OBJECTIVE To compare the risk of pneumonitis and interstitial lung disease （ILD） associated with different antibody-drug conjugates （ADC） in the treatment of breast cancer. METHODS CNKI， VIP， PubMed， Embase and other Chinese and English databases， and ClinicalTrials.gov were searched from the inception to June 15， 2025. Randomized controlled trials （RCT） about pneumonitis and ILD associated with ADC （T-DM1， T-DXd， SG， Dato-DXd， SHR-A1811，ARX788， and T-Duo） in the treatment of breast cancer were included. After literature screening， data extraction， and quality assessment， a network meta-analysis was conducted using Stata 17.0 software， and the surface under the cumulative ranking curve（SUCRA） of all interventions were ranked. RESULTS A total of 19 RCTs involving 10 556 patients were included. The overall incidence of pneumonitis with ARX788 and T-DXd was significantly higher than that with T-DM1， T-DM1 plus TPC（T-DM1combined with pertuzumab or atezolizumab）， TPC（treatment of primary care）， and SG （ P ＜0.05）， for grade 1-2 pneumonitis， ARX788 and T-DXd showed significantly higher incidence than T-DM1， T-DM1 plus TPC， and TPC （ P ＜0.05）. For both indicators， ARX788 and T-Duo were ranked as the top two by SUCRA. For the incidence of grade ≥3 pneumonitis， T-DXd and T-DM1 were significantly higher than SG （ P ＜0.05）， T-Duo and Dato-DXd were ranked as the top two by SUCRA. For overall incidence of ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， TPC， and SG （ P ＜0.05）， for the incidence of grade 1-2 ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， and TPC （ P ＜0.05）， for the incidence of grade ≥3 ILD， ARX788 was significantly higher than TPC （ P ＜0.05）. For three indicators above， ARX788 and T-DXd combined with pertuzumab were ranked as the top two by SUCRA. CONCLUSIONS Compared with other ADCs， ARX788 and T-Duo are associated with a higher risk of pneumonitis and ILD in patients with breast cancer.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Depression,as a severe psychological and psychiatric disorder,significantly impairs the long-term physical and mental health of patients.Current depression detection methods are plagued by strong subjectivity,limited techniques,and inadequate intelligence.Previous studies have mostly relied on single-modal signal analysis,making it difficult to comprehensively reflect the multidimensional characteristics of depression.Based on the independently developed intelligent depression detection system,wearable devices are used to collect prefrontal dual-lead EEG signals,PPG signals,and single-lead ECG signals.Data from 30 patients with depression and 40 healthy controls are collected and analyzed.A multimodal depression recognition model named RBLF-Net is proposed,which integrates spatiotemporal features,weighted attention,and random forests to utilize the multi-signal features for depression recognition.The model exhibits superior performance in the five-fold cross-validation,achieving a classification accuracy of 81.43%,a precision of 81.02%,and a recall rate of 81.25%,outperforming other comparative models,and thus providing an intelligent analysis approach for depression recognition from the perspective of multi-modal fusion.

Objective:To explore the influence of value orientation brief therapy (VBT) on anxiety and depression symptoms, social function, coping style and self-acceptance level of major depressive disorder adolescents with anxious distress.Methods:From June 2021 to June 2022, seventy adolescent major depressive disorder patients with anxious distress were included in the study, who were randomly divided into study group(35 people, 31 people completed)and control group (35 people, 30 people completed). The study group was given routine treatment combined with VBT, while the control group was given routine treatment only. Before and after treatment, Hamilton anxiety scale(HAMA), Hamilton depression scale (HAMD), social disability screening schedule (SDSS), coping style questionnaire(CSQ) and self-acceptance questionnaire (SAQ) were used to evaluate the two groups, and SPSS 26.0 software was used to statistically analyze the data of the two groups. Paired sample t-test was used for intra-group comparison, and independent sample t-test was used for inter-group comparison. Results:After 6 weeks of treatment, the scores of HAMA((6.03±3.58) vs (14.03±7.06), t=5.55, P<0.01), HAMD((8.77±5.52 ) vs (16.50±7.59), t=4.56, P<0.01)and SDSS((4.23±1.50) vs (6.63±0.96), t=7.43, P<0.01)in the study group were significantly lower than those in the control group, the differences were statistically significant. The scores of self-acceptance((19.23±1.33) vs (13.47±1.46), t=-16.12, P<0.01)and self-evaluation ((19.87±2.87) vs (12.77±1.68), t=-11.75, P<0.01) in the SAQ scale and the scores of problem-solving((8.71±2.30) vs (6.23±3.45), t=3.31, P<0.05) and rationalization ((6.20±3.11) vs (4.67±2.43), t=2.13, P<0.05) in the CSQ questionnaire were significantly higher than those in the control group, the differences were statistically significant. The total effective rate of the study group(90.3%(28/31) vs 66.7%(20/30), χ2=5.09, P<0.05) was significantly higher than that of the control group, the difference was statistically significant. Conclusion:The effect of routine treatment combined with VBT is better, which can effectively improve anxiety and depression symptoms, social function and coping style, and enhance self-acceptance and self-evaluation in adolescent major depressive disorder patients, which is worthy of clinical application.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective To establish a high-throughput non-targeted screening and prioritization method for emerging pollutants(EPs)in sewage using direct injection high-resolution mass spectrometry(HRMS).Methods The sewage samples were filtered by membrane filter and directly subjected to the liquid chromatography-time-of-flight mass spectrometer based on a method modified from our previous study.A C18 chromatographic column was applied for a gradient elution separation,and accurate mass and mass spectral fragment information were obtained through the MS full scan mode and MS/MS DIA data collection mode.After peak detection and alignment,the features from the raw data through open source software MZmine 3,and then high-throughput screening strategies such as MassBank and PubChem databases were used for compound annotation.Finally,the candidate features were confirmed with chemical standards by compared their retention time and mass spectrum fragmentation ion peaks.Results 13 EPs were identified,including 7 industrial chemicals,4 pharmaceuticals,1 pesticide and 1 metabolite.High detection rates were observed for metformin(86.2％),2-hydroxybenzothiazole(79.3％),1,2-benzisothiazole-3-one(72.4％),and 1,2-benzisothiazole-3-one(72.4％).The quantitative concentration range of EPs was 1.37～19.05 ng/mL,with the high concentrations observed for melamine(19.05 ng/mL)and furosemide(18.49 ng/mL).Ecological risk assessment identified 1,2-benzisothiazol-3-one,4-aminoacetophenone,creatinine,2-hydroxybenzothiazole,and furosemide as key pollutants.Conclusion This direct injection coupled with HRMS workflow enables efficient non-targeted screening and prioritization of emerging EPs in sewage samples,highlighting five ecotoxicologically critical EPs.The methodology enhances environmental monitoring capabilities and provide critical technical support for interdisciplinary research such as environmental forensics and health risk assessment.

This study aims to investigate the therapeutic efficacy of 50 Hz-0.6 mT low-frequency pulsed electromagnetic field (PEMF) on postmenopausal osteoporosis in ovariectomized rats. Thirty 3-month-old female SD rats were selected and divided into a sham operation group (Sham), an ovariectomized model group (OVX), and a low-frequency pulsed electromagnetic field (PEMF) treatment group, with 10 rats in each group. After 8 weeks, the whole-body bone mineral density (BMD) of each group of rats was measured. The treatment group began to receive PEMF stimulation for 90 minutes daily, while the OVX group only received a simulated placement without electricity. After 6 weeks of intervention, all rats were sacrificed and tested for in vitro BMD, micro-CT, biomechanics, serum biochemical indicators, and bone tissue-related proteins. The results showed that the BMD of the OVX group was significantly lower than that of the Sham group 8 weeks after surgery, indicating successful modeling. After 6 weeks of treatment, compared with the OVX group, the PEMF group exhibited significantly increased BMD in the whole body, femur, and vertebral bodies. Micro-CT analysis results showed improved bone microstructure, significantly increased maximum load and bending strength of the femur, elevated levels of serum bone formation markers, and increased expression of osteogenic-related proteins. In conclusion, this study demonstrates that daily 90-minute exposure to 50 Hz-0.6 mT PEMF effectively enhances BMD, improves bone biomechanical properties, optimizes bone microstructure, stimulates bone formation, and inhibits bone resorption in ovariectomized rats, highlighting its therapeutic potential for postmenopausal osteoporosis.
Female ; Animals ; Rats, Sprague-Dawley ; Osteoporosis, Postmenopausal/therapy* ; Rats ; Bone Density ; Ovariectomy ; Magnetic Field Therapy/methods* ; Electromagnetic Fields

Phages, as obligate bacterial and archaeal parasites, constitute a virus group of paramount ecological significance due to their exceptional abundance and genetic diversity. These biological entities serve as critical regulators in Earth's ecosystems, driving biogeochemical cycles, energy fluxes, and ecosystem services across terrestrial and marine environments. Within soil microbiomes, phages function as microbial "dark matter," maintaining the soil-plant system balance through precise modulation of the microbial community structure and functional dynamics. Despite the growing research interests in soil phages in recent years, the proportion of such studies in environmental virology remains disproportionately low, which is primarily attributed to researchers' limited familiarity with the research methodologies for phage microecology, incomplete technical frameworks, and inherent challenges posed by soil environmental complexity. To address these challenges, this review synthesizes cutting-edge methodologies for soil phage investigation from four aspects: (1) tangential flow filtration (TFF)-based phage enrichment strategies; (2) integrated quantification approaches combining double-layer agar plating, epifluorescence microscopy, and flow cytometry; (3) multi-omics analytical pipelines leveraging metagenomics and viromics datasets; and (4) computational frameworks merging machine learning algorithms with eco-evolutionary theory for deciphering phage-host interaction networks. Through comparative analysis of methodological principles, technical merits, and application scopes, we establish a comprehensive workflow for soil phage research. Future research in this field should prioritize: (1) construction of soil phage resource libraries, (2) exploration of RNA phages based on transcriptomes, (3) functional characterization of unknown genes, and (4) deep integration and interaction validation of multi-omics data. This systematic methodological synthesis provides critical technical references for addressing fundamental challenges in characterizing soil phages regarding the community structure, functional potential, and interaction mechanisms with hosts.
Bacteriophages/physiology* ; Soil Microbiology ; Ecosystem ; Microbiota ; Metagenomics/methods*

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.