OBJECTIVE To investigate the therapeutic effect and mechanism of Qiwei dongqingye powder （QDP） on bronchial asthma in mice. METHODS The mice were divided into blank group （normal saline）， model group （normal saline）， dexamethasone group （2 mg/kg）， and QDP low-， medium-， and high-dose groups （200， 400， 800 mg/kg）， with 14 mice in each group. Except for the blank group， mice in all other groups were given ovalbumin via intraperitoneal injection followed by aerosol inhalation to induce a bronchial asthma model. During the modeling process， mice in each group were administered corresponding drug solutions or normal saline intragastrically/intraperitoneally. After the last medication， the number of cells in the bronchoalveolar lavage fluid （BALF） of the mice was observed and counted； the pathological changes of the bronchus and lung tissue were observed； the levels of malondialdehyde （MDA）， nitric oxide （NO）， total superoxide dismutase （T-SOD）， and glutathione peroxidase （GSH-Px） in the lung tissue of the mice were determined， and the level of interleukin-17 （IL-17） in the BALF and serum was determined. Transcriptomics was employed to predict and validate the mechanism of action of QDP against bronchial asthma. RESULTS Compared with the model group， the total cell count， neutrophil count， lymphocyte count， and macrophage counts in the BALF of the QDP high-dose group were all significantly reduced （ P ＜0.05）； the levels of MDA and NO in the lung tissue， and the levels of IL-17 in the BALF and serum were all decreased significantly （ P ＜0.05）； the levels of T-SOD and GSH-Px were significantly increased （ P ＜0.05）； the arrangement of lung tissue cells tended to normalize， with reduced infiltration of inflammatory cells and decreased exfoliation of bronchial simple columnar epithelial cells. The transcriptomic results revealed that the differentially expressed genes were B-cell receptor signaling pathway， nuclear factor κB （NF-κB） signaling pathway， ferroptosis signaling pathway， and others. Further validation revealed that， compared with the model group， the expression levels of NF-κB p65 and chemokine ligand 20， as well as the phosphorylation level of NF-κB inhibitor protein α， were significantly decreased in the lung tissues of the mice in all QDP groups （ P ＜0.05）. Conversely， the protein expression of nuclear factor erythroid 2-related factor 2 （Nrf2） and heme oxygenase 1 （HO-1） were significantly increased （ P ＜0.05）. CONCLUSIONS QDP can effectively alleviate bronchial asthma by inhibiting the NF-κB signaling pathway， activating the Nrf2/HO-1 signaling pathway， regulating oxidative stress， and reducing inflammatory responses.

Recent research from the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) indicates that breast cancer is the most prevalent malignant tumor among women, posing a significant threat to women's health. Surgery remains the primary therapeutic modality for breast cancer. Recently, endoscopic and robotic breast surgical techniques have gained acceptance among both surgeons and patients. However, considerable variation exists in surgical approaches and outcomes. To standardize these techniques, facilitate their broader clinical adoption, and ultimately improve patient care, the Endoscopic-robotic Breast Surgery Clinical Trials Consortium (ErBSCTC) of China has developed this guideline. This document encompasses the technologies and instrumentation utilized in endoscopic and robotic breast surgery, surgical techniques, perioperative management, complication handling, long-term follow-up, and oncologic outcomes, aiming to provide evidence-based guidance for healthcare professionals involved in the prevention, diagnosis, and treatment of breast diseases.

Breast cancer is the most common malignant tumor among women in China, with surgery being one of the primary treatment modalities. Endoscopic/robotic breast surgery (ErBS) is gaining widespread acceptance among patients and surgeons alike due to its advantages of minimal invasiveness, superior cosmetic outcomes, and accelerated recovery. However, substantial heterogeneity currently exists across China regarding patient selection, standardized operative techniques, perioperative management, and complication handling, underscoring the urgent need for evidence-based consensus guidelines. To promote standardization and ensure consistent quality of ErBS, the Chinese Endoscopic-Robotic Breast Surgery Clinical Trials Consortium (CErBSCTC) has systematically reviewed the latest high-quality evidence and formulated the "Protocol for China Endoscopic and Robotic Breast Surgery Guidelines (2026 edition)", which outlines a comprehensive methodology for guideline development.

This guideline, presented in three parts, details the core aspects of endoscopic/robotic breast surgery, including its techniques, equipment, surgical procedures, perioperative management, complication treatment, long-term follow-up, and outcomes. Part one offered a comprehensive overview of indications for endoscopic and robotic breast surgery, intraoperative techniques, surgical instrument choices, and common endoscopic and robotic breast reconstruction procedures. This part will cover other endoscopic breast procedures beyond immediate breast reconstruction and include perioperative management strategies, to provide healthcare professionals involved in endoscopic and robotic breast surgery with systematic operational guidelines and clinical decision-making references.

OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

Malignant tumors represent a major threat to global health. Conventional anti-tumor pharmacotherapy often encounters challenges such as drug resistance, highlighting an urgent need for the development of novel therapeutic strategies. Fatty acid synthase (FASN), the key enzyme catalyzing de novo fatty acid synthesis, is subject to precise regulation at multiple levels, including transcriptional control, various post-translational modifications such as ubiquitination and phosphorylation, as well as modulation by diverse signaling pathways. Recent studies have revealed that FASN is aberrantly overexpressed in various malignant tumors and is closely associated with tumor progression and poor patient prognosis. FASN is a homodimer composed of seven functional domains that catalyzes the NADPH-dependent condensation of acetyl-CoA and malonyl-CoA to generate saturated fatty acids, primarily palmitic acid. Its stability is regulated by multiple ubiquitin ligases and deubiquitinating enzymes. Additionally, FASN is subject to upstream regulation via neural precursor cell-expressed developmentally downregulated 8 (Nedd8) modification and the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway, thereby establishing a metabolic-signaling positive feedback loop. As a core executor of metabolic reprogramming, FASN promotes tumorigenesis through dual mechanisms. First, its fatty acid synthesis product, palmitate, participates in membrane phospholipid synthesis, lipid raft formation, and protein palmitoylation, thereby activating several key oncogenic signaling pathways, including PI3K/AKT/mTOR, wingless-type MMTV integration site family member (Wnt)/β‑catenin, and signal transducer and activator of transcription 3 (STAT3)/matrix metalloproteinase (MMP), leading to tumor development and progression. Second, FASN plays a pivotal role in modulating the anti-tumor functions of immune cells and remodeling the tumor immune microenvironment. Specifically, FASN enhances immune checkpoint inhibition by inducing programmed death-ligand 1 (PD-L1) palmitoylation, suppresses the activation of cytotoxic T lymphocytes and natural killer cells, and promotes the polarization of M2-type macrophages, consequently facilitating tumor immune evasion and malignant progression. Precisely due to its significant overexpression in tumor cells, its critical functional role, and its differential expression compared to normal cells, FASN has emerged as a highly promising target for anti-tumor drug development. Highly selective small-molecule inhibitors, notably represented by TVB-2640, have advanced to clinical trial stages and demonstrated favorable anti-tumor activity. Furthermore, the combination of FASN inhibitors with other chemotherapeutic agents or targeted drugs can overcome the limitations of monotherapy through synergistic effects or by resensitizing tumor cells to conventional drugs, achieving a “1+1>2” therapeutic outcome. With the advancement of modern traditional Chinese medicine (TCM), numerous active ingredients derived from TCM have been confirmed to exert anti-tumor effects by modulating FASN-related pathways. This integrated approach leverages the precision of Western medicine while simultaneously harnessing the holistic regulatory benefits of TCM to alleviate the side effects of radiotherapy and chemotherapy. Despite the promising prospects of FASN-targeted therapies, challenges remain, including tumor cell metabolic plasticity, tumor context-dependent responses, and heterogeneity. This review systematically summarizes the molecular structure, physiological functions, and mechanisms of FASN in tumorigenesis, as well as recent advances in targeted therapies. Future directions—including the precise identification of responsive patient populations using spatial transcriptomics, the development of novel combination regimens, and the active exploration of integrative strategies combining traditional Chinese and Western medicine—will facilitate the clinical translation of FASN-targeted therapies and open new avenues for improving the quality of life and prognosis of cancer patients.

Objective: To investigate the incidence, characteristics, and influencing factors of resolution discrepancies within the minipool (MP) testing model across Chinese blood station laboratories in 2024. Methods: A nationwide, multicenter, cross-sectional study was conducted, including 334 blood station laboratories that reported nucleic acid reactive data among enzyme immunoassay non-reactive samples. Of these, 296 laboratories adopted the pool resolution model, with a total of 12 536 273 samples tested. Systematic analysis was performed on resolution data, focusing on the MP-NAT reactivity rate, the pool resolution concordance rate, and the resolution discrepancy rate. Subgroup analyses were conducted based on reagent types, viral targets, and Ct values. Potential causes were further explored through laboratory surveys and re-examination of raw amplification curves. Results: In 2024, the national average MP-NAT reactivity rate was 0.15%. The overall pool resolution concordance rate was 57.86%, which showed a gradual decline as Ct values increased across all reagents. The national average resolution discrepancy rate was 0.081‱(102/12 536 273), with 17.91%(53/296) of laboratories reporting at least one discrepancy. Nine reagent types were associated with these events, exhibiting reagent-specific patterns. For Reagent A2, the predominant discrepancy was HBV reactive pools resolving as HIV (36.36%); for Reagent D1, HBV pools frequently resolved as HCV (38.89%); and for Reagent E, the most common pattern was HIV pools resolving as HBV (48.00%). These resolution discrepancies were strongly associated with high Ct values: the median pool Ct for HBV exceeded 38, while those for HCV and HIV both exceeded 40. Investigations across 16 laboratories revealed that most discrepant samples exhibited “tailing” amplification curves, with some cases linked to cross-contamination or reagent batch-specific issues. Conclusion: While the incidence of resolution discrepancies in the MP-NAT model remains low in China, variations exist across different reagents and laboratories. These discrepancies are closely associated with low viral load, reagent performance, and laboratory operational practices.

ObjectiveTo investigate the ability of clinically isolated， Helicobacter pylori （H. pylori）-specific gene polymerase chain reaction （PCR）-positive gastric， vaginal， and fecal Candida to release H. pylori. MethodsResuscitate 4 strains of H. pylori -specific 16S rDNA and ureA gene PCR-positive Candida strains isolated in laboratory from clinical sources， including 1 strain of gastric Candida， 1 strain of fecal Candida， 2 strains of vaginal Candida and the standard Candida albicans strain ATCC10231 （Ca10231）. The presence of H. pylori-specific ureA in the 5 strains of Candida isolates was confirmed by PCR. The aforementioned strains of Candida and H.pylori were inoculated into urea medium and cultured in a constant temperature incubator at 37 ℃. The color change of the medium was observed daily. A change in the medium's color from yellow to red indicated the presence of urease activity. Then， the five strains of Candida and H. pylori were co-incubated with the magnetic beads coated with H. pylori antibodies respectively. Scanning electron microscopy （SEM） was employed to observe the presence of bacilli adsorbed on the surface of the magnetic beads. PCR was used to detect the presence of H.pylori-specific 16S rDNA and ureA genes on magnetic beads. ResultsThe PCR analysis of the ureA gene in the four Candida isolates was positive， whereas the Ca10231 strain tested negative. Upon culturing the four Candida isolates on urea medium， the medium color changed from yellow to red which was determined to be urease positive， while the medium containing Ca10231 remained unchanged， which was urease negative. SEM revealed that bacilli could be observed on the surface of magnetic beads co-incubated with the 4 strains of Candida of clinical origin and H.pylori isolate. Specifically， PCR testing of the magnetic beads co-incubated with one vaginal Candida， one gastric Candida and H.pylori isolate showed positive results for the 16S rDNA and ureA genes of H. pylori； however， the PCR tests for the two genes were negative for the magnetic beads co-incubated with the other two Candida isolate. ConclusionThis study demonstrates that H. pylori-specific genes Candida can release H. pylori.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective To investigate the transgenerational effects of paternal PM2.5 exposure on offspring growth and development,and to preliminarily elucidate the role of sperm DNA methylation modifications in mediating these effects.Methods Eight-week-old male C57BL/6 mice were randomly divided into filtered air(FA),unfiltered air(UA),and concentrated PM2.5(CAP)groups,with 10 animals in each group.The exposure was conducted from November 2019 to April 2020,and then,these male mice were mated with unexposed females to generate F1 offspring,which were bred successively to produce F2 and F3 generations.All the offspring were living in PM2.5-free environment.The birth body weight,birth number,and sex ratio of the offspring were recorded,body weight growth was monitored,and organ coefficients of the heart,liver,lung,and brain were calculated.Whole-genome methylation sequencing was performed on the sperm DNA of the CAP group,FA group,and their F1 generation offspring to screen for differentially methylated regions,and the genes and pathways associated with these regions were analyzed.Results When compared with the F1～F3 offspring of the FA group,the CAP group had significantly reduced birth body weight in the F1 generation(P<0.05),no statistical differences were observed in the birth body weight in the F2 and F3 generations(P>0.05),or either in the sex ratio and birth number among the F1,F2 and F3 generations.Compared with the FA group offspring,the F1～F3 offspring of CAP group exhibited delayed body weight gain,especially in the males(P<0.05),the CAP-F1 male generation had obviously elevated liver organ coefficient(P<0.01),but no statistical changes were observed in the heart,lung,or brain coefficients among the F1～F3 generations.Between the FA group and the CAP group,37 997 differentially methylated regions were detected,with a reduction of approximately 50%in the number of differentially methylated regions in the F1 generation.Differentially methylated genes in F0 and F1 sperm were potentially related to developmental processes,including imprinting genes(Gnas,Igf2)and metabolic genes(Ppard,Rps6kb1).Conclusion Paternal exposure to PM2.5 leads to reduced birth weight and intergenerational growth retardation in offspring.Its impact on phenotypic effects is gradually weakened during intergenerational transmission.Changes in the methylation of development-related genes in sperm may be one of the mechanisms mediating this intergenerational effect.