Objective: Traumatic brain injury (TBI) patients often experience massive bleeding and require blood transfusion. However, the storage duration of the transfused blood may affect the prognosis of these patients. This study explored the influence of exosomes derived from fresh and aged blood on the prognosis of rats with TBI, so as to provide theoretical support for the blood transfusion management of TBI patients. Methods: Exosomes were isolated from red blood cell (RBC) suspensions stored for 1 week and 5 weeks using ultracentrifugation method. The size, morphology and surface markers of the exosomes were identified by nanoparticle flow cytometry, transmission electron microscopy and Western blotting, respectively. A rat model of TBI was constructed using a mechanical impactor for brain injury. After the successful establishment of the model, exosomes from RBC suspensions stored for 1 week and 5 weeks were injected into the extracellular space of rat brain cells using a stereotactic syringe. Cerebral edema at day 1, 3, 7 and 14 were recorded through cranial magnetic resonance imaging (MRI) scans. Magnetic tracing technology (the tracer was Gd-DTPA solution) was used to evaluate the drug metabolism level in the extracellular space of brain cells of TBI rats. The cranial magnetic resonance imaging was scanned every 15 or 30 minutes, and the recording lasted for a total of 240 minutes. The magnetic images were imported into the 3D-Slicer software in Dicom data format for analysis. Mass spectrometry technology was used to analyze the differential proteins of exosomes from RBC suspensions stored for 1 week and 5 weeks, and functional prediction was carried out to explore the possible mechanisms by which exosomes affect the prognosis of TBI. Results: After injection of exosomes into TBI rats, the areas of cerebral edema on the day 1, 3, 7, and 14 were all significantly higher in the rats treated with exosomes from 5-week-stored RBC suspensions, with peak cerebral edema occurring at day 3. The diffusion volume of the tracer was significantly higher in TBI rats than in normal rats, which implied there was a disorder in the structure of the traumatic brain tissue in TBI rats. Compared with the rats injected with exosomes from 1-week-stored RBC suspensions, those treated with exosomes from 5-week-stored RBC suspensions showed increased tracer diffusion volume within 120 minutes. Mass spectrometry analysis identified 81 differentially expressed proteins between exosomes from RBC suspensions stored for 5 weeks vs 1 week. Among them, 93.83% (76/81) proteins had increased expression levels. The neurodegeneration-related pathways were among the most enriched pathways for upregulated proteins. Conclusion: The exosomes from aged RBC suspensions can lead to exacerbated cerebral edema, disrupted extracellular space, and suppressed metabolic rate in TBI rats, suggesting that transfusion of aged RBC suspensions may have adverse effects on TBI patients.

OBJECTIVES: To investigate the clinical sub-phenotype (SP) of pediatric acute kidney injury (AKI) and their association with clinical outcomes. METHODS: General status and initial values of laboratory markers within 24 hours after admission to the pediatric intensive care unit (PICU) were recorded for children with AKI in the derivation cohort (n=650) and the validation cohort (n=177). In the derivation cohort, a least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify death-related indicators, and a two-step cluster analysis was employed to obtain the clinical SP of AKI. A logistic regression analysis was used to develop a parsimonious classifier model with simplified metrics, and the area under the curve (AUC) was used to assess the value of this model. This model was then applied to the validation cohort and the combined derivation and validation cohort. The association between SPs and clinical outcomes was analyzed with all children with AKI as subjects. RESULTS: In the derivation cohort, two clinical SPs of AKI (SP1 and SP2) were identified by the two-step cluster analysis using the 20 variables screened by LASSO regression, namely SP_d1 group (n=536) and SP_d2 group (n=114). The simplified classifier model containing eight variables (P<0.05) had an AUC of 0.965 in identifying the two clinical SPs of AKI (P<0.001). The validation cohort was clustered into SP_v1 group (n=156) and SP_v2 group (n=21), and the combined derivation and validation cohort was clustered into SP1 group (n=694) and SP2 group (n=133). After adjustment for confounding factors, compared with the SP1 group, the SP2 group had significantly higher incidence rates of multiple organ dysfunction syndrome and death during the PICU stay (P<0.001), and SP2 was significantly associated with the risk of death within 28 days after admission to the PICU (P<0.001). CONCLUSIONS This study establishes a parsimonious classifier model and identifies two clinical SPs of AKI with different clinical features and outcomes.The SP2 group has more severe disease and worse clinical prognosis.
Humans ; Acute Kidney Injury/diagnosis* ; Prognosis ; Male ; Female ; Child ; Child, Preschool ; Phenotype ; Infant ; Logistic Models ; Adolescent

Liraglutide (Lira), a glucagon-like peptide-1 (GLP-1) receptor agonist approved for diabetes and obesity, has shown significant potential in treating metabolic dysfunction-associated steatotic liver disease (MASLD). However, its systematic molecular regulation and mechanisms remain underexplored. In this study, a mouse model of MASLD was developed using a high-fat diet (HFD), followed by Lira administration. Proteomics and glycoproteomics were analyzed using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS), while potential molecular target analysis was conducted via quantitative real-time polymerase chain reaction (qPCR) and Western blotting. Our results revealed that Lira treatment significantly reduced liver weight and serum markers, including alanine aminotransferase (ALT) and others, with glycosylation changes playing a more significant role than overall protein expression. The glycoproteome identified 255 independent glycosylation sites, emphasizing the impact of Lira on amino acid, carbohydrate metabolism, and ferroptosis. Simultaneously, proteomic analysis highlighted its effects on lipid metabolism and fibrosis pathways. 21 signature molecules, including 7 proteins and 14 N-glycosylation sites (N-glycosites), were identified as potential targets. A Lira hydrogel formulation (Lira@fibrin (Fib) Gel) was developed to extend drug dosing intervals, offering enhanced therapeutic efficacy in managing chronic metabolic diseases. Our study demonstrated the importance of glycosylation regulation in the therapeutic effects of Lira on MASLD, identifying potential molecular targets and advancing its clinical application for MASLD treatment.

Objective:To explore the clinical characteristics and prognostic influencing factors of multiple primary lung cancer (MPLC), and to construct a prognostic prediction model.Methods:The clinical data and prognostic information of MPLC patients diagnosed by pathological examination included in the Surveillance, Epidemiology, and End Results (SEER) database from January 2010 to December 2020 were retrospectively analyzed. Patients were randomly divided into training and validation sets according to a 7:3 ratio using R software. Survival curves were plotted by using the Kaplan-Meier method and log-rank test was used for comparison between groups. The independent influencing factors of overall survival (OS) of MPLC patients in the training set were screened using univariate and multivariate Cox proportional hazards models, and accordingly, the nomogram predicting the survival rate of patients at 3, 5 and 8 years were plotted. In the training and validation sets, using the actual survival as the gold standard, the receiver operating characteristic (ROC) curves of the constructed models for predicting the patients' 3-, 5- and 8-year OS rates were plotted, the area under the curve (AUC) was obtained, and C-index of the model was analyzed by using R software. The calibration curves of 3-, 5- and 8-year OS rates predicted by the models and the actual OS rates were plotted.Results:A total of 5 495 MPLC patients were included, 3 846 in the training set and 1 649 in the validation set. The differences in the composition of patients of different ages and AJCC stages between the training and validation sets were statistically significant (both P < 0.05), and the differences in the comparison of other clinicopathological characteristics were not statistically significant (all P > 0.05). The results of multivariate Cox regression analysis showed that males (compared with females, HR = 1.256, 95% CI: 1.144-1.379, P < 0.001), age ≥ 70 years old (compared with 50-59 years old, HR = 1.201, 95% CI: 1.030-1.400, P = 0.019), FPLC with pathological types of squamous cell carcinoma or other types (compared with adenocarcinoma, HR = 1.275, 95% CI: 1.137-1.431, P < 0.001; HR = 1.208, 95% CI: 1.041-1.403, P = 0.013), and SPLC with pathological types of squamous cell carcinoma, small cell lung carcinoma, or other types (compared with adenocarcinoma, HR = 1.270, 95% CI: 1.121-1.440, P < 0.001; HR = 1.978, 95% CI: 1.642-2.384, P < 0.001; HR = 1.246, 95% CI: 1.090-1.424, P = 0.001), and AJCC stage Ⅲ and Ⅳ (compared with stage Ⅰ, HR = 1.645, 95% CI: 1.447-1.869, P < 0.001; HR = 2.078, 95% CI: 1.669-2.587, P < 0.001), FPLC without operation (compared with operation, HR = 1.263, 95% CI: 1.038-1.536, P = 0.020), SPLC without operation (operation vs. no operation, HR = 0.680, 95% CI: 0.579-0.799, P < 0.001), FPLC without lymph node dissection or with clearance of 1-3 regional lymph nodes (compared with clearance of ≥4, HR = 1.225, 95% CI: 1.016-1.477, P = 0.034; HR = 1.314, 95% CI: 1.103-1.566, P = 0.002), FPLC with maximum diameter 3-5 cm or >5 cm (compared with <3 cm, HR = 1.181, 95% CI: 1.053-1.324, P = 0.005; HR = 1.232, 95% CI: 1.069-1.420, P = 0.004), and SPLC with maximum diameter 3-5 cm or >5 cm (compared with <3 cm, HR = 1.560, 95% CI: 1.362-1.786, P < 0.001; HR = 1.727, 95% CI: 1.451-2.054, P < 0.001), and FPLC without chemotherapy (chemotherapy vs. no chemotherapy or unknown, HR = 0.744, 95% CI: 0.655-0.845, P < 0.001) were the independent risk factors of patients' poor OS (all P < 0.05). The results of Kaplan-Meier survival analysis showed that the OS of patients with different gender, race, age, two tumor locations, AJCC staging, pathological type of two lung tumors, maximum diameter of two tumors, and whether two tumors were treated surgically or not, and whether two tumors were treated with chemotherapy or not in the training set were compared, and the differences were all statistically significant (all P < 0.05). Based on the independent factors affecting the OS of MPLC patients screened by the results of multivariate Cox regression analysis, nomogram predicting the 3-, 5- and 8-year OS rates of MPLC were plotted. The results of ROC curve analysis showed that the C-index of the training set's nomogram was 0.679 (95% CI: 0.649-0.701), and the AUC values for predicting the 3-, 5- and 8-year OS rates were 0.601, 0.595 and 0.586, respectively; the C-index of the validation set was 0.678 (95% CI: 0.633-0.720), and the AUC values for predicting 3-, 5- and 8-year OS rates were 0.643, 0.631 and 0.626, respectively. The calibration curves showed that the 3-, 5- and 8-year OS rates of patients predicted by the nomogram models in both the training and validation sets were in good agreement with the actual results with a high goodness-of-fit. Conclusions:The established prognostic model has good predictive value and can effectively assess the prognosis of patients.

Objective To establish the pharmacokinetic model of linezolid in neonates,and to optimize the administration regimen. Methods A prospective study was conducted among 64 neonates with sepsis who received linezolid as anti-infective therapy,and liquid chromatography-tandem mass spectrometry was used to measure the plasma concentration of the drug. Clinical data were collected,and nonlinear mixed effects modeling was used to establish a population pharmacokinetic (PPK) model. Monte Carlo simulation and evaluation was performed for the optimal administration regimen of children with different features. Results The pharmacokinetic properties of linezolid in neonates could be described by a single-compartment model with primary elimination,and the population typical values for apparent volume of distribution and clearance rate were 0.79 L and 0.34 L/h,respectively. The results of goodness of fit,visualization verification,and the Bootstrap method showed that the model was robust with reliable results of parameter estimation and prediction. Monte Carlo simulation results showed that the optimal administration regimen for linezolid in neonates was as follows:6 mg/kg,q8h,at 28 weeks of gestational age (GA);8 mg/kg,q8h,at 32 weeks of GA;9 mg/kg,q8h,at 34-37 weeks of GA;11 mg/kg,q8h,at 40 weeks of GA. Conclusions The PPK model established in this study can provide a reference for individual administration of linezolid in neonates. GA and body weight at the time of administration are significant influencing factors for the clearance rate of linezolid in neonates.

Objective To explore the value of electrocardiogram in predicting culprit vessels in acute inferior myocardial infarction.Methods The clinical data of 129 patients with acute inferior myocardial infarction admitted to First Affiliated Hospital of Army Medical University from January 2015 to December 2021 were retrospectively analyzed.Patients were received coronary intervention treatment,and the culprit vessels were identified by coronary angiography.The culprit vessels during surgery were recorded.The preoperative electrocardio-gram of patients were analyzed,a new method for predicting culprit vessels in acute inferior myocardial infarction was established based on the previous researches,and the accuracies of the Fiol method,Tiala method,Huang's algorithm and new method in predicting the culprit vessels in acute inferior myocardial infarction were also counted.The predictive abilities of various methods on culprit vessels were evaluated using receiver operating characteristic(ROC)curve and the area under the curve(AUC)was calculated.Results The culprit vessels of 109 patients were the right coronary artery,16 cases were the left circumflex artery,and 4 cases were the anterior descending artery.A total of 52 patients developed clinical complications,of which the culprit vessels of 47 cases were right coronary artery and 5 cases were circumflex artery.The accuracies of the Fiol method,Tierala method,Huang's algorithm,and new method in predicting culprit vessels were 83.7%,81.4%,82.9%,and 85.3%,respectively.The ROC curve analysis showed that the Fiol method(AUC=0.941),Tierrala method(AUC= 0.945),Huang's algorithm(AUC=0.945),and new method(AUC=0.964)all had strong predictive ability for culprit vessels.Conclusion For patients with acute inferior myocardial infarction,the Fiol method,Tierala method,Huang's algorithm,and new method all have high predictive value for culprit vessels in analyzing the preoperative electrocardiogram,and the new method has a higher predictive value.

Objective:To investigate the clinical efficacy and safety of ixazomib-containing regimens in the treatment of patients with multiple myeloma(MM).Methods:A retrospective analysis was performed on the clinical efficacy and adverse reactions of 32 MM patients treated with a combined regimen containing ixazomib in the Hematology Department of the First People's Hospital of Lianyungang from January 2020 to February 2022.Among the 32 patients,15 patients were relapsed and refractory multiple myeloma(R/RMM)(R/RMM group),17 patients who responded to bortezomib induction therapy but converted to ixazomib-containing regimen due to adverse events(AE)or other reasons(conversion treatment group).The treatment included IPD regimen(ixazomib+pomalidomide+dexamethasone),IRD regimen(ixazomib+lenalidomide+dexamethasone),ICD regimen(ixazomib+cyclophosphamide+dexamethasone),ID regimen(ixazomib+dexamethasone).Results:Of 15 R/RMM patients,overall response rate(ORR)was 53.3％(8/15),among them,1 achieved complete response(CR),2 achieved very good partial response(VGPR)and 5 achieved partial response(PR).The ORR of the IPD,IRD,ICD and ID regimen group were 100％(3/3),42.9％(3/7),33.3％(1/3),50％(1/2),respectively,there was no statistically significant difference in ORR between four groups(x2=3.375,P=0.452).The ORR of patients was 50％after first-line therapy,42.9％after second line therapy,60％after third line therapy or more,with no statistically significant difference among them(x2=2.164,P=0.730).In conversion treatment group,ORR was 88.2％(15/17),among them,6 patients achieved CR,5 patients achieved VGPR and 4 patients achieved PR.There was no statistically significant difference in ORR between the IPD(100％,3/3),IRD(100％,6/6),ICD(100％,3/3)and ID(60％,3/5)regimen groups(x2=3.737,P=0.184).The median progression-free survival(PFS)time of R/RMM patients was 9 months(95％CI:6.6-11.4 months),the median overall survival(OS)time was 18 months(95％CI:11.8-24.4 months).The median PFS time of conversion treatment group was 15 months(95％CI:7.3-22.7 months),the median OS time not reached.A total of 10 patients suffered grade 3-4 adverse event(AE).The common hematological toxicities were leukocytopenia,anemia,thrombocytopenia.The common non-hematological toxicities were gastrointestinal symptoms(diarrhea,nausea and vomit),peripheral neuropathy,fatigue and infections.Grade 1-2 peripheral neurotoxicity occurred in 7 patients.Conclusion:The ixazomib-based chemotherapy regimens are safe and effective in R/RMM therapy,particularly for conversion patients who are effective for bortezomib therapy.The AE was manageable and safe.

Aim To explore the effect and mechanism of the artesunate(ART)on hepatocellular carcinoma(HCC).Methods The cell lines MHCC-97H and HCC-LM3 were used to be detected.MTT and clone formation were used to determine the cell proliferation;Wound healing was used to detect the cell migration;Transwell was used to test the cell invasion.Flow-cy-tometry was used to detect cell apoptosis and cell cy-cle.RNA-seq and qRT-PCR was used to detect the genes expression.Results The proliferation,migra-tion and invasion of treated cells were obviously inhibi-ted(P＜0.01).Moreover,the apoptosis rate in-creased significantly,so did the proportion of G2/M cells.Transcriptomic analysis identified GADD45A as a potential target of ART through RNA-sequencing da-ta,and suggested that ART might induce apoptosis and cell cycle arrest through regulating the expression of GADD45A.In addition,the results of mechanism studies and signaling analysis suggested that GADD45A had interaction with its upstream gene NACC1(nucle-us accumbens associated 1).Moreover,after ART treatment,the expressions of GADD45A and NACC1 were changed significantly.Conclusion ART may be a potential drug to resist HCC by affecting the expres-sion of GADD45A and its upstream gene NACC1,which provides a new drug,a new direction and a new method for the clinical treatment of HCC.

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1-L3 vertebrae were measured based on QCT.Spongy bones of T5-T10 vertebrae were segmented as RO1,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,MLBagging OP and RadBagging-OP had the best performances for classification of OP.In test set,AUC of MLBagging-OP,RadBagging-op and DLOP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P＞0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of(x)±1.96s),which were highly positively correlated(r=0.910-0.974,all P＜0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.