The prescription of Qidong Yixin oral liquid is derived from the experience of national medical master Ren Jixue in treating viral myocarditis （VMC）. It has the functions of tonifying Qi， nourishing the heart，calming the mind， and relieving palpitations. It is used to treat VMC and angina pectoris of coronary heart disease caused by deficiency of both Qi and Yin. However，the understanding of its efficacy evidence， advantageous aspects， dosage and administration， and medication safety remains insufficient in clinical practice. Therefore，the development of the Expert Consensus on the Clinical Application of Qidong Yixin Oral Liquid （hereinafter referred to as consensus） was initiated. Consensus strictly followed the process and methods of the expert consensus on the clinical application of Chinese patent medicines of the China Association of Chinese Medicine，successively completing multiple tasks such as the consensus project initiation，determination of clinical problems，evidence search and evaluation，formation of recommendation opinions and consensus suggestions，solicitation of opinions，peer review， submission for review and release， and so on. Consensus formed a total of 10 recommendation opinions and 12 consensus suggestions，clarifying the clinical positioning，efficacy advantages，syndrome differentiation，dosage and administration，combination therapy，timing of medication，adverse reactions，contraindications， and precautions of Qidong Yixin oral liquid，indicating that it has good clinical advantages and safety in the treatment of VMC and angina pectoris of coronary heart disease，providing norms and references for physicians to safely and rationally apply Qidong Yixin oral liquid. Consensus was reviewed and approved for release by the Standardization Office of the China Association of Chinese Medicine on December 23， 2024. Standard number：GSCACM-376-2024.

AIM:To investigate the mechanism by which the Z-DNA-binding protein 1(ZBP1)/receptor-in-teracting protein kinase 1(RIPK1)/mixed lineage kinase domain-like protein(MLKL)pathway modulates the necroptosis of neurons in a mouse model of Alzheimer disease(AD).METHODS:Thirty mice were randomly divided into three groups:normal control(NC)group,APP/PS1 model(MOD)group,and necroptosis inhibitor necrostatin-1(Nec-1)group,each with 10 mice.The learning and memory capacities of mice were assessed using the Morris water maze assays.The pathological morphology of hippocampal tissue was examined based on the HE staining assay.The expression levels of tumor necrosis factor-α(TNF-α)and interleukin-10(IL-10)in serum samples were measured by ELISA.The phosphory-lation of amyloid precursor protein(APP),Tau protein and the expression levels of proteins related to the ZBP1/RIPK1/MLKL pathway in hippocampal tissue were measured by Western blot.Immunofluorescence analysis was performed to de-tect the positive expression of p-RIPK1,while the mRNA level of ZBP1 was measured by RT-qPCR.RESULTS:Com-pared with NC group,the escape latency of mice in the MOD group was significantly longer(P<0.05),the number of crossing platforms was reduced(P<0.05),and the arrangement of hippocampal neurons was disordered accompanied with nuclear condensation.The concentration of TNF-α in serum was increased,whereas the concentration level of IL-10 was decreased(P<0.05).The expression levels of APP,p-Ttau and ZBP1 proteins in the hippocampal tissue and the ratios of p-RIPK1/RIPK1,p-RIPK3/RIPK3 and p-MLKL/MLKL were significantly upregulated(P<0.05).Similarly,the positive expression level of p-RIPK1 and the mRNA level of ZBP1 in hippocampal tissue were significantly upregulated(P<0.05).Compared with the MOD group,the cognitive function of AD mice,pathological damage of hippocampal tissue,and the levels of TNF-α and IL-10 in serum were reversed in the Nec-1 group(P<0.05).Moreover,the Nec-1 treatment signifi-cantly downregulated the expression levels of the above proteins(P<0.05),and the positive expression of p-RIPK1 and the mRNA level of ZBP1 were significantly decreased(P<0.05).CONCLUSION:The ZBP1/RIPK1/MLKL pathway is involved in the occurrence of neuronal necroptosis and the pathological process of AD mice.Inhibition of this pathway sig-nificantly ameliorates cognitive dysfunction and neuroinflammatory responses in AD mice.

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.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

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 explore the relationship between general demographic characteristics,inflammatory indicators,nutritional indicators,pathological data and lymph node metastasis in endometrial cancer(EC)pa-tients,and to construct and validate a model for preoperative prediction of lymph node status in endometrial canc-er patients.Methods:The preoperative clinical data of 473 patients with EC who underwent surgical treatment in the Zhu Jiang Hospital of Southern Medical University from January 2010 to April 2024 were retrospectively ana-lyzed.The independent risk factors of lymph node metastasis of endometrial cancer were screened by univariate and multivariate Logistic regression analyses,and the nomogram prediction model was constructed by R soft-ware.The performance of the model was evaluated by the receiver operating characteristic(ROC)curve,calibra-tion curve and clinical decision curve.Results:Menopausal status,high grade biopsy pathology,CA125 ≥24.47U/ml,systemic immune inflammatory index(SII)≥710.91,and prognostic nutritional index(PNI)＜52.90 were in-dependent risk factors for lymph node metastasis in endometrial cancer(OR＞1,P＜0.05).The nomogram model constructed based on these five factors had an AUC of 0.853 in the training set and 0.871 in the test set.The cali-bration curve fitted well,and the clinical decision curve shows a positive benefit.Conclusions:The endometrial cancer lymph node metastasis prediction model constructed based on menopausal status,biopsy pathology,CA125,SII,and PNI has good accuracy and fit,with certain clinical application value.

AIM:To investigate the mechanism by which the Z-DNA-binding protein 1(ZBP1)/receptor-in-teracting protein kinase 1(RIPK1)/mixed lineage kinase domain-like protein(MLKL)pathway modulates the necroptosis of neurons in a mouse model of Alzheimer disease(AD).METHODS:Thirty mice were randomly divided into three groups:normal control(NC)group,APP/PS1 model(MOD)group,and necroptosis inhibitor necrostatin-1(Nec-1)group,each with 10 mice.The learning and memory capacities of mice were assessed using the Morris water maze assays.The pathological morphology of hippocampal tissue was examined based on the HE staining assay.The expression levels of tumor necrosis factor-α(TNF-α)and interleukin-10(IL-10)in serum samples were measured by ELISA.The phosphory-lation of amyloid precursor protein(APP),Tau protein and the expression levels of proteins related to the ZBP1/RIPK1/MLKL pathway in hippocampal tissue were measured by Western blot.Immunofluorescence analysis was performed to de-tect the positive expression of p-RIPK1,while the mRNA level of ZBP1 was measured by RT-qPCR.RESULTS:Com-pared with NC group,the escape latency of mice in the MOD group was significantly longer(P<0.05),the number of crossing platforms was reduced(P<0.05),and the arrangement of hippocampal neurons was disordered accompanied with nuclear condensation.The concentration of TNF-α in serum was increased,whereas the concentration level of IL-10 was decreased(P<0.05).The expression levels of APP,p-Ttau and ZBP1 proteins in the hippocampal tissue and the ratios of p-RIPK1/RIPK1,p-RIPK3/RIPK3 and p-MLKL/MLKL were significantly upregulated(P<0.05).Similarly,the positive expression level of p-RIPK1 and the mRNA level of ZBP1 in hippocampal tissue were significantly upregulated(P<0.05).Compared with the MOD group,the cognitive function of AD mice,pathological damage of hippocampal tissue,and the levels of TNF-α and IL-10 in serum were reversed in the Nec-1 group(P<0.05).Moreover,the Nec-1 treatment signifi-cantly downregulated the expression levels of the above proteins(P<0.05),and the positive expression of p-RIPK1 and the mRNA level of ZBP1 were significantly decreased(P<0.05).CONCLUSION:The ZBP1/RIPK1/MLKL pathway is involved in the occurrence of neuronal necroptosis and the pathological process of AD mice.Inhibition of this pathway sig-nificantly ameliorates cognitive dysfunction and neuroinflammatory responses in AD mice.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

OBJECTIVES: To investigate the application value of thromboelastography (TEG) in assessing coagulation function in children with severe hemophilia A (HA) after emicizumab (EMI) therapy. METHODS: A retrospective analysis was performed on the activated partial thromboplastin time (APTT) and TEG testing results of 17 children with severe HA before and after EMI treatment at Shenzhen Children's Hospital from January 2023 to July 2024. Correlation analysis was conducted between coagulation factor VIII (FVIII) equivalent activity and reaction time (R value) measured by TEG. RESULTS: After EMI treatment, the mean bleeding rate for children with severe HA was 1.6 events per year, with 15 children (88%) without spontaneous bleeding or joint bleeding. The children with severe HA showed a significant reduction in APTT after EMI treatment (P<0.05), with a significantly shorter APTT than the normal control group (P<0.05). There was no correlation between APTT and FVIII equivalent activity after treatment (P>0.05). After EMI treatment, TEG parameters, including R value, kinetic time, alpha angle (α), maximum amplitude, clot strength, and coagulation index, shifted from a hypocoagulable state before treatment to a nearly normal state after treatment (P<0.05). The R value demonstrated a strong negative correlation with FVIII equivalent activity (r=-0.758, P<0.05). CONCLUSIONS The bleeding condition of children with severe HA can be effectively controlled after EMI treatment. Routine APTT testing cannot reflect true coagulation function, whereas TEG testing is clinically valuable in assessing the coagulation function of children with severe HA undergoing EMI treatment.
Humans ; Thrombelastography ; Hemophilia A/physiopathology* ; Male ; Child ; Antibodies, Bispecific/therapeutic use* ; Antibodies, Monoclonal, Humanized/therapeutic use* ; Blood Coagulation/drug effects* ; Child, Preschool ; Retrospective Studies ; Female ; Partial Thromboplastin Time ; Adolescent ; Infant