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.

Humans ; PPAR gamma/metabolism* ; Multiple Sclerosis ; Transcription Factors/metabolism* ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha

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.

The patient,a male newborn,was admitted to the hospital 2 hours after birth due to prematurity(gestational age 27+5 weeks)and respiratory distress occurring 2 hours postnatally.After admission,the infant developed fever and elevated C-reactive protein levels.On the fourth day after birth,metagenomic next-generation sequencing of cerebrospinal fluid indicated a positive result for Mycoplasma hominis(9 898 reads).On the eighth day,a retest of cerebrospinal fluid metagenomics confirmed Mycoplasma hominis(56 806 reads).The diagnosis of purulent meningitis caused by Mycoplasma hominis was established,and the antibiotic treatment was switched to moxifloxacin[5 mg/(kg·day)]administered intravenously for a total of 4 weeks.After treatment,the patient's cerebrospinal fluid tests returned to normal,and he was discharged as cured on the 76th day after birth.This article focuses on the diagnosis and treatment of neonatal Mycoplasma hominis purulent meningitis,introducing the multidisciplinary diagnosis and treatment of the condition in extremely preterm infants.[Chinese Journal of Contemporary Pediatrics,2024,26(4):432-436]

Objective To study the composition,abundance,and functional profiles of the intestinal microbiota in infants and young children with Kawasaki disease(KD)during the acute phase,and to explore the potential role of intestinal microbiota in the pathogenesis of KD.Methods Six children aged 0-3 years with acute KD admitted to the Department of Cardiology,Children's Hospital Affiliated to Capital Institute of Pediatrics from July to October 2021 were prospectively included as the KD group.Six age-and sex-matched healthy children who underwent physical examinations at the hospital during the same period were selected as the healthy control group.Metagenomics sequencing was used to detect and compare the differences in the microflora structure and functional profiles of fecal samples between the two groups.Results There were significant differences in the structural composition and diversity of intestinal microbiota between the two groups(P<0.05).Compared with the healthy control group,the abundance of Listeria_monocytogenes(family Listeriaceae and genus Listeria),Bifidobacterium_rousetti,Enterococcus_avium,and Enterococcus_hirae was significantly higher in the intestinal microbiota in the KD group(|LDA|>2.0,P<0.05).The steroid degradation and apoptosis pathways were significantly upregulated in the KD group compared with the healthy control group,while the Bacterial_secretion_system,Sulfur_metabolism,Butanoate_metabolism,Benzoate_degradation,β-alanine metabolism,and α-linolenic acid pathways were significantly downregulated(|LDA|>2,P<0.05).Conclusions There are significant differences in the structure and diversity of intestinal microbiota between children aged 0-3 years with acute KD and healthy children,suggesting that disturbances in intestinal microbiota occur during the acute phase of KD.In particular,Listeria_monocytogenes,Enterococcus_avium,and Enterococcus_hirae may be involved in the pathogenesis of KD through steroid degradation and apoptosis pathways.

Background: Porcine circovirus type 2 (PCV2) infection is ubiquitous around the world.Diagnosis of the porcine circovirus-associated disease requires clinic-pathological elements together with the quantification of viral loads. Furthermore, given pig farms in regions lacking access to sufficient laboratory equipment, developing diagnostic devices with high accuracy, accessibility, and affordability is a necessity. Objectives: This study aims to investigate two newly developed diagnostic tools that may satisfy these criteria. Methods: We collected 250 specimens, including 170 PCV2-positive and 80 PCV2-negative samples. The standard diagnosis and cycle threshold (Ct) values were determined by quantitative polymerase chain reaction (qPCR). Then, two point-of-care (POC) diagnostic platforms, convective polymerase chain reaction (cPCR, qualitative assay: positive or negative results are shown) and EZtargex (quantitative assay: Ct values are shown), were examined and analyzed. Results: The sensitivity and specificity of cPCR were 88.23% and 100%, respectively; the sensitivity and specificity of EZtargex were 87.65% and 100%, respectively. These assays also showed excellent concordance compared with the qPCR assay (κ = 0.828 for cPCR and κ = 0.820 for EZtargex). The statistical analysis showed a great diagnostic power of the EZtargex assay to discriminate between samples with different levels of positivity. Conclusions The two point-of-care diagnostic platforms are accurate, rapid, convenient and require little training for PCV2 diagnosis. These POC platforms can discriminate viral loads to predict the clinical status of the animals. The current study provided evidence that these diagnostics were applicable with high sensitivity and specificity in the diagnosis of PCV2 infection in the field.

In recent years, the prevalence of hyperglycemia has been increasing, and patients’ bodies have been seriously damaged. Compared with conventional Western drugs, natural products have fewer adverse reactions and delay the complications of hyperglycemia. As a valuable natural product resource, Small-leaf Kuding (SLK) contains various beneficial components for the human body. The aim of this study was to study the regulation effect of SLK extract at different doses on blood glucose metabolism in hyperglycemic mice. Lipopolysaccharide and streptozotocin were used to induce hyperglycemia in mice. Extract of SLK were administered intragastrically at low, medium, and high doses (5 g·kg

Abstract: Objective To explore and analyze the diagnostic value of multicolor melting curve analysis (MMCA) for the resistance of five anti-tuberculosis drugs, so as to clarify the clinical value of MMCA in detecting drug resistance of Mycobacterium tuberculosis. Methods From April 2021 to May 2022, 200 patients with positive Mycobacterium tuberculosis admitted to the Fourth People's Hospital of Qinghai Province were selected as research objects, and sputum specimens were taken from the patients. Traditional Mycobacterium tuberculosis drug sensitivity test (modified Löwenstein-Jensen medium method) and MMCA analysis were respectively given to detect the resistance of five anti-tuberculosis drugs, including isoniazid, ethambutol, streptomycin, rifampicin and isoniazid, respectively. Those samples with inconsistent results between the two diagnosis methods were subjected to gene sequencing verification, and the diagnosis efficiency of MMCA for the five anti-tuberculosis drugs was compared. Results Using Mycobacterium tuberculosis drug sensitivity as the gold standard for drug resistance diagnosis, the sensitivity of MMCA for detecting drug resistance of rifampicin, ethambutol, streptomycin, isoniazid and levofloxacin were 95.83% (46/48), 93.75% (15/16), 100.00% (15/15), 100.00% (20/20) and 70.00% (7/10), respectively, with statistical differences between groups (P<0.05). There were no statistically significant differences in the specificity, positive predictive value, negative predictive value and accuracy of MMCA for the five anti-tuberculosis drugs (P>0.05). For the 8 samples with inconsistent results between MMCA and modified Löwenstein-Jensen medium method, gene sequencing was performed and compared with the results of gene sequencing. After comparison with gene sequencing results, it was found that the coincidence rate of MMCA and gene sequencing results was 75.00% (6/8). Conclusions In the detection of drug-resistant mutations in TB patients, multi-color probe fusion curve analysis has high diagnostic efficacy for first-line anti-tuberculosis drugs, but is not sensitive to second-line anti-tuberculosis drug levofloxacin. Therefore, for the detection of first-line anti-tuberculosis drugs, MMCA has a good clinical application prospect.

We investigated the effects of decursin on the proliferation, apoptosis, and migration of colorectal cancer HT29 and HCT116 cells through the phosphatidylinositol 3-kinase(PI3K)/serine-threonine kinase(Akt) pathway. Decursin(10, 30, 60, and 90 μmol·L~(-1)) was used to treat HT29 and HCT116 cells. The survival, colony formation ability, proliferation, apoptosis, wound hea-ling area, and migration of the HT29 and HCT116 cells exposed to decursin were examined by cell counting kit-8(CCK8), cloning formation experiments, Ki67 immunofluorescence staining, flow cytometry, wound healing assay, and Transwell assay, respectively. Western blot was employed to determine the expression levels of epithelial cadherin(E-cadherin), neural cadherin(N-cadherin), vimentin, B-cell lymphoma/leukemia-2(Bcl-2), Bcl-2-associated X protein(Bax), tumor suppressor protein p53, PI3K, and Akt. Compared with the control group, decursin significantly inhibited the proliferation and colony number and promoted the apoptosis of HT29 and HCT116 cells, and it significantly down-regulated the expression of Bcl-2 and up-regulated the expression of Bax. Decursin inhibited the wound healing and migration of the cells, significantly down-regulated the expression of N-cadherin and vimentin, and up-regulated the expression of E-cadherin. In addition, it significantly down-regulated the expression of PI3K and Akt and up-regulated that of p53. In summary, decursin may regulate epithelial-mesenchymal transition(EMT) via the PI3K/Akt signaling pathway, thereby affecting the proliferation, apoptosis, and migration of colorectal cancer cells.
Humans ; Proto-Oncogene Proteins c-akt/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; bcl-2-Associated X Protein ; Vimentin/metabolism* ; Cell Proliferation ; Signal Transduction ; Apoptosis ; Cell Line, Tumor ; Colorectal Neoplasms/genetics* ; Cadherins/genetics* ; Cell Movement