Metabolic dysfunction-associated fatty liver disease （MAFLD）， as one of the most common chronic liver diseases in the world， poses a severe challenge to precision diagnosis and treatment due to its complex pathogenesis and highly heterogeneous disease progression. Existing clinical classification systems cannot meet the needs for comprehensively analyzing the complexity of the disease and the heterogeneity of its adverse outcomes. In recent years， data-driven prognostic risk classification methods have gradually emerged， optimizing the ability for predicting adverse outcomes and enhancing the accuracy of identifying different endpoint outcomes. However， such paradigm of “classify first， associate outcomes later” suffers from a “black-box” nature， and there are various indicators for classification， leading to limited stability and generalizability in clinical application. Future research needs to integrate or establish large-scale population cohorts， develop outcome-oriented prognostic risk classification models， incorporate dynamic data， refine classification algorithms， and validate their generalizability across multiple populations， thereby providing reliable support for the precision diagnosis and treatment of MAFLD.

ObjectiveTo clarify the independent and synergistic effects of dyslipidemia in the progression of hepatic steatosis in metabolic dysfunction-associated fatty liver disease （MAFLD）. MethodsA total of 7 697 participants who underwent physical examination in Beijing Friendship Hospital， Capital Medical University， from January 2022 to December 2024 were enrolled， and finally 2 177 patients with MAFLD were enrolled as subjects. Transient elastography was used to quantify the severity of hepatic steatosis （grades S1-S3）. The multivariable ordinal Logistic regression analysis was used to investigate the independent and synergistic associations of serum triglyceride （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） with the severity of hepatic steatosis， and their interactions and potential nonlinear relationships with metabolic factors were also examined. One-way analysis of variance or Kruskal-Wallis H test was used for comparison of continuous data between groups， and chi-square test was used for comparison of categorical data between groups. ResultsAn increase in TG （odds ratio ［OR］=1.77， 95% confidence interval ［CI］： 1.48 — 2.10， P<0.001） and a reduction in HDL-C （OR=1.35， 95%CI： 1.11 — 1.65， P=0.003） were independently associated with a greater severity of hepatic steatosis， with the strongest association when both abnormalities coexisted （OR=2.40， 95%CI： 1.87 — 3.07， P<0.001）. The dose-response relationship analysis further revealed a nonlinear threshold effect of TG on hepatic steatosis at the threshold of 1.51 mmol/L （P_nonlinearity=0.001）， below which the severity of steatosis increased more rapidly with the increase in TG concentration （P=0.001）. The subgroup analysis showed that the association between the reduction in HDL-C and the severity of steatosis was observed only in males， young adults （aged <45 years）， and metabolically healthier subgroups （without diabetes， obesity， hyperuricemia or hypertension）. Significant interactions were observed between the presence or absence of obesity and the abnormal levels of TG and HDL‑C （both P_interaction<0.05）. The association of the increase in LDL-C with steatosis was confined to specific subgroups （without obesity or hyperuricemia）. ConclusionThe increase in TG and the reduction in HDL-C are independently associated with the severity of hepatic steatosis in MAFLD. The synergistic effect of blood lipids and their interactions with metabolic factors may further refine risk stratification， so as to provide a basis for precise management of MAFLD.

Objective To investigate the value of serum lipoprotein-associated phospholipase A2(Lp-PLA2)for predicting high-risk coronary plaques in elderly males.Methods A retrospective study was conducted on 46 elderly males aged ≥60 years undergoing health check-ups and coro-nary computed tomography angiography in our hospital between May and July 2024.Their general clinical data were collected.Artificial intelligence software was used to analyze coronary calcium scores and plaque characteristics.The participants were divided into a high-risk plaque group(n=15)and a non-high-risk plaque group(n=31).The differences were compared between the two groups.Multivariate logistic regression analysis was used to identify the influencing factors for high-risk coronary plaques.ROC curve was plotted to determine the predictive value of serum Lp-PLA2 for high-risk plaques,and its AUC value was calculated.Results The high-risk plaque group had significantly larger proportions of smoking history and hyperlipidemia,and higher level of homocysteine and Lp-PLA2 than the non-high-risk plaque group(P＜0.05,P＜0.01).Multiva-riate logistic regression analysis indicated that Lp-PLA2 was an independent risk factor for high-risk coronary plaques(HR=1.030,95％CI:1.008-1.053,P＜0.05).ROC curve analysis revealed that the AUC value of Lp-PLA2 in predicting high-risk coronary plaques was 0.833(95％CI:0.694-0.927,P＜0.01),with a sensitivity of 93.3％,a specificity of 71.0％,a positive predictive value of 62.5％,and a negative predictive value of 100％.Conclusion Serum Lp-PLA2 is of signif-icant value in predicting high-risk coronary plaques in elderly men.

Objective:To explore the distribution of HIV-1 genetic subtypes and drug resistance profiles among HIV-1 infected patients with antiretroviral treatment (ART) failure in Henan Province and to provide evidence for optimizing ART regimens.Methods:HIV-1 infected patients who had received ART for at least 6 months with viral loads (VL) ≥200 copies/ml in 18 cities of Henan from January to December 2023. The plasma samples were collected, and partial pol gene sequences and full-length integrase ( int) gene sequences of HIV-1 were amplified using nested RT-PCR. HIV-1 subtypes were determined using the REGA HIV-1 subtyping tool, and drug resistance mutations were analyzed using the Stanford University HIV Drug Resistance Database ( http://hivdb.stanford.edu/). Chi-square tests and multivariate logistic regression were used to identify risk factors associated with drug resistance of HIV-1 infected patients. Results:Among 697 HIV-1 infected patients with ART failure, 14 HIV-1 genetic subtypes were identified. Subtype B was predominant (58.68%, 409/697), followed by CRF01_AE (21.95%, 153/697) and CRF07_BC (12.91%, 90/697). The overall drug resistance rate was 72.31% (504/697), with CRF55_01B exhibiting a resistance rate of 91.30% (21/23). Non-nucleoside reverse transcriptase inhibitors (NNRTIs) had the highest resistance mutation rate (67.29%, 469/697), followed by nucleoside reverse transcriptase inhibitors (NRTIs)(56.81%, 396/697), protease inhibitors (PIs)(5.74%, 40/697), and integrase strand transfer inhibitors (INSTIs)(2.75%, 19/691). The results of multivariate analysis showed that the positive correlation factor for drug resistance in HIV-1 infected individuals with failed ART was baseline CD4 +T lymphocyte counts <200 cells/μl (a OR=3.84, 95% CI: 1.69-8.72), and the negative correlation factor was ART duration of 3-5 years (a OR=0.32, 95% CI: 0.13-0.77), the initial treatment ART protocol used two types of NRTIs plus one type of PIs (a OR=0.14, 95% CI: 0.05-0.43) and two types of NRTIs plus one type of INSTIs protocol (a OR=0.12, 95% CI: 0.03-0.57). Conclusions:The drug resistance rate of HIV-1 infected patients with ART failure was relatively higher in Henan Province in 2023. Strengthening the monitoring of HIV-1 drug resistance is of great significance to improve the ART effect of HIV-1 infected patients.

Objective To construct an evaluation index system for the technical labor value of operators of large-scale medical equipment and conduct a practical measurement of it.Methods The literature survey method and semi-structured interview were used to preliminarily construct the evaluation index framework.The questionnaire survey method and expert consultation method were employed to screen and determine the final evaluation index system,and the entropy method was used to calculate the weight of each evaluation index.Based on the KANO model,the evaluation requirements of the technical labor value of MRI operators were investigated.Results The final expert authority coefficient of the consultation questionnaire was 0.80;the chi-square test results of Kendall's W coefficient were all statistically significant differences(P＜0.05);finally,5 first-level indicators,13 second-level indicators,and 22 third-level indicators were screened out,jointly forming the evaluation index system.The Cronbach's coefficients of the positive and negative questionnaires in the reliability analysis of the KANO model were 0.953 and 0.983 respectively;MRI operators perceived that the cerebral thinking load,the steps taken to operate the imaging equipment,and the difficulty in interpreting imaging results were more reflective of the value of their technical labor.Conclusion The evaluation index system of technical labor value of large medical equipment operators has been scientifically constructed to provide theoretical support for improving the performance evaluation system of large medical equipment operators.

Objective To identify the key influencing factors and role mechanisms of large-scale medical equip-ment allocation decision-making in public hospitals,and to provide a reference basis for optimizing resource alloca-tion strategies.Methods Through searching the literature related to large-scale medical equipment decision-making in public hospitals and combing the policies,the system of decision-making influencing factors was initially screened.The Delphi method and decision-making trial and evaluation laboratory method were used to obtain the key influencing factors of equipment allocation decision-making and to determine the interaction effects among the factors.Results A total of seven cause factors and nine effect factors were screened.Among them,cost-benefit analysis,equipment technical performance,and evaluation of similar equipment were the top three key drivers;leadership emphasis,equipment market price,and equipment supporting facilities were the top three key con-straints.Conclusion Priority be given to strengthening the management of driving factors,mainly by conducting a full-cycle assessment of cost-effectiveness,paying attention to the clinical value output of equipment technical performance,and monitoring regionally similar equipment.A dynamic response mechanism for constraints should be established,mainly to strengthen leadership decision-making,implement a centralized procurement price nego-tiation model and improve the pre-assessment system for ancillary facilities.

Promoting whole life cycle management of large medical equipment is a crucial initiative to enhance hospital operational efficiency and service quality.It adopts the full life cycle theoretical,focusing on analyzing key operational issues in configuration planning,procurement,utilization,maintenance,and decommissioning during the planning,implementation,and decline phases of large medical equipment.Through in-depth analysis of these issues,the research proposes corresponding strategies:establishing multi-stakeholder participation mechanisms and equipment utilization protocols during the planning phase;improving allocation and performance evaluation mechanisms during the implementation phase;and scientifically standardizing maintenance and retirement procedures during the decline phase.These recommendations provide theoretical support and practical guidance for public hospitals to achieve lean operation of large medical equipment.

OBJECTIVE To investigate the regulatory effects of salvianolic acid C(SAC)on the level of cuproptosis and inflammatory injury in cardiomyocytes after myocardial infarction(MI).METHODS①C57BL/6 mice were divided into a sham group,an MI model group,and SAC(5,10 and 20 mg·kg-1)groups,with 10 mice in each group.Mice in the SAC groups were pretreated with oral gavage of SAC for 1 week,while those in the sham and model groups received an equal volume of saline.One week later,an MI model was established in the model and SAC groups by ligating the left anterior descending coronary artery,while the sham group underwent thoracotomy without ligation.MI size was assessed using triphenyltetrazolium chloride(TTC)staining.Cardiomyocyte apoptosis was evaluated by TUNEL staining.The ultrastructure of cardiomyocyte mitochondria was observed under a transmission electron microscope.② Mouse cardiomyocytes HL-1 were divided into a control group,an oxygen-glucose deprivation(OGD)model group,OGD+SAC 1,5 and 10 μmol·L-1 groups,and a OGD+SAC(5 μmol·L-1)+nuclear factor erythroid 2-related factor 2(Nrf2)inhibitor ML385(2 μmol·L-1)group.Cells in the OGD+SAC groups were pretreated with SAC for 24 h while those in the OGD+SAC+ML385 group were pretreated with both SAC 5 μmol·L-1 and ML385 2 μmol·L-1 for 24 h.Except for the control group,an OGD model was established in HL-1 cells.ELISA was used to detect the levels of tumor necrosis factor-α(TNF-α),interleukin-6(IL-6)and IL-1β in mouse serum and HL-1 cell culture supernatants.The Cu+detection kit was used to measure Cu+levels in myocardial tissue and HL-1 cells.Cell viability was assessed using the CCK-8 kit.Apoptosis rates of HL-1 cells were detected by flow cytometry.Reactive oxygen species(ROS)levels in HL-1 cells were measured using a ROS detection kit.Western blotting analysis was performed to detect the expression levels of Nrf2,heme oxygenase-1(HO-1),and cupro-ptosis markers,ferredoxin 1(FDX1)and solute carrier family 31 member 1(SLC31A1)in myocardial tissue and HL-1 cells.RESLUTS ① Compared with the sham group,the MI model group exhibited increased myocardial infarction size,elevated cardiomyocyte apoptosis rates,mitochondrial swelling,vacuolation,and cristae rupture in cardiomyocytes,increased serum levels of TNF-α,IL-6,and IL-1β,elevated Cu+levels and expressions of FDX1 and SLC31A1 in myocardial tissue,and decreased expressions of Nrf2 and HO-1(P<0.01).Compared with the model group,the SAC 5,10 and 20 mg·kg-1 groups showed reduced MI size,decreased cardiomyocyte apoptosis rates,alleviated mitochondrial swelling,vacuola-tion,and cristae rupture,lower serum levels of TNF-α,IL-6 and IL-1β,decreased Cu+levels and expres-sions of FDX1 and SLC31A1 in myocardial tissue,and increased expressions of Nrf2 and HO-1(P<0.05,P<0.01).② Compared with the cell control group,the OGD model group demonstrated signifi-cantly decreased HL-1 cell viability,increased cell apoptosis rates,Cu+and ROS levels,expressions of FDX1 and SLC31A1,elevated levels of TNF-α,IL-6 and IL-1β in cell culture supernatants,and decreased expressions of Nrf2 and HO-1(P<0.01).Compared with the OGD model group,the SAC 1,5 and 10 μmol·L-1 groups showed increased HL-1 cell viability,decreased cell apoptosis rates,Cu+and ROS levels,expressions of FDX1 and SLC31A1,reduced levels of TNF-α,IL-6 and IL-1β in cell culture supernatants,and increased expressions of Nrf2 and HO-1(P<0.05,P<0.01).Compared with the SAC 5 μmol·L-1 group,the SAC 5 μmol·L-1+ML385 2 μmol·L-1 group exhibited decreased cell viability,increased cell apoptosis rates,Cu+and ROS levels,expressions of FDX1 and SLC31A1,elevated levels of TNF-α,IL-6,and IL-1β in cell culture supernatants,and decreased expressions of Nrf2 and HO-1(P<0.01).CONSLUSION SAC can activate the Nrf2/HO-1 signaling pathway,alleviate cuproptosis in cardiomyocytes after MI,and reduces inflammatory damage.

Objective To investigate the relationship between four metabolic indices reflecting insulin resistance(IR)and the risk of diabetic kidney disease(DKD)in patients with type 2 diabetes mellitus(T2DM).Methods 157 T2DM patients with DKD(DKD group)and 198 T2DM patients(T2DM group)were included in our study.The general data and clinical indicators were collected.Triglyceride/high density lipoprotein cholesterol ratio(TG/HDL-C),triglyceride glucose(TyG)index,triglyceride glucose-body mass index(TyG-BMI)and metabolic score for IR(METS-IR)were calculated.Results Compared with T2DM group,TG/HDL-C,TyG index,TyG-BMI and METS-IR in DKD group were significantly increased(P<0.05).Logistic regression analysis showed that TyG index(OR=8.303,95%CI 1.787～38.573,P=0.007)was an independent risk factor for DKD.The risk of DKD in the fourth quantile of TyG index group was 5.652 times than the first quantile group(P<0.05).ROC curve analysis showed that when the cutoff value of TyG index was 9.03,its sensitivity and specificity for predicting DKD were 56.7%and 71.7%,respectively.Conclusions Among the four simple IR indicators,TyG index is an independent risk factor for the occurrence of DKD in T2DM patients.Increased TyG index indicates increased UACR level and high risk of DKD.

Objective:To analyze the drug resistance characteristics and influencing factors in human immunodeficiency virus (HIV)-1 treated patients in Henan Province.Methods:HIV-1 treated patients who had received anti-retroviral therapy (ART) for more than six months and had a viral load >200 copies/mL in the Zhengzhou Sixth People′s Hospital from January to December 2024 were enrolled. Plasma samples were collected. Partial pol region gene sequences and integrase gene sequences of HIV-1 were amplified by reverse transcription nested polymerase chain reaction. The REGA HIV-1 subtype analysis tool was used to determine the subtypes of HIV-1 isolates, and the HIV drug resistance database of Stanford University in the United States was used to analyze the genetic drug resistance mutations and antiviral drug susceptibility. The multivariate logistic regression analysis was used to analyze the factors related to drug resistance. Results:Among 933 HIV-1 treated patients with ART failure, 825 samples were successfully amplified, with the amplification success rate of 88.42%. The overall drug resistance rate was 70.06%(578/825), among which the drug resistance rates of nucleoside reverse transcriptase inhibitor (NRTI), non-nucleoside reverse transcriptase inhibitor (NNRTI), protease inhibitor (PI), and integrase inhibitor (INSTI) were 55.15%(455/825), 64.36%(531/825), 5.70%(47/825), and 2.31%(19/821), respectively. The most common drug resistance mutations included M184I/V (47.88%(395/825)), K103N/S (38.18%(315/825)), and K70E/G/N/Q/R/S/T/del (16.61%(137/825)). Multivariate analysis showed that the baseline CD4 + T cell count <200 cells/μL (adjusted odds ratio ( OR)=2.239, 95% confidence interval ( CI)1.011 to 4.960), an initial 2NRTI+ NNRTI-based treatment regimen (adjusted OR=44.332, 95% CI 5.191 to 378.593), initial 2NRTI+ PI/r (r means ritonavir)-based regimen (adjusted OR=14.391, 95% CI 1.304 to 158.805) and a change in the ART regimen (adjusted OR=5.941, 95% CI 2.373 to 14.878) were independent risk factors for drug resistance (all P<0.05). Conclusions:The drug resistance rate after virological failure in HIV-1 treated patients in Henan Province is relatively high, which is mainly characterized by NNRTI resistance. The baseline immune status and the choice of the initial treatment regimen are important factors affecting the occurrence of drug resistance. The treatment monitoring and drug resistance monitoring should be strengthened.