Objective To investigate the impact of red blood cell suspension infusion across various perioperative periods on patients with valvular heart disease. Methods The patients with valvular heart disease admitted to Tianjin Chest Hospital from 2018 to 2020 were selected. Based on the timing of perioperative red cell suspension infusion, patients were categorized into three groups: a group 1 receiving intraoperative red cell suspension infusion, a group 2 receiving red cell suspension infusion within 24 hours after entering the ICU, and a group 3 receiving red cell suspension infusion at both time points. The laboratory results, perioperative blood component infusion volume, and other relevant parameters were retrospectively analyzed. After propensity score matching, the differences in different variables among the three groups were compared. Results After propensity score matching, 102 patients were enrolled, including 52 males and 50 females, with an average age of (61.74±10.58) years. There were 34 patients in each group. The preoperative hemoglobin (Hb) value of the group 2 was significantly higher than that of the group 1 and the group 3, and the amount of red cell suspension and autoblood transfusion was the lowest (P<0.05). Group 1 had the highest postoperative Hb, as well as the highest Hb and hematocrit (HCT) levels within 24 hours post-surgery (P<0.05). The group 1 had the lowest plasma, platelet and cryoprecipitate infusion volumes, and the shortest cardiopulmonary bypass time, aortic occlusion time, postoperative ICU stay and hospital stay, and the least blood loss and total drainage volume (P<0.05). The difference between postoperative and preoperative Hb (△Hb1) was highest in group 1 (P<0.05). Conclusion For patients with valvular heart disease, intraoperative-only infusion of red blood cell suspension is associated with a better prognosis at discharge and during follow-up.

Animal model research on spleen and stomach diseases in traditional Chinese medicine （TCM） is of great significance for elucidating the nature of diseases and syndromes and for revealing the mechanisms of action of Chinese herbal medicinals. At present， studies on classical TCM syndrome models of spleen and stomach diseases mainly focus on spleen deficiency syndrome， liver constraint syndrome， and damp-heat syndrome. Model construction is mostly based on the etiological and pathophysiological characteristics of syndrome， and model evaluation primarily involves macroscopic manifestations and physicochemical indicators. This paper summarizes the current research status of animal models integrating disease and syndrome for seven common spleen and stomach diseases， including chronic gastritis and gastric precancerous lesions， gastroesophageal reflux disease， functional dyspepsia， inflammatory bowel disease， irritable bowel syndrome， functional constipation， and functional diarrhea. The modeling methods and characteristics of disease-syndrome combined animal models for each disease are analyzed. It is proposed that future research on disease-syndrome integration in spleen and stomach diseases should move toward syste-matic， precise， and integrative development， and that interdisciplinary and cross-disciplinary research approaches should be adopted to enhance the predictive value and application efficiency of disease-syndrome combined animal models.

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.

Objective To investigate the association between cystatin C level and 6-month mortali-ty as well as re-hospitalization in elderly patients with heart failure(HF).Methods The clinical data in this study were from a retrospective cohort study,Zigong Heart Failure Study.A total of 1786 elderly HF patients admitted in Zigong Fourth People's Hospital from December 2016 to June 2019 were selected.According to the tertiles of cystatin C level,the subjected patients were divided into three groups,with the cystatin C level of 1.10±0.17(587 cases),1.60±0.17(599 ca-ses),and 2.91±0.90 mg/L(600 cases),respectively.The primary endpoint was a composite end-point of death at 6 months after discharge and readmission due to HF.Multivariate Cox propor-tional hazards regression analysis was employed to analyze the relationship of the cystatin C level with the composite endpoint of 6-month mortality and readmission due to HF.Restricted cubic spline was used to model the relationship between the cystatin C level and the composite end-point,Kaplan-Meier survival curve was plotted to analyze the differences in 6-month event free survival rates among the three groups,and ROC curve was drawn to analyze the predictive value of cystatin C level for the composite endpoint.Results Multivariate Cox proportional hazards re-gression analysis showed that the middle and upper tertiles of cystatin C level were risk factors for the composite endpoint of 6-month mortality and readmission due to HF(HR=1.170,95％CI:0.970-1.390,P=0.111;HR=1.452,95％CI:1.190-1.756,P=0.000).When taking cystatin C level as a continuous variable,the results remained consistent:for every one standard deviation increase in cystatin C level,HR=1.141,95％CI:1.060-1.226 in Model 3;For every 1 mg/L in-crease,HR=1.152,95％CI:1.057-1.250 in Model 3.Restricted cubic spline displayed a non-linear inverse J-shaped relationship between cystatin C level and the composite endpoint of 6-month mortality and readmission due to HF,with a risk inflection point of cystatin C level at 2.13 mg/L.ROC curve analysis showed that the AUC value of cystatin C level in predicting the composite endpoint,6-month death and re-admission due to HF was 0.572,0.667 and 0.554,respectively.Conclusion Elevated cystatin C level is independently associated with an increased risk of the composite endpoint of 6-month death and re-admission in elderly HF patients.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Purpose To explore the effect of Calumenin(CALU)on migration and invasion ability of gastric cancer cells,as well as epithelial-mesenchymal transition(EMT).Methods The immunohistochemical experiments and Western blot were applied to evaluate the protein level of CALU in gastric cancer.After constructing a gastric canc-er cell line with low expression of CALU,CCK8 assay,wound-healing analysis and Transwell migration and invasion assays were performed to determine cell proliferation,Migration and invasion ability.Western blot was performed to an-alyse the effect of CALU knockdown on EMT molecules.Results CALU expression was significantly higher in gastric cancer tissues compared to normal gastric tissues(P＜0.05),and high CALU expression was significantly associated with TNM stage and lymph node metastasis(P＜0.05).Compared with GES-1 cells,the protein expression of CALU upregulated in gastric cancer cells(P＜0.05).CALU knockdown suppressed the proliferation,migration,invasion of BGC823 cells and SGC7901 cells(P＜0.05).Rescue experimental evidence showed that synonymous mutations of CALU could reverse the inhibitory effect of CALU knockdown on the proliferation,migration,and invasion ability of gastric cancer cells(P＜0.05).Knockdown of CALU resulted in the downregulation of vimentin and Snail expression,while E-cadherin and β-catenin expression were upregulated in human gastric cancer cells(P＜0.05).Conclusion CALU knockdown inhibits the proliferation,migration,invasion,and EMT of human gastric cancer cells.

Aim To examine the pathogenesis of disul-fide death gene in vascular dementia(VD)by bioin-formatics analysis of disulfide death differentially ex-pressed genes(DEGs)combined with experimental verification.Methods The death DEGs of disulfide were screened and their correlation was analyzed.The VD patients data in the data set were analyzed by clus-tering and typing and gene set variation.The clustering risk of DEGs was tested with a nomogram model,and the optimal learning model was predicted.After the es-tablishment of VD rat model,water maze test,HE stai-ning and RT-qPCR detection were performed to verify the results of health information.Results Four DEGs including SLC7A11 were obtained,which had antago-nistic or synergistic interaction with each other.The genetic data could be divided into two subtypes with significant differences.After typing,VD disulfide DEGs were mainly concentrated in GnRH signaling pathways.The accuracy of the nomogram prediction model was high.Generalized linear was the best ma-chine learning model.Compared with the sham opera-tion group,the escape latency of rats in the model group was prolonged,the number of crossing platforms decreased,the relative mRNA expression levels of Slc3a2 and Slc7a11 decreased,and LRPPRC in-creased.Conclusions SLC7A11 and other disulfide death DEGs and its related GnRH signaling pathway may be an important part of the pathogenesis of VD di-sulfide death.SLC3A2,LRPPRC and SLC7A11 can be used as characteristic genes in the regulation of VD by disulfide death,which may affect VD progression through the regulation of disulfide death.

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 investigae microbial community structure of lower respiratory tract in severe hospital-acquired pneumonia(SHAP)patients in intensive care unit(ICU)using metagenomic next-generation sequencing(mNGS).Methods mNGS was performed on bronchoalveolar lavage fluid(BALF)of 84 patients with SHAP.Patients were grouped based on age,smoking status,underlying diseases and duration of artificial airway.The differences in α diversity,β diversity,microbial composition and community structure of airway microbiota were compared between different groups.The differential airway microbiota associated with artificial airway were screened,and microbial co-occurrence networks was constructed to observe the interaction in microorganisms.Results Results of α diversity analysis revealed that diversity and evenness of the microbial community were higher in young adults compared to those of middle-aged patients,while microbial diversity and evenness were significantly reduced in patients with comorbid stroke.In the group of artificial airway treatment,the diversity and uniformity of microorganisms decreased as the duration of artificial airway treatment increased.The diversity was the lowest when the artificial airway treatment lasted for more than 3 days.β diversity analysis confirmed that there were significant differences in the distinct microbial community structures between the>3 days support group and the non-intubated and≤3 days support cohorts.Acinetobacter baumannii was dominant in all groups.The bacterial diversity was significantly higher in the middle-aged group,the non-smoking group,the group without artificial airway therapy,the group without diabetes mellitus,the group with artificial airway therapy≥3 days and the group with chronic lung disease than those of other groups.In particular,pseudomonas aeruginosa,corynebacterium striatum and veillonella parvula were enriched in these groups.Difference analysis showed that there were significant differences in pseudomonas aeruginosa and corynebacterium striatum between the group with artificial airway treatment>3 days,the group without artificial airway therapy and the group with artificial airway treatment≤3 days.Network co-occurrence showed that there may be synergistic or antagonistic relationships between some microorganisms.Conclusion The microbial diversity of the lower respiratory tract in patients with SHAP significantly decreases in the elderly,those with concurrent stroke and those receiving artificial airway treatment.For these groups,rational use of antibiotics should be adopted to guide precise anti-infection treatment.