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.

OBJECTIVE: To explore the rules of acupoint selection and compatibility of acupuncture and moxibustion in treatment of chronic cough using data mining. METHODS: The ancient and modern medical record cloud platform, and the databases, i.e. CNKI, Wanfang, VIP, EMbase, Web of Science and PubMed, were searched to screen the ancient and modern literature on acupuncture and moxibustion treatment of chronic cough. The prescription database was established for acupuncture and moxibustion treatment of chronic cough, and the analysis conducted on the frequency and use percentage in the aspects of intervention measures, acupoint selection, acupoint distribution, meridian tropism, special points and acupoint combination, as well as the association rules and clustering rules of acupoint selection. The subgroup analysis was performed in accordance with the etiology of chronic cough and intervention measures. RESULTS: A total of 106 articles were included and 158 prescriptions were extracted. The intervention measures were acupuncture, moxibustion, herbal medication and the combination of several measures. The high-frequency acupoints included Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17), Shenshu (BL23), Lieque (LU7), Dingchuan (EX-B1), Tiantu (CV22), and Fenglong (ST40). These acupoints are mainly distributed on the back, lumbar region, chest and abdomen. The involved meridians were bladder meridian of foot-taiyang, conception vessel, and lung meridian of hand-taiyin. The special points covered back-shu points, crossing points and five-shu point. Regarding the compatibility of acupoints, the combination of upper and lower points, and the combination of front and back points were predominant in treatment. The analysis of association rules found that the support of Feishu (BL13)→Zusanli (ST36) was the highest; the cluster analysis obtained 8 clusters of acupoints. The acupoint compatibility and overall rules were similar when cough variant asthma (CVA) or the mixed reasons were involved, and the local treatment approach was adopted if the etiology of disease was related to upper airway cough syndrome (UACS) and gastroesophageal reflux cough (GERC). The acupoint selection was similar among different intervention measures. When two kinds of measures were combined in treatment, Feishu (BL13), Pishu (BL20) and Zusanli (ST36) were the most common. CONCLUSION In treatment with acupuncture and moxibustion for chronic cough, the acupoints are selected on the affected local area, depending on syndrome differentiation, and focusing on back-shu points. The main acupoints are Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17) and Shenshu (BL23). The combined therapy is dominant with acupuncture, moxibustion and herbal medicine involved.
Acupuncture Points ; Moxibustion/history* ; Humans ; Cough/history* ; Acupuncture Therapy/history* ; Chronic Disease/therapy* ; Data Mining ; History, Ancient ; Meridians ; Chronic Cough

Hepatocellular carcinoma(HCC)is categorized into two major classes based on the heterogeneity of histological phenotypes:proliferative HCC and non-proliferative HCC.These classes exhibit distinct clinical,molecular and imaging characteristics.Within these two major categories,there exist multiple pathological subtypes,each demonstrating unique molecular and histological features that manifest differently in imaging findings.Additionally,the prognosis of these HCC pathological subtypes diverges from that of not-otherwise-specified HCC,and current clinical guidelines for their treatment remain unclear.This article aims to summarize the imaging manifestations and prognosis of the histopathological subtypes of HCC,so as to enhance identification and judgement of HCC subtypes,and to provide a theoretical basis for selecting appropriate therapeutic strategies.

In clinical practice,the diagnosis of hepatocellular carcinoma primarily relies on imaging findings.For cases with atypical imaging features or insufficient diagnostic specificity,pathological analysis remains essential.With the advancement of precision medicine,research focus has expanded from pure diagnostic evaluation to therapeutic efficacy prediction.Imaging-based prognostic biomarkers have emerged as a key research frontier in hepatocellular carcinoma management.Although accurate diagnosis remains paramount,current investigations increasingly prioritize the identification of biomarkers for treatment response prediction and outcome stratification.Recent studies demonstrate that radiological characteristics not only reflect tumor heterogeneity but also carry prognostic implications for hepatocellular carcinoma.These imaging biomarkers enable non-invasive outcome prediction and provide objective evidence to optimize therapeutic decision-making.This comprehensive review summarizes MRI-derived imaging features associated with hepatocellular carcinoma prognosis,aiming to guide personalized treatment strategies and ultimately improve survival outcomes for hepatocellular carcinoma patients.

Objective To observe the effects of a stepped early activity program combined with lower limb joint rehabilitation devices in mechanically ventilated patients in the intensive care unit(ICU).Methods Sixty mechanically ventilated patients admitted to the ICU of Tianjin First Central Hospital from October 2022 to June 2023 were selected as study subjects and randomly divided into an intervention group(n=30)and a control group(n=30)using a random number table.The control group received routine rehabilitation nursing combined with lower limb joint rehabilitation devices,while the intervention group was additionally treated with the stepped early activity program.The duration of mechanical ventilation,length of ICU stay,incidence of delirium,Medical Research Council(MRC)muscle strength scores,phase angle(PA),and skeletal muscle mass index(SMI)were compared between the two groups.Results The intervention group showed significantly shorter durations of mechanical ventilation and the length of ICU stay compared to the control group[mechanical ventilation time(days):9.20±4.51 vs.11.73±4.59,the length of ICU stay(days):10.73±5.37 vs.14.00±6.03,both P<0.05].Post-intervention MRC muscle strength scores,PA,and SMI significantly increased in both groups,with greater improvements observed in the intervention group[MRC muscle strength score:54.17±2.10 vs.50.17±3.51;PA(°):5.80±0.60 vs.5.49±0.54;SMI(kg/m2):6.87±0.46 vs.6.62±0.45,all P<0.05].No statistically significant difference was found in delirium incidence between the two groups[26.7%(8/30)vs.33.3%(10/30),P>0.05].Conclusion The combination of a stepped early activity program and lower limb joint rehabilitation devices effectively shortens mechanical ventilation time and the length of ICU stay,restores muscle strength,and promotes recovery in mechanically ventilated ICU patients,demonstrating significant clinical value.

This study was aimed at understanding the resistance status of dairy cow-derived Streptococcus strains in China,and providing scientific guidance for the rational use of antimicrobials and the development of new antimicrobials.Meta-analysis was used to explore the resistance of Streptococcus strains to 20 antimicrobials between 2000 and 2023.A total of 67 articles de-scribing 3 154 strains were included after a literature search,and a meta-analysis was conducted on the overall collection area according to time subgroups for 20 antimicrobials.Streptococci of dairy origin in China showed varying resistance rates(≥30％),as follows:penicillin(60％,95％CI=0.48-0.72),streptomycin(57％,95％CI=0.46-0.68),cotrimoxazole(56％,95％CI=0.28-0.82),lincomycin(51％,95％CI=0.26-0.76),tetracycline(49％,95％CI=0.40-0.59),doxycyc-line(42％,95％CI=0.24-0.60),clindamycin(41％,95％CI=0.28-0.54),ampicillin(39％,95％CI=0.27-0.52),e-rythromycin(37％,95％CI=0.28-0.45),kanamycin(36％,95％CI=0.20-0.54),and amoxicillin(30％,95％CI=0.10-0.53).On the basis of findings in the collection area,the resistance rates of dairy cow-derived Streptococcus to antimicrobials in Northeast China and Southwest China was generally high.The resistance rates of Streptococcus from dairy cattle to antimi-crobial drugs such as tetracycline,doxycycline,and lincomycin increased significantly over time.However,the resistance rates to antimicrobial drugs such as streptomycin,gentamicin,and enrofloxacin showed a significant decreasing trend.Dairy cow-de-rived Streptococcus had high resistance to some antimicrobials,and the resistance varied by region,because of differences in breeding and management.Monitoring of antimicrobial resistance rates,enhancing research on resistance mechanisms,and reg-ulating the use of antimicrobials remain necessary.

Single-cell assay for transposase-accessible chromatin sequencing(scATAC-seq)is a power-ful technique for studying cellular heterogeneity and gene regulatory networks,widely applied in epigenet-ic research.However,the complexity of data analysis workflows and high programming requirements have limited its broader adoption among non-programmer researchers.To address this issue,we developed Sig-nac.UIO,a modular and visual scATAC-seq analysis platform based on the R Shiny framework,integra-ting mainstream tools such as Signac and Seurat.The platform includes ten key modules covering quality control,cell filtering,dimensionality reduction,clustering,differential analysis,cell annotation,path-way enrichment,motif analysis,and transcription factor footprinting.Through a graphical user interface,users can perform full analyses and obtain interactive visualization results.The platform's stability and u-tility have been validated using a public PBMC dataset and it is currently deployed online(https://xula-bgdpu.org.cn/Signac.UIO),providing an efficient and user-friendly tool for single-cell epigenomics re-search.

Objective To explore the incidence and its influencing factors of transient severe motion(TSM)in the arterial phase of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced MRI.Methods The databases of China National Knowledge Network(CNKI),VIP,Wanfang,PubMed,and Embase were searched for studies on the incidence and influencing factors of TSM,and the search time was from the establishment of the databases to October 2024.Meta-analysis was performed via Stata 17.0 software.Results A total of 30 papers(33 studies)were finally included,totaling 12 565 patients.Meta-analysis results showed that the incidence of TSM in the arterial phase of Gd-EOB-DTPA enhanced MRI was 13.0％.The risk factors for TSM included age[odds ratio(OR)=1.03;95％confidence interval(CI)1.02-1.05;P＜0.001),chronic obstructive pulmonary disease(COPD)(OR=4.21;95％CI 1.76-10.09;P=0.001),and moderate-to-severe pleural effusion(OR=3.34;95％CI 1.69-6.63;P=0.001),while a previous usage history of Gd-EOB-DTPA(OR=0.56;95％CI 0.39-0.81;P=0.002)was a protective factor of TSM.Conclusion The incidence of TSM in the arterial phase of Gd-EOB-DTPA enhanced MRI is relatively high.Age,COPD,moderate-to-severe pleural effusion are risk factors for TSM,while the previous usage history of Gd-EOB-DTPA is a protective factor for TSM.

Objective To investigate the expression of regional cerebral oxygen saturation(rSO2)in preterm infants with brain injury(BIPI)and its relationship with amplitude-integrated electroencephalogram(aEEG)parameters and neurodevelopment.Methods Retrospectively,116 cases of BIPI(Bilateral Intra-ventricular Perforation)born in the hospital between February 2022 and February 2023 were selected as the study subjects.According to the Expert Consensus on the Diagnosis and Prevention of Premature Infant Brain Injury,these cases were categorized into mild,moderate,and severe groups,with 59,35,and 22 cases,respectively.The study compared the general characteristics of premature infants with different brain injury levels.Regression analysis was conducted to identify the factors affecting brain injury in premature infants,and correlation analyses were performed on aEEG scores,rSO2,and GMS scores.ROC curve analysis was used to evaluate the value of combining brain oxygen saturation monitoring with aEEG in predicting abnormal whole-body motor quality assessment.Results On the 3rd and 7th days after birth,severe brain-injured premature infants had significantly lower rSO2 and aEEG scores compared to those with mild and moderate brain injuries(P<0.05).At 7 days,these infants also had lower scores for graph continuity,sleep-wake cycles,lower boundary amplitude,bandwidth,total score,rSO2,gestational age,and birth weight,and a higher proportion of abnormal developmental outcomes(PR+CS)(P<0.05).Multivariate logistic regression analysis revealed that the 3-day aEEG total score(OR=0.448,95％CI:0.094～0.890),7-day aEEG total score(OR=0.384,95％CI:0.058～0.726),3-day rSO2(OR=0.574,95％CI:0.398～0.750),and 7-day rSO2(OR=0.431,95％CI:0.115～0.777)were all protective factors for brain injury in premature infants,P<0.05.Correlation analysis showed that brain oxygen saturation was negatively correlated with aEEG scores and overall motor quality.The prediction value for abnormal overall motor quality using 7-day rSO2,aEEG,and the combination of 7-day rSO2 and 7-day aEEG scores was as follows:the positive predictive value for rSO2 was 86.46％,the negative predictive value was 96.85％,the sensitivity was 92.31％,the specificity was 92.21％,and the cut-off value was 0.845;The positive predictive value(PPV)of aEEG was 78.26％,the negative predictive value(NPV)was 96.86％,the sensitivity was 89.74％,and the specificity was 92.21％,with a cut-off value of 0.820.The positive predictive value(PPV)of 7-day rSO2 combined with 7-day aEEG score was 89.04％,the NPV was 96.88％,the sensitivity was 94.90％,and the specificity was 93.51％,with a cut-off value of 0.884,P<0.05.ROC curve analysis showed that the AUC of 7-day rSO2+7-day aEEG score was 0.895,De-long test P<0.005,indicating high predictive value for overall exercise quality.Conclusion Combined with rSO2 and EEG,the prediction of overall motor quality is better,which may have clinical value for excluding high-risk children.