To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

Objective:To investigate the relationship between 18F-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography(18F-FDG PET/CT)and tumor markers and the prognosis of patients with differentiated thyroid cancer(DTC)treated with surgery combined with iodine-131,and to construct a nomogram prediction model.Methods:The clinical data of 134 patients with DTC who underwent surgery combined with iodine-131 treatment in our hospital from January 2021 to January 2023 were retrospectively analyzed.According to the prognosis after 1 year of treatment,they were divided into a good prognosis group(n=106)and a poor prognosis group(n=28).The general data,18F-FDG PET/CT related parameters[maximum standardized uptake value(SUVmax),metabolic volume(MTV),total lesion gly-colysis(TLG)]and serum tumor markers[thyroglobulin(Tg),thyroglobulin antibody(TgAb)]levels were compared between the two groups.Pearson correlation coefficient was used to analyze the correlation between the related parameters and the tumor marker levels.Logistic multivariate analysis was used to analyze the influencing factors of DTC prognosis.Re-ceiver operating characteristic curve(ROC)was used to analyze the predictive efficacy of related parameters combined with tumor markers on poor prognosis.Anomogram prediction model for poor prognosis was constructed and the predic-tive efficacy of the model was evaluated.Results:The proportion of stage Ⅲ-Ⅳ,the proportion of total resection and the levels of thyroid stimulating hormone(TSH),SUVmax,MTV,TLG,Tg and TgAb in the poor prognosis group were higher than those in the good prognosis group,and the differences were statistically significant(P<0.05).Pearson correlation co-efficient showed that SUVmax,MTV,TLG and Tg,TgAb levels were positively correlated with tumor markers(P<0.05).Lo-gistic analysis showed that after adjusting for confounding variables,SUVmax,MTV,TLG,Tg and TgAb were independent influencing factors for the poor prognosis of DTC(P<0.05).ROC analysis showed that the combination of SUVmax,MTV,TLG,Tg and TgAb was significantly better than each parameter alone in predicting poor prognosis(P<0.05).The nomo-gram prediction model was constructed.ROC evaluation showed that the model had good prediction performance.K-fold cross validation showed that the model had stable performance and good generalization ability.Conclusion:The 18F-FDG PET/CT related parameters SUVmax,MTV,TLG and tumor markers Tg and TgAb are all independent factors affecting the poor prognosis of DTC patients treated with surgery combined with iodine-131.The prognostic nomogram prediction model based on the above factors has good predictive efficacy and can be used to guide clinical decision-making.

In recent years,organs-on-chips(OOCs)technology has gradually matured and been recognized by regulatory agencies,playing a key role in the construction of pathophysiological models,pharmacodynamic screening,toxicological evaluation and other fields,providing guidance for the research and development of innovative drugs of Chinese materia medica and the clinical application of classic prescriptions.This article reviewed the application progress of OOCs technology in the research of Chinese materia medica from four dimensions:pharmacodynamic and toxicological evaluation,quality control,active component analysis and innovative drug research and development,in order to provide a reference for the precise application of this technology in the field of Chinese materia medica.

AIM To investigate the mechanism of Jiedu Yizhi Formula on cognitive function and neuroinflammation in a mouse model of Alzheimer's disease(AD).METHODS 50 APP/PS1 double transgenic mice were randomly divided into the model group,the donepezil group,and the low-dose,moderate-dose,and high-dose Jiedu Yizhi Formula group(1.78,3.56 and 7.12 g/kg),with 10 mice in each group,in contrast to the 10 WT mice of the blank group.Following anesthesia administration and 8-week oral gavage regimen with respective drugs,all mice underwent final tissue sample collection.The mice had their learning and memory ability assessed by Morris water maze and nesting behavior scores;their pathology of brain tissue and Aβ expression observed using HE,Nissl and IHC staining;their polarization of microglia and the expression of inflammatory factors in hippocampal tissue detected by IF and ELISA;their hippocampal expression of PI3K/Akt/mTOR signaling pathway detected by RT-qPCR and Western blot.RESULTS Compared with the blank group,the model group had lower scores in total swimming distance,frequency in crossing the platform,residence time in the target quadrant,and nesting behavior scores(P＜0.05,P＜0.01);prolonged evasion latency(P＜0.01);more disorganized arrangement of pyramidal cells,solidification and deep staining,unclear demarcation,irregular cell shapes,reduction of Nyctinidia,and increased Aβ deposition in the brain tissue(P＜0.01);elevated expression of hippocampal microglia M1-type markers CD16/32 and lba-1(P＜0.01);decreased levels of M2-type marker CD206(P＜0.05);elevated levels of TNF-α and IL-1β(P＜0.01);decreased expressions of IL-13 and IL-4(P＜0.01);and decreased levels of PI3K,Akt and mTOR mRNA,and reduced p-PI3K,p-Akt and p-mTOR protein expressions(P＜0.01).Compared to the model group,the donepezil group and the Jiedu Yizhi Formula groups showed statistically significant improvements in the aforementioned indexes(P＜0.05,P＜0.01),with the magnitude of improvement being higher in the high-dose Jiedu Yizhi Formula group.CONCLUSION Jiedu Yizhi Formula suppresses microglia Ml-type polarization while enhancing M2-type polarization via activation the PI3K/Akt/mTOR signaling pathway,which subsequently reduces inflammatory cytokine secretion.This mechanism attenuates Aβ deposition in brain tissues and ameliorates cognitive dysfunction in AD mouse models.

Objective To construct a diagnostic model for phlegm-dampness syndrome in hypertension based on multimodal feature fusion.Methods Clinical text information(physiological/lifestyle data,symptoms,pulse characteristics)and tongue image data were collected from 261 hypertension patients.For clinical text data,statistical analyses,including ANOVA,Mann-Whitney U test,and Chi-square test,were performed to identify significant features(P<0.05),which were incorporated into a clinical text-based diagnosis model(CTDM)using a multilayer perceptron algorithm.For tongue images,a tongue image-based diagnosis model(TIDM)was constructed based on channel attention mechanisms and residual networks.A multimodal diagnostic model(MDM)was built by fusing clinical text and tongue image features using a feature concatenation method.The diagnostic performance of each model was evaluated using five-fold cross-validation with the area under the receiver operating characteristic curve(AUC),accuracy,specificity,and sensitivity.Results Seven clinical text features,including physiological/lifestyle factors(disease duration,body mass index),symptoms(chest tightness,loss of appetite,excessive phlegm),and pulse characteristics(slippery pulse,damp pulse),were identified as risk factors for phlegm-dampness syndrome in hypertension.The AUC of the CTDM was 0.831±0.021,the AUC of the TIDM was 0.878±0.035,and the MDM achieved an AUC of 0.972±0.015.Conclusion The multimodal diagnostic model that integrates clinical text and tongue image features demonstrates high diagnostic accuracy and provides valuable guidance for AI-assisted diagnosis of phlegm-dampness syndrome in hypertension.

Objective To investigate the influencing factors of antibiotic-associated diarrhea(AAD)following congenital heart disease(CHD)surgery in pediatric patients,develop a nomogram-based predictive model,and validate its efficacy.Methods A retrospective analysis was conducted on the clinical data of pediatric patients who underwent CHD surgery in the Pediatric Intensive Care Unit(PICU)of a tertiary hospital in Guang-dong Province from July 2022 to July 2024.Patients were categorized into an AAD group and a non-AAD group.Univariate and multivariate logistic regression analyses were performed to identify risk factors for AAD occurrence following CHD surgery.A risk prediction model was developed,and a nomogram was constructed.The predictive performance of the model was evaluated using the Receiver Operating Characteristic(ROC)curve to calculate the area under the curve(AUC),the Hosmer-Lemeshow goodness-of-fit test,calibration curves,and clinical decision curve analysis.External validation of the model was conducted using data from patients in the Surgical Intensive Care Unit(SICU).Results The incidence of AAD following CHD surgery was 48.52%(229 out of 472 cases).Risk factors for AAD included the combined use of antibiotics,mechanical ventilation,elevated C-reactive protein levels,prolonged surgical duration,and extended antibiotic usage time(all with OR>1,P<0.05).Conversely,probiotic administration was identified as a protective factor(OR<1,P<0.05).The predictive model demon-strated excellent discrimination,as evidenced by the ROC curve areas:0.922(95%CI:0.894～0.951)in the modeling group,0.886(95%CI:0.838～0.915)in the internal validation group,and 0.862(95%CI:0.784～0.941)in the external validation group.Additionally,the model exhibited satisfactory calibration,as indicated by the Hosmer-Lemeshow test results:χ2=7.96,P=0.538 in the modeling group;χ2=4.24,P=0.895 in the inter-nal validation group;and χ2=9.923,P=0.270 in the external validation group.Furthermore,the model provided significant clinical utility.Conclusions Combined antibiotic use,duration of antibiotic therapy,mechanical ventilation,surgical duration,C-reactive protein(CRP)levels,and probiotic administration are key factors influ-encing the occurrence of AAD.The risk prediction model developed based on these variables demonstrates robust predictive performance and can serve as a valuable reference for the development and implementation of preventive and therapeutic strategies in clinical practice.

Aim To verify the therapeutic effect of the Qushi Huoxue decoction(QSHXF)on a mouse model of non-alcoholic fatty liver disease(NAFLD)using network pharmacology and experimental approaches,to examine the changes in the PI3K-AKT-lipid metabo-lism signaling pathway,and to elucidate its molecular mechanisms.Methods The potential active ingredi-ents and targets of the QSHXF were identified using the TCMSP platform.NAFLD-related genes were sourced from the GeneCards,PharmGkb,TTD,and OMIM data-bases.The intersection of drug targets and NAFLD treatment targets was analyzed to identify the key tar-gets of the QSHXF in treating NAFLD.The STRING database and Cytoscape 3.9.1 software were utilized to construct networks linking traditional Chinese medicine active ingredients to disease targets and PPI networks,allowing for the screening of key active ingredients and core targets.GO and KEGG enrichment analyses of the intersecting targets were conducted using R version 4.2.2.The NAFLD model was established by feeding mice a methionine-choline deficient diet for a duration of five weeks.Following successful modeling,low,me-dium,and high doses of the QSHXF were administered for intervention over a period of six weeks.The efficacy was verified and the underlying mechanisms were ex-plored using methods such as HE staining,Oil Red O staining,and Western blot analysis.Results The net-work pharmacology prediction indicated that QSHXF might effectively treat NAFLD through key components such as quercetin and kaempferol,as well as core tar-gets including STAT3,AKT1,and HIF1A.KEGG en-richment analysis further suggested that QSHXF might exert its therapeutic effects on NAFLD via signaling pathways such as AGE-RAGE and PI3K-AKT.Verifi-cation through animal experiments demonstrated that QSHXF could significantly reduce hepatic steatosis and lipid droplet accumulation in NAFLD mice.Specifical-ly,it markedly decreased serum levels of TC,TG,ALT,AST,and LDL,while increasing HDL levels.Addition-ally,the treatment significantly reduced the protein ex-pression levels of p-PI3K,p-AKT,SREBP-1c,FASN,and ACC1 in the liver.Conclusions QSHXF can sig-nificantly enhance liver function,improve blood lipid levels,and alleviate hepatic steatosis in NAFLD mice,with its mechanism potentially linked to the inhibition of the PI3K-AKT-lipid metabolism signaling pathway.

Objective:To investigate the relationship between 18F-fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography(18F-FDG PET/CT)and tumor markers and the prognosis of patients with differentiated thyroid cancer(DTC)treated with surgery combined with iodine-131,and to construct a nomogram prediction model.Methods:The clinical data of 134 patients with DTC who underwent surgery combined with iodine-131 treatment in our hospital from January 2021 to January 2023 were retrospectively analyzed.According to the prognosis after 1 year of treatment,they were divided into a good prognosis group(n=106)and a poor prognosis group(n=28).The general data,18F-FDG PET/CT related parameters[maximum standardized uptake value(SUVmax),metabolic volume(MTV),total lesion gly-colysis(TLG)]and serum tumor markers[thyroglobulin(Tg),thyroglobulin antibody(TgAb)]levels were compared between the two groups.Pearson correlation coefficient was used to analyze the correlation between the related parameters and the tumor marker levels.Logistic multivariate analysis was used to analyze the influencing factors of DTC prognosis.Re-ceiver operating characteristic curve(ROC)was used to analyze the predictive efficacy of related parameters combined with tumor markers on poor prognosis.Anomogram prediction model for poor prognosis was constructed and the predic-tive efficacy of the model was evaluated.Results:The proportion of stage Ⅲ-Ⅳ,the proportion of total resection and the levels of thyroid stimulating hormone(TSH),SUVmax,MTV,TLG,Tg and TgAb in the poor prognosis group were higher than those in the good prognosis group,and the differences were statistically significant(P<0.05).Pearson correlation co-efficient showed that SUVmax,MTV,TLG and Tg,TgAb levels were positively correlated with tumor markers(P<0.05).Lo-gistic analysis showed that after adjusting for confounding variables,SUVmax,MTV,TLG,Tg and TgAb were independent influencing factors for the poor prognosis of DTC(P<0.05).ROC analysis showed that the combination of SUVmax,MTV,TLG,Tg and TgAb was significantly better than each parameter alone in predicting poor prognosis(P<0.05).The nomo-gram prediction model was constructed.ROC evaluation showed that the model had good prediction performance.K-fold cross validation showed that the model had stable performance and good generalization ability.Conclusion:The 18F-FDG PET/CT related parameters SUVmax,MTV,TLG and tumor markers Tg and TgAb are all independent factors affecting the poor prognosis of DTC patients treated with surgery combined with iodine-131.The prognostic nomogram prediction model based on the above factors has good predictive efficacy and can be used to guide clinical decision-making.

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.

Purpose This study aims to investigate the clinicopathological features of diffuse pulmonary menin-gotheliomatosis(DPM).Methods The clinical data of 10 patients with DPM undergoing video-assisted thoracic sur-gery(VATS)were collected,and their clinical and pathological characteristics were analyzed using immunohistochem-istry.Results The detection rate of DPM was 1.19‰,with 90％of the patients being female.DPM predominantly occurred in the age range of 40-60 years,with an average age at diagnosis of 50.7 years.Most patients had no smok-ing history.Pathological diagnosis combined with imaging findings was the main method for diagnosing DPM.80％of the patients were prone to concurrent early-stage invasive pulmonary adenocarcinoma.Laboratory indicators,including pulmonary function,were generally normal.Chest CT showed diffuse multiple ground-glass opacity or cystic nodules in both lungs,with the number of nodules in both lungs ranging from dozens to hundreds,and the maximum diameter of the nodules was 2-6 mm.The median volume and CT value of the pulmonary nodules were 35.32 mm3 and-566 HU,respectively.Pathological features mainly included multiple meningothelial-like nodules observed under the micro-scope.Immunophenotypically,CD56,EMA,PR,and vimentin were often positive.Conclusion DPM is a rare lung disease with no obvious clinical symptoms,and is more common in middle-aged and elderly women.Diffuse multiple nodules in both lungs are its main imaging features.Most DPM patients are complicated with lung adenocarcinoma,and regular follow-up is recommended.