OBJECTIVE To evaluate the efficacy and safety of immune checkpoint inhibitors （ICIs） combined with neoadjuvant chemotherapy in the treatment of early triple-negative breast cancer （TNBC）. METHODS Randomized controlled trials （RCTs） comparing ICIs combined with neoadjuvant chemotherapy （experimental group） versus neoadjuvant chemotherapy alone （control group） were retrieved from PubMed， Cochrane Library， Embase， Web of Science， CNKI， Wanfang Data， and VIP databases， as well as relevant studies published at oncology academic conferences. The search period was from database inception to June 30， 2025. After literature screening， data extraction， and quality assessment， a meta-analysis was performed by using RevMan 5.4 software. RESULTS A total of 6 RCTs involving 3 786 patients were finally included. The meta-analysis results showed that the experimental group had superior event-free survival [HR＝0.73， 95%CI （0.62， 0.85）， P＜0.000 1]， overall survival [HR＝0.69， 95%CI （0.57， 0.84）， P＝0.000 3]， and pathological complete response （pCR） [OR＝1.57， 95%CI （1.37， 1.80）， P＜0.000 01] compared to the control group. The incidence of ≥grade 3 adverse event （AE）， severe AE （SAE）， and ≥ grade 3 immune-related adverse event （irAE） in the experimental group was significantly higher than that in the control group. There was no statistically significant difference between the two groups in the incidence of any AE or any irAE （P＞0.05）. Subgroup analysis revealed that， regardless of programmed cell death ligand 1 expression status （negative or positive），the pCR in the experimental group was significantly higher than that in the control group （P＜0.05）. Additionally， the pCR of the patients with positive lymph nodes in the experimental group was significantly higher to that in the ontrol group （P＜0.05）. There was no statistically significant difference in pCR between the two groups with negative lymph nodes （P＝0.09）. CONCLUSIONS ICIs combined with neoadjuvant chemotherapy can significantly improve event-free survival and overall survival in patients with TNBC， providing patients with long-term survival benefits. However， the risk of ≥ grade 3 AE， SAE and ≥ grade 3 irAE has increased.

Congenital blood group chimerism refers to the coexistence of two or more distinct blood types within an individual, resulting from the presence of hematopoietic cell populations with different genotypes. Consequently, red blood cells in such individuals may express different blood group antigens. Based on the timing and mechanism of formation, blood group chimerism can be classified as either congenital or acquired. Although congenital blood group chimerism is rare and involves complex mechanisms, it holds significant implications in transfusion medicine, transplantation, and obstetrics. This article reviews the formation mechanisms, detection methods, and clinical significance of congenital blood group chimerism in transfusion medicine. Particular emphasis is placed on the principles, advantages, and limitations of various detection techniques. Furthermore, the potential applications of these technologies in clinical diagnosis are discussed, providing a technical foundation for the development of precise transfusion strategies.

ObjectiveTo investigate the clinical features of tumor-induced acute pancreatitis （TIAP）， to construct and validate a predictive model for TIAP， and to provide help for early identification in clinical practice. MethodsA retrospective analysis was performed for the clinical data of 3 051 patients with acute pancreatitis （AP） who were admitted to The First Affiliated Hospital of Xinjiang Medical University from January 2020 to January 2026， among whom there were 72 patients with TIAP. To reduce class imbalance， 216 patients with non-tumor-related AP （2 979 patients） were randomly selected as conventional group using sex-stratified sampling， resulting in a cohort of 288 patients， and this cohort was randomly divided into a training set with 201 patients and a test set with 87 patients at a ratio of 7∶3. The two groups were compared in terms of general information and laboratory markers. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. Recursive feature elimination and least absolute shrinkage and selection operator regression were used for screening of characteristic variables， and five machine learning models were constructed， i.e.， logistic regression model， random forest model， support vector machine model， extreme gradient boosting model， and light gradient boosting machine model. The receiver operating characteristic curve and the precision-recall curve were used to assess model performance； the calibration curve was used to assess goodness of fit； decision curve analysis was used to evaluate clinical applicability and practicality； Shapley additive explanations were used to assess model interpretability. ResultsIn the training set of 201 patients， there were 52 patients （25.9%） in the TIAP group， and in the test set of 87 patients， there were 20 patients （23.0%） in the TIAP group. Compared with the conventional group， the TIAP group had a significantly higher proportion of patients with pancreatic duct dilatation （χ²=79.474， P<0.05）， a significantly higher age （Z=-5.838， P<0.05）， and significantly lower levels of white blood cell count （Z=5.630， P<0.05）， amylase （Z=2.606， P<0.05）， hemoglobin （Z=5.038， P<0.05）， and neutrophil percentage （Z=5.269， P<0.05）， as well as a lower level of direct bilirubin （Z=0.936， P>0.05）. The five machine learning models constructed based on these seven variables had a certain predictive ability， among which the logistic regression model had the best performance in the test set， with an area under the curve of 0.893 （95% confidence interval： 0.821 — 0.953）， an average precision of 0.654 in the precision-recall curve， good calibration， and good clinical benefits based on the decision curve analysis. ConclusionThe predictive model for TIAP based on pancreatic duct dilatation， age， white blood cell count， amylase， hemoglobin， neutrophil percentage， and direct bilirubin shows good predictive performance and can provide important guidance for the early diagnosis of TIAP.

Objective To explore the method for establishing a pig left lung orthotopic transplantation model. Methods A total of 4 male Yorkshire pigs weighing (40.0±2.5) kg underwent surgical procedures, including anesthesia, tracheal intubation, donor lung procurement, and recipient lung transplantation. Histological morphology and blood gas analysis of the transplanted lungs were assessed 2 hours after reperfusion to evaluate the histological changes and function of the transplanted lungs. Results The pigs underwent left lung in situ transplantation, effectively simulating conditions relevant to human lung transplantation. Two hours after the transplantation, arterial blood gas analysis showed that arterial partial pressure of oxygen was 155.4-178.6 mm Hg, arterial partial pressure of carbon dioxide was 53.1-62.4 mm Hg, and the oxygenation index was 310.8-357.2 mm Hg. Hematoxylin and eosin staining indicated a low degree of pulmonary edema and minimal cellular infiltration. Conclusion The pig left lung orthotopic transplantation model possesses strong operability and stability. Researchers can replicate this model according to the described methods and further conduct basic research and explore clinical translational applications.

Fecal microbiota transplantation (FMT) technology originated in China during the Eastern Jin Dynasty and has rapidly developed over the past two decades, becoming a primary method for studying the causal relationship between gut microbiota and the occurrence and progression of diseases. At the same time, the therapeutic effects of FMT in the field of gastrointestinal diseases have gained widespread recognition and are gradually expanding into other disease areas. The FMT procedure is relatively complex, and there is currently no standardized method; its success is influenced by various factors, including the donor, recipient, processing of the fecal material, and the method of implantation. Given the increasingly recognized relationship between gut microbiota and various diseases, FMT has become a research hotspot in both scientific studies and clinical applications, achieving a series of significant advancements. To help researchers better understand this technology, this paper will outline the development history of FMT, summarize common operational methods in research and clinical settings, review its application progress, and look forward to future development directions.

Glioblastoma(GBM)is the most aggressive primary malignant tumor in the central nervous system.GBM frequently recurs after surgery and has limited therapeutic options.Hydrogels,characterized by their injectability,biocompatibility,and controlled drug release,of-fer innovative solutions for postoperative GBM management.Advances in hydrogel technology provide new avenues for personalized GBM treatments with significant clinical potential.This article focuses on the current progress in the research on hydrogels as carriers for chemo-therapeutic drugs,immunomodulatory platforms,and multimodal therapeutic systems.Key strategies,including thermo-and pH-responsive gels,co-delivery systems,and the regulation of macrophage function,are analyzed for their therapeutic efficacy.Additionally,the advant-ages of hydrogels in surgical cavity filling,targeted therapy,and recurrence prevention are highlighted.We also discuss the challenges in clin-ical translation and future directions of hydrogel application in postoperative GBM management.

Objective:To investigate the genetic etiology of 15 patients with suspected Marfan syndrome(MFS).Methods:Fifteen patients clinically suspected of having MFS who attended the Women and Children′s Hospital Affiliated to Qingdao University between January 2020 and August 2024 were enrolled. Amniotic fluid samples from fetuses and EDTA-anticoagulated peripheral blood samples from the patients and their family members were collected. Genomic DNA was extracted and subjected to whole exome sequencing(WES). Variants identified in positive cases were further validated by Sanger sequencing. The pathogenicity of the detected variants was assessed according to the guidelines and supplemental criteria of the American College of Medical Genetics and Genomics(ACMG).Results:All 15 patients were found to carry variants in the FBN1 gene, including 9 pathogenic variants, 5 likely pathogenic variants, and 1 variant of uncertain significance(VUS). Notably, eight novel pathogenic or likely pathogenic variants not previously reported in the literature were identified: c. 213G>C, c. 469G>T, c. 3337+ 2dup, c. 4087+ 1G>T, c. 7331_7334dup, c. 8146del, c. 8227dup, and c. 8425_8426insG. According to the revised Ghent criteria(2010), only 2 patients could be clinically diagnosed with MFS prior to WES. However, after incorporating WES-derived molecular evidence, 8 patients fulfilled the diagnostic criteria for MFS.Conclusion:The combination of WES and clinical phenotype assessment can substantially improve the diagnostic yield for MFS. Furthermore, the identification of these novel FBN1 variants expands the mutational spectrum of the gene and provides valuable evidence for future genetic counselling, prenatal diagnosis, and pathogenicity interpretation of neighboring variants.

Objective To screen antidepressant-active compounds from Polygonati Rhizoma and explore their effects and possible mechanisms against depression induced by simulated weightlessness.Methods A systems pharmacology approach was used to screen potential antidepressant-active compounds and their targets from Polygonati Rhizoma.The hindlimb unloading(HLU)rat model was employed for the study.Twenty-four healthy male Sprague-Dawley rats were randomly divided into three groups:control group(administered 0.5%carboxymethylcellulose by gavage),HLU group(hindlimb unloading),and HLU+treatment group(hindlimb unloading+active compound gavage),with 8 rats in each group.After 28 days of hindlimb unloading,depressive-like behaviors in rats were evaluated using the forced swimming test and tail suspension test.Hippocampal morphology was examined with H&E staining,and GO and KEGG enrichment analyses were conducted on the targets of active compounds.Results A total of 38 active compounds were screened from Polygonati Rhizoma,among which apigenin had an oral bioavailability of 23.06%and a drug-likeness score of 0.21.Compound-target network analysis indicated that apigenin had the highest degree and betweenness centrality values,suggesting it might be the key active component with antidepressant potential in Polygonati Rhizoma.In the forced swimming and tail suspension tests,rats in the HLU group showed a significant increase in immobility time compared to the control group,indicating successful establishment of the depression model.However,compared to the HLU group,rats in the HLU plus apigenin group exhibited significantly reduced immobility time.The H&E staining results of hippocampal tissue showed a significant reduction in the number of hippocampal neurons,along with numerous shrunken neurons and small vacuoles in nerve fibers in the HLU group.In contrast,the treatment group exhibited an increased number of hippocampal neurons,with improved cellular morphology.Target enrichment analysis indicated that apigenin targets were mainly involved in the regulation of apoptosis and cancer-related signaling pathways.Conclusion Apigenin significantly improved depressive-like behaviors in rats subjected to hindlimb unloading,and it has a protective effect on hippocampal tissue.It may provide a new natural active compound for the treatment of depression caused by spaceflight-induced weightlessness.

Objective:To explore the association between albumin-corrected serum calcium (ACSC) levels and 30-day all-cause mortality in patients hospitalized for community-acquired bacterial pneumonia (CABP).Methods:A secondary analysis was conducted on 1 899 patients with CABP from a Norwegian cohort study. The relationship between baseline ACSC levels and 30-day mortality was assessed using multivariable logistic regression models, adjusted for potential confounders.Results:A significant positive correlation was found between ACSC levels and 30-day mortality risk after adjusting for confounding variables ( OR=1.95, 95% CI=1.48-2.58). When ACSC levels were categorized into tertiles (T1-T3), a trend analysis revealed that the T2 and T3 groups had significantly higher mortality risks compared to the lowest tertile (T1), with odds ratios ( OR) and 95% confidence intervals ( CI) of 1.52(95% CI: 0.97-2.38) and 2.21 (95% CI: 1.44-3.39), respectively ( P for trend <0.001). Subgroup analyses demonstrated no significant interactions across predefined subgroups (all P for interaction > 0.05). Conclusions:In patients with CABP and admission ACSC levels of ≥8.6 mg/dL, higher ACSC levels were positively associated with an increased risk of 30-day mortality. These findings highlight the potential prognostic value of ACSC levels in CABP patients.

Objective:To analyze the risk factors for in-hospital malignant ventricular arrhythmia (MVA) in acute myocardial infarction (AMI) and to construct and validate a risk prediction model.Methods:This study was a retrospective cohort study. Patients aged≥18 years who were admitted to Qilu Hospital of Shandong University with a diagnosis of AMI and underwent coronary angiography (CAG) from May 2016 to March 2023 were selected, and the patients' clinical routine test indicators and CAG results were collected. Univariate and bidirectional stepwise logistic regression were used to screen out the risk factors for constructing the best prediction model. The prediction model was constructed by combining the results of multivariate logistic regression. The Hosmer-Lemeshow test and ROC curve, calibration curve, and decision curve were drawn to evaluate the model. The nomogram was drawn to visualize the model, and the Bootstrap self-sampling method was used for internal validation. The ROC curve was drawn to evaluate the predictive performance of each risk factor and prediction model. Finally, a multicollinearity test was performed.Results:Among the 4 205 patients finally included in the study, 115 patients (2.735%) developed MVA during hospitalization. The predictive factors screened out included age (X1), diastolic blood pressure (X2), respiratory rate (X3), blood glucose (X4), serum potassium (X5), logarithmic NT-proBNP (X6), myocardial infarction type (NSTEMI=X7, unclassified=X8), J wave (X9), Killip grade (Ⅱ=X10, Ⅲ=X11, Ⅳ=X12), and the regression equation was ln(p/1-p)=-4.699+0.029×X1-0.012×X2+0.059×X3+0.148×X4-1.175×X5+0.866×X6-1.427×X7-0.475×X8+0.758×X9+0.294×X10+0.902×X11+1.815×X12. The area under the ROC curve (AUC) of the model was 0.855 (95% CI: 0.816-0.894), and the Hosmer-Lemeshow test ( χ2=14.178, P=0.077) and the calibration curve showed that the predicted probability was consistent with the actual probability. The probability threshold of 0% to 65% had a better clinical net benefit. The area under the internal validation ROC curve (AUC) was 0.855, 95% CI: 0.813-0.891. The prediction performance of the nine variables was stronger than that of any single variable. There was no multicollinearity between the variables. Conclusions:Age, diastolic blood pressure, respiratory rate, blood glucose, serum potassium, NT-proBNP, type of AMI, J wave, and Killip class are forecasting indicator for in-hospital MVA in AMI. The risk prediction model based on the above factors has good predictive performance.