Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.

ObjectiveThis paper aims to observe the syndrome improvement and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome）. MethodsThrough a multi-center randomized controlled methodology design，confirmed influenza cases were collected from October 2022 to April 2023 in the pediatrics department of eight hospitals，such as Dongfang Hospital of Beijing University of Chinese Medicine. A total of 180 children with influenza and heat accumulation in the lung and stomach syndrome conforming to the standard were recruited through the clinic. The sick children meeting the inclusion criteria were randomly divided into groups by a block-randomized method. The children in the experimental group were treated with Qingxuan Daozhi formula for five days，and those in the control group were treated with Oseltamivir Phosphate Granules for five days. The primary efficacy indicator was the negative conversion rate of influenza antigen detection. Secondary efficacy indicators were the Canadian acute respiratory illness and flu scale （CARIFS） and the incidence of complications，severe cases， and critical cases. Follow-up observation was conducted on the day of enrollment，48 hours after medication，72 hours after medication， and （6+1） d after medication. ResultsOne hundred and eighty participants were randomly assigned to the experimental group （90 cases） or the control group （90 cases）. All participants were followed up during the study. Comparison of influenza antigen detection results in the primary efficacy indicators showed that the average time of negative influenza antigen conversion in the experimental group was （5.29±1.25） d，and that in the control group was （5.40±1.68） d，without a statistically significant difference. After five days of intervention，52 cases in the experimental group and 51 cases in the control group converted to negative，without a statistically significant difference. CARIFS score results in the secondary efficacy indicators showed that during 72 hours after intervention，there were statistically significant differences between the experimental group and the control group in three dimensions， including headache，muscle soreness， and the need for extra care （P<0.05）. On the （6+1） days after the intervention，the differences in both the experimental group and the control group were statistically significant in 10 dimensions， including sore throat，bad sleep，uncomfortable feeling，poor spirit and fatigue，crying more than usual，the need for extra care，symptom，function，influence on parents，and total score （P<0.05）. The comparison results within the group in the dimensional scores of symptom， function， and influence on parents，as well as the CARIFS total score showed that with the delay of follow-up time，scores of both groups decreased significantly，with a statistically significant difference （P<0.01）. Inter-group comparison results showed that the mean score of the experimental group was higher than that of the control group at the time of enrollment. With the progress of intervention，the score of the experimental group was significantly decreased compared with that of the control group. At the end of follow-up，the mean score of the experimental group was lower than that of the control group，with no statistically significant difference. In terms of the incidence of complications，severe cases， and critical cases， there were no complications，severe cases， and critical cases in the two groups，without a statistically significant difference. ConclusionThe symptom improvement effect and negative antigen conversion rate of Qingxuan Daozhi formula in the treatment of influenza in children （heat accumulation in the lung and stomach syndrome） are not inferior to Oseltamivir Phosphate granules， and children's acceptance is better. It can be more widely used in clinical treatment of influenza in children （heat accumulation in the lung and stomach syndrome）.

Objective To evaluate the performance of lightweight Chinese large language models (LLMs) in answering specialized lung cancer questions, and to explore the impact of retrieval-augmented generation (RAG) on model performance. Methods Eleven lightweight Chinese LLMs with parameter sizes ranging from 7B to 32B were included. A lung cancer-specific evaluation dataset consisting of 200 questions [100 A1-type (basic knowledge) and 100 A2-type (clinical case) questions], constructed based on clinical guidelines and thoracic surgery textbooks, was used for assessment. Model performance was evaluated under two conditions (with and without RAG). Accuracy was used to assess model performance, and response latency was recorded to reflect inference efficiency. An accuracy–latency scatter plot was constructed for descriptive analysis of overall model performance. Results All models successfully completed the evaluation. With the introduction of RAG, the overall average accuracy improved from 61.68% to 76.36%. Smaller models demonstrated the most significant improvement (e.g., the accuracy of DeepSeek-7B increased from 32.50% to 60.00%, P<0.001). The average response latency increased from 12.58 s to 13.80 s. The Qwen3 series showed the best overall performance, and Qwen3-32B achieved the highest accuracy under both conditions (76.50% and 84.00%, respectively). After RAG integration, performance differences among model families were markedly reduced. Based on the accuracy-latency trade-off, Qwen3-32B achieved the best balance between accuracy and response latency under the baseline condition, whereas Qwen3-14B demonstrated superior overall performance in terms of accuracy, latency, and computational cost after RAG integration. Conclusion The integration of RAG technology improves the ability of lightweight Chinese LLMs to answer specialized lung cancer questions. Under the dual practical constraints of limited computational resources and medical data security requirements, the "lightweight model+RAG" technical framework may represent a promising deployment solution.

Objective: To investigate the associations of sleep quality and weight stigma with depressive mood among college students, so as to provide evidence for mental health promotion in higher education institutions. Methods: From September to November 2024, a stratified cluster random sampling method was used to survey 4 524 undergraduate students from the first to third year in comprehensive universities across various cities in Inner Mongolia. The χ 2 test was used to compare the detection rates of poor sleep quality, experiences of weight stigma, and depressive mood among students with different characteristics, and multivariate Logistic regression analysis was conducted to examine the independent and combined associations between sleep quality, the number of types of weight stigma experienced, and depressive mood. Results: Among students, the detection rate of poor sleep quality was 21.60%; those with experiences of weight stigma had a detection rate of 11.52%; those with depressive mood had a detection rate of 9.46%. Multivariate Logistic regression analysis showed that, compared with those who had good sleep quality, individuals with poor sleep quality were more likely to experience depressive mood [ OR (95% CI )=2.99(2.41- 3.71 )]; compared with those who had no experience of weight stigma, individuals who experienced ≥2 types of weight stigma were more likely to experience depressive mood [ OR (95% CI )=4.51(2.82-7.22)] (both P <0.01). Multivariate Logistic regression analysis, with "good sleep quality and no weight stigma experience" as the reference group, showed that all other joint groups had a higher likelihood of developing depressive mood, with the highest likelihood observed among students who had poor sleep quality and had experienced ≥2 types of weight stigma [ OR (95% CI )=14.21(6.95-29.06), P <0.01]. Conclusions Poor sleep quality and a greater number of weight stigma types are both associated with depressive mood among college students. Mental health programs in higher education institutions should simultaneously address students sleep problems and weight related adverse experiences, and implement comprehensive interventions.

Objective: To analyze the mortality trend of chronic respiratory diseases in Lianyungang City, Jiangsu Province from 2011 to 2024, and predict the mortality from 2025 to 2029, so as to provide the evidence for developing forward-looking prevention and control strategies and targeted intervention measures. Methods: Chronic respiratory disease death surveillance data in Lianyungang City from 2011 to 2024 were collected through the Jiangsu Chronic Disease Management Information Platform. The crude mortality was calculated and standardized using the data of the Sixth National Population Census in 2010. Average annual percent change (AAPC) was used to analyze the mortality trends of chronic respiratory diseases by gender, region, and age in Lianyungang City from 2011 to 2024. The GM (1,1) grey model was established using the crude mortality of chronic respiratory diseases from 2011 to 2024 to predict the crude mortality of chronic respiratory diseases from 2025 to 2029. Results: From 2011 to 2024, the crude mortality and standardized mortality of chronic respiratory diseases in Lianyungang City were 52.20/105 and 36.57/105, respectively. The crude mortality and standardized mortality were 53.14/105 and 43.79/105 in males, respectively, which were higher than 51.17/105 and 30.14/105 in females (both P<0.05). The crude mortality and standardized mortality were 55.62/105 and 39.85/105 in rural areas, respectively, which were higher than 38.11/105 and 24.15/105 in urban areas (both P<0.05). From 2011 to 2024, the standardized mortality of chronic respiratory diseases showed downward trends in the total population, males, females, urban areas, and rural areas (AAPC=-6.956%, -5.175%, -8.659%, -4.290%, and -7.369%, all P<0.05). The crude mortality of chronic respiratory diseases in the total population showed an upward trend with increasing age (P<0.05), reaching a peak of 1 371.20/105 in the ≥80 years group. The top two causes of chronic respiratory disease deaths were chronic obstructive pulmonary disease and bronchial asthma, with 31 792 cases and 3 254 cases, accounting for 82.40% and 8.43%, respectively. The GM (1,1) grey model prediction results showed that the crude mortality of chronic respiratory diseases in the total population from 2025 to 2029 would be 37.91/105, 36.32/105, 34.80/105, 33.34/105, and 31.95/105, respectively (average relative error=8.76%). Conclusions From 2011 to 2024, the mortality of chronic respiratory diseases in Lianyungang City showed a downward trend. The risk of death from chronic respiratory diseases was higher in males, rural areas, and the elderly. It is predicted that the mortality of chronic respiratory diseases will decrease year by year from 2025 to 2029.

Ulcerative colitis(UC) is a chronic, non-specific inflammatory disease with a complex etiology and a tendency for recurrence. So far, the clinical efficacy of western medicine in treating UC has been poor and is often accompanied by adverse reactions. Therefore, the multi-target, multi-level, synergistic, and heterogeneous characteristics of traditional Chinese medicine(TCM) are more beneficial for the treatment of UC. As one of the largest microbiotas, the intestinal flora is closely related to human health and disease. Once the intestinal flora becomes dysfunctional, it can affect the integrity of the intestinal mucosal barrier, thereby exacerbating UC. Additionally, the abnormal activation of signaling pathways may lead to dysregulation of the inflammatory response and play an important role in the pathogenesis of UC. Many studies have shown that individual TCMs and their compounds can further protect the intestinal barrier and immune system function by regulating the intestinal flora and associated signaling pathways, achieving therapeutic effects for UC. This paper summarizes the latest research results in China and abroad on the regulation of intestinal flora and related signaling pathways by individual TCMs and compounds in the treatment of UC, aiming to provide theoretical references for the clinical practice of TCM in treating UC and for related new drug research and development.
Humans ; Colitis, Ulcerative/immunology* ; Drugs, Chinese Herbal/administration & dosage* ; Gastrointestinal Microbiome/drug effects* ; Animals ; Medicine, Chinese Traditional

This study primarily investigates the effect of Liuwei Dihuang Pills on the activation and proliferation of female germline stem cells(FGSCs) in the ovaries and cortex of mice with premature ovarian failure(POF), and how it improves ovarian function. ICR mice were randomly divided into the control group, model group, Liuwei Dihuang Pills group, Liuwei Dihuang Pills double-dose group, and estradiol valerate group. A mouse model of POF was established by intraperitoneal injection of cyclophosphamide. After successful modeling, the mice were treated with Liuwei Dihuang Pills or estradiol valerate for 28 days. Vaginal smears were prepared to observe the estrous cycle and body weight. After the last administration, mice were sacrificed and sampled. Serum levels of estradiol(E_2), follicle-stimulating hormone(FSH), luteinizing hormone(LH), and anti-Müllerian hormone(AMH) were measured by enzyme-linked immunosorbent assay(ELISA). Hematoxylin-eosin(HE) staining was used to observe ovarian morphology and to count follicles at all stages to evaluate ovarian function. Immunohistochemistry was used to detect the expression of mouse vasa homolog(MVH), a marker of ovarian FGSCs. Immunofluorescence staining, using co-labeling of MVH and proliferating cell nuclear antigen(PCNA), was used to detect the expression and localization of specific markers of FGSCs. Western blot was employed to assess the protein expression of MVH, octamer-binding transcription factor 4(Oct4), and PCNA in the ovaries. The results showed that compared with the control group, the model group exhibited disordered estrous cycles, decreased ovarian index, increased atretic follicles, and a reduced number of follicles at all stages. FSH and LH levels were significantly elevated, while AMH and E_2 levels were significantly reduced, indicating the success of the model. After treatment with Liuwei Dihuang Pills or estradiol valerate, hormone levels improved, the number of atretic follicles decreased, and the number of follicles at all stages increased. MVH marker protein and PCNA proliferative protein expression in ovarian tissue also increased. These results suggest that Liuwei Dihuang Pills regulate estrous cycles and hormone disorders in POF mice, promote the proliferation of FGSCs, improve follicular development in POF mice, and enhance ovarian function.
Animals ; Female ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Cell Proliferation/drug effects* ; Mice, Inbred ICR ; Ovary/cytology* ; Primary Ovarian Insufficiency/genetics* ; Follicle Stimulating Hormone/metabolism* ; Humans ; Anti-Mullerian Hormone/blood* ; Antineoplastic Agents/adverse effects* ; Luteinizing Hormone/metabolism* ; Cyclophosphamide/adverse effects*

Objective To investigate the protective effects of paeonol(PAE)on autophagy in human neuroblastoma cells(SH-SY5Y)induced by overexpression of α-synuclein(α-Syn),and to explore its related mechanism.Methods SH-SY5Y cells served as control group,while those induced with A53T-α-Syn mutation were used as model group.Additional groups included PAE(150 μg/ml)group,3-MA(1 mmol/L)group,and PAE(150 μg/ml)+3-MA(1 mmol/L)group.Cell viability was assessed using CCK-8 method,cell morphology was observed under an optical microscope,and protein expressions of α-Syn,LC3-Ⅱ,p62,Beclin-1,phosphorylated c-Jun N-terminal kinase(p-JNK),and p-Bcl-2 were determined by Western blotting.Results Compared with control group,model control exhibited decreased cell survival(P＜0.01),increased α-Syn expression(P＜0.001),reduced expression of autophagy-related proteins LC3-Ⅱ and Beclin-1(P＜0.01,P＜0.05),elevated autophagy substrate protein p62(P＜0.05),and decreased expression of autophagy pathway-related proteins p-JNK and Bcl-2(P＜0.05,P＜0.01).Compared with model group,PAE group showed increased cell survival(P＜0.01),decreased α-Syn and p62 protein expression(P＜0.01,P＜0.05),and increased expression of LC3-Ⅱ,Beclin-1,p-JNK and Bcl-2(P＜0.05).Compared with PAE group,3-MA+PAE group demonstrated increased α-Syn expression(P＜0.05).Conclusions PAE could attenuate the injury of SH-SY5Y cells induced by A53T-α-Syn and eliminate over-expressed α-Syn by activating autophagy pathway,which may be associated with the upregulation of JNK/Bcl-2 mediated autophagy pathway.

Good endometrial receptivity is an essential factor for embryo implantation,and gene expression in endometrial tissue during the window of implantation(WOI)is closely related to receptivity.Transcriptome sequencing technology enables the identification of gene expression profiles of endometrium during different menstrual phases,as well as microRNAs and long-chain non-coding RNA sequences involved in regulating gene expression.Combining this technology with bioinformatics analysis provides a better understanding of specific gene expression during the receptive period and offers technical support for studying its regulatory mechanism.Moreover,gene expression profiles of the endometrium during different menstrual phases hold significant clinical application value for accurately assessing endometrium receptivity in infertility patients and those with repeated implantation failure,thereby guiding individualized embryo transfer strategies.This review summarizes the progress of transcriptome sequencing in evaluating human endometrial receptivity and discusses future research directions.This review aims to understand the complex molecular mechanisms of endometrial receptivity formation and regulation from the transcriptional level,in order to improve the implantation rate of embryos in assisted reproductive technology and reduce the abortion rate.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.