OBJECTIVES: To investigate the clinicopathological characteristics and prognostic factors of pediatric Hodgkin lymphoma (HL). METHODS: A retrospective analysis was conducted on the clinical data of children with newly diagnosed HL from January 2011 to December 2023 at four hospitals: Fujian Medical University Union Hospital, Fujian Medical University Zhangzhou Hospital, First Affiliated Hospital of Xiamen University, and Fujian Children's Hospital. Patients were categorized into low-risk (R1), intermediate-risk (R2), and high-risk (R3) groups based on HL staging and pre-treatment risk factors. The patients received ABVD regimen or Chinese Pediatric HL-2013 regimen chemotherapy. Early treatment response and long-term efficacy were assessed, and prognostic factors were analyzed using the Cox proportional hazards regression model. RESULTS: The overall complete response (CR) rates after 2 and 4 cycles of chemotherapy were 42% and 68%, respectively. Compared with the ABVD regimen group, patients treated with the HL-2013 regimen in the R1 group showed significantly higher CR rates after both 2 and 4 cycles (P<0.05). However, no statistically significant differences in CR rates were observed between the two regimens in the R2 and R3 groups (P>0.05). The 5-year event-free survival (EFS) rate, overall survival rate, and freedom from treatment failure rate were 83%±4%, 97%±2%, and 88%±4%, respectively. Cox analysis indicated that the presence of a large tumor mass at diagnosis and failure to achieve CR after 4 cycles of chemotherapy were independent risk factors for lower EFS rates (P<0.05). CONCLUSIONS Pediatric HL generally has a favorable prognosis. The presence of a large tumor mass at diagnosis and failure to achieve CR after 4 cycles of chemotherapy indicate poor prognosis.
Humans ; Hodgkin Disease/pathology* ; Male ; Child ; Female ; Adolescent ; Retrospective Studies ; Child, Preschool ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Prognosis ; Proportional Hazards Models ; Survival Analysis ; Infant

Cold has been a long-term survival challenge in the evolutionary process of mammals. In response to cold stress, in addition to brown adipose tissue (BAT) dissipating energy as heat through glucose and lipid oxidation to maintain body temperature, cold stimulation can strongly activate thermogenesis and energy expenditure in beige fat cells, which are widely distributed in the subcutaneous layer. However, the effects of cold stimulation on other tissues and systemic lipid metabolism remain unclear. Our previous research indicated that, under cold stress, BAT not only produces heat but also secretes numerous exosomes to mediate BAT-liver crosstalk. Whether subcutaneous fat has a similar mechanism is still unknown. Therefore, this study aimed to investigate the alterations in lipid metabolism across various tissues under cold exposure and to explore whether subcutaneous fat regulates systemic glucose and lipid metabolism via exosomes, thereby elucidating the regulatory mechanisms of lipid metabolism homeostasis under physiological stress. RT-qPCR, Western blot, and H&E staining methods were used to investigate the physiological changes in lipid metabolism in the serum, liver, epididymal white adipose tissue, and subcutaneous fat of mice under cold stimulation. The results revealed that cold exposure significantly enhanced the thermogenic activity of subcutaneous adipose tissue and markedly increased exosome secretion. These exosomes were efficiently taken up by hepatocytes, where they profoundly influenced hepatic lipid metabolism, as evidenced by alterations in the expression levels of key genes involved in lipid synthesis and catabolism pathways. This study has unveiled a novel mechanism by which subcutaneous fat regulates lipid metabolism through exosome secretion under cold stimulation, providing new insights into the systemic regulatory role of beige adipocytes under cold stress and offering a theoretical basis for the development of new therapeutic strategies for obesity and metabolic diseases.
Animals ; Lipid Metabolism/physiology* ; Mice ; Exosomes/metabolism* ; Cold Temperature ; Subcutaneous Fat/physiology* ; Thermogenesis/physiology* ; Adipose Tissue, Brown/metabolism* ; Male

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To analyze the serum metabolomic changes of preterm infants with bronchopulmonary dysplasia(BPD)at postmenstrual age(PMA)36 weeks,screen potential biomarkers and associated metabolic pathways,and assess their relationship with short-term respiratory outcomes.Methods A retrospective case-control study was conducted.Infants with gestational age 28-32 weeks admitted to the Children's Hospital Affiliated to Zhengzhou University from January to December 2024 were included.Twenty infants with BPD and 20 gestational age-,birth weight-,and sex-matched non-BPD preterm infants were included.Serum collected at PMA 36 weeks was subjected to untargeted metabolomics analysis,and associations with short-term respiratory outcomes were analyzed.Results Thirteen potential biomarkers distinguishing BPD were identified(area under the curve>0.75,P<0.05).Eight biomarkers—including terephthalic acid,phosphatidylinositol,fumarate,and lysophosphatidic acid—were significantly upregulated(FC≥1.5),while five biomarkers,such as 7α-hydroxy-3-oxo-4-cholestenoate ester and phosphatidylcholine,were significantly downregulated(FC≤1/1.5).Pathway analysis indicated five pathways associated with BPD,including glycerophospholipid metabolism and phenylalanine metabolism.Dysregulation of glycerophospholipid and bile acid metabolism may affect adverse short-term respiratory outcomes in infants with BPD.Conclusions The 13 significantly different metabolites may serve as biomarkers for the diagnosis of BPD.Glycerophospholipid metabolism is associated with the occurrence of BPD and with adverse short-term respiratory outcomes.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Objective To analyze the serum metabolomic changes of preterm infants with bronchopulmonary dysplasia(BPD)at postmenstrual age(PMA)36 weeks,screen potential biomarkers and associated metabolic pathways,and assess their relationship with short-term respiratory outcomes.Methods A retrospective case-control study was conducted.Infants with gestational age 28-32 weeks admitted to the Children's Hospital Affiliated to Zhengzhou University from January to December 2024 were included.Twenty infants with BPD and 20 gestational age-,birth weight-,and sex-matched non-BPD preterm infants were included.Serum collected at PMA 36 weeks was subjected to untargeted metabolomics analysis,and associations with short-term respiratory outcomes were analyzed.Results Thirteen potential biomarkers distinguishing BPD were identified(area under the curve>0.75,P<0.05).Eight biomarkers—including terephthalic acid,phosphatidylinositol,fumarate,and lysophosphatidic acid—were significantly upregulated(FC≥1.5),while five biomarkers,such as 7α-hydroxy-3-oxo-4-cholestenoate ester and phosphatidylcholine,were significantly downregulated(FC≤1/1.5).Pathway analysis indicated five pathways associated with BPD,including glycerophospholipid metabolism and phenylalanine metabolism.Dysregulation of glycerophospholipid and bile acid metabolism may affect adverse short-term respiratory outcomes in infants with BPD.Conclusions The 13 significantly different metabolites may serve as biomarkers for the diagnosis of BPD.Glycerophospholipid metabolism is associated with the occurrence of BPD and with adverse short-term respiratory outcomes.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective To evaluate the process risk of the implementation of prevention and control measures for surgical site infection(SSI)after colorectal surgery,and explore the application effect of failure mode and effects analysis(FMEA)based on action priority.Methods FMEA based on action priority was adopted to evaluate the whole process of the implementation of prevention and control measures for SSI after colorectal surgery.Prioritiza-tion ranking was conducted according to whether optimized measures were taken.Standard-reaching rate of comp-liance to SSI prevention and control measures as well as SSI incidence before and after the implementation of FMEA were compared.Results After evaluation,there were 7 high-priority and 22 medium-priority prevention and control measures for SSI.The control of medium-priority measures was strengthened,with a focus on developing further preventive and detectable measures for high-priority measures.The re-evaluation results after improvement showed that 7 high-priority measures have been downgraded to medium priority,and 16 medium-priority measures have been downgraded to low priority.Standard-reaching rate of compliance to SSI prevention and control measures in-creased from 77.15％(2 566/3 326)to 92.47％(3 096/3 348),and SSI incidence decreased from 6.04％(58/960)to 2.54％(60/2 364).Conclusion Application of FMEA based on action priority can effectively evaluate the risk of prevention and control process of SSI after colorectal surgery,and adopting preventive risk control measures accord-ing to the current situation can reduce the incidence of SSI after colorectal surgery.

Objective: To explore the characteristics and correlations of vaginal flora in women with cervical lesions. Methods: A total of 132 women, including 41 women diagnosed with normal cervical (NC), 39 patients with low-grade cervical intraepithelial neoplasia (CIN 1), 37 patients with high-grade cervical intraepithelial neoplasia (CIN 2/3) and 15 patients with cervical squamous cell carcinoma (SCC), who came from the gynecological clinic of Second Hospital of Shanxi Medical University during January 2018 to June 2018, were enrolled in this study according to the inclusive and exclusive criteria strictly. The vaginal flora was detected by 16S rDNA sequencing technology. Co-occurrence network analysis was used to investigate the Spearman correlations between different genera of bacteria. Results: The dominant bacteria in NC, CIN 1 and CIN 2/3 groups were Lactobacillus [constituent ratios 79.4% (1 869 598/2 354 098), 63.6% (1 536 466/2 415 100) and 58.3% (1 342 896/2 301 536), respectively], while Peptophilus [20.4% (246 072/1 205 154) ] was the dominant bacteria in SCC group. With the aggravation of cervical lesions, the diversity of vaginal flora gradually increased (Shannon index: F=6.39, P=0.001; Simpson index: F=3.95, P=0.012). During the cervical lesion progress, the ratio of Lactobacillus gradually decreased, the ratio of other anaerobes such as Peptophilus, Sneathia, Prevotella and etc. gradually increased, and the differential bacteria (LDA score >3.5) gradually evolved from Lactobacillus to other anaerobes. The top 10 relative abundance bacteria, spearman correlation coefficient>0.4 and P<0.05 were selected. Co-occurrence network analysis showed that Prevotella, Peptophilus, Porphyrinomonas, Anaerococcus, Sneathia, Atopobium, Gardnerella and Streptococcus were positively correlated in different stages of cervical lesions, while Lactobacillus was negatively correlated with the above anaerobes. It was found that the relationship between vaginal floras in CIN 1 group was the most complex and only Peptophilus was significantly negatively correlated with Lactobacillus in SCC group. Conclusions: The increased diversity and changed correlations between vaginal floras are closely related to cervical lesions. Peptophilus is of great significance in the diagnosis, prediction and early warning of cervical carcinogenesis.
Female ; Humans ; Vagina/microbiology* ; Uterine Cervical Neoplasms/genetics* ; Uterine Cervical Dysplasia ; Cervix Uteri ; Lactobacillus/genetics* ; Papillomavirus Infections