Objective To summarize and analyze the efficacy and influencing factors of second allogeneic hematopoietic stem cell transplantation (allo-HSCT) for acute leukemia relapsing after the first allo-HSCT. Methods Clinical data of 17 patients with acute leukemia who underwent second allo-HSCT at Peking University First Hospital from January 2005 to December 2024 were retrospectively analyzed. Results Among the 17 patients, 7 achieved long-term disease-free survival after second transplantation. The median progression-free survival after successful second transplantation was 7 months (range 8 days to 69 months). The relapse fatality was 24%, and the transplant-related fatality was 35%. Conclusions Second transplantation is an effective treatment for relapsed and refractory acute leukemia, but the relapse fatality and transplant-related fatality remain high. Patient age, time of relapse after the first transplantation and disease status before second transplantation are all factors that affect the efficacy of second transplantation. Younger age, late relapse and complete remission of disease before second transplantation are all beneficial for long-term disease-free survival after second transplantation.

In the era of evidence-based medicine， the progress of medical science and technology has enriched medical diagnostic tools and treatment methods， but it has also led to the loss of medical warmth and the alienation of the doctor-patient relationships. William Osler emphasized that while medical technology advances， attention should also be paid to the practice of narrative medicine and the development of physician’s narrative literacy. The view of the physician he advocated reminds us that the core of medicine still lies in the narrative connection between doctors and patients， as well as a deep understanding of human nature. By exploring the relationship between Osler’s view of the physician and narrative medicine as well as physician’s narrative literacy， this paper analyzed the methods of cultivating physician’s narrative literacy， providing references for modern medical education and practice， and assisting in the harmony and unity of science and technology and humanity.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

Objective To investigate the effects of paeoniflorin(PF)on lipopolysaccharide(LPS)-induced aerobic glycolysis in renal tubular epithelial cell line HK-2 and its underlying mechanism of action.Methods This study consists of a preliminary experiment and a formal experiment.Preliminary experiment:CCK-8 assay and RT-qPCR were used respectively to measure cell viability and mRNA expression levels of inflammatory factors in HK-2 cells after LPS stimulation to determine the optimal LPS concentration for modeling as well as to evaluate the toxicity of PF and screen for its appropriate concentration.Formal experiment:HK-2 cells were divided into control group(CON group),LPS group,LPS+PF group and LPS+PF+740Y-P group.LPS was used to establish a cell model of sepsis associated-acute kidney injury(SA-AKI)in HK-2 cells,and then the cell model was treated with PF and PI3K activator 740Y-P,correspondingly for 24 h.CCK-8 assay was employed to detect cell viability,and Extracellular Acidification Rate(ECAR)Kit was utilized to measure the rate.The contents of IL-1β,IL-18,lactic acid(Lac)and lactate dehydrogenase A(LDHA)were determined with ELISA.Western blotting was applied to detect the expression of p-PI3K,p-AKT,HIF-1α,pyruvate kinase 2(PKM2,a key enzyme in aerobic glycolysis)and NOD-like receptor thermal protein domain associated protein 3(NLRP3),and immunofluorescence assay was performed to observe the expression and distribution of PKM2.Results ① Our preliminary experiment identified that the optimal concentration of LPS for modeling was 20.0 μg/mL,a safe dosage range of PF was 0～100.0 μmol/L,and its optimal therapeutic concentration was 25.0 μmol/L.② Compared with the CON group,LPS stimulation resulted in significantly decreased cell viability(P<0.05),increased ECAR(P<0.05),elevated contents of IL-1β,IL-18,Lac and LDHA(P<0.05),up-regulated protein levels of p-PI3K,p-AKT,HIF-1α,p-PKM2 and NLRP3(P<0.05),and enhanced fluorescence intensity of PKM2 in the nucleus of cells(P<0.05).Compared with the model group,PF treatment reversed all above effects induced by LPS stimulation(all P<0.05).Compared with the LPS+PF group,in the LPS+PF+740Y-P group,ECAR was elevated(P<0.05),the contents of IL-1β,IL-18,Lac and LDHA were increased(P<0.05),and the relative expression levels of p-PI3K,p-AKT,HIF-1α,p-PKM2 and NLRP3 were increased(P<0.05),and the fluorescence intensity of PKM2 was strengthened(P<0.05)and enhanced in the nucleus(P<0.05).Conclusion PF reduces aerobic glycolysis in HK-2 cells and alleviates the inflammatory response by inhibiting the PI3K/AKT/HIF-1α signaling pathway.

Objective: To analyze the distribution characteristics of immunoglobulin A (IgA) concentration in Nanning Zhuang blood donors by measuring the concentration of plasma IgA. Methods: Enzyme-linked immunosorbent assay (ELISA) was performed to measure the absorbance of 2 000 plasma samples from Zhuang blood donors. The IgA concentration in samples was calculated using the ELISA Calc regression/fitting technology program. Results: The standard curve demonstrated that ELISA detection of plasma IgA concentration exhibited good precision. The frequency of IgA deficiency was 0/2 000. No statistically significant difference in the distribution of IgA concentration was observed between males and females (P>0.05). The distribution of IgA concentration varied significantly across age groups: younger individuals (18-39 years old) had lower plasma IgA levels (mg/dL) compared to older individuals (40-56 years old): 5-89.99 mg/dL group, 8.80% (176/2 000) vs 17.20% (344/2 000); 90-450 mg/dL group,20.65% (413/2 000) vs 51.20% (1 024/2 000); >450 mg/dL group, 0.45%, (9/2 000) vs 1.70% (34/2 000), P<0.05. No significant difference in IgA concentration was found among different ABO blood types in Zhuang blood donors (P>0.05). Spearman correlation analysis revealed a positive correlation between age and IgA concentration (R =0.114, P<0.05). Conclusion: No individuals with IgA deficiency were screened out among the Zhuang blood donors in Nanning area, and plasma IgA levels progressively increase with age.

Objective: To analyze the implementation status and challenges of sex education in special education schools, so as to provide a scientific basis for formulating effective promotion strategies. Methods: From November 2023 to January 2024, a census survey was conducted among 120 in service teachers from 7 special education schools in Luzhou. The questionnaire covered the current status of sex education in schools, teachers attitudes and knowledge toward sex education, and their coping methods for students inappropriate sexual behaviors. Results: About 77.5% of teachers reported having provided sex education to students, but 93.2% indicated a lack of specialized sex education textbooks for special children, 90.4% reported no full time teachers for sex education, and the methods of sex education were relatively limited (50.0% mainly based on lecture method). Nearly 95.8% of teachers held a positive attitude toward sex education, with 98.3% supporting its implementation. Only 26.7% of teachers demonstrated a good grasp of sex education knowledge, with the best understood topic being "recognition and protection of private parts" (21.6%). When dealing with students inappropriate sexual behaviors, the active response rate of teachers was 23.9%, with the highest active response rate observed for "intentionally hugging or kissing the opposite sex" (39.7%). Conclusions The special education schools in Luzhou lack comprehensive sex education curricula, teaching materials and full time teachers, sufficient knowledge among teachers, and adequate proactive responses to students inappropriate sexual behaviors. Greater emphasis should be placed on sex education for special children, including the training of dedicated teachers, to provide comprehensive and high quality sex education services for special children.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

Objective:To assess the clinical value of digital PCR (dPCR) for the prenatal diagnosis of common fetal aneuploidies.Methods:A dPCR-based assay was developed for detecting trisomies 21, 18, and 13. A retrospective analysis was carried out on 173 amniotic fluid samples collected by the Prenatal Diagnosis Center of Taizhou Hospital between January 2017 and December 2023. By using chromosomal karyotyping as the gold standard, the diagnostic performance of the multiplex dPCR system was evaluated in a double-blind manner. This study has been approved by the Ethics Committee of Taizhou Hospital (Ethics No. K20250339).Results:Chromosomal karyotyping has identified 59 cases of trisomy 21, 5 cases of trisomy 18, 2 cases of trisomy 13, 6 cases with chromosomal structural abnormalities or mosaicisms, and 101 cases with a normal karyotype. The dPCR results ( Z-score cutoff = 4.0, CI = 99.997%) showed full concordance with karyotyping (sensitivity = 100%, specificity = 100%, Kappa = 1). Among the 6 structurally abnormal or mosaicism samples, dPCR has accurately detected 4 cases, but mis-classified 2 cases of trisomy 21 with very low-level mosaicisms (3.3%, 6.9%, respectively) as normal. Conclusion:The established multiplex dPCR system demonstrated high diagnostic accuracy for common chromosomal aneuploidies, with results available within 24 hours. It can serve as an efficient supplementary tool to conventional chromosomal karyotyping, providing reliable support for time-sensitive clinical decision-making in prenatal diagnosis.

Protein arginine methyltransferase 5 (PRMT5) acts as an oncogene in liver cancer, yet its roles and in-depth molecular mechanisms within the liver cancer immune microenvironment remain mostly undefined. Here, we demonstrated that disruption of tumor-intrinsic PRMT5 enhances CD8⁺ T-cell-mediated antitumor immunity both in vivo and in vitro. Further experiments verified that this effect is achieved through downregulation of the inhibitory immune checkpoint molecule, fibrinogen-like protein 1 (FGL1). Mechanistically, PRMT5 catalyzed symmetric dimethylation of transcription factor 12 (TCF12) at arginine 554 (R554), prompting the binding of TCF12 to FGL1 promoter region, which transcriptionally activated FGL1 in tumor cells. Methylation deficiency at TCF12-R554 residue downregulated FGL1 expression, which promoted CD8⁺ T-cell-mediated antitumor immunity. Notably, combining the PRMT5 methyltransferase inhibitor GSK591 with PD-L1 blockade efficiently inhibited liver cancer growth and improved overall survival in mice. Collectively, our findings reveal the immunosuppressive role and mechanism of PRMT5 in liver cancer and highlight that targeting PRMT5 could boost checkpoint immunotherapy efficacy.

Metabolic reprogramming plays a central role in tumors. However, the key drivers modulating reprogramming of gluconeogenesis/lipogenesis are poorly understood. Here, we try to identify the mechanism by which histone acetyltransferase 1 (HAT1) confers reprogramming of gluconeogenesis/lipogenesis in liver cancer. Diethylnitrosamine (DEN)/carbon tetrachloride (CCl₄)-induced hepatocarcinogenesis was hardly observed in HAT1-knockout mice. Multi-omics identified that HAT1 modulated gluconeogenesis and lipogenesis in liver. Protein phosphatase 2 scaffold subunit alpha (PPP2R1A) promoted gluconeogenesis and inhibited lipogenesis by phosphoenolpyruvate carboxykinase 1 (PCK1) serine 90 dephosphorylation to suppress the tumor growth. HAT1 succinylated PPP2R1A at lysine 541 (K541) to block the assembly of protein phosphatase 2A (PP2A) holoenzyme and interaction with PCK1, resulting in the depression of dephosphorylation of PCK1. HAT1-succinylated PPP2R1A contributed to the remodeling of gluconeogenesis/lipogenesis by PCK1 serine 90 phosphorylation, leading to the inhibition of gluconeogenic enzyme activity and activating sterol regulatory element-binding protein 1 (SREBP1) nuclear accumulation-induced lipogenesis gene expression, which enhanced the tumor growth. In conclusion, succinylation of PPP2R1A lysine 541 by HAT1 converses the role in modulation of gluconeogenesis/lipogenesis remodeling through PCK1 S90 phosphorylation to support liver cancer. Our finding provides new insights into the mechanism by which post-translational modifications (PTMs) confer the conversion of tumor suppressor function to oncogene.