AIM To investigate the variations in mercury dissolution from HgS-containing traditional medicines in three kinds of simulated gastrointestinal dissolution media.METHODS 39 batches of 15 types of HgS-containing traditional medicines were collected,total mercury content and dissolved mercury concentrations in simulated gastric fluid,simulated intestinal fluid,and L-cysteine-containing simulated intestinal fluid were measured.The maximum daily intake of total mercury and soluble mercury was calculated based on the maximum daily clinical dosage.RESULTS Among the 15 types of medicines,the maximum daily intake of total mercury varied by 156 times,the daily intake of soluble mercury varied by 3 502 times in simulated gastric fluid,313 times in simulated intestinal fluid,and 10 663 times in L-cysteine-containing simulated intestinal fluid,approximately.CONCLUSION For the 15 types of HgS-containing traditional medicines,the daily maximum intake of soluble mercury showed greater variations than that of total mercury.Soluble mercury concentration is more closely correlated with intestinal absorption of mercury and thus represents a more rational quality control indicator for HgS-containing traditional medicines.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To investigate the value of first platelet count(PLT)to respiratory rate(RR)ratio(PLT/RR)on admission in the diagnosis and prognosis of secondary sepsis in pneumonia patients.Methods A total of 100 patients with pneumonia admitted to the First Affiliated Hospital of Army Medical University from May 2023 to August 2024 were selected as subjects.According to the presence or absence of pneumonia sepsis,they were divided into sepsis group(63 cases)and non-sepsis group(37 cases).The secondary sepsis in pneumonia pa-tients were followed up continuously for 30 d.According to the survival situation,they were divided into sur-vival group(54 cases)and death group(9 cases).PLT in peripheral blood was measured,vital signs were col-lected on the first day of admission,and PLT/RR was calculated.The receiver operating characteristic curve was used to evaluate the predictive value of PLT,RR and PLT/RR for secondary sepsis in pneumonia pa-tients.The systemic inflammatory response syndrome(SIRS)score,modified early warning score(MEWS)and quick sequential organ failure assessment(qSOFA)score on admission were calculated,and the clinical predictive value of SIRS score,MEWS and qSOFA score was compared.Results PLT and PLT/RR in sepsis group were lower than those in non-sepsis group(P<0.000 1),RR was higher than that in non-sepsis group(P<0.01).The area under the curve(AUC,95%CI)of PLT,RR and PLT/RR were 0.858(0.785-0.931),0.693(0.589-0.796)and 0.902(0.843-0.962),respectively.The optimal cut-off values were 146.5×109/L,20.5 per minute and 8.075,respectively.The specificity were 8.1%,83.8%and 2.7%,respec-tively.The sensitivity was 33.3%,50.8%and 30.2%,respectively.Compared with the non-sepsis group,the sepsis group had a significantly higher SIRS score(P<0.001),a significantly lower MEWS(P<0.000 1),and no significant difference in qSOFA score between the two groups(P>0.05).The AUC(95%CI)of SIRS score,MEWS and qSOFA score in predicting secondary sepsis in pneumonia patients were 0.717(0.616-0.818),0.748(0.650-0.846)and 0.505(0.389-0.622),respectively.The optimal cut-off values were 4.5,2.5 and 1.5 points,respectively.The specificity were 91.9%,2.7%and 100.0%,respectively.The sensitivity was 42.9%,33.3%and 6.3%,respectively.PLT and PLT/RR in death group were lower than those in sur-vival group(P<0.05),RR was higher than that in survival group(P<0.05).Secondary sepsis in pneumonia patients were followed up for 30 d,Kaplan-Meier survival curve showed that patients with PLT≤138.5×109/L had a lower 30 d survival rate(P=0.007 8).Patients with RR>24.5 per minute had a lower 30 d sur-vival rate(P=0.016 1).Patients with PLT/RR≤6.375 had a lower 30 d survival rate(P=0.002 3).Conclu-sion PLT/RR can be used as a biological index to predict secondary sepsis in pneumonia patients,which is better than SIRS score,MEWS and qSOFA score,and the prognosis of secondary sepsis in pneumonia patients with low PLT/RR is worse.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

AIM To investigate the variations in mercury dissolution from HgS-containing traditional medicines in three kinds of simulated gastrointestinal dissolution media.METHODS 39 batches of 15 types of HgS-containing traditional medicines were collected,total mercury content and dissolved mercury concentrations in simulated gastric fluid,simulated intestinal fluid,and L-cysteine-containing simulated intestinal fluid were measured.The maximum daily intake of total mercury and soluble mercury was calculated based on the maximum daily clinical dosage.RESULTS Among the 15 types of medicines,the maximum daily intake of total mercury varied by 156 times,the daily intake of soluble mercury varied by 3 502 times in simulated gastric fluid,313 times in simulated intestinal fluid,and 10 663 times in L-cysteine-containing simulated intestinal fluid,approximately.CONCLUSION For the 15 types of HgS-containing traditional medicines,the daily maximum intake of soluble mercury showed greater variations than that of total mercury.Soluble mercury concentration is more closely correlated with intestinal absorption of mercury and thus represents a more rational quality control indicator for HgS-containing traditional medicines.

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 Aedes albopictus is the primary vector of the dengue virus.Screening and the analysis of immune-related genes in DENV2-infected Ae.albopictus provides a scientific basis for further research on blocking the extrinsic incubation period of the dengue virus.Methods Through the approach of literature mining,thirty-three potential immune-related genes were screened from species such as Aedes aegypti and Anopheles gambiae,which have a close genetic relationship with Ae.albopictus.The protein—protein interaction(PPI)analysis is employed to explore the interaction relationship of the proteins encoded by genes.The alterations in mRNA expression levels of the relevant genes in DENV2-infected Ae.albopictus midgut were detected using the qRT-PCR method.Results The PPI results indicates that TLR and Spz of Ae.albopictus;Rel1,Rel2,DefC,Spz,PIWI,Ago2,DOME and HOP of Ae.aegypti;and Rel1,Rel2,CACT,STAT and DOME of An.gambiae exhibit PPI relationships.After Ae.albopictus was infected with DENV2,10 genes showed significant difference in expression.Ago3(7.39,P<0.05),DOMEa(1.63,P<0.01),DOMEb(21.29,P<0.001),and TLRb(1.61,P<0.05)were significantly up-regulated.Rel1(0.62,P<0.001),CACTl(0.65,P<0.001),Rel2a(0.65,P<0.01),Rel2b(0.24,P<0.001),GATAa(0.64,P<0.01)and DefC(0.28,P<0.05)were significantly down-regulated.Conclusions The concordance of Ae.albopictus with Ae.aegypti was higher than that with An.gambiae.DOMEb,Ago3,Rel2b and DefC,can serve as the preferred target genes for subsequent studies on DENV2 immune blockade.

ObjectiveTo develop an emotion management course and evaluate its effectiveness in improving emotion regulation, coping strategies, and anxiety and depression among first-year university students, so as to provide a basis for colleges to optimize mental health education courses. MethodsUsing a multi-stage cluster random sampling method, five classes of first-year students (n=169) from a university were randomly selected as participants, with three classes assigned to the experimental group (n=102) and two classes to the control group (n=67). The experimental group attended both the standard mental health education course and the emotion management course developed in this study, while the control group only attended the standard mental health education course. Pre- and post-intervention assessments were conducted using the Emotion Regulation Questionnaire (ERQ), Simplified Coping Style Questionnaire (SCSQ), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS). ResultsBefore the intervention, there were no significant differences between the experimental group and the control group in ERQ, SCSQ, SDS, and SAS scores (P>0.05). After the intervention, the experimental group demonstrated greater improvements than the control group in the ERQ expression inhibition subscale (14.42±5.05, 16.12±5.65), SCSQ positive coping tendency (1.97±0.51, 1.80±0.49) and negative coping tendency (1.26±0.55, 1.47±0.50), as well as in SDS (50.26±11.48, 53.86±8.21) and SAS (43.96±11.97, 47.59±9.50) scores (t value: 2.039, 2.144, 2.572; Z value: -2.214, -2.486; P<0.05). Compared with pre-intervention scores, the experimental group also showed improvements in the ERQ cognitive reappraisal subscale (32.19±5.76, 30.92±6.18), SCSQ positive coping tendency (1.97±0.51, 1.83±0.48), and SDS scores (50.26±11.48, 50.75±11.59) (t value: -2.654, -3.027; Z value: -2.100, P<0.05). ConclusionThe emotion management course effectively enhances students’ use of cognitive reappraisal strategies while reducing reliance on expressive suppression. It also contributes to improvements in coping strategies for life events and alleviates symptoms of depression and anxiety. Universities should consider integrating emotion management education into their curricula to enhance the mental well-being of first-year students.