ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

The development of the rare disease discipline is a crucial pathway for enhancing the diagnosis and treatment of rare diseases, cultivating specialized professionals, and fostering technological innovation. Currently, China' rare disease discipline is accelerating its development driven by both policy and demand. However, it still faces multi-dimensional challenges, including an incomplete clinical management mechanism, a shortage of interdisciplinary talents, a weak scientific research system, and limited outreach capacity. To address these challenges, this paper proposes and constructs an integrated development system with clinical diagnosis and treatment as the foundation, talent cultivation as the engine, scientific research as the support, and disciplinary outreach capacity as the extension. Specific strategies include: enhancing clinical management through artificial intelligence-assisted diagnosis systems and multidisciplinary collaboration platforms; strengthening the talent pool through textbooks, curricula, and hierarchical training mechanisms; bolstering research collaboration and translational outcomes by leveraging international data-sharing platforms, national rare disease medical centers, the State Key Laboratory of Complex Severe and Rare Diseases, and the National Key Scientific Infrastructure for Translational Medicine; and expanding grassroots outreach and public awareness through the National Rare Disease Diagnosis and Treatment Collaboration Network, the National Rare Disease Quality Control Center, and integrated media communication channels. In the future, the rare disease discipline should further deepen the integration of medicine and engineering, expand international cooperation, focus on the translational closed loop, improve the regional collaboration network, so as to build a more resilient and dynamic disciplinary ecosystem, and ultimately achieve a comprehensive improvement in the diagnosis and treatment of rare diseases.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

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*

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.