Background/Aims: Acetyl coenzyme A (acetyl-CoA) is one of the most essential metabolites in cell metabolism but its function and concentration in hepatocellular carcinoma (HCC) remain elusive and controversial. Methods: A comprehensive analysis of acetyl-CoA levels and acetyl-CoA synthetase 2 (ACSS2) expression across a range of samples, including patient specimens from both hepatitis B virus (HBV) positive and HBV negative HCC individuals, HBV-transgenic mouse HCC models, and multiple cell lines. Furthermore, to evaluate the functional significance of ACSS2 in HBV-related HCC, we implemented both genetic and pharmacological inhibition strategies targeting ACSS2. Molecular mechanism and mitophagy assessment were revealed by cleavage under target and tagmentation sequencing, RNA sequencing, bioinformatic analyses, transmission electron microscopy and JC-1 staining. Results: Our study revealed a distinct metabolic signature of HBV-related HCC, marked by elevated acetyl-CoA, which was driven by ACSS2. ACSS2 was upregulated by the carbohydrate response element-binding protein in HBV-related HCC. Furthermore, ACSS2 improved tumor cell proliferation, an effect that was dependent on its enzymatic activity. Mechanistically, ACSS2-induced acetyl-CoA accumulation activated voltage-dependent anion channels 1 transcription through increased H3K27ac occupancy, which subsequently promoted mitophagy and HBV-related HCC tumorigenesis. Notably, targeting ACSS2 by depletion or inhibition with a catalytic inhibitor significantly suppressed tumor growth. Conclusions These findings not only illustrate the interplay between metabolic reprogramming, epigenetic modification, and tumorigenesis in the context of HBV infection, but also highlight ACSS2 as a novel metabolic vulnerability in HBV-related HCC. Therefore, targeting ACSS2 could be a novel strategy against HBV-related HCC.

BACKGROUND:Neuregulin 1 has been shown to be characterized in cell proliferation,differentiation,and vascular growth.Human amniotic mesenchymal stem cells are important seed cells in the field of tissue engineering,and have been shown to be involved in tissue repair and regeneration. OBJECTIVE:To construct human amniotic mesenchymal stem cells overexpressing neuregulin 1 and investigate their proliferation and migration abilities,as well as their effects on wound healing. METHODS:(1)Human amniotic mesenchymal stem cells were in vitro isolated and cultured and identified.(2)A lentivirus overexpressing neuregulin 1 was constructed.Human amniotic mesenchymal stem cells were divided into empty group,neuregulin 1 group,and control group,and transfected with empty lentivirus and lentivirus overexpressing neuregulin 1,or not transfected,respectively.(3)Edu assay was used to detect the proliferation ability of the cells of each group,and Transwell assay was used to detect the migration ability of the cells.(4)The C57 BL/6 mouse trauma models were constructed and randomly divided into control group,empty group,neuregulin 1 group,with 8 mice in each group.Human amniotic mesenchymal stem cells transfected with empty lentivirus or lentivirus overexpressing neuregulin-1 were uniformly injected with 1 mL at multiple local wound sites.The control group was injected with an equal amount of saline.(5)The healing of the trauma was observed at 1,7,and 14 days after model establishment.Histological changes of the healing of the trauma were observed by hematoxylin-eosin staining.The expression of CD31 on the trauma was observed by immunohistochemistry. RESULTS AND CONCLUSION:(1)Human amniotic mesenchymal stem cells overexpressing neuregulin-1 were successfully constructed.The mRNA and protein expression of intracellular neuregulin 1 was significantly up-regulated compared with the empty group(P<0.05).(2)The overexpression of neuregulin 1 promoted the migratory ability(P<0.01)and proliferative ability of human amniotic mesenchymal stem cells(P<0.05).(3)Human amniotic mesenchymal stem cells overexpressing neuregulin 1 promoted wound healing in mice(P<0.05)and wound angiogenesis(P<0.05).The results showed that overexpression of neuregulin 1 resulted in an increase in the proliferative and migratory capacities of human amniotic mesenchymal stem cells,significantly promoting wound healing and angiogenesis.

ObjectiveTo investigate the effect of Qingrun prescription（QRP）-containing serum on improving insulin resistance in HepG2 cells and its potential mechanisms. MethodsAn insulin resistance model was established in HepG2 cells with 1×10^-6 mol·L^-1 insulin. Branched-chain α-keto acid dehydrogenase （BCKDH） gene silencing was achieved using siRNA， and the cells were divided into 8 groups： normal group， model group （1×10^-6 mol·L^-1 insulin）， metformin group （1 mmol·L^-1 metformin）， high-， medium-， and low-dose QRP groups （20%， 10%， and 5% QRP-containing serum， respectively）， QRP + siRNA-silenced BCKDH （si-BCKDH） group （10% QRP-containing serum + si-BCKDH）， and QRP + si-NC group （10% QRP-containing serum + si-NC）. Glucose levels in the supernatant were measured with a glucose assay kit， while glycogen content was assessed using a glycogen assay kit. Levels of branched-chain amino acids （BCAAs） and branched-chain keto acids （BCKAs） were determined using ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS）. mRNA transcription and protein expression levels of BCKDH， dishevelled， Egl-10， and pleckstrin （DEP） domain-containing mammalian target of rapamycin （mTOR）-interacting protein （DEPTOR）， mTOR， and ribosomal protein S6 kinase 1 （S6K1） were detected using real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot. ResultsCompared to the normal group， the model group exhibited significantly decreased glucose consumption and glycogen content， increased levels of BCAAs and BCKAs， downregulated expression of BCKDH and DEPTOR， and upregulated mTOR and S6K1 expression （P<0.01）. In comparison to the model group， QRP treatment at all doses significantly enhanced glucose consumption and glycogen content while reducing BCAAs and BCKAs levels （P<0.01）. The high- and medium-dose QRP groups demonstrated significant upregulation of BCKDH mRNA transcription and protein expression， as well as DEPTOR mRNA transcription. Moreover， the DEPTOR protein expression level was significantly increased in high-， medium-， and low-dose QRP groups， while mTOR and S6K1 mRNA and protein expression levels were markedly downregulated （P<0.05， P<0.01）. Compared to the QRP + si-NC group， the QRP + si-BCKDH group exhibited increased BCAAs and BCKAs levels， significantly decreased BCKDH mRNA transcription and protein expression， downregulated DEPTOR mRNA and protein expression， and upregulated mTOR and S6K1 mRNA and protein expression （P<0.05， P<0.01）. ConclusionQRP may improve insulin resistance by reprogramming BCAAs metabolism. This effect involves upregulating BCKDH， reducing BCAAs and BCKAs levels， and suppressing the mTOR pathway activation.

Sufficient keratinized mucosa is important for ensuring the long-term stability and aesthetics of dental implants.How to ef-fectively augment the soft tissue volume at sites with insufficient keratinized mucosa width(KMW)has gradually become a hot research topic for current scholars.Apically positioned flap(APF)with free gingival graft(FGG)is recognized as the approach of choice for peri-implant keratinized mucosal augmentation,but the postoperative shrinkage and its influencing factors are not completely clear.The objective of this review is to explain the significance of keratinized mucosa to peri-implant tissue health,analyze the relevant factors af-fecting postoperative contraction of free gingival grafts,and finally propose a risk factor assessment table for postoperative shrinkage of FGG,with the aim of providing clinicians with a scientific and effective strategy for peri-implant soft tissue management.

Objective:To investigate the effect of the transfer of blastocysts that have not re-expanded after 2-4 h of thawing on pregnancy and neonatal outcomes.Methods:A retrospective cohort study was performed to analyze the clinical data from 2 428 vitrified frozen-thawed single blastocyst transfer cycles at the Reproductive Medicine Center of the 901st Hospital of the Joint Logistics Support Force of PLA between January 2015 and March 2024. Based on the re-expansion status of the blastocoel cavity after thawing, the cycles were divided into group A (110 non-re-expanded) and group B (2 318 re-expanded). After propensity score matching, there were 109 cycles in each group. Pregnancy and neonatal outcomes between the two groups were compared.Results:Before propensity score matching, there were statistical differences in percentage of good-quality blastocyst transfer, percentage of degree 4 blastocyst, percentage of endometriosis and others in reasons for infertility between the two groups (all P<0.05). After propensity score matching, there were no statistical differences in baseline characteristics between the two groups (all P>0.05). The clinical pregnancy rate [27.52% (30/109)], the ongoing pregnancy rate [21.10% (23/109)] and the live birth rate [19.27% (21/109)] in group A were all significantly lower than those in group B [61.47% (67/109), 51.38% (56/109), 47.70% (52/109), all P<0.001]. Neonatal outcomes showed no statistically significant differences between the two groups in terms of birth weight, neonatal length, malformation rate, monozygotic twin rate and male neonatal rate (all P>0.05). Conclusion:Transfer of non-re-expanded blastocysts after thawing may reduce clinical pregnancy rate but does not negatively affect neonatal outcomes.

OBJECTIVE To study the characteristics,micro-traits and microscopic characteristics of Peucedani radix and seven kinds of its common varieties and summarize the key identification characteristics so as to provide a reference for the effective identifica-tion of Peucedani radix and its common varieties.METHODS The key identification features and high-definition images of Peucedani radix and its common varieties were obtained by using the identification methods of traits,microtraits and microscopy,combined with the techniques of depth-of-field extended imaging and image stitching,and some of the features were digitally extracted and statistical-ly analyzed by SPSS26.0 software.RESULTS The high-definition color image data of Peucedani radix and its common varieties were obtained.Its specific identification features were:root head length and annular sparseness,skin pore shape and area,root texture,and fracture surface oil spot density,etc.under the property identification;the diameter and number of oil chambers,the number of cathe-ters,the presence or absence of bast fibers and wood fibers,etc.under the microscopic identification.The results of statistical analysis showed that there were significant differences in skin pore area,oil chamber diameter and density,and conduit density among different varieties of Peucedani radix(P<0.01).CONCLUSION Micro-traits and microidentification methods can be comprehensively ap-plied to distinguish Peucedani radix and its common varieties.In particular,the microscopic features of polarized light holographic col-or images in cross section have significant distinguishing significance,and some of the features are digitally extracted and statistically analyzed,which makes up for the shortcomings of subjective factors in the traditional empirical identification research,and provides a reference for the circulation,testing,clinical medication,and standard drafting of Peucedani radix.

Objective To quantify the intraretinal fluid(IRF)volume in patients with diabetic macular edema(DME)using a deep learning-based three-dimensional segmentation model and to investigate the relationship of IRF volume with visual function and retinal biomarkers based on optical coherence tomography(OCT).Methods A total of 37 pa-tients(42 eyes)with DME who received treatment in the Ophthalmology Department of Sichuan Provincial People's Hospi-tal from July 2022 to September 2024 were prospectively included in this study.A three-dimensional segmentation model was used to automatically quantify the IRF volume within a 6 mm × 6 mm OCT scan at baseline and at the last follow-up.The correlation of visual acuity with IRF volume,central subfield thickness(CST),disorganization of the retinal inner lay-ers(DRIL),hyperreflective foci(HRF),external limiting membrane(ELM),ellipsoid zone(EZ),and vitreomacular in-terface abnormality(VMIA)was analyzed at baseline and the last follow-up.Additionally,the correlation of IRF volume with CST,DRIL,HRF,ELM,EZ,and VMIA was analyzed at both time points.Furthermore,the correlation of the visual acuity at the last follow-up with the IRF volume,CST,DRIL,HRF,ELM,EZ,and VMIA at baseline was analyzed.Results Compared with the baseline value,patients exhibited a significant increase in the best corrected visual acuity(BCVA)(logMAR),a significant decrease in the IRF volume and CST,a significant reduction in the HRF,a significant re-covery in the DRIL,ELM,and EZ(all P＜0.05),and no significant changes in the VMIA(P=1.000)at the last follow-up.At baseline,the BCVA was negatively correlated with the IRF volume,CST,DRIL,and HRF,but positively correlated with the ELM and EZ(all P＜0.05);there was no correlation between the BCVA and VMIA(P=0.069).At the last follow-up,the BCVA was negatively correlated with the DRIL,HRF,and VMIA,but positively correlated with the ELM and EZ(all P＜0.01);the BCVA did not correlate with the IRF volume and CST(P=0.419 and 0.994).At baseline,the IRF volume was positively correlated with the CST(P＜0.001)but negatively correlated with the ELM and EZ(P＜0.01);the IRF vol-ume did not correlate with the DRIL,HRF,and VMIA(all P＞0.05).At the last follow-up,the IRF volume was positively correlated with the CST and HRF(all P＜0.01);however,it was not correlated with the DRIL,ELM,EZ,and VMIA(all P＞0.05).The BCVA at the last follow-up was positively correlated with the BCVA,ELM,and EZ at baseline,but negative-ly correlated with the IRF volume,CST,DRIL,HRF,and VMIA at baseline(all P＜0.05).Conclusion The baseline IRF volume in DME patients is an important influencing factor of visual acuity at baseline and the last follow-up.Hence,the IRF volume may serve as a potential biomarker in the management of DME.

This paper focuses on the application of health big data in cancer screening. Firstly, the sources and characteristics of health big data are introduced, then the commonly used epidemiological designs and analytical techniques in hospital-based cancer screening studies are summarized and the application scenarios of such studies are described. Finally, the challenges and future development in the application of health big data are analyzed to provide reference for the future studies.

Osteoporosis is a systemic metabolic disease characterized by decreased bone mass, leading to an increased risk of fractures. Although osteoporosis in children and adolescents is rare, its incidence in younger populations is showing an increasingly notable trend. The diagnostic criteria for osteoporosis in children and adolescents include a bone mineral density(BMD) Z-score of≤-2.0 accompanied by a significant fracture history, defined as two or more long bone fractures before the age of 10, three or more long bone fractures before the age of 19, or the presence of low-energy vertebral compression fractures even in the absence of low BMD. The genetic causes and underlying mechanisms of pediatric osteoporosis remain largely unknown, requiring further research to elucidate the molecular pathways involved. Such advances could help reduce the disease′s impact on growth and development and improve the quality of life in affected children and adolescents.

Objective:To develop a multi-parameter diagnostic model for pediatric McCune-Albright syndrome(MAS) using machine learning techniques based on laboratory data from MAS patients, with the goal of providing a rapid and reliable auxiliary diagnostic tool for clinical practice.Methods:In this retrospective study, 232 children diagnosed with MAS at the Department of Pediatrics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from March 2023 to November 2024 were enrolled as the positive group. After removing duplicate or missing data, 119 cases were finally selected for statistical analysis as the positive group. Meanwhile, 113 children with normal physical examinations during the same period were selected as the control group. The clinical manifestations of the classic " triad" in the positive group were documented. Fasting serum samples were obtained from both groups at 8: 00 AM for laboratory testing, including bone metabolism-related and hormone-related indicators, which served as candidate features. Baseline descriptive analysis was conducted on the hormone-related indicators. For the bone metabolism indicators, six machine learning models—support vector machine(SVM), XGBoost, decision tree, random forest, Logistic regression, and K-nearest neighbor(KNN)—were constructed using R software. XGBoost subgroup analysis was performed based on the triad symptoms. The contribution of individual features to model predictions was visualized using SHAP diagrams. Results:SHAP visualization indicated that age, serum phosphorus, osteocalcin, and β-C-terminal cross-linked telopeptide of type Ⅰ collagen had the greatest average impact on model predictions. Among the six models, the SVM model achieved the highest diagnostic performance, with a sensitivity of 0.742 9, a specificity of 0.909 1, and an area under the curve (AUC) of 0.917.Conclusion:This study demonstrates that machine learning models, based on data from the positive patients and normal controls, can effectively distinguish MAS patients from healthy controls. The diagnostic model developed offers clinicians a valuable tool for early detection of MAS in children, contributing to earlier diagnosis, timely intervention, and improved clinical management.