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.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To identify high-risk factors for healthcare-associated infection(HAI)in patients in inten-sive care units(ICUs),and develop a quick response(QR)code-based APP prediction tool.Methods Information of inpatients in general ICUs of three hospitals in Guizhou Province from January to December 2024 were collected.Risk factors were analyzed with a logistic regression model.QR code-based APP was constructed and validated.Results A total of 1 782 patients in general ICUs of three hospitals in Guizhou Province in 2024 were included in the analysis,out of which 410 were HAI cases,and the incidence of HAI was 23.01％.Multivariate logistic regre-ssion analysis results of HAI in ICU inpatients showed that regional gross domestic product(GDP)≥58 685 Yuan,performing pathogen culture during this hospitalization,history of diabetes mellitus,history of cancer,length of hospital stay ≥7 days before infection,and duration of persistent fever＞5 days before infection were independent risk factors for HAI in ICU patients(all P＜0.05).The discrimination of the model(area under the receiver operating characteristic curve[AUC]of 0.841),calibration(Brier score of 0.129),and clinical effectiveness(net benefit of 11.4％when the risk threshold was 5％-74％)all performed well.Conclusion The QR code-based APP prediction tool is of great significance for scientific research transformation and precise HAI control.

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.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

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.

Objective:To explore the efficacy of non-invasive prenatal testing (NIPT) of fetal free DNA in maternal peripheral blood in fetuses with increased nuchal translucency (NT).Methods:A retrospective analysis was conducted on 1 184 singleton pregnant women that underwent chromosomal microarray analysis (CMA) at Nanjing Drum Tower Hospital, Nanjing University Medical School from June 2014 to December 2022 due to fetal increased NT (≥3.0 mm). These subjects were categorized based on whether the increased NT was accompanied by other high-risk factors into isolated increased NT without advanced maternal age (further subdivided into 3.0 mm≤NT<3.5 mm, 3.5 mm≤NT<4.0 mm, and NT≥4.0 mm subgroups), isolated increased NT with advanced maternal age, increased NT with nasal bone abnormalities, increased NT with other soft markers, and increased NT with structural abnormalities groups. Assuming the sensitivity and specificity of NIPT and expanded NIPT at this center were both 100%, genomic abnormalities outside the detection range of NIPT or expanded NIPT were termed as residual risk of NIPT or expanded NIPT. Chi-square test and Bonferroni correction were used to compare the residual risks of NIPT and expanded NIPT among the three subgroups of isolated increased NT without advanced maternal age group. Results:(1) In the group of isolated increased NT without advanced maternal age: For the 3.0 mm≤NT<3.5 mm subgroup (329 cases), 19 abnormalities were detected by CMA [12 cases of chromosome aneuploidy, seven cases of pathogenic copy number variation (pCNV)], with residual risks of NIPT and expanded NIPT both at 2.1% (7/329). For the 3.5 mm≤NT<4.0 mm subgroup (173 cases), 29 abnormalities were detected by CMA (17 cases of chromosome aneuploidy, nine cases of pCNV, three cases of chromosome unbalanced translocation), with residual risks of NIPT at 8.1% (14/173) and expanded NIPT at 7.5% (13/173). For the NT≥4.0 mm subgroup (270 cases), CMA detected abnormalities in 70 cases (50 cases of chromosome aneuploidy, 16 cases of pCNV, three cases of unbalanced translocations, and one case of sex chromosome abnormality combined with pCNV). The residual risk of NIPT was 12.2% (33/270), and the residual risk of expanded NIPT was 7.0% (19/270). The residual risks of NIPT and expanded NIPT in the 3.0 mm≤NT<3.5 mm subgroup were lower than those in the 3.5 mm≤NT<4.0 mm and NT≥4.0 mm subgroups (Bonferroni correction, all P<0.017). (2) In the group of 92 cases with isolated increased NT and advanced maternal age, CMA detected abnormalities in 36 cases (29 cases of chromosome aneuploidy, five cases of pCNV, one case of trisomy 21 combined with sex chromosome abnormality, and one case of trisomy 18 combined with sex chromosome abnormality). The residual risk of NIPT was 7.6% (7/92), and that of expanded NIPT was 5.4% (5/92). (3) In the group of 49 cases with increased NT combined with nasal bone abnormalities, CMA detected abnormalities in 24 cases (23 cases of chromosome aneuploidy and one case of pCNV). The residual risks of NIPT and expanded NIPT were both 2.0% (1/49). (4) In the group of 26 cases with increased NT combined with other soft markers, CMA detected abnormalities in nine cases (six cases of chromosome aneuploidy, one case of pCNV, and two cases of chromosome unbalanced translocations). The residual risks of NIPT and expanded NIPT were both 11.5% (3/26). (5) In the group of 245 cases with increased NT combined with structural abnormalities, CMA detected abnormalities in 121 cases (107 cases of chromosome aneuploidy, seven cases of pCNV, four cases of chromosome unbalanced translocations, one case of trisomy 21 combined with trisomy 20, and two cases of trisomy 18 combined with sex chromosome abnormalities). The residual risk of NIPT was 16.7% (41/245), and that of expanded NIPT was 4.1% (10/245). Conclusions:For isolated NT≥3.5 mm or NT≥3.0 mm combined with other high-risk factors, chorionic villus sampling in early pregnancy can be recommended, advancing the timing of prenatal diagnosis from the second trimester to the first trimester. For fetuses with isolated 3.0 mm≤NT<3.5 mm, the 2.1% residual risk of chromosomal abnormalities should be fully informed during counseling, even if the risk of NIPT is low.

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.