLR,NLR and Fib levels are closely related to the occur-rence of DVT in stroke patients.]The combined application of PLR,NLR and Fib has a high predictive value in the occurrence of DVT in stroke patients and can be used as an effective biomarker to predict DVT occur-rence.