Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveTo understand the infection characteristics and drug resistance of carbapenem-resistant Serratia marcescens (CRSM) in a general hospital in Shanghai, and to provide a theoretical basis for clinical anti-infective treatment and prevention of drug-resistant bacteria. MethodsClinical data on cases with CRSM infections detected in clinical specimens at a gradeⅢ level A general hospital in Shanghai from June 2022 to June 2024 were retrospectively collected, and their clinical distributions, factors of hospital-acquired infections, prognosis, and drug-resistant situation were analyzed simultaneously. ResultsA total of 38 cases with CRSM were detected from June 2022 to June 2024, and the number of CRSM strains accounted for 25.00% (38/152) of the number of SM strains. The 38 CRSM infection samples were all derived from sputum. CRSM were distributed in 9 clinical departments, and the top 3 departments having the highest percentages of CRSM among SM strains, were intensive care unit (ICU) (78.79%, 26/33), gastrointestinal surgery department (57.14%, 4/7), and thyroid hernia surgery department (50.00%, 1/2). Among the 38 patients with CRSM infections, 8 cases were identified as hospital-acquired infection, resulting in a hospital-acquired infection rate of 21.05. The mortality rate of the 38 cases of CRSM infected patients within 30 days after detection of CRSM was 23.68% (9/38). The results of multivariate logistic regression analysis showed that sequential organ failure assessment (SOFA) score ≥6.5 points (OR=15.33, P<0.001), septic shock (OR=4.85, P=0.032), and suffering from neoplastic diseases (OR=0.12, P=0.018) were the related factors for death within 30 days after the detection of CRSM in patients with CRSM infection. The results of drug sensitivity test showed that the 38 cases of CRSM exhibited 100.00% (38/38) sensitivity to trimethoprim/sulfamethoxazole, tigecycline, or ceftazidime/avibactam; demonstrated high resistance toβ-lactams except for ceftazidime (18.42%, 7/38), the latter of which was one of the third-generation of cephalosporins; showed elevated resistance to fluoroquinolones [levofloxacin (89.47%, 35/38), ciprofloxacin (94.74%, 36/38)]; maintained good tetracycline sensitivity [doxycycline (97.37%, 37/38), minocycline (76.32%, 29/38)]; and displayed high susceptibility to the aminoglycoside gentamicin (94.74%, 36/38) and elevated resistance to tobramycin (86.84%, 34/38). The detection rate of serine carbapenemase in the 38 strains of CRSM was 100.00%, while all strains tested negative for metallo-β-lactamases. ConclusionFrom June 2022 to June 2024, the detection rate of CRSM in a gradeⅢ level A general hospital in Shanghai was relatively high, especially in the ICU. CRSM has a high resistance rate to commonly used antibacterial drugs such as the first and second-generation cephalosporins, quinolones, and polypeptide antibacterial drugs. Therefore the dynamics of drug-resistant bacteria should be tracked in a timely manner to guide the rational clinical application of antibacterial drugs.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Generative artificial intelligence (GAI) represents a prominent research focus in medicine, with medical education being a key application area. GAI demonstrates potential to enhance residency training efficacy through personalized instruction, automated assessment item generation, question bank updating, and intelligent scoring systems. However, current limitations exist regarding output accuracy and content consistency. To address these constraints, strategic measures are required: continuous GAI model refinement, development of standardized usage guidelines, enhanced data quality control, and implementation of human verification protocols for generated content. Concurrently, residents should proactively acquire GAI utilization skills to strengthen the practical application of theoretical knowledge. With these advancements, GAI is anticipated to evolve into a valuable asset for improving the efficiency and quality of residency training programs.

Objective: To investigate the detection of depressive symptoms and its influencing factors among middle school students in Huzhou City, so as to provide insights for improving the mental health levels among middle school students. Methods: From September to November 2024, a total of 4 729 middle school students from five counties (districts) in Huzhou City were selected through the stratified cluster random sampling method. Demographic information, lifestyle, and school bullying were collected through questionnaire surveys. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D). Factors affecting depressive symptoms among middle school students were analyzed using a multivariable logistic regression model. Results: A total of 4 729 middle school students were surveyed, including 2 200 boys (46.52%) and 2 529 girls (53.48%). Depressive symptoms were detected in 1 026 students, with a detection rate of 21.70%. Multivariable logistic regression analysis showed that girl (OR=1.960, 95%CI: 1.659-2.317), high school (ordinary high school, OR=1.789, 95%CI: 1.465-2.186; vocational high school, OR=1.581, 95%CI: 1.105-2.263), consumption of sugar-sweetened beverages >0 time/day (<1 time/day, OR=1.363, 95%CI: 1.009-1.841; ≥1 time/day, OR=1.568, 95%CI: 1.098-2.239), fried food intake ≥1 time/day (OR=1.890, 95%CI: 1.291-2.769), skipping breakfast daily (OR=2.178, 95%CI: 1.825-2.599), TV viewing time ≥2 hours/day (OR=1.457, 95%CI: 1.154-1.838), insufficient sleep duration (OR=1.761, 95%CI: 1.422-2.181), smoking (OR=2.798, 95%CI: 1.834-4.269), alcohol consumption (OR=2.282, 95%CI: 1.861-2.798), experiencing school bullying (OR=5.440, 95%CI: 3.148-9.402) and parental physical/verbal abuse (OR=3.954, 95%CI: 3.189-4.902) were associated with a higher risk of depressive symptoms among middle school students. Conversely, the middle school students who engaged in moderate-to-vigorous physical activity ≥3 times/week (OR=0.784, 95%CI: 0.668-0.921) and attended physical education classes ≥3 sessions/week (OR=0.736, 95%CI: 0.613-0.884) were associated with a lower risk of depressive symptoms. Conclusion The prevalence of depressive symptoms among middle school students in Huzhou City was lower than national average, and was influenced by dietary habits, physical exercise, sleep duration, smoking, alcohol consumption, and experiencing school bullying.