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 observe the effect of M1 bone marrow-derived macrophages （M1-BMDM） with Wnt5a knockdown on liver fibrosis and regeneration in a rat model of liver cirrhosis， and to investigate its gain-of-function effect compared with unmodified M1-BMDM. MethodsPrimary bone marrow-derived macrophages were isolated from rats and were polarized to M1 phenotype to construct M1-BMDM^Wnt5a-KD cells. A rat model of liver cirrhosis induced by CCl₄/2-AAF was established， and at the end of week 8， rats were randomly divided into model group， M1-BMDM group， M1-BMDM Wnt5a-knockdown empty vector group （M1-BMDM^KD-EV group）， and M1-BMDM Wnt5a-knockdown group （M1-BMDM^Wnt5a-KD group）， with 6 rats in each group. On the first day of week 9， the rats in each group were given a single injection of the corresponding cells via the caudal vein， along with an intraperitoneal injection of a CCR2 inhibitor. Six rats without any treatment were used as normal control group. Samples were collected at the end of week 12 to assess liver histopathology， serum liver function parameters， hepatic stellate cell activation， and the expression levels of mature hepatocyte markers. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the model group， all cell treatment groups had significant alleviation of liver inflammatory response and significant reductions in the activities of alanine aminotransferase and aspartate aminotransferase （AST） in serum （all P<0.01）， and the M1-BMDM^Wnt5a-KD group had a significantly lower serum level of AST than the M1-BMDM group （P<0.05）. The semi-quantitative analysis based on immunohistochemical staining showed that compared with the model group， all cell treatment groups had a significant reduction in the percentage of CD68-positive area （all P<0.05）， and compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had a significant reduction in the percentage of CD68-positive area and a significant increase in the percentage of CD163-positive area （both P<0.05）. Compared with the model group， all cell treatment groups had significant reductions in the mRNA expression levels of CD68 and tumor necrosis factor-α （all P<0.05） and the protein expression level of CD68 （all P<0.01）； compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had significant increases in the protein and mRNA expression levels of CD163 （both P<0.05）， significant reductions in the protein and mRNA expression levels of CD68 （both P<0.05）， and a significant reduction in the protein expression level of tumor necrosis factor-α （P<0.01）. Sirius Red collagen staining and alpha-smooth muscle actin （α-SMA） immunohistochemical staining showed that compared with the model group， all cell treatment groups had significant alleviation of liver collagen deposition and α-SMA-positive area， with the most significant changes in the M1-BMDM^Wnt5a-KD group， and compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had significantly smaller Sirius Red-positive area and α-SMA-positive area and a significantly lower content of hydroxyproline in liver tissue （all P<0.05）. Compared with the M1-BMDM^KD-EV group， the M1-BMDM^Wnt5a-KD group had significant reductions in the protein and mRNA expression levels of α-SMA and the mRNA expression level of COL-I and TGF-β （all P<0.05）. Compared with the model group， all cell treatment groups had a significant increase in the protein expression level of HNF-4α in liver tissue （all P<0.05）， and the M1-BMDM^Wnt5a-KD group had significantly higher protein and mRNA expression levels of HNF-4α and hepatocyte specific antigen than the M1-BMDM^KD-EV group （both P<0.05）. The M1-BMDM^Wnt5a-KD group had a significantly higher serum level of albumin than the M1-BMDM^KD-EV group （P<0.01）. Immunofluorescence co-staining showed that compared with the model group， all cell treatment groups had a significant increase in the number of cells stained positive for HNF and HNF-4α and Ki67 （all P<0.01）， and the M1-BMDM^Wnt5a-KD group had a significantly higher number of such cells than the M1-BMDM^KD-EV group （P<0.05）. ConclusionInhibition of Wnt5a expression enhances the therapeutic effect of M1-BMDM on rats with liver cirrhosis induced by CCl₄/2-AAF， which provides new ideas for enhancing the anti-cirrhotic effect of M1-BMDM through genetic modification.

Traditional Chinese medicine （TCM）， through its multi-target and systematic regulatory effects， has demonstrated unique advantages in the treatment of gastric precancerous lesions （GPL）. At present， TCM theoretical research on GPL is mainly reflected in three aspects， the integration of macroscopic syndrome differentiation， the inflammation-carcinoma transformation mechanism， as well as the systematization and scientization of theoretical inheritance from famous TCM practitioners. High-quality evidence-based research findings serve as the foundation for clinical practice guidelines on GPL， and TCM has gained international academic recognition in the field of GPL prevention and treatment. Research on TCM mechanisms has yielded a series of important outcomes in the aspects of signaling pathways， gene expression regulation， cellular epigenetics， histone modification， and intestinal microecology. It is proposed that future research on GPL should focus on four key directions， establishing multi-omics data， exploring targeted intervention strategies on key regulatory nodes， advancing the standardization process of integrated traditional Chinese and western medicine prevention and treatment technologies， and constructing stratified screening and intervention platforms. The in-depth integration of TCM microcosmic mechanism of action with its macroscopic syndrome differentiation and treatment system， coupled with interdisciplinary research， will provide valuable references for the clinical treatment and scientific research of GPL.

OBJECTIVE To investigate the mechanism of Shenling baizhu san （SLBZS） in ameliorating ulcerative colitis （UC）. METHODS Mice were randomly divided into normal group， model group， and low-， medium-， high-dose SLBZS groups （3， 6， 12 g/kg）， with 10 mice in each group. Except for the normal group， mice in other groups were given free access to 3% dextran sulfate sodium solution for 7 days to establish UC models. Simultaneously， mice in each group were intragastrically administered corresponding medicinal liquid or double-distilled water once a day for consecutive 7 days. After the last administration， the histopathological morphology of colon tissues was observed； the serum levels of inflammatory factors including tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β） and IL-18 were detected； the total bile acid contents in liver， gallbladder and colon tissues were determined； the expression level of NOD-like receptor family pyrin domain-containing protein 3 （NLRP3） in colon tissues was tested. The expression levels of flora metabolism-related proteins [G protein-coupled receptor 41（GPR41），GPR43，farnesoid X receptor （FXR）， G protein-coupled bile acid receptor 1 （TGR5）， flavin-containing monooxygenase 3 （FMO3）， cytochrome P450 family 27 subfamily A member 1 （CYP27A1）， CYP7A1] in liver or colon tissues， as well as the proteins related to Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB）/NLRP3 inflammatory axis [TLR4， NF-κB， phosphorylated NF-κB （p-NF-κB）， myeloid differentiation factor 88 （MyD88）， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， caspase-1] in colon tissues were measured. RESULTS Compared with the model group， the colon tissue injury and inflammatory cell infiltration were alleviated in medium- and high-dose SLBZS groups. The serum levels of TNF-α， IL-1β and IL-18， total bile acid contents in liver and colon tissues， as well as the protein expression levels of FMO3 and CYP7A1 in liver tissues， TLR4， p-NF-κB， NF-κB， MyD88， NLRP3， ASC and caspase-1 in colon tissues were significantly decreased （P＜0.05）. Meanwhile， the total bile acid content in gallbladder， the protein expression levels of GPR41 and GPR43 in colon tissues， along with CYP27A1， FXR and TGR5 in liver tissues were significantly increased （P＜0.05）. CONCLUSIONS SLBZS may relieve colonic inflammatory injury and ameliorate UC by regulating the expression of flora metabolism-related proteins and inhibiting the abnormal activation of TLR4/NF-κB/NLRP3 inflammatory axis.

ObjectiveTo investigate the spontaneous premature cardiac aging in SHJH^hr mice. MethodsA comparative study was conducted between SHJH^hr mice (SHJH^hr group) and wild-type ICR mice (WT group) at different ages (10 and 24 weeks). Cardiac function was analyzed using a small animal in vivo ultrasound imaging system. After euthanasia, organs were collected and weighed to assess the extent of cardiac atrophy. Cardiac pathological damage was observed using hematoxylin-eosin (HE) staining. Cardiac fibrosis was analyzed using Masson staining. Myocardial cell area was analyzed after wheat germ agglutinin (WGA) staining. The activities of oxidative damage indicators in myocardial tissue, including superoxide dismutase (SOD), glutathione peroxidase (GPX), and catalase (CAT), as well as the content of 8-hydroxy-2'-deoxyguanosine (8-OHdG), were measured using enzyme-linked immunosorbent assay. Real-time fluorescence quantitative PCR was used to measure the mRNA expression levels of factors associated with inflammation, fibrosis, and oxidative stress. Colorimetric assay was used to measure malondialdehyde (MDA) levels. ResultsCompared to WT group mice of the same age, 10-week-old mice in the SHJH^hr group showed no significant differences in stroke volume (SV), ejection fraction (EF), fractional shortening (FS), or heart and lung weights. However, at 24 weeks of age, mice in the SHJH^hr group had significantly lower SV, EF, and FS values compared to mice of the same age in the WT group (P<0.05), with no significant change in lung weight but a significant reduction in heart weight (P<0.05). Histological analysis of heart tissue from 24-week-old mice revealed no significant difference in cardiac fibrosis levels between SHJH^hr and WT groups, but WGA staining showed a significant reduction in myocardial cell area in mice in the SHJH^hr group (P<0.05). PCR analysis revealed a significant downregulation of mRNA levels of oxidative stress factors Sod2, Gpx1, and Cat genes (P<0.05). Biochemical assays indicated significantly reduced activities of oxidative damage-related enzymes SOD, GPX, and CAT in myocardial tissue (P<0.05), while the levels of oxidative damage markers 8-OHdG and MDA significantly increased (P<0.05). ConclusionMice in the SHJH^hr group exhibit premature cardiac aging, which may be associated with oxidative stress damage in myocardial tissue.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

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.

Readiness for Hospital Discharge(RHD)refers to a multidimensional assessment of a patient's ability to transition safely from hospital to home,encompassing physiological stability,psychological preparedness,and social support adequacy.For patients requiring Home Nutrition Support(HNS),discharge readiness is particularly critical due to their heightened need for post-discharge specialized care,which significantly influences long-term recovery and quality of life.This paper reviews the concept,influencing factors,and unmet needs of RHD in patients with HNS and proposes targeted strategies to enhance discharge preparedness.By addressing gaps in current practices,we aim to optimize RHD in this vulnerable population and provide clinicians with evidence-based guidance for developing effective discharge plans.

Objective To describe and analyze the influencing factors of psychological crisis among college students with borderline personality disorder(BPD)traits.Methods Self-compiled general information questionnaire,personality assessment inventory-borderline features scale(PAI-BOR),brief version of the difficulties in emotion regulation scale(DERS-16),short version of the UPPS-P impulsive behavior scale(S-UPPS-P),patient health questionnaire-9(PHQ-9),and psychological crisis screening questionnaire were used to survey 340 college students in Shanghai selected by convenience sampling.Participants were assigned to BPD trait or non-BPD trait groups based on PAI-BOR scores.The risk of psychological crisis and influencing factors of the 2 groups were analyzed.Results A total of 323 valid questionnaires were collected.The average age of the participants was(21.39±2.98)years old,and 164 participants were male and 159 were female.The detection rate of borderline personality disorder traits was 19.20%(62/323).There were significant differences in family relationship,experiences of major changes,difficulties in emotion regulation,impulsivity and depression between the 2 groups(all P＜0.05).The detection rates of mild psychological crisis and severe psychological crisis were significantly higher in the BPD trait group than in the non-BPD trait group(both P＜0.001).Stepwise multinomial logistic regression analysis showed that sensation seeking and difficulties in emotion regulation were risk factors for mild psychological crisis in the BPD trait group(both P＜0.05),and sensation seeking and history of mental disorders in close relatives were risk factors for severe psychological crisis in the BPD trait group(both P＜0.05).Conclusion BPD traits in college students are associated with the risk of psychological crisis.Sensation seeking,difficulties in emotion regulation,and history of mental disorders in close relatives are risk factors of psychological crisis among students with BPD traits.Colleges and universities should put more emphasis on the mental health of students with BPD traits,and formulate targeted preventive measures.