Hepatocellular carcinoma(HCC)is one of the most prevalent malignancies worldwide,and accurate prognostic assessment and treatment planning are vital for improving patient outcomes.Conventional prognostic models,which rely on limited clinicopathological parameters,often fail to capture the profound heterogeneity of HCC.In recent years,artificial intelligence(AI)-particularly machine learning and deep learning-has driven a paradigm shift in precision oncology by leveraging its powerful capabilities in data mining and pattern recognition.This review provides a comprehensive overview of recent advances in AI for prognostic assessment and treatment optimization in HCC,with an emphasis on key methodologies such as radiomics and multi-modal data integration.It further discusses the clinical potential and challenges of AI in predicting postoperative recurrence,evaluating therapeutic response,and supporting individualized treatment decisions,while also outlining future directions in this rapidly evolving field.The review aims to inform and facilitate the clinical translation of AI technologies into the management of HCC.

Objective To investigate the perioperative management of antithrombotic drugs in patients undergoing non-cardiac surgery.Methods Patients on long-term antithrombotic drugs who underwent non-cardiac surgery in our hospital were included.Through interviews with patients and physicians,perioperative antithrombotic medication regimens were reviewed and compared with the"Multidisciplinary Expert Consensus on Perioperative Management of Antithrombotic Therapy"to evaluate compliance with consensus and analyze influencing factors.Results A total of 372 patients were included in the analysis.Among them,355 patients were on long-term antiplatelet therapy alone,and 17 were on long-term oral anticoagulantion.364(97.8％)discontinued antithrombotic medications prior to surgery.109 patients(29.3％)received low molecular weight heparin(LMWH)bridging therapy.Among the 355 patients on antiplatelet therapy,108(30.4％)had discontinuation durations consistent with the consensus recommendations,while 186(52.4％)discontinued medications for longer periods.Postoperatively,the average hospital stay for antiplatelet therapy patients was 6.64 days,with only 37(10.4％)resuming therapy during hospitalization.The average hospital stay for patients on anticoagulants was 9.94 days,with only 2(11.8％)resuming therapy during hospitalization.Regarding perioperative risk assessment,only 40(10.8％)of patients underwent additional internal medical evaluation for thromboembolic risk after medication discontinuation,with the remainder assessed soly by surgeons.Coronary heart disease was an independent risk factor associated with internal medical evaluation(OR 2.851,95％CI 1.160-7.011,P=0.022).For bleeding risk assessment,surgeons evaluations aligned with the consensus in 68.0％of cases,but surgeons tended to underestimate risk compared to the consensus.Conclusions In this single-center study,perioperative antithrombotic management showed low compliance with expert consensus,characterized by prolonged preoperative medication discontinuation,high rates of LMWH bridging,and low postoperative in-hospital resumption of therapy.A robust multidisciplinary collaboration system should be established to enhance comprehensive patient assessment.

Objective To investigate the perioperative management of antithrombotic drugs in patients undergoing non-cardiac surgery.Methods Patients on long-term antithrombotic drugs who underwent non-cardiac surgery in our hospital were included.Through interviews with patients and physicians,perioperative antithrombotic medication regimens were reviewed and compared with the"Multidisciplinary Expert Consensus on Perioperative Management of Antithrombotic Therapy"to evaluate compliance with consensus and analyze influencing factors.Results A total of 372 patients were included in the analysis.Among them,355 patients were on long-term antiplatelet therapy alone,and 17 were on long-term oral anticoagulantion.364(97.8％)discontinued antithrombotic medications prior to surgery.109 patients(29.3％)received low molecular weight heparin(LMWH)bridging therapy.Among the 355 patients on antiplatelet therapy,108(30.4％)had discontinuation durations consistent with the consensus recommendations,while 186(52.4％)discontinued medications for longer periods.Postoperatively,the average hospital stay for antiplatelet therapy patients was 6.64 days,with only 37(10.4％)resuming therapy during hospitalization.The average hospital stay for patients on anticoagulants was 9.94 days,with only 2(11.8％)resuming therapy during hospitalization.Regarding perioperative risk assessment,only 40(10.8％)of patients underwent additional internal medical evaluation for thromboembolic risk after medication discontinuation,with the remainder assessed soly by surgeons.Coronary heart disease was an independent risk factor associated with internal medical evaluation(OR 2.851,95％CI 1.160-7.011,P=0.022).For bleeding risk assessment,surgeons evaluations aligned with the consensus in 68.0％of cases,but surgeons tended to underestimate risk compared to the consensus.Conclusions In this single-center study,perioperative antithrombotic management showed low compliance with expert consensus,characterized by prolonged preoperative medication discontinuation,high rates of LMWH bridging,and low postoperative in-hospital resumption of therapy.A robust multidisciplinary collaboration system should be established to enhance comprehensive patient assessment.

The relationship between hyperuricemia (HUA) and erectile dysfunction (ED) remains inadequately understood. Given that HUA is often associated with various metabolic disorders, this study aims to explore the multivariate linear impacts of metabolic parameters on erectile function in ED patients with HUA. A cross-sectional analysis was conducted involving 514 ED patients with HUA in the Department of Andrology, Jiangsu Province Hospital of Chinese Medicine (Nanjing, China), aged 18 to 60 years. General demographic information, medical history, and laboratory results were collected to assess metabolic disturbances. Sexual function was evaluated using the 5-item version of the International Index of Erectile Function (IIEF-5) questionnaire. Based on univariate analysis, variables associated with IIEF-5 scores were identified, and the correlations between them were evaluated. The effects of these variables on IIEF-5 scores were further explored by multiple linear regression models. Fasting plasma glucose ( β = -0.628, P < 0.001), uric acid ( β = -0.552, P < 0.001), triglycerides ( β = -0.088, P = 0.047), low-density lipoprotein cholesterol ( β = -0.164, P = 0.027), glycated hemoglobin (HbA1c; β = -0.562, P = 0.012), and smoking history ( β = -0.074, P = 0.037) exhibited significant negative impacts on erectile function. The coefficient of determination ( R ²) for the model was 0.239, and the adjusted R ² was 0.230, indicating overall statistical significance ( F -statistic = 26.52, P < 0.001). Metabolic parameters play a crucial role in the development of ED. Maintaining normal metabolic indices may aid in the prevention and improvement of erectile function in ED patients with HUA.
Humans ; Male ; Erectile Dysfunction/metabolism* ; Hyperuricemia/metabolism* ; Adult ; Middle Aged ; Cross-Sectional Studies ; Glycated Hemoglobin/metabolism* ; Blood Glucose/metabolism* ; Uric Acid/blood* ; Young Adult ; Triglycerides/blood* ; Adolescent ; Cholesterol, LDL/blood* ; Penile Erection/physiology* ; Surveys and Questionnaires

Hepatocellular carcinoma(HCC)is one of the most prevalent malignancies worldwide,and accurate prognostic assessment and treatment planning are vital for improving patient outcomes.Conventional prognostic models,which rely on limited clinicopathological parameters,often fail to capture the profound heterogeneity of HCC.In recent years,artificial intelligence(AI)-particularly machine learning and deep learning-has driven a paradigm shift in precision oncology by leveraging its powerful capabilities in data mining and pattern recognition.This review provides a comprehensive overview of recent advances in AI for prognostic assessment and treatment optimization in HCC,with an emphasis on key methodologies such as radiomics and multi-modal data integration.It further discusses the clinical potential and challenges of AI in predicting postoperative recurrence,evaluating therapeutic response,and supporting individualized treatment decisions,while also outlining future directions in this rapidly evolving field.The review aims to inform and facilitate the clinical translation of AI technologies into the management of HCC.

Objectives: The effectiveness of combining romosozumab (ROMO) with denosumab (Dmab) remains uncertain.We compare the six-month effects of Dmab plus monthly ROMO versus Dmab plus daily teriparatide (TPTD) on bone mineral density (BMD) in treatment-naïve postmenopausal women with osteoporosis. Methods: This retrospective cohort study analyzed 26 treatment-naïve postmenopausal women with primary osteoporosis. Participants received either a monthly regimen of ROMO and Dmab (N = 14) or a daily regimen of TPTD plus Dmab (N = 12). BMD at the lumbar spine, total hip, and femoral neck was measured at baseline, 3 months, and 6 months by dual-energy X-ray absorptiometry. Serum levels of C-terminal telopeptide (CTX) and procollagen type I N-terminal propeptide (P1NP) were assessed at the same intervals. Results: Both regimens significantly improved lumbar spine BMD at 6 months (ROMO + Dmab: +9.75%; TPTD +Dmab: +7.42%). Improvements in total hip and femoral neck BMD were modest and similar between groups (~2%). Serum CTX and P1NP were significantly suppressed in both groups at 3 months, but P1NP suppression waned in the TPTD + Dmab group by 6 months. No statistically significant differences in BMD or marker changes were detected between the two regimens. Conclusions Both combination therapies effectively improve lumbar spine BMD over 6 months. The ROMO +Dmab regimen yielded numerically greater increases with fewer injections.

Background::Alterations in the placental expression of glucose transporters (GLUTs), the crucial maternal-fetal nutrient transporters, have been found in women with hyperglycemia in pregnancy (HIP). However, there is still uncertainty about the underlying effect of the high-glucose environment on placental GLUTs expression in HIP.Methods::We quantitatively evaluated the activity of mammalian target of rapamycin (mTOR) and expression of GLUTs (GLUT1, GLUT3, and GLUT4) in the placenta of women with normal pregnancies (CTRL, n = 12) and pregnant women complicated with poorly controlled type 2 diabetes mellitus (T2DM, n = 12) by immunohistochemistry. In addition, BeWo cells were treated with different glucose concentrations to verify the regulation of hyperglycemia. Then, changes in the expression of GLUTs following the activation or suppression of the mTOR pathway were also assessed using MHY1485/rapamycin (RAPA) treatment or small interfering RNA (siRNA)-mediated silencing approaches. Moreover, we further explored the alteration and potential upstream regulatory role of methyltransferase-like 3 (METTL3) when exposed to hyperglycemia. Results::mTOR, phosphorylated mTOR (p-mTOR), and GLUT1 protein levels were upregulated in the placenta of women with T2DM compared with those CTRL. In BeWo cells, mTOR activity increased with increasing glucose concentration, and the expression of GLUT1, GLUT3, and GLUT4 as well as GLUT1 cell membrane translocation were upregulated by hyperglycemia to varying degrees. Both the drug-mediated and genetic depletion of mTOR signaling in BeWo cells suppressed GLUTs expression, whereas MHY1485-induced mTOR activation upregulated GLUTs expression. Additionally, high glucose levels upregulated METTL3 expression and nuclear translocation, and decreasing METTL3 levels suppressed GLUTs expression and mTOR activity and vice versa. Furthermore, in METTL3 knockdown BeWo cells, the inhibitory effect on GLUTs expression was eliminated by activating the mTOR signaling pathway using MHY1485. Conclusion::High-glucose environment-induced upregulation of METTL3 in trophoblasts regulates the expression of GLUTs through mTOR signaling, contributing to disordered nutrient transport in women with HIP.

The assessment of adverse drug events is an important basis for clinical safety evaluation and post-marketing risk control of drugs,and its causality assessment is gaining increasing attention.The existing methods for assessing the causal relationship between drugs and the occurrence of adverse reactions can be broadly classified into three categories:global introspective methods,standardized methods,and probabilistic methods.At present,there is no systematic introduction of the operational details of the various methods in the domestic literature.This paper compares representative causality assessment methods in terms of definition and concept,methodological steps,industry evaluation and advantages and disadvantages,clarifies the basic process of determining the causality of adverse drug reactions,and discusses how to further improve the adverse drug reaction monitoring and evaluation system,with a view to providing a reference for drug development and pharmacovigilance work in China.

Objective To understand the change in distribution and antimicrobial resistance of bacteria isolated from blood specimens of Hunan Province,and provide for the initial diagnosis and treatment of clinical bloodstream infection(BSI).Methods Data reported from member units of Hunan Province Antimicrobial Resistance Survei-llance System from 2012 to 2021 were collected.Bacterial antimicrobial resistance surveillance method was imple-mented according to the technical scheme of China Antimicrobial Resistance Surveillance System(CARSS).Bacteria from blood specimens and bacterial antimicrobial susceptibility testing results were analyzed by WHONET 5.6 soft-ware and SPSS 27.0 software.Results A total of 207 054 bacterial strains were isolated from blood specimens from member units in Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021,including 107 135(51.7％)Gram-positive bacteria and 99 919(48.3％)Gram-negative bacteria.There was no change in the top 6 pathogenic bacteria from 2012 to 2021,with Escherichia coli(n=51 537,24.9％)ranking first,followed by Staphylococcus epidermidis(n=29 115,14.1％),Staphylococcus aureus(n=17 402,8.4％),Klebsiella pneu-moniae(17 325,8.4％),Pseudomonas aeruginosa(n=4 010,1.9％)and Acinetobacter baumannii(n=3 598,1.7％).The detection rate of methicillin-resistant Staphylococcus aureus(MRSA)decreased from 30.3％in 2015 to 20.7％in 2021,while the detection rate of methicillin-resistant coagulase-negative Staphylococcus(MRCNS)showed an upward trend year by year(57.9％-66.8％).No Staphylococcus was found to be resistant to vancomy-cin,linezolid,and teicoplanin.Among Gram-negative bacteria,constituent ratios of Escherichia coli and Klebsiella pneumoniae were 43.9％-53.9％and 14.2％-19.5％,respectively,both showing an upward trend(both P＜0.001).Constituent ratios of Pseudomonas aeruginosa and Acinetobacter baumannii were 3.6％-5.1％and 3.0％-4.5％,respectively,both showing a downward trend year by year(both P＜0.001).From 2012 to 2021,resistance rates of Escherichia coli to imipenem and ertapenem were 1.0％-2.0％and 0.6％-1.1％,respectively;presenting a downward trend(P＜0.001).The resistant rates of Klebsiella pneumoniae to meropenem and ertapenem were 7.4％-13.7％and 4.8％-6.4％,respectively,presenting a downward trend(both P＜0.001).The resistance rates of Pseudomonas aeruginosa and Acinetobacter baumannii to carbapenem antibiotics were 7.1％-15.6％and 34.7％-45.7％,respectively.The trend of resistance to carbapenem antibiotics was relatively stable,but has de-creased compared with 2012-2016.The resistance rates of Escherichia coli to the third-generation cephalosporins from 2012 to 2021 were 41.0％-65.4％,showing a downward trend year by year.Conclusion The constituent ra-tio of Gram-negative bacillus from blood specimens in Hunan Province has been increasing year by year,while the detection rate of carbapenem-resistant Gram-negative bacillus remained relatively stable in the past 5 years,and the detection rate of coagulase-negative Staphylococcus has shown a downward trend.

Objective To investigate changes in the distribution and antimicrobial resistance of bacteria isolated from cerebrospinal fluid(CSF)specimens in Hunan Province,and provide reference for correct clinical diagnosis and rational antimicrobial use.Methods Data reported by member units of Hunan Province Antimicrobial Resistance Surveillance System from 2012 to 2021 were collected according to China Antimicrobial Resistance Surveillance Sys-tem(CARSS)technical scheme.Data of bacteria isolated from CSF specimens and antimicrobial susceptibility tes-ting results were analyzed with WHONET 5.6 and SPSS 20.0 software.Results A total of 11 837 bacterial strains were isolated from CSF specimens from member units of Hunan Province Antimicrobial Resistance Surveillance Sys-tem from 2012 to 2021.The top 5 strains were coagulase-negative Staphylococcus(n=6 397,54.0％),Acineto-bacter baumannii(n=764,6.5％),Staphylococcus aureus(n=606,5.1％),Enterococcus faecium(n=465,3.9％),and Escherichia coli(n=447,3.8％).The detection rates of methicillin-resistant coagulase-negative Staphyloco-ccus(MRCNS)and methicillin-resistant Staphylococcus aureus(MRSA)were 58.9％-66.3％and 34.4％-62.1％,respectively.No Staphylococcus spp.were found to be resistant to vancomycin,linezolid,and teicoplanin.The de-tection rate of Enterococcus faecium was higher than that of Enterococcus faecalis,and the resistance rates of En-terococcus f aecium to penicillin,ampicillin,high concentration streptomycin and levofloxacin were all higher than those of Enterococcus faecalis(all P=0.001).Resistance rate of Streptococcus pneumoniae to penicillin was 85.0％,at a high level.Resistance rate of Escherichia coli to ceftriaxone was＞60％,while resistance rates to enzyme inhibitors and carbapenem antibiotics were low.Resistance rate of Klebsiella pneumoniae to ceftriaxone was＞60％,to en-zyme inhibitors piperacillin/tazobactam and cefoperazone/sulbactam was＞30％,to carbapenem imipenem and me-ropenem was about 30％.Resistance rates of Acinetobacter baumannii to most tested antimicrobial agents were＞60％,to imipenem and meropenem were 59.0％-79.4％,to polymyxin B was low.Conclusion Among the bac-teria isolated from CSF specimens,coagulase-negative Staphylococcus accounts for the largest proportion,and the overall resistance of pathogenic bacteria is relatively serious.Bacterial antimicrobial resistance surveillance is very important for the effective treatment of central nerve system infection.