Objective:To investigate the effects of brief mindfulness-based stress reduction(MBSR)on preoperative anxiety in pa-tients undergoing painless gastrointestinal endoscopy.Methods:We enrolled 100 patients scheduled to undergo elective painless gas-trointestinal endoscopy at The First Affiliated Hospital of Zhengzhou University from September 2024 to April 2025.The inclusion cri-teria were:age,18-60 years;body mass index,18.0-28.0 kg/m2;American Society of Anesthesiologists physical status,class Ⅰ orⅡ;and no gender restriction.The patients were assigned to experimental group(n=50)or control group(n=50)using a random num-ber table.A dedicated nursing team implemented the brief MBSR protocol.At 30 minutes before endoscopy,both groups underwent anxiety assessment using the Amsterdam Preoperative Anxiety and Information Scale(APAIS).All the patients received routine preop-erative education.Guided by the nurses,the experimental group received the brief MBSR intervention consisting of mindful body scan-ning,mindful breathing,and mindful music listening,for 12 minutes each at 30 and 15 minutes before the procedure.We recorded the APAIS score,bispectral index(BIS),heart rate(HR),systolic blood pressure(SBP),diastolic blood pressure(DBP),and mean arterial pressure(MAP)at 30 minutes before the procedure(T0),after brief MBSR(T1),and immediately before anesthesia induction(T2);the length of stay in the post-anesthesia care unit(PACU)and postoperative adverse reactions;and the APAIS score and degree of sat-isfaction of patients at discharge from the PACU(T3).Results:Com-(all P<0.05).However,no significant differences were observed be-pared with the control group,the experimental group exhibited sig-nificantly lower APAIS scores,significantly reduced BIS values,and significantly lower HR values at T1 and T2 and a significantly lower APAIS score and a significantly higher degree of satisfaction at T3 tween the groups in SBP,DBP,MAP,postoperative adverse events,or PACU length of stay at any time point(all P>0.05).Conclusion:Brief MBSR is an effective non-pharmacological intervention to cope with perioperative negative emotions in patients undergoing pain-less gastrointestinal endoscopy,which can alleviate preoperative anxiety,reduce electroencephalographic arousal,and improve patient satisfaction.

Objective To develop models for predicting response to chemotherapy combined with immunotherapy in patients with esophageal squamous carcinoma with various machine learning algorithms,and then select the optimal model.Methods A retrospective study was performed for 174 patients with esophageal squamous cell carcinoma undergoing chemotherapy combined with immunotherapy admitted in Department of Thoracic Surgery of the First Affiliated Hospital of Army Medical University from January 2022 to December 2023.The CT scans and clinical information were collected before treatment.They were randomly divided into a training set(n=122)and a testing set(n=52)in a ratio of 7∶3.CT radiomic features were extracted and selected,and then 5 machine-learning algorithms were employed to establish the prediction models,including radiomics model and clinical-radiomics model.Five-fold cross-validation was conducted on the training set,and the performance of the prediction models was evaluated on the testing set using receiver operating characteristic(ROC)curve and the F1 score.The best-performing model was further explained using local interpretable model-agnostic explanations(LIME)algorithm.Results Among the 174 patients,115(66.1%)achieved clinical remission.From the clinical information and CT images,1 clinical features and 10 radiomic features were identified.The area under of ROC curve(AUC)for the radiomics and clinical-radiomics models was 0.750(95%CI:0.616～0.883),and 0.766(95%CI:0.637～0.895),respectively.The F1 score of the optimal clinical-radiomics model was 0.829.LIME algorithm indicated that this best model demonstrated reliability in predicting individual samples.Conclusion The clinical-radiomics prediction model based on machine learning algorithm performs well,and can provide a reference for doctors'clinical decision-making by predicting the response to chemotherapy combined with immunotherapy in patients with esophageal squamous cell carcinoma.

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.

BackgroundDementia seriously affects the quality of life and lifespan of elderly people， with Alzheimer's disease （AD） being the most common type of dementia. Previous studies have suggested that gout may reduce the risk of developing AD， but the causal relationship between the two still requires further research. ObjectiveTo investigate the potential causal relationship between gout and AD through a two-sample Mendelian randomization （MR） analysis， so as to provide references for the prevention and treatment of AD. MethodsData from Genome-Wide Association Studies （GWAS） extracted in 2024 were analyzed， using pooled data on gout （6 810 cases in the case group and 477 788 cases in the control group） published by UK Biobank in 2021 as the exposure variable， and data on AD （3 899 cases in the case group and 214 893 cases in the control group） published by FinnGen in the same year as the outcome variable. The inverse-variance weighted， MR-Egger regression， weighted median estimation， simple model and weighted model were used to analyze the potential causal relationship between gout and AD. Pleiotropic effects were assessed using MR-Egger regression. Heterogeneity assessment was conducted using Cochran's Q test. The leave-one-out analysis was carried out for sensitivity analysis. And a funnel plot was drawn to detect potential publication bias. ResultsThe inverse-variance weighted analysis demonstrated a negative causal relationship between gout and AD （OR=0.004， 95% CI： 0~0.700， P<0.05）. The plot resembled a symmetrical inversed funnel， indicating the absence of publication bias. No heterogeneity was detected by Cochran's Q test. The MR-Egger regression indicated no significant horizontal pleiotropy. Concerning the reverse directions， no significant associations between AD and gout were noted. ConclusionThere is a negative causal relationship between gout and AD， with gout potentially reducing the risk of developing AD. ［Funded by The Third Batch of Social Welfare and Basic Research Projects （Medical and Health） of Zhongshan City in 2022 （number， 2022B3017）］

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 investigate the antidepressant effects of Xiaoyao Pill (XYP) by exploring its interactions with gut microbiota and tryptophan metabolism. METHODS: Utilizing network pharmacology, the functional substance groups, key targets, and pathways of XYP in the treatment of depression were identified. The chronic unpredictable mild stress (CUMS) protocol was implemented in male Sprague-Dawley rats to establish depression model. Thirty rats were randomly divided into 3 groups according to their body weight (10 for each): control, CUMS and XYP groups (1.8 g/kg). After 28-day interventions, behavioral phenotyping including sucrose preference test (SPT) and open field test (OFT) were performed. Biochemical validation encompassed enzyme-linked immunosorbent assay for serum cortisol, hematoxylin-eosin histopathology, and immunohistochemistry. Liquid chromatography-mass spectrometry was utilized to profile serum metabolites, while fecal samples underwent metagenomic sequencing for gut microbiota characterization. RESULTS: Network pharmacology studies predicted that key components can protect the nervous system by regulating inflammatory pathways through the blood-brain barrier. SPT and OFT showed that XYP treatment significantly ameliorated depressive-like behaviors (all P<0.05). XYP treatment also restored hippocampal neuronal density, increased serum neurotransmitter levels of neurotransmitters such as 5-hydroxytryptamine and vasoactive intestinal peptide, and while suppressing inflammatory markers such as tumor necrosis factor-alpha, interleukin-1 beta (IL-1 β), and IL-6 (all P<0.05). Metagenomics revealed significant restructuring of gut microbiota, notably the regulation of Parabacteroides distasonis (P<0.05). Non-targeted metabolomics analysis showed that the level of metabolites in the tryptophan and kynurenine pathway significantly changed (variable importance in the projection >1, P<0.05), and the change of metabolic flux was significantly correlated with behavioral improvement (P<0.05). CONCLUSIONS XYP exerts antidepressant effects by increasing neurotransmitter levels, reducing inflammatory makers and modulating Parabacteroides distasonis. Through further exploration of metabolomics, we found that XYP may play a protective role in depression by regulating tryptophan metabolism.
Animals ; Tryptophan/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Gastrointestinal Microbiome/drug effects* ; Rats, Sprague-Dawley ; Depression/blood* ; Male ; Stress, Psychological/drug therapy* ; Behavior, Animal/drug effects* ; Rats ; Chronic Disease ; Hippocampus/drug effects*