This paper summarizes Professor LIU Shangyi's clinical experience in treating acute mastitis based on the "membrane collaterals" theory. It is considered that constraint and stagnation of the membrane collaterrals is the primary pathogenic factor， with damp， heat， phlegm， and stasis being the secondary manifestations. If untreated， the condition can progress to heat toxin injuring the membrane. In treatment， the emphasis is diffusing and unblocking membrane collaterals， unblocking breast and relieving constraint. The clinical course of the disease can be divided into three stages including the early stage with mild constraint heat， the middle stage with escalating toxic heat， and the later stage with a decline of pathogens but deficiency of healthy qi. In correspondence， self-made Tongru Formula （通乳方） for diffusing membrane and venting constraint， self-made Toumo Jiedu Formula （透膜解毒方） for unblocking membrane and relieving toxin， and Tuoli Xiaodu Powder （托里消毒散） with modifications for restoring membrane and rectifying healthy qi should be used， respectively.

Despite of the widespread use of hydrogen and methane breath test, the variability in testing protocols, gas measurement techniques, and interpretation criteria continues to challenge the reproducibility and comparability across centers, especially in the Asia-Pacific region. The Asian Neurogastroenterology and Motility Association hence presents the first Asian monograph guiding application and interpretation of breath test. The monograph was formulated according to the framework of indications, preparatory process, performance, and interpretation of results, as well as future direction for research.

Purpose To investigate the clinical significance of Gasdermin B(GSDMB)in ovarian cancer and its relationship with immune infiltration,aiming to explore novel biomarkers for immunotherapy.Methods Gene expres-sion matrix,somatic mutations,somatic copy number alterations(SCNA),and clinical data were obtained from the The Cancer Genome Atlas(TCGA)database.Copy number variation(CNV)analysis was performed using the GISTIC algorithm,and the CIBERSORT algorithm was applied to quantify the relative abundance of 22 immune cell types in the tumor microenvironment.Protein-protein interaction(PPI)network analysis was conducted to identify GSDMB-associ-ated interacting proteins.Additionally,multiplex immunofluorescence was used to verify the spatial distribution differ-ences of GSDMB protein in clinical ovarian cancer samples with different immune phenotypes and its interaction with immune cells.Results The expression level of the GSDMB gene was significantly higher in adjacent non-cancerous tissues than in tumor tissues(P＜0.001).Patients with high GSDMB expression exhibited elevated levels of immune chemokines(such as CXCL9 and CXCL10,P＜0.01)and tumor-killing lymphocytes(the proportion of CD8+T cell was significantly higher in the high-expression group than in the low-expression group,P＜0.001).CNV analysis re-vealed that GSDMB copy number alterations significantly influenced immune cell infiltration:patients with GSDMB cop-y number amplification had decreased infiltration levels of CD4+T cells and dendritic cells(P＜0.05),while those with deep deletion of GSDMB had significantly reduced infiltration levels of CD8+T cells and neutrophils(P＜0.01).PPI network analysis indicated that GSDMB might interact with key immune molecules,including IL-37,IL-18BP,IL-33,and IL-2(Pearson correlation coefficient r＞0.6,P＜0.001).Multiplex immunofluorescence analysis demonstra-ted that tumors with high GSDMB expression were more likely to exhibit an immune-inflamed phenotype(52.6％),while tumors in the low-expression group were predominantly immune-desert type(47.3％).Immunotherapy cohort a-nalysis suggested that GSDMB could serve as a potential predictive biomarker for immunotherapy responsiveness,with high predictive efficacy in multiple immune checkpoint inhibitor therapy cohorts targeting PD-1,PD-L1,and CTLA4(AUC＞0.8).Conclusion GSDMB plays a crucial role in reshaping the tumor microenvironment in ovarian cancer and may serve as a novel sensitizing target for immunotherapy.

With the establishment of bio-psycho-social medical model,both social and psychological factors play an important role in the occurrence,development and treatment of diseases.Hypertension is a common chronic multiple disease in China,and patients are often complicated with depression and other e-motional disorders.The interaction between hypertension and depression significantly increases the risk of poor prognosis.Current studies have shown a bidirectional promoting relationship between hypertension and depression,and they have some com-mon pathogenesis.However,the specific mechanism of their co-morbidity has not been fully elucidated.Renin-angiotensin sys-tem(RAS)plays an important role in the regulation of hyperten-sion and depression and other emotions.It is composed of two antagonistic pathways.The balance is maintained by angioten-sin-converting enzyme 2(ACE2).Therefore,this article reviews the relationship and mechanism of RAS in hypertension,depres-sion and comorbid states,in order to provide new treatment ide-as for hypertension and depression.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Aim To investigate the changes in hepatic lactylation during liver regeneration and its impact on regeneration.Methods A partial hepatectomy(PHx)mouse model was used to study liver regenera-tion.Sodium oxamate was administered intraperitoneal-ly to inhibit lactate dehydrogenase,and blood and liver tissues were collected at different time points post-sur-gery.The histopathological status was observed using HE staining.Proliferating cell nuclear antigen(PC-NA)levels were detected by immunohistochemistry.Lactylation was assessed using immunofluorescence.Liver LDH enzyme activity,lactate levels and serum alanine aminotransferase(ALT)and aspartate trans-aminase(AST)levels were measured using assay kits.Results After PHx,the liver volume of mice gradual-ly increased,returning to preoperative size on day 7.PCNA levels peaked at 48 hours post-surgery.Liver tissue lactate levels increased to approximately 1.5 times the preoperative level at 12 hours post-surgery and remained elevated until day 7.The lactylation lev-el in hepatocytes peaked at 24 hours post-surgery,gradually declined after 48 hours,and returned to pre-operative levels on day 7.Compared to the PHx group,the sodium oxamate(750 mg·kg-1)+PHx group showed significantly reduced lactylation levels in hepa-tocytes and a smaller liver regeneration volume on day 7.Conclusion Lactylation regulates hepatocyte pro-liferation and promotes liver regeneration after PHx.

Purpose To investigate the clinical significance of Gasdermin B(GSDMB)in ovarian cancer and its relationship with immune infiltration,aiming to explore novel biomarkers for immunotherapy.Methods Gene expres-sion matrix,somatic mutations,somatic copy number alterations(SCNA),and clinical data were obtained from the The Cancer Genome Atlas(TCGA)database.Copy number variation(CNV)analysis was performed using the GISTIC algorithm,and the CIBERSORT algorithm was applied to quantify the relative abundance of 22 immune cell types in the tumor microenvironment.Protein-protein interaction(PPI)network analysis was conducted to identify GSDMB-associ-ated interacting proteins.Additionally,multiplex immunofluorescence was used to verify the spatial distribution differ-ences of GSDMB protein in clinical ovarian cancer samples with different immune phenotypes and its interaction with immune cells.Results The expression level of the GSDMB gene was significantly higher in adjacent non-cancerous tissues than in tumor tissues(P＜0.001).Patients with high GSDMB expression exhibited elevated levels of immune chemokines(such as CXCL9 and CXCL10,P＜0.01)and tumor-killing lymphocytes(the proportion of CD8+T cell was significantly higher in the high-expression group than in the low-expression group,P＜0.001).CNV analysis re-vealed that GSDMB copy number alterations significantly influenced immune cell infiltration:patients with GSDMB cop-y number amplification had decreased infiltration levels of CD4+T cells and dendritic cells(P＜0.05),while those with deep deletion of GSDMB had significantly reduced infiltration levels of CD8+T cells and neutrophils(P＜0.01).PPI network analysis indicated that GSDMB might interact with key immune molecules,including IL-37,IL-18BP,IL-33,and IL-2(Pearson correlation coefficient r＞0.6,P＜0.001).Multiplex immunofluorescence analysis demonstra-ted that tumors with high GSDMB expression were more likely to exhibit an immune-inflamed phenotype(52.6％),while tumors in the low-expression group were predominantly immune-desert type(47.3％).Immunotherapy cohort a-nalysis suggested that GSDMB could serve as a potential predictive biomarker for immunotherapy responsiveness,with high predictive efficacy in multiple immune checkpoint inhibitor therapy cohorts targeting PD-1,PD-L1,and CTLA4(AUC＞0.8).Conclusion GSDMB plays a crucial role in reshaping the tumor microenvironment in ovarian cancer and may serve as a novel sensitizing target for immunotherapy.

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

Extensive studies have identified potential adverse effects on semen quality of obesity, based on body mass index, but the association between body fat distribution, a more relevant indicator for obesity, and semen quality remains less clear. We conducted a longitudinal study of 4304 sperm donors from the Guangdong Provincial Human Sperm Bank (Guangzhou, China) during 2017-2021. A body composition analyzer was used to measure total and local body fat percentage for each participant. Generalized estimating equations were employed to assess the association between body fat percentage and sperm count, motility, and morphology. We estimated that each 10% increase in total body fat percentage (estimated change [95% confidence interval, 95% CI]) was significantly associated with a 0.18 × 10 6 (0.09 × 10 6 -0.27 × 10 6 ) ml and 12.21 × 10 6 (4.52 × 10 6 -19.91 × 10 6 ) reduction in semen volume and total sperm count, respectively. Categorical analyses and exposure-response curves showed that the association of body fat distribution with semen volume and total sperm count was stronger at higher body fat percentages. In addition, the association still held among normal weight and overweight participants. We observed similar associations for upper limb, trunk, and lower limb body fact distributions. In conclusion, we found that a higher body fat distribution was significantly associated with lower semen quality (especially semen volume) even in men with a normal weight. These findings provide useful clues in exploring body fat as a risk factor for semen quality decline and add to evidence for improving semen quality for those who are expected to conceive.
Humans ; Male ; Adult ; Semen Analysis ; China ; Body Fat Distribution ; Longitudinal Studies ; Sperm Count ; Sperm Motility ; Body Mass Index ; Tissue Donors ; Obesity/complications* ; Spermatozoa ; Young Adult ; Middle Aged ; East Asian People

OBJECTIVE: Observational studies have found associations between inflammatory bowel disease (IBD) and the risk of dementia, including Alzheimer's dementia (AD) and vascular dementia (VD); however, these findings are inconsistent. It remains unclear whether these associations are causal. METHODS: We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia. Mendelian randomization (MR) analysis based on summary genome-wide association studies (GWASs) was performed. Genetic correlation and Bayesian co-localization analyses were used to provide robust genetic evidence. RESULTS: Ten observational studies involving 80,565,688 participants were included in this meta-analysis. IBD was significantly associated with dementia (risk ratio [ RR] =1.36, 95% CI = 1.04-1.78; I ² = 84.8%) and VD ( RR = 2.60, 95% CI = 1.18-5.70; only one study), but not with AD ( RR = 2.00, 95% CI = 0.96-4.13; I ² = 99.8%). MR analyses did not supported significant causal associations of IBD with dementia (dementia: odds ratio [ OR] = 1.01, 95% CI = 0.98-1.03; AD: OR = 0.98, 95% CI = 0.95-1.01; VD: OR = 1.02, 95% CI = 0.97-1.07). In addition, genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia. CONCLUSION Our study did not provide genetic evidence for a causal association between IBD and dementia risk. The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
Humans ; Mendelian Randomization Analysis ; Inflammatory Bowel Diseases/complications* ; Dementia/etiology* ; Observational Studies as Topic ; Genome-Wide Association Study