Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Objective To investigate the value of MRI of the sternal end of clavicle in bone age assessment in Chinese population,especially its applicability in the determination of criminal responsible age.Methods A total of 431 patients aged from 10.00 to 29.99 years with neck or chest MRI were retrospectively collected.According to the Schmeling grading method,the epiphyseal development of the clavicle MRI was divided into five grades.The consistency of methods was evaluated.The correlation and general descriptive analysis between MRI grades and age was analyzed.The sex difference was analyzed.Curve fitting was used to establish a nonlinear model between age and grades.Results The grades of clavicle MRI showed a significant age-related trend(Figure 2),and the correlation was 0.861(0.887 in males and 0.840 in females).Except for grade 1,there was no significant difference between males and females in other grades.The minimum age of male grade 3 was greater than 14 years old,and the minimum age of female grade 3 was greater than 16 years old.The minimum age in grade 4 and grade 5 was over 18 years old in both sexes.The best curve fitting model was cubic model for both sexes(R2=0.805 for men and 0.722 for women).Conclusion Clavicle MRI can be used for the assessment of bone age in Chinese population.Complete epiphyseal plate closure can be used as a reliable indicator for the determination of age at 18 years old,and it is expected to achieve radiation-free forensic bone age assessment.

Objective To investigate the value of MRI of the sternal end of clavicle in bone age assessment in Chinese population,especially its applicability in the determination of criminal responsible age.Methods A total of 431 patients aged from 10.00 to 29.99 years with neck or chest MRI were retrospectively collected.According to the Schmeling grading method,the epiphyseal development of the clavicle MRI was divided into five grades.The consistency of methods was evaluated.The correlation and general descriptive analysis between MRI grades and age was analyzed.The sex difference was analyzed.Curve fitting was used to establish a nonlinear model between age and grades.Results The grades of clavicle MRI showed a significant age-related trend(Figure 2),and the correlation was 0.861(0.887 in males and 0.840 in females).Except for grade 1,there was no significant difference between males and females in other grades.The minimum age of male grade 3 was greater than 14 years old,and the minimum age of female grade 3 was greater than 16 years old.The minimum age in grade 4 and grade 5 was over 18 years old in both sexes.The best curve fitting model was cubic model for both sexes(R2=0.805 for men and 0.722 for women).Conclusion Clavicle MRI can be used for the assessment of bone age in Chinese population.Complete epiphyseal plate closure can be used as a reliable indicator for the determination of age at 18 years old,and it is expected to achieve radiation-free forensic bone age assessment.

Objective:To investigate the risk factors for patients with hypertriglyceridemia-related acute pancreatitis (HTG-AP) developing into severe acute pancreatitis or experiencing organ failure.Methods:This retrospective cohort study collected clinical data from 2 429 patients diagnosed with acute pancreatitis from five hospitals in China between January 2019 and December 2023 using a pre-designed data collection form. The cohort included 1 516 males and 913 females,with an age of (50.2±16.5)years(range: 11 to 99 years). Among them,353 patients (16.1%) had HTG-AP,while 1 846 (83.9%) had non-HTG-AP. HTG-AP was defined as serum triglyceride levels>500 mg/dl with other etiologies excluded. Intergroup comparisons were performed using t-tests,Mann-Whitney U test or χ2 tests,respectively. Univariate and multivariate logistic regression analyses were conducted to assess risk factors for severe acute pancreatitis after adjusting for potential confounders,and a predictive model was developed and validated. Results:Compared with other etiologies,HTG-AP patients had a higher risk of progressing to SAP ( OR=1.415,95% CI: 0.866 to 2.312, P=0.017) and organ failure ( OR=1.256,95% CI: 1.015 to 1.554, P=0.036). Among HTG-AP patients,risk factors for SAP included body mass index ( OR=1.856,95% CI: 1.742 to 1.987, P=0.033),fasting blood glucose ( OR=1.128,95% CI: 1.036 to 1.229, P=0.006),white blood cell count( OR=1.162,95% CI: 1.055 to 1.281, P=0.002),and the presence of pleural effusion ( OR=13.151,95% CI: 4.330 to 19.946, P<0.01). A nomogram prediction model for SAP in HTG-AP was constructed based on these risk factors,demonstrating good discriminative ability with area under the curve values of 0.877 in the training set and 0.894 in the validation set,along with satisfactory calibration. Conclusions:HTG-AP patients are at higher risk of developing SAP and organ failure. The risk prediction model incorporating body mass index,fasting blood glucose,white blood cell count,and pleural effusion shows good predictive value for SAP.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

Objective To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation(MPR),and to explore the applicability of cranial suture closure rule in age estimation of northern Chinese Han population.Methods The head CT samples of 132 northern Chinese Han adults aged 29-80 years were retrospectively collected.Volume reconstruction(VR)and MPR were performed on the skull,and 160 cranial suture tomography images were generated for each sample.Then the MPR images of cranial sutures were scored according to the closure grading criteria,and the mean closure grades of sagittal suture,coronal sutures(both left and right)and lambdoid sutures(both left and right)were calculated respectively.Finally taking the above grades as independent variables,the linear regression model and four machine learning models for age estimation(gradient boosting regression,support vector regression,decision tree regression and Bayesian ridge regression)were established for northern Chinese Han adults age estimation.The accu-racy of each model was evaluated.Results Each cranial suture closure grade was positively correlated with age and the correlation of sagittal suture was the highest.All four machine learning models had higher age estimation accuracy than linear regression model.The support vector regression model had the highest accuracy among the machine learning models with a mean absolute error of 9.542 years.Conclusion The combination of skull CT-MPR and machine learning model can be used for age esti-mation in northern Chinese Han adults,but it is still necessary to combine with other adult age estima-tion indicators in forensic practice.

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 analyze the relationship between plasma uranium concentration and renal injury.Methods:A case-control study was conducted in Hunan province, involving 102 renal injury cases and 102 matched controls. The association between plasma uranium concentration and renal injury was analyzed using conditional logistic regression models, and the dose-response relationship was analyzed through restricted cubic spline regression. The linear regression model and Spearman correlation were used to analyze the association between plasma uranium concentration and renal injury indicators.Results:The median of plasma uranium concentration was 8.94 ng/L in all subjects and 10.19 ng/L in the case group. The plasma uranium may be a risk factor for renal injury, with a dose-response relationship between the both representing nonlinear association ( χ2=5.15, P<0.05). The risk of renal injury was 4.21 times higher in the group exposed to highest uranium concentration than that in the group exposed to lowest uranium concentration. Plasma uranium concentration was closely related to glomerular filtration rate, serum creatinine and β 2-microglobulin ( r=0.211, -0.142, 0.195, P<0.05). Conclusions:The plasma uranium concentration is significantly associated with the renal injury, which may provide epidemiology evidence for the prevention of renal injury.