Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

Atherosclerosis (AS), the primary pathological contributor to cardiovascular diseases (CVDs), has increasingly affected younger populations due to modern dietary habits and sedentary lifestyles. Current diagnostic modalities, including ultrasound, MRI, and CT, primarily identify advanced lesions and inadequately evaluate plaque vulnerability, thereby hindering early detection. Conventional treatments, which involve long-term medications associated with side effects such as hepatic injury and surgical interventions that carry risks of restenosis and hemorrhage, underscore the urgent need for non-invasive, cost-effective early diagnostic methods and targeted therapies. Gut microbiota metabolites are pivotal in AS pathogenesis, with trimethylamine N-oxide (TMAO) and short-chain fatty acids (SCFAs) serving as functionally opposing biomarkers. TMAO is produced when gut bacteria, specifically Firmicutes and Proteobacteria, metabolize dietary choline and carnitine into trimethylamine (TMA), which the liver subsequently converts to TMAO via flavin-containing monooxygenase 3 (FMO3); TMAO is then excreted in urine. Variability in TMAO levels is influenced by marine food consumption and FMO3 modulation, which can be affected by genetics, age, and diet. Mechanistically, TMAO exacerbates AS by disrupting cholesterol metabolism, inducing endothelial dysfunction through the elevation of reactive oxygen species (ROS) and pro-inflammatory cytokines such as IL-6, and reducing nitric oxide levels. Additionally, TMAO activates NF-κB and NLRP3 pathways while enhancing platelet reactivity. Clinically, elevated TMAO levels correlate with early AS and serve as predictors of mortality in patients with stable coronary artery disease (CAD) and acute coronary syndrome (ACS), as well as major adverse cardiovascular events (MACE) in stroke patients. Conversely, SCFAs—namely acetate, propionate, and butyrate—are produced by gut bacteria such as Akkermansia muciniphila and Faecalibacterium prausnitzii through the fermentation of dietary fiber. These metabolites exert anti-AS effects: acetate aids in maintaining metabolic homeostasis; propionate protects endothelial function and reduces plaque area; and butyrate fortifies intestinal barriers while suppressing inflammation. Furthermore, SCFAs cross-regulate bile acid metabolism, thereby influencing TMAO levels, and antagonize the pro-inflammatory and lipid-disrupting effects of TMAO. The use of TMAO and SCFAs as standalone biomarkers is constrained by limitations. TMAO lacks specificity, while SCFA levels fluctuate based on gut microbiota and dietary intake. Traditional AS risk assessment tools, which include clinical indicators, imaging techniques, and single biomarkers such as CRP, LDL-C, and ASCVD scores, overlook gut metabolism and demonstrate inadequate performance in younger populations. This review advocates for an “antagonistic-complementary” combined strategy: utilizing acetate and TMAO for early AS, propionate and TMAO for progressive AS, and butyrate and TMAO for advanced AS, addressing endothelial dysfunction, lipid deposition, and plaque stability/thrombosis risk, respectively. For clinical application, standardization of detection methods is crucial; liquid chromatography-mass spectrometry (LC-MS) is the gold standard, necessitating a unified sample pretreatment protocol, such as extraction with 1% formic acid in methanol. Additionally, dried blood spots (DBS) facilitate non-invasive testing, provided that dietary controls are implemented prior to detection, including a 12-hour fast and avoidance of high-choline and high-fiber foods. Existing challenges encompass the absence of standardized systems, limited large-scale validation, and ambiguous interactions with conditions such as hypertension. The authors’ team has previously established connections between gut metabolites and AS, including the reduction of TMAO as a preventive measure for AS, thereby reinforcing this proposed strategy. Future research should prioritize standardization, the development of machine learning-optimized models, validation of interventions, and the exploration of multi-omics-based “gut microbiota-metabolite-vascular” networks. In conclusion, the combined detection of TMAO and SCFAs offers a novel framework for AS risk assessment, facilitating early diagnosis and targeted interventions while enhancing the integration of gut metabolism into cardiovascular disease management.

ObjectiveTo explore the mechanism by which Qidan Yifei Tongqiao granules （QDYF） alleviate nasal mucosal remodeling in allergic rhinitis （AR） via the interleukin-33 （IL-33）/growth stimulation expressed gene 2 （ST2）/interleukin-1 receptor accessory protein （IL-1RAP） signaling pathway from the perspective of Qi-replenishing and blood-activating therapy. MethodsFirst， according to the previous network pharmacology results， this study predicted the potential mechanisms of QDYF in treating AR by screening key pathways， components， and targets. Molecular docking was performed via AutoDock and PyMOL 2.5.5. Subsequently， a rat model of ovalbumin （OVA）-induced AR was used for validation through in vivo experiments. Forty-eight rats were assigned into 6 groups： Control， model， low-dose QDYF （QDYF-L， 4.04 g·kg^-1）， medium-dose QDYF （QDYF-M， 8.08 g·kg^-1）， high-dose QDYF （QDYF-H， 16.16 g·kg^-1）， and loratadine （0.9 mg·kg^-1）. After 14 days of intervention， behavioral scores of the rats were observed. The morphological changes of nasal mucosa tissue were observed by hematoxylin-eosin （HE） staining. Masson staining was used to observe collagen fiber deposition in the nasal mucosal tissue and to calculate the collagen volume fraction （CVF）. The expression of E-cadherin （E-cad） in the nasal mucosa tissue was detected by immunofluorescence. The serum levels of helper T cell 2 （Th2） cytokines interleukin-4 （IL-4）， interleukin-5 （IL-5）， and interleukin-13 （IL-13） as well as helper T cell 1 （Th1） cytokines interleukin-2 （IL-2） and interferon-γ （INF-γ） were quantified by enzyme-linked immunosorbent assay （ELISA）. The protein levels of transforming growth factor-beta 1 （TGF-β₁）， IL-33， ST2， and IL-1RAP in the nasal mucosa tissue were determined by Western blot. ResultsIL-33， ST2， and IL-1RAP had strong binding ability with the main active ingredients—wogonin， 7-methoxy-2-methylisoflavone， formononetin， naringenin， stigmasterol， and beta-sitosterol of QDYF， with the binding energy < -4.25 kcal⋅mol^-1（1 cal≈4.184 J）. The results of in vivo experiments showed that compared with the control group， the model group exhibited increased behavioral scores （P<0.05）， aggravated pathological damage of nasal mucosa， increased collagen fiber deposition and CVF （P<0.05）， elevated serum levels of IL-4， IL-5， and IL-13， up-regulated protein levels of TGF-β₁， IL-33， ST2， and IL-1RAP in the nasal mucosa （P<0.05）， down-regulated expression of E-cad， and declined serum levels of IL-2， IFN-γ， and IFN-γ/IL-4 ratio （P<0.05）. Compared with the model group， the QDYF groups and loratadine group showed reduced behavioral scores （P<0.05）， alleviated pathological damage of nasal mucosa， reduced collagen fiber deposition and CVF （P<0.05）， and up-regulated E-cad expression （P<0.05）. Compared with the model group， the QDYF-H group and the loratadine group showed raised levels of INF-γ and IFN-γ/IL-4 ratio （P<0.05）， declined serum levels of IL-4， IL-5， and IL-13， and down-regulated protein levels of TGF-β₁， IL-33， ST2， and IL-1RAP in the nasal mucosa （P<0.05）. In addition， the QDYF-H group exhibited an elevated serum IL-2 level （P<0.05）. The QDYF-M group showed down-regulated protein levels of TGF-β₁， IL-33 and IL-1RAP in the nasal mucosa （P<0.05）. The QDYF-L group demonstrated a down-regulated protein level of ST2 in the nasal mucosa （P<0.05）. ConclusionQDYF may regulate the Th1/Th2 balance through the IL-33/ST2/IL-1RAP signaling pathway， thereby ameliorating nasal mucosal tissue remodeling and alleviating AR.

Objective:To investigate the effect of PD-1/PD-L1 inhibitor BMS-1 on LPS-induced inflammation in mouse microg-lia cells(BV-2 cells).Methods:Bv-2 cells were divided into Control group,LPS group and LPS+BMS-1 group.Bv-2 cells in Control group were cultured in DMEM medium for 78 hours,cells in LPS group were stimulated with 100 ng/ml LPS for 6 hours after 72 hours of normal culture,Bv-2 cells in LPS+BMS-1 group were treated with 50 nmol/ml BMS-1 for 72 hours and then stimulated with 100 ng/ml LPS for 6 hours.Expressions of PD-1 and iNOS mRNA in each group were detected by RT-qPCR,and expressions of PD-1 and iNOS protein in microglia were detected by Western blot.Flow cytometry was used to detect cell apoptosis in each group.Levels of inflamma-tory cytokines IL-1β,IL-6,TNF-α and IL-10 were detected by ELISA.Results:RT-qPCR and Western blot results showed that com-pared with Control group,LPS group had significantly increased expression of PD-1 and iNOS(P<0.05).Compared with LPS group,LPS+BMS-1 group had significantly decreased expression of PD-1(P<0.05)and significantly increased expression of iNOS(P<0.05).Flow cytometry showed that compared with Control group,LPS group had a significantly increased in apoptosis of microglia(P<0.000 1).Compared with LPS group,LPS+BMS-1 group had a significantly increased in apoptosis of microglia(P<0.000 1).ELISA results showed that compared with Control group,LPS group had no significantly increased in pro-inflammatory factors IL-1β and IL-6(P>0.05),while significantly increased in TNF-α(P<0.000 1)and anti-inflammatory factor IL-10(P<0.000 1).Pro-inflammatory cyto-kine IL-1β in LPS+BMS-1 group was significantly higher than that in LPS group(P=0.000 1),IL-6 and TNF-α were also significantly higher than those in LPS group(P<0.000 1),while anti-inflammatory cytokine IL-10 in LPS+BMS-1 group was significantly lower than that in LPS group(P<0.000 1).Conclusion:BMS-1 can promote LPS-induced inflammatory response or impede the recovery of inflammation,and increase apoptosis of microglia.PD-1/PD-L1 pathway may be a potential therapeutic target for neuroinflammation.

Objective To propose a dynamic electrical impedance tomography imaging algorithm based on complementary information fusion network(CIFN)to enhance image quality of dynamic electrical impedance imaging.Methods There were three modules for initialization,multi-frame complementary information extraction and information fusion involved in the CIFN.Firstly,multi-frame dynamic conductivity distribution images were obtained by the initialization module;secondly,spatial complementary information was extracted from the images by using the multi-frame complementary information extraction module;finally,the fusion of lesion target distribution information and target re-reconstruction were realized by the information fusion module to aquire high-quality EIT images.With a 16-electrode multilayer cranial simulation model,the CIFN-based imaging method was compared with Tikhonov regularization algorithm,spectral constraint algorithm and U-Net algorithm in terms of imaging results of types of lesions to verify its performance.Results Compared with the Tikhonov regularization algorithm,spectral constraint algorithm and U-Net algorithm,the proposed CIFN-based algorithm exhibited the lowest mean absolute error(MAE)and the highest structural similarity(SSIM)when used to image different lesion targets,which accurately reconstructed the distribution of lesion targets and gained high imaging stability under common noise levels.Conclusion The proposed CIFN-based imaging algorithm obtains high imaging quality on a cranial simulation model and reconstruction results close to the real model distribution,which provides algorithmic support for subsequent clinical studies on electrical impedance imaging.[Chinese Medical Equipment Journal,2025,46(6):1-6]

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.

To rapidly detect and differentiate Mycoplasma gallisepticum(MG)and Mycoplasma synovialis(MS),two sets of specific primers and TaqMan probes were designed in this study based on the conserved regions of the 16S rRNA gene of two pathogens in NCBI.A dual TaqMan fluorescence quantitative PCR method for simultaneous detection of MG and MS was established by optimizing the reaction conditions,and the specificity,sensitivity,repeatability,and reliability of the method were verified.The results showed that this method could specifically amplify MG and MS without cross reactivity with 21 pathogens.The sensitivity experiment results showed that the detection limits of this method for MG and MS were 5.40×10 1 copies/μL and 6.60 × 10 1 copies/μL,and the sensitivity was 10 to 100 times higher than that of known methods.In addition,the re-sults of repetitive experiments showed that the coefficient of variation within and between groups was less than 1％.Compared with the single PCR amplification method in NY/T 553-2015,the positive sample detection coincidence rate,negative sample detection coincidence rate,and total sample detection coincidence rate were all 100.00％,indicating the strong reliability of this method.Using this method to detect 84 suspected Mycoplasma infected chicken samples,the results showed that the MG positivity rate was 32.14％(27/84),the MS positivity rate was 22.62％(19/84),and the positivity rate of samples infected with MG and MS was 16.67％(14/84).Concurrent-ly,182 healthy chicken cloacal swab samples,118 healthy chicken nasal swab samples,and 74 chicken farm environmental samples were detected,and the results showed that all samples were positive for Mycoplasma.The above results indicate that this method can be applied to the detec-tion of various clinical samples.In summary,the method established in this study had the advanta-ges of high specificity,high sensitivity,and good reproducibility.It could be used for clinical differ-ential diagnosis,epidemiological investigation,and pathogen purification of MG and MS infections.

Objective To validate the diagnostic performance and risk stratification ability of an AI-based recognition system(PE-AI)for pulmonary embolism(PE)using computed tomography pulmonary angiography(CTPA)so as to analyze its diagnostic value in clinical practice.Methods A total of 416 patients with suspected PE who underwent CTPA from January 1,2023 to December 10,2023 at our hospital were included in this study.Two junior radiologists and PE-AI separately detected and diagnosed emboli in the collected cases by double-blind method,and recorded the diagnosis time respectively.Three senior radiologists reviewing with clinical follow-up results were used as the gold standard in this study.Diagnostic performance was evaluated by using the receiver operating characteristic(ROC)curve analysis and Delong-t test.For positive cases,the pulmonary artery obstruction index(PAOI)calculated by AI and manually were collected respectively and consistency analysis was performed.Results The area under the curve(AUC)of PE-AI,manual and combined diagnosis was 85.6％,90.8％and 95.1％,respectively,which differed significantly(P＜0.05).The reading time of PE-AI[(0.16±0.07)min]was significantly lower than the time of manual[(4.42±1.85)min,P＜0.001]and combined diagnosis[(4.58±1.84)min,P＜0.001].The PAOI measured by PE-AI and manually had high consistency(intraclass correlation efficient,ICC=0.80)in the subgroup analysis of confirmed cases.Conclusion AI can quickly identify pulmonary artery emboli in a short time and assist radiologists to improve diagnostic efficiency.At the same time,through the intelligent detection of PAOI,it is helpful for the risk stratification of patients with PE and optimizing the diagnosis and treatment pathway for pulmonary embolism.

Animal disease models are important biological tools for basic medical research.Establishing an ideal animal model is a critical prerequisite for acquiring reliable experimental data.By enabling molecular-level characterization,omics technologies can enhance the precision of animal model assessments,thereby improving the evaluation criteria.This review summarizes the current applications of omics in evaluating animal disease models,discusses their potential for quality control implementation,and proposes novel frameworks for standardized model validation.