Autosomal dominant polycystic kidney disease （ADPKD） is a systemic hereditary renal disorder and can affect multiple organs， and congenital hepatic fibrosis is one of the manifestations of liver involvement and is an important complication of ADPKD. Symptomatic management is currently the main treatment method for this disease， and disease-specific drugs such as tolvaptan have limited indications and cannot correct the underlying genetic defect. This article reports a case of ADPKD with congenital hepatic fibrosis， and sirolimus was identified as the individualized treatment regimen based on peripheral blood functional genomic analysis and drug sensitivity prediction platform. The patient achieved significant improvements in symptoms and quality of life after treatment， with a stable kidney volume. This case shows that functional genomics has a potential value in guiding individualized treatment of rare genetic disorders， which provides new treatment ideas and practice paths for similar patients.

OBJECTIVE To provide an experimental basis for quality control， clinical application and development of hepatoprotective drugs derived from Thesium chinense Turcz.METHODS Network pharmacology was adopted to predict and screen potential hepatoprotective constituents and their action targets of T. chinense Turcz. A liver-injured model of transgenic zebrafish Tg （ fabp10a ： dsRed ） with fluorescent-labeled liver was induced by 4 mmol/L isoniazid. The relative liver fluorescence area and relative fluorescence intensity of zebrafish larvae， as well as the levels of aspartate aminotransferase （AST）， alanine aminotransferase （ALT）， glutathione （GSH） and interleukin-6 （IL-6） were taken as indexes to evaluate the hepatoprotective activity of potential active constituents. High-performance liquid chromatography was used to determine the contents of hepatoprotective active constituents in 17 batches of T. chinense Turcz. medicinal materials from different producing areas.RESULTS Four potential hepatoprotective constituents including kaempferol-3- O -glucorhamnoside （KOG）， kaempferol-3，7-di- O -glucoside （KDG）， buddleoside （BUD） and apigenin-5- O -neohesperidoside （AON） were screened out via network pharmacology， and their core targets involved mitogen-activated protein kinase 1， nuclear factor-κB subunit 1， etc. Pharmacodynamic verification results showed that 25 μmol/L KOG， BUD， AON and 50 μmol/L KDG could significantly increase the relative liver fluorescence area and relative fluorescence intensity of liver-injured model larvae （ P ＜0.05）， reduce the levels of AST， ALT and IL-6 （ P ＜0.05）， and elevate the GSH level （ P ＜0.05）. Content determination results indicated that KOG could be detected in all 17 batches of T. chinense Turcz. medicinal materials， with contents ranging from 0.097 0 to 8.082 0 mg/g；KDG， AON and BUD were not detected in partial batches of samples， and their contents in detectable batches were 0.019 3-0.123 2 mg/g， 0.018 4-0.109 1 mg/g and 0.385 1-1.189 3 mg/g， respectively.CONCLUSIONS KOG， KDG， AON and BUD in T.chinense Turcz. may be its potential hepatoprotective active constituents. Among them， KOG can be detected in T.chinense Turcz. medicinal materials from different producing areas with relatively high content， which can be used as the main marker constituent for evaluating the hepatoprotective effect of T.chinense Turcz.

Objective To analyze the cognitive function and sleep quality of the elderly in Shanghai community, and explore the related influencing factors. Methods A stratified cluster random sampling method was used to select 8 community health centers in Shanghai for a questionnaire survey, including 3 677 elderly individuals who completed the “Comprehensive Health Status Survey of Elderly Residents in Shanghai” from September 2023 to November 2023. Basic information of the elderly was collected, including age, gender, education level, smoking, drinking, mahjong playing behavior, and exercise habits. The Pittsburgh sleep quality index (PSQI) was used to assess the sleep quality of the elderly, subjective cognitive decline (SCD) self-assessment questionnaire and Mini-Mental State Examination (MMSE) were used to evaluate cognitive function, while the Hamilton Anxiety Scale (HAMA) and patient health questionnaire-9 (PHQ-9) were used to assess anxiety and depression levels, and the mini nutritional assessment (MNA) was used to evaluate nutritional status. According to the MMSE scores, the elderly were divided into three groups: no cognitive impairment (MMSE ≥ 27), mild cognitive impairment (MMSE 21-26), and moderate to severe cognitive impairment (MMSE ≤ 20). The general data, lifestyle habits, and scale scores of the three groups were compared. Ordered logistic regression was used to analyze the influencing factors of sleep quality. Results There were statistically significant differences in age, gender, waist circumference, body mass index (BMI), education level, pet ownership, smoking, drinking, mahjong playing behavior, exercise habits, and scale scores among the three groups (P＜0.05). Logistic regression analysis showed that age, waist circumference, gender, drinking habits, mahjong playing behavior, and chronic comorbidities are influencing factors for the PSQI grading in the elderly (P＜0.05). The MMSE score (OR＝1.037, P＝0.001), SCD score (OR＝1.123, P＜0.001), HAMA score (OR＝1.183, P＜0.001), PHQ-9 score (OR＝1.249, P＜0.001) are positive influencing factors for PSQI grading, while the MNA score is a negative influencing factor (OR＝0.960, P＝0.037). Conclusions Advanced age, female gender, low education level, no pet ownership, no mahjong playing behavior, no exercise habits, and poor sleep quality are risk factors for cognitive impairment in the elderly. Advanced age, female gender, no mahjong playing behavior and poor nutritional status are influencing factors for poor sleep quality in the elderly, and severe comorbidities, anxiety, depression, and subjective decline in cognitive function all affect sleep quality.

Crigler-Najjar syndrome(CNS)is an autosomal recessive genetic disorder caused by mutations in the UGT1A1 gene.This author retrospectively analyzes the clinical data of one patient presenting with postnatal hyperbilirubinemia,who was genetically diagnosed with CNS.Her clinical course,genetic characteristics,diagnostic and therapeutic approaches are discussed to enhance clinicians'understanding of this condition.The patient exhibited recurrent jaundice due to elevated unconjugated bilirubin(UCB)levels since birth.During this period,the gallstones were identified and surgically removed,yet her bilirubin levels did not improve.In March 2024,the patient presented to our hospital and underwent genetic testing via a third-party facility.The results revealed two risk variants in the UGT1A1 gene.After one week of oral phenobarbital administration,her UCB levels decreased by approximately 47%,confirming a diagnosis of CNS type Ⅱ.The patient is currently under active follow-up with regular monitoring of bilirubin levels.For the infants and children presenting with persistent,fluctuating,non-hemolytic,and non-hepatitic hyperbilirubinemia since birth,early genetic testing should be prioritized to establish the definitive diagnosis.

Objectives:To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods:Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation.Results:A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions:The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.Objectives To evaluate the predictive value of Tabular Prior-data Fitted Network(TabPFN) for short-term outcome in patients with spontaneous intracerebral hemorrhage (sICH), and compared with the Extreme Gradient Boosting (XGboost) model and traditional logistic regression (LR) model. Methods Patients with sICH admitted to the Department of Neurology, Hefei Second People's Hospital from January 2018 to March 2024 were included retrospectively. The demographic and baseline data were collected. At 3 months after onset, the modified Rankin Scale score was used to determine the outcome, 0-2 was defined as good outcome and >2 was defined as poor outcome. All enrolled patients were randomly divided into a training set and a testing set at a ratio of 7:3. Feature selection was performed using recursive feature elimination (RFE) method, and then the selected feature variables were included into TabPFN, XGboost, and LR models for training and testing. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the models. Shapley additive explanations (SHAP) method was used for model interpretation. Results A total of 547 patients with sICH were enrolled, including 367 males (67.1%), with a median age of 65 (interquartile range, 54-76) years. Two hundred twenty-six patients (41.3%) had poor outcome. Age, baseline blood pressure (systolic blood pressure, diastolic blood pressure), baseline laboratory tests (white blood cell count, red blood cell count, platelet count, neutrophil count, hemoglobin, fasting blood glucose, creatinine, uric acid, urea nitrogen, alanine aminotransferase, aspartate aminotransferase), hematoma rupture into the ventricle, island sign, baseline hematoma volume, and baseline National Institutes of Health Stroke Scale (NIHSS) score were selected as characteristic variables using RFE method. ROC curve analysis showed that the ROC AUC for TabPFN, Xgboost, and LR models predicting poor short-term outcome in the testing set were 0.918 (95% confidence interval [ CI] 0.870-0.966], 0.883 (95% CI 0.826-0.940), and 0.905 (95% CI 0.854-0.957), respectively. SHAP analysis showed that the top four important variables in the TabPFN model were baseline NIHSS score, baseline hematoma volume, baseline aspartate aminotransferase, and age. Conclusions The TabPFN model is superior to the LR model and the XGBoost model in predicting poor outcome in patients with sICH. In the TabPFN model, baseline NIHSS score, baseline hematoma volume, aspartate aminotransferase, and age are the most important predictors of poor outcome in patients with sICH.

Objective To analyze the current status of outcome measures in randomized controlled trials(RCTs)of acupuncture treatment for vascular dementia(VD)and promote the development of a standardized set of outcome measures.Methods Chinese and English literature databases were searched,including the Chinese Medical Periodical Full-Text Database,the Chinese Biology Medicine disc,China National Knowledge Infrastructure,Wanfang Data,VIP Database,PubMed,Embase,the Cochrane Library,MEDLINE,Web of Science,Chinese Clinical Trials Registry,and the International Traditional Medicine Clinical Trial Registry.Two researchers independently screened RCT literature on acupuncture treatment for VD between January 1,2015 and January 1,2025,risk of bias was assessed using the Cochrane Risk of Bias 2 tool.Extract basic study information,intervention measures,diagnostic criteria for both Chinese and Western medicine,TCM syndromes,and outcome measures.Summarize the indicator domains of RCT studies on acupuncture treatment for VD,and analyze the basic information and outcome measures of the included studies.Results A preliminary search identified 2,898 articles,of which 93 RCTs were ultimately included.These studies involved 84 outcome measures,covering six indicator domains:symptoms/signs(23.81%),traditional Chinese medicine(TCM)syndromes(3.57%),medical checkups(60.71%),quality of life(5.95%),safety assessment(4.76%),and prognosis follow-up(1.19%).A total of 91(97.85%)RCTs reported treatment duration,ranging from 2 to 24 weeks;72(77.42%)RCTs used clinical efficacy as the outcome indicator;11 studies(11.83%)reported safety assessments and adverse events.Conclusion Currently,the RCT study design for acupuncture treatment of VD lacks unified standards and has numerous methodological issues.These include insufficient description of sample size estimation processes,strong reliance on subjective rating scales,ambiguous definitions of primary and secondary outcome measures,incomplete integration of Chinese and Western medical indicators,and insufficient reflection of individualized syndrome differentiation and treatment characteristics.In addition,safety assessments and follow-up mechanisms remain relatively weak.Future research should focus on the essential nature of VD,establish a core set of indicators aligned with the clinical characteristics of traditional Chinese medicine,promote the scientific and standardized development of acupuncture research for VD,and provide more compelling evidence-based support for clinical practice.

Objective:The differentially expressed genes(DEGs)and activated signaling pathways in systemic sclerosis(SSc)were screened by bioinformatics methods,and Chinese medicines for potential treatment of SSc were explored,providing a new theoretical basis for the study of SSc and the screening of potential markers.Methods:The data sets GSE58095,GSE130953,GSE33463 and GSE58613 were selected from GEO database and divided into skin group and peripheral blood group according to the sample source.The DEGs of SSc patients was analyzed by R language,and the Wayne diagram was drawn to take the intersection of the two groups.Metascape was used for GO enrichment analysis and KEGG pathway enrichment analysis,and STRING and Cytoscape were used for protein interaction network analysis to find key pathways and hub genes.The core genes were mapped to the medical on-tology information retrieval platform,and related Chinese medicines for SSc treatment were screened.The effective components of Chi-nese medicines were obtained through TCMSP and HERB databases,and the target letters of active ingredients were obtained through swiss database.The"drug-active ingredient-target"network was constructed by Cytoscape.Results:Total 218 DEGs were identified from the skin group of patients with SSc,and 283 DEGs were screened from peripheral blood of patients with SSc.Among them,there were 7 DEGs co-upregulated in skin and peripheral blood,namely ISG15,LGALS3BP,BST2,C1QB,IFI27,CEACAM1 and FBP1.CAMK2N1 was up-regulated in skin but down-regulated in peripheral blood,ARG1 was down-regulated in skin but up-regulated in pe-ripheral blood.GO and KEGG analysis of SSc DEGs showed that these genes were significantly enriched in inflammatory response,he-moglobin complex,immune receptor activity and extracellular matrix.The results of protein interaction network suggest that more than 10 genes such as COL1A1,CTGF12,IL1B,IFNG and JUN may be potential markers of SSc and core genes of therapeutic targets.The potential Chinese medicines screened for SSc treatment include ginseng,sanguisorba,convolvula,wolfberry,safflower,etc.The main components of these herbs were β-sitosterol,quercetin,kaempferol,stigmasterol,luteolin,sitosterol,Spinasterol,and the target were AKR1B1,AR,CYP1B1,XDH,etc.Conclusion:This study uses bioinformatics to screen out core genes that may be potential markers and therapeutic targets for SSc,which is expected to be a new target for the early diagnosis and mechanism research of SSc.Meanwhile,the mapped Chinese medicine and its effective components can provide ideas for the research and development of Chinese medicine compounds for the treatment of SSc.

Objective:To investigate the effect of concentrated growth factor (CGF) on the biological performance of human dental pulp stem cells (hDPSCs) under oxidative stress status induced by hydrogen peroxide (H 2O 2). Methods:The hDPSCs were isolated by using tissue block separation method from healthy permanent teeth extracted for orthodontic reason. hDPSCs surface markers CD34, CD45, CD90 and CD105 were detected by flow cytometry. Alkaline phosphatase (ALP), alizarin red S (ARS), oil red O staining and colony formation assay were used to identify hDPSCs. After the cell counting kit-8 (CCK-8) detection, the optimal H 2O 2 concentration was used to construct the hDPSCs oxidative stress model. CGF conditioned medium was prepared by repeated freeze-thaw methods. After CCK-8 detection, the optimum CGF concentration was chosen for the subsequent experiments. The hDPSCs were divided into control group, H 2O 2 (only H 2O 2 processing), H 2O 2+CGF group (H 2O 2 processing in combination with the CGF) and CGF group (only CGF processing). Subsequent experiments were performed according to these groups. The oxidative stress model was verified by reactive oxygen species, β-galactosidase staining and Western blotting. The effects of CGF on the proliferation and migration of hDPSCs under oxidative stress status were detected by CCK-8 and cell scratch assay, respectively. ALP activity and ARS staining were used to detect the effect of CGF on the osteogenic differentiation of hDPSCs under oxidative stress status. The mRNA expression levels of odontogenesis related genes were detected by real-time fluorescence quantitative PCR (RT-qPCR), and the expression levels of odontogenesis and osteogenesis related proteins were detected by Western blotting. Results:Isolated hDPSCs showed positive expression of mesenchymal stem cells surface markers of CD90, CD105, and negative expression of hematopoietic stem cells surface markers CD34, CD45. The hDPSCs were proved to have the capacity of osteogenic, adipogenic differentiation and clone formation. The optimal concentration to construct the oxidative stress model was 200 μmol/L H 2O 2. Twenty percent CGF was the optimal concentration for subsequent experiments. Compared with the control group, the expression of aging protein p53 was significantly up-regulated from (0.82±0.12) to (1.19±0.14) in H 2O 2 group ( P<0.05), with deepened β-galactosidase staining and increased fluorescence intensity of reactive oxygen species. The proliferative capacity of cells in H 2O 2+CGF group on day 1, 3, 5 and 7 (0.23±0.01, 0.50±0.02, 1.60±0.07, 1.80±0.21) were all higher than in H 2O 2 group (0.15±0.01, 0.14±0.02, 0.50±0.03, 0.90±0.09) ( P<0.05). Cell healing capacity of cells in H 2O 2+CGF group at 12 h and 24 h [(47±7)%, (58±44)%] also increased compared with the H 2O 2 group [(36±2)%, (44±2)%] ( P<0.05), and similar results in the activity of ALP and the formation of mineralized nodules. On day 28, the mRNA expressions of dentin sialophosphoprotein (0.52±0.16) and dental matrix protein 1 (DMP-1) (0.39±0.13) in H 2O 2 group were all significantly lower than those in H 2O 2+CGF group (0.96±0.24, 0.83±0.30, respectively) and CGF group (1.12±0.18, 1.23±0.19, respectively) ( P<0.05). On day 28, the expressions of odontogenesis related protein DMP-1 (0.27±0.04) and osteogenesis related protein Runt-related transcription factor-2 (0.42±0.15) in H 2O 2 group were all significantly lower than those in H 2O 2+CGF group (0.66±0.18, 0.68±0.04) and CGF group (1.15±0.13, 1.06±0.19, respectively) ( P<0.05). Conclusions:H 2O 2 can induce oxidative stress in hDPSCs, while CGF can promote proliferation, migration, odontogenic and osteogenic differentiation of hDPSCs under oxidative stress status.

Objective:To investigate the molecular mechanisms of bexarotene in treating double hit lymphoma(DHL)based on Weighted Gene Co-expression Network Analysis(WGCNA),thereby providing potential targets and experimental evidence for DHL treatment.Methods:The gene expression datasets GSE44164 and GSE43677 were downloaded from the Gene Expression Omnibus(GEO)database,and differentially expressed genes(DEGs)were identified.WGCNA was employed to identify gene modules associated with DHL.A protein-protein interaction(PPI)network was constructed to screen for key hub genes.Drug-gene association analysis was conducted using the EpiMed platform to identify potential targeted drugs for DHL.The effects of bexarotene on DHL cell proliferation and key protein expression were evaluated using the CCK-8 assay and Western blotting(WB),and its effects on cell apoptosis was evaluated using flow cytometry.Results:WGCNA identified a turquoise module highly associated with DHL,and 10 hub genes(COL1A2,COL3A1,MMP2,COL5A2,DCN,BGN,FN1,MMP9,FBN1,and LUM)were screened from the PPI network.Drug association analysis nominated bexarotene as a potential therapeutic agent.In vitro validation demonstrated that bexarotene significantly inhibited U2932 cell viability(P<0.05),promoted cell apoptosis(P<0.001),and downregulated c-Myc and COL1A2 expression(P<0.05).Conclusion:Bexarotene may exert anti-DHL effects by suppressing the c-Myc signaling pathway and modulating extracellular matrix-related genes.Further studies are warranted to validate its in vivo efficacy and potential for combination therapy.

This study characterized the whole-genome sequences of 45 Coxsackievirus A6(CVA6)strains isolated from Pudong District,Shanghai,during 2015-2023,to elucidate regional genetic evolution and recombination patterns.Viral genomes were ampli-fied and sequenced with Illumina MiSeq platforms,and phylogenetic analysis of the VP1 and 3D regions was conducted via MEGA 11(maximum-likelihood method,bootstrap=1 000).Nucleotide/amino acid homology and variation sites were assessed in DNAstar v7.0,and recombination events were identified with SimPlot v3.5.1 and RDP4.All isolates belonged to the D3a subtype,and exhibited intra-strain nucleotide and amino acid homologies of 88.0%-99.9%and 92.4%-100%,respectively,in contrast to lower homologies to the prototype Gdula strain(78.0%-80.5%nucleotide;94.5%-95.1%amino acid).Thirty-six mutation sites were identified in the VP1 re-gion.Recombination analysis revealed frequent cross-serotype events involving CVA4 and EV-A71,with dominant RF-A(84.5%)and minor RF-K(15.5%)patterns localized in the 3D region.This study elucidated the gene recombination and genetic evolution of CVA6 in Pudong District,Shanghai,thereby providing data support to enhance understanding of the evolutionary trends and genetic characteristics of coxsackieviruses,and offering theoretical evidence for the prevention and control of CVA6.