Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94～0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.

Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94～0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.

Loop-mediated isothermal amplification(LAMP)is a newin vitronucleic acid amplification technique,which has been widely used in rapid detection of pathogenic bacteria,with advantages of high efficiency,simple operation and low cost.Microfluidic chip technique is a kind of miniaturized and integrated analytical technology,which integrates automation and high throughput,and can effectively avoid sample cross-contamination and has the advantages of high sample utilization rate and high cost-effectivenes.LAMP combined with microfluidic chip can detect multiple samples of the same pathogen at the same time or single samples of different pathogens at the same time,providing a new method for the rapid,field detection of pathogens.In this paper,the research progresses of LAMP microfluidic chip and its application in rapid detection of pathogenic bacteria in recent years were reviewed,and the future prospect was discussed.

Objective To establish a rapid screening and analysis method for etomidate and its ana-logues using a portable mass spectrometer equipped with a thermal desorption-atmospheric pressure chemical ionization source-linear ion trap.Methods A 10 μL aliquot of a standard solution at a con-centration of 1 μg/mL was taken,and after the solvent evaporated,the sample was inserted into the in-let of the portable mass spectrometer for detection.By adjusting the collision-induced dissociation pa-rameters,the molecular ion peak and fragment ion peak information of the standard were obtained and used to establish a reference database.In addition,the method was applied to 29 seized liquid and plant samples.Results A screening system for etomidate and its analogues was established based on the portable mass spectrometer and the corresponding mass spectrometry library.The system enables qualitative screening analysis by identifying primary protonated molecular ions and secondary product ions of etomidate and its analogues.The limits of detection for etomidate and its 12 analogues ranged from 0.1 to 10 μg/mL.Etomidate and its analogues were detected in all 29 liquid and plant samples.However,this method could not distinguish between isomeric imidazole esters,such as isopropoxate and propoxate.Additionally,when testing 2-SH-etomidate,there was a false positive for the detection of etomidate.Conclusion This study established a rapid screening method for etomidate and its ana-logues using a portable mass spectrometer.The method combines the high sensitivity of mass spectrome-try with the on-site applicability of portable devices,significantly improving detection efficiency and meeting the on-site detection needs of etomidate and its analogues.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

In this study, lipopolysaccharide(LPS), ovalbumin(OVA), and compound 48/80(C48/80) were administered to establish non-infectious pneumonia models under simulated clinical conditions, and the correlation between their pathological characteristics and traditional Chinese medicine(TCM) syndromes was compared, providing the basis for the selection of appropriate animal models for TCM efficacy evaluation. An acute pneumonia model was established by nasal instillation of LPS combined with intraperitoneal injection for intensive stimulation. Three doses of OVA mixed with aluminum hydroxide adjuvant were injected intraperitoneally on days one, three, and five and OVA was administered via endotracheal drip for excitation on days 14-18 to establish an OVA-induced allergic pneumonia model. A single intravenous injection of three doses of C48/80 was adopted to establish a C48/80-induced pneumonia model. By detecting the changes in peripheral blood leukocyte classification, lung tissue and plasma cytokines, immunoglobulins(Ig), histamine levels, and arachidonic acid metabolites, the multi-dimensional analysis was carried out based on pathological evaluation. The results showed that the three models could cause pulmonary edema, increased wet weight in the lung, and obvious exudative inflammation in lung tissue pathology, especially for LPS. A number of pyrogenic cytokines, inclading interleukin(IL)-6, interferon(IFN)-γ, IL-1β, and IL-4 were significantly elevated in the LPS pneumonia model. Significantly increased levels of prostacyclin analogs such as prostaglandin E2(PGE2) and PGD2, which cause increased vascular permeability, and neutrophils in peripheral blood were significantly elevated. The model could partly reflect the clinical characteristics of phlegm heat accumulating in the lung or dampness toxin obstructing the lung. The OVA model showed that the sensitization mediators IgE and leukotriene E4(LTE4) were increased, and the anti-inflammatory prostacyclin 6-keto-PGF2α was decreased. Immune cells(lymphocytes and monocytes) were decreased, and inflammatory cells(neutrophils and basophils) were increased, reflecting the characteristics of "deficiency", "phlegm", or "dampness". Lymphocytes, monocytes, and basophils were significantly increased in the C48/80 model. The phenotype of the model was that the content of histamine, a large number of prostacyclins(6-keto-PGE1, PGF2α, 15-keto-PGF2α, 6-keto-PGF1α, 13,14-D-15-keto-PGE2, PGD2, PGE2, and PGH2), LTE4, and 5-hydroxyeicosatetraenoic acid(5S-HETE) was significantly increased, and these indicators were associated with vascular expansion and increased vascular permeability. The pyrogenic inflammatory cytokines were not increased. The C48/80 model reflected the characteristics of cold and damp accumulation. In the study, three non-infectious pneumonia models were constructed. The LPS model exhibited neutrophil infiltration and elevated inflammatory factors, which was suitable for the efficacy study of TCM for clearing heat, detoxifying, removing dampness, and eliminating phlegm. The OVA model, which took allergic inflammation as an index, was suitable for the efficacy study of Yiqi Gubiao formulas. The C48/80 model exhibited increased vasoactive substances(histamine, PGs, and LTE4), which was suitable for the efficacy study and evaluation of TCM for warming the lung, dispersing cold, drying dampness, and resolving phlegm. The study provides a theoretical basis for model selection for the efficacy evaluation of TCM in the treatment of pneumonia.
Animals ; Disease Models, Animal ; Mice ; Pneumonia/genetics* ; Medicine, Chinese Traditional ; Male ; Humans ; Cytokines/immunology* ; Female ; Lipopolysaccharides/adverse effects* ; Lung/drug effects* ; Drugs, Chinese Herbal ; Ovalbumin ; Mice, Inbred BALB C

OBJECTIVES: To investigate the role and mechanism of fibroblast growth factor (FGF) 19 in inflammation-induced injury of vascular endothelial cells caused by high glucose (HG). METHODS: Human umbilical vein endothelial cells (HUVECs) were randomly divided into four groups: control, HG, FGF19, and HG+FGF19 (n=3 each). The effect of different concentrations of glucose and/or FGF19 on HUVEC viability was assessed using the CCK8 assay. Flow cytometry was utilized to examine the impact of FGF19 on HUVEC apoptosis. Levels of interleukin-6 (IL-6), inducible nitric oxide synthase (iNOS), total superoxide dismutase (T-SOD), and malondialdehyde (MDA) were measured by ELISA. Real-time quantitative PCR and Western blotting were used to determine the mRNA and protein expression levels of vascular endothelial growth factor (VEGF), nuclear factor erythroid 2 related factor 2 (Nrf2), and heme oxygenase-1 (HO-1). Cells were further divided into control, siRNA-Nrf2 (siNrf2), HG, HG+FGF19, HG+FGF19+negative control, and HG+FGF19+siNrf2 groups (n=3 each) to observe the effect of FGF19 on oxidative stress injury in HUVECs induced by high glucose after silencing the Nrf2 gene. RESULTS: Compared to the control group, the HG group exhibited increased apoptosis rate, increased IL-6, iNOS and MDA levels, and increased VEGF mRNA and protein expression, along with decreased T-SOD activity and decreased mRNA and protein expression of Nrf2 and HO-1 (P<0.05). Compared to the HG group, the HG+FGF19 group showed reduced apoptosis rate, decreased IL-6, iNOS and MDA levels, and decreased VEGF mRNA and protein expression, with increased T-SOD activity and increased Nrf2 and HO-1 mRNA and protein expression (P<0.05). Compared to the HG+FGF19+negative control group, the HG+FGF19+siNrf2 group had decreased T-SOD activity and increased MDA levels (P<0.05). CONCLUSIONS FGF19 can alleviate inflammation-induced injury in vascular endothelial cells caused by HG, potentially through the Nrf2/HO-1 signaling pathway.
Humans ; NF-E2-Related Factor 2/genetics* ; Signal Transduction ; Human Umbilical Vein Endothelial Cells/drug effects* ; Fibroblast Growth Factors/pharmacology* ; Heme Oxygenase-1/physiology* ; Apoptosis/drug effects* ; Glucose ; Inflammation ; Interleukin-6/analysis* ; Vascular Endothelial Growth Factor A/genetics* ; Nitric Oxide Synthase Type II/analysis* ; Cells, Cultured

Objective:To development a deep learning（DL） model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma（NPC） and nasopharyngeal lymphoma（NPL）. Methods:The retrospective study included 142 patients with NPL and 292 patients with NPC who underwent conventional MRI at Renmin Hospital of Wuhan University from June 2012 to February 2023. MRI from 80 patients were manually segmented to train the segmentation model. The automatically segmented regions of interest（ROIs） formed four datasets: T1 weighted images（T1WI）, T2 weighted images（T2WI）, T1 weighted contrast-enhanced images（T1CE）, and a combination of T1WI and T2WI. The ImageNet-pretrained ResNet101 model was fine-tuned for the classification task. Statistical analysis was conducted using SPSS 22.0. The Dice coefficient loss was used to evaluate performance of segmentation task. Diagnostic performance was assessed using receiver operating characteristic（ROC） curves. Gradient-weighted class activation mapping（Grad-CAM） was imported to visualize the model's function. Results:The DICE score of the segmentation model reached 0.876 in the testing set. The AUC values of classification models in testing set were as follows: T1WI: 0.78（95%CI 0.67-0.81）, T2WI: 0.75（95%CI 0.72-0.86）, T1CE: 0.84（95%CI 0.76-0.87）, and T1WI+T2WI: 0.93（95%CI 0.85-0.94）. The AUC values for the two clinicians were 0.77（95%CI 0.72-0.82） for the junior, and 0.84（95%CI 0.80-0.89） for the senior. Grad-CAM analysis revealed that the central region of the tumor was highly correlated with the model's classification decisions, while the correlation was lower in the peripheral regions. Conclusion:The deep learning model performed well in differentiating NPC from NPL based on conventional MRI. The T1WI+T2WI combination model exhibited the best performance. The model can assist in the early diagnosis of NPC and NPL, facilitating timely and standardized treatment, which may improve patient prognosis.
Humans ; Nasopharyngeal Carcinoma/diagnostic imaging* ; Deep Learning ; Magnetic Resonance Imaging ; Retrospective Studies ; Nasopharyngeal Neoplasms/diagnostic imaging* ; Lymphoma/diagnostic imaging* ; Diagnosis, Differential ; ROC Curve ; Male ; Female ; Middle Aged ; Adult

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To investigate the efficacy and toxicity of blinatumomab in the first-line and second-line treatment of pediatric B-cell acute lymphoblastic leukemia (B-ALL).Methods:A multi-center retrospective cohort study was conducted to analyze clinical data from 323 pediatric B-ALL patients treated with blinatumomab across 14 hospitals in China from May 2021 to July 2023. Patients were divided into four groups based on the treatment phase and disease status when blinatumomab was used: relapsed/refractory group, post-consolidation minimal residual disease (MRD)-positive group, early MRD-positive group, and MRD-negative group. Blinatumomab for the relapsed/refractory group was considered as second-line treatment, while the other 3 groups as first-line treatment. The MRD negativity rate after treatment, the survival rates and the incidence of severe adverse events were compared across these groups. Patients who received blinatumomab for more than 7 days were included in the efficacy analysis. Survival analysis was performed using the Kaplan-Meier method, and Log-Rank test was used to compare the survival rates among groups.Results:Among the 323 patients, 191 (59.1%) were male, with the age of 6.2 (3.9, 10.5) years. There were 117 patients in the relapsed/refractory group, 62 cases in the post-consolidation MRD-positive group, 43 cases in the early MRD-positive group, and 101 cases in the MRD negative group. In the relapsed/refractory group, the complete remission rate and MRD negativity rate after one course of blinatumomab were 71.4% (35/49) and 81.5% (75/92) for the 49 children without complete remission and the 92 children with flow cytometry-positive MRD, respectively. In the post-consolidation MRD-positive group, the MRD negativity rates after one course of blinatumomab were 100.0% (27/27), 12/16 and 9/19 for patients with MRD positivity detected by flow cytometry, polymerase chain reaction and next-generation sequencing, respectively. In the early MRD-positive group, the MRD negativity rates were 96.7% (29/30) and 9/9 for flow cytometry and next-generation sequencing, respectively. The 2-year overall survival rate and event-free survival rate for the 319 children evaluable for efficacy were (90.6±1.7)% and (87.6±1.9)%, respectively, with the relapsed/refractory group showing significantly lower overall survival rates and event-free survival rate compared to the other groups ( χ2=21.40, 26.21,both P<0.001). Grade 3 or higher adverse events occurred in 128 cases (39.6%), with hematological toxicity observed in 101 cases, while cytokine release syndrome (CRS), infection, and neurotoxicity occurred in 11, 26 and 8 cases, respectively. In addition, there were statistically significant differences in the grade 3 or higher CRS among the four groups ( χ2=8.03, P<0.05). Conclusion:Blinatumomab can clear MRD more effectively and achieve superior survival outcomes when used as first-line treatment for pediatric B-ALL, with less CRS.