Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Objective To preliminary explore the imaging manifestations of digital breast tomosynthesis (DBT) and contrast-enhanced mammography (CEM) in triple-negative breast cancer (TNBC) patients with different levels of human epidermal growth factor receptor 2 (HER2) expression. Methods A retrospective analysis was conducted on TNBC patients who underwent preoperative DBT or CEM examinations at Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2018 to December 2019 and Shanghai Second People’s Hospital from January 2022 to May 2025. Clinical data, pathological and immunohistochemical results, and imaging data were collected. Results A total of 69 TNBC patients pathologically confirmed as invasive ductal carcinoma were included, among which 34 underwent DBT and 35 underwent CEM. Among these patients, 34 (49.28%) had HER2-low expression and 35 (50.72%) had HER2-zero expression. DBT results showed that the proportion of spiculation signs in HER2-low group (n＝14) was significantly higher than that in HER2-zero group (n＝20; P＝0.009, P_adj＝0.045). However, there were no significant differences in breast density type, mass shape, or calcification between the two groups. CEM results showed that on low-energy images, the proportion of spiculation signs in the HER2-low group (n＝20) was higher than that in the HER2-zero group (n＝15; P＝0.011, P_adj＝0.077). Results of CEM showed that on reconstructed images, differences in background parenchymal enhancement and mass enhancement patterns between the two groups were not statistically significant; in both groups, heterogeneous enhancement was the most common, followed by homogeneous enhancement, with ring enhancement being the least common. Conclusions TNBC with low HER2 expression and TNBC with zero HER2 expression may have potential differences in the presentation of spiculation signs on DBT. However, the correlation between CEM manifestations and TNBC with different HER2 expression levels requires further research.

Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective:To identify the serotype and genotype characteristics of the first cluster infection of Brucella in Nujiang Lisu Autonomous Prefecture of Yunnan Province. Methods:The information of seven suspected cluster brucellosis cases reported in Lanping County, Nujiang Lisu Autonomous Prefecture in April 2023 were collected, blood samples were collected, and the strains were isolated and cultured. Serological methods were employed for brucellosis diagnosis, bacterial species identification was performed using BCSP31-PCR and AMOS-PCR. Multilocus locus variable-number tandem repeat analysis (MLVA) was conducted for strain genotyping, followed by phylogenetic analysis comparing the strains with those from other regions of China.Results:All seven cases were diagnosed with brucellosis, they were all villagers from the same village and had daily contact with sheeps. Four suspected Brucella strains were isolated, identified as Brucella melitensis biotype by BCSP31-PCR and AMOS-PCR. The four isolated strains exhibited identical MLVA-16 genotype, with MLVA-8 genotype 42 and MLVA-11 genotype 180, belonging to the Eastern Mediterranean lineage. Compared with the MLVA-16 of the isolated strains from other regions of China, the four isolated strains formed an independent cluster. Conclusion:The first cluster infection of Brucella in Nujiang Lisu Autonomous Prefecture of Yunnan Province is caused by Brucella melitensis biotype, and the four isolated strains have showed unique MLVA genotype.

Objective:To learn about the geographical distribution and bio-tying diversity characteristics of Brucella strains isolated in Yunnan Province. Methods:From March 2017 to December 2023, 516 suspected Brucella strains were collected from brucellosis surveillance sites and hospitals in Yunnan Province, and Yunnan Institute of Endemic Disease Control and Prevention. The Brucella isolates were confirmed to genus level by BCSP31-PCR, and subsequently identified to species and biovar level using conventional biotyping methods and AMOS-PCR. The geographical distribution of the strains was visualized using ArcGIS 10.8 software, simultaneously analyze the general characteristics of brucellosis patients. Results:Among the 516 suspected Brucella strains, 514 strains were isolated from patient blood samples and 2 strains were isolated from sheep blood samples. BCSP31-PCR identification showed that all strains were Brucella spp. The results of conventional biotyping and AMOS-PCR identification revealed that the isolates comprised 514 Brucella melitensis strains (16 strains of Brucella melitensis biovar 1 and 498 strains of Brucella melitensis biovar 3), one Brucella abortus (biovar 1) strain, and one Brucella canis strain. The strain was distributed in 69 counties/cities of 13 prefectures/cities in Yunnan Province, involving 390 administrative villages in 186 townships. Brucella melitensis was the dominant epidemic strain, and the largest number of Brucella melitensis was distributed in Kunming City( n = 205), followed by Honghe Hani and Yi Autonomous Prefecture ( n = 98) and Qujing City ( n = 72). Brucella abortus was only distributed in Lincang City ( n = 1), and Brucella canis was distributed Wenshan Zhuang and Miao Autonomous Prefecture ( n = 1). The age range of 514 brucellosis patients ranged from 10 months to 88 years, with the majority being between 40 and 60 years old (52.72%, 271/514). The predominant occupational group was farmers (89.11%, 458/514), followed by students (5.06%, 26/514). Conclusion:Brucella exhibits a wide distribution and species/biovar diversity in Yunnan Province, with infection among the farming population emerging as a serious public health problem in the area.

Objective To systematically evaluate the factors that promote and hinder exercise in frail older adults,and to provide references for the formulation of exercise intervention programs.Methods We searched PubMed,Web of Science,Embase,CINAHL,Cochrane library,CNKI,Wanfang,VIP database,and China Biomedical Literature Database for qualitative studies on exercise facilitators and hindrances in frail older adults,and the search time period was from the establishment of the databases to September 1,2024.The quality of the literature was evaluated using the Joanna Brigg Institute Australian Centre for Evidence-Based Health Care Quality Assessment Criteria for Qualitative Research(2016),and the results were integrated by integrating methods.Results A total of 18 studies were included,and 72 research results were extracted,and 10 categories were summarized.The final synthesis included 2 integrated results:the facilitators included personal exercise motivation,physical and psychological benefits,positive interpersonal interactions,multiple social support systems and person-centred exercise programme;the impediments included underlying diseases and somatic functional limitations,negative psychological status,low health literacy,family role conflicts and limits of the environment.Conclusion Exercise for frail older adults is affected by a variety of factors.Healthcare professionals should improve the positive perception of exercise for frail older people and help them overcome psychological barriers;establish an all-round support system to enhance the sense of social contact of the frail elderly;formulate a personalised exercise programme with a human-centred approach to enhance the motivation of the frail elderly.

AIM:To investigate the effects and underlying mechanisms of paeoniflorin(PF)on lipopolysac-charide(LPS)-induced intestinal injury in septic mice,using a combination of network pharmacology,molecular docking,and animal experiments.METHODS:Network pharmacology was used to identify key active components and therapeutic targets of Red Peony for treating sepsis.Molecular docking was performed to explore the binding affinity be-tween PF and silent information regulator 1(SIRT1).An LPS-induced mouse model of sepsis with intestinal injury was es-tablished.Samples were collected 24 h after modeling,and hematoxylin-eosin(HE)staining was performed to observe pathological changes in intestinal tissues.Chiu's scoring system was utilized to evaluate the extent of intestinal injury.En-zyme-linked immunosorbent assay(ELISA)was employed to measure levels of inflammatory factors in intestinal tissues,including interleukin-1β(IL-1β)and IL-18,as well as indicators of intestinal permeability such as diamine oxidase(DAO)and intestinal-type fatty acid-binding protein(I-FABP),alongside serum levels of D-lactate and the aerobic gly-colysis product L-lactate.Western blot analysis was performed to assess changes in protein levels of SIRT1,M2-type pyru-vate kinase(PKM2),and NOD-like receptor protein 3(NLRP3)in intestinal tissues.RESULTS:Network pharmacolo-gy suggested that paeoniflorin,an active component of Red Peony,treats sepsis by targeting SIRT1 among other proteins.Molecular docking revealed a strong binding affinity of PF with SIRT1.In vivo experimentation revealed significant patho-logical damage in intestinal tissues in the LPS group compared to the control group as evidenced by HE staining.Chiu's score,along with levels of IL-1β,IL-18,D-lactate,and L-lactate were significantly elevated,while DAO and I-FABP levels were reduced(P＜0.05).SIRT1 expression decreased,while PKM2 and NLRP3 levels increased(P＜0.05).In contrast,the LPS+PF group displayed reduced intestinal histopathological injury,lower Chiu's scores,and decreased levels of IL-1β,IL-18,D-lactate,and L-lactate,along with increased DAO and I-FABP levels(P＜0.05).Notably,SIRT1 protein expression increased while PKM2 and NLRP3 levels decreased(P＜0.05).Furthermore,compared to the LPS+PF group,the LPS+PF+EX527 group exhibited exacerbated intestinal histopathological injury,increased Chiu's scores,as well as elevated levels of IL-1β,IL-18,D-lactate,and L-lactate,alongside reduced DAO and I-FABP levels(P＜0.05),decreased SIRT1 expression,and increased PKM2 and NLRP3 levels(P＜0.05).CONCLUSION:Paeoni-florin effectively alleviates intestinal injury in mice with sepsis,potentially through the upregulation of SIRT1 expression and the inhibition of PKM2-mediated aerobic glycolysis,which subsequently reduces the activation of NLRP3 inflamma-somes,mitigates the release of inflammatory factors,and lessens intestinal inflammation.

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.