This study employed bioinformatics to screen the feature genes related to efferocytosis in diabetic kidney disease(DKD) and explores traditional Chinese medicine(TCM) regulating these feature genes. The GSE96804 and GSE30528 datasets were integrated as the training set, and the intersection of differentially expressed genes and efferocytosis-related genes(ERGs) was identified as DKD-ERGs. Subsequently, correlation analysis, protein-protein interaction(PPI) network construction, enrichment analysis, and immune infiltration analysis were performed. Consensus clustering was conducted on DKD patients based on the expression levels of DKD-ERGs, and the expression levels, immune infiltration characteristics, and gene set variations between different subtypes were explored. Eight machine learning models were constructed and their prediction performance was evaluated. The best-performing model was evaluated by nomograms, calibration curves, and external datasets, followed by the identification of efferocytosis-related feature genes associated with DKD. Finally, potential TCMs that can regulate these feature genes were predicted. The results showed that the training set contained 640 differentially expressed genes, and after intersecting with ERGs, 12 DKD-ERGs were obtained, which demonstrated mutual regulation and immune modulation effects. Consensus clustering divided DKD into two subtypes, C1 and C2. The support vector machine(SVM) model had the best performance, predicting that growth arrest-specific protein 6(GAS6), S100 calcium-binding protein A9(S100A9), C-X3-C motif chemokine ligand 1(CX3CL1), 5'-nucleotidase(NT5E), and interleukin 33(IL33) were the feature genes of DKD. Potential TCMs with therapeutic effects included Astragali Radix, Trionycis Carapax, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma, which mainly function to clear heat, replenish deficiency, activate blood, resolve stasis, and promote urination and drain dampness. Molecular docking revealed that the key components of these TCMs, including β-sitosterol, quercetin, and sitosterol, exhibited good binding activity with the five target genes. These results indicated that efferocytosis played a crucial role in the development and progression of DKD. The feature genes closely related to both DKD and efferocytosis, such as GAS6, S100A9, CX3CL1, NT5E, and IL33, were identified. TCMs such as Astragali Radix, Trionycis Carapa, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma may provide a new therapeutic strategy for DKD by regulating efferocytosis.
Humans ; Computational Biology ; Diabetic Nephropathies/physiopathology* ; Protein Interaction Maps ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Phagocytosis/genetics* ; Efferocytosis

OBJECTIVE: Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection frequently develop central nervous system damage, yet the mechanisms driving this pathology remain unclear. This study investigated the primary pathways and key factors underlying brain tissue damage induced by the SARS-CoV-2 beta variant (lineage B.1.351). METHODS: K18-hACE2 and C57BL/6 mice were intranasally infected with the SARS-CoV-2 beta variant. Viral replication, pathological phenotypes, and brain transcriptomes were analyzed. Gene Ontology (GO) analysis was performed to identify altered pathways. Expression changes of host genes were verified using reverse transcription-quantitative polymerase chain reaction and Western blot. RESULTS: Pathological alterations were observed in the lungs of both mouse strains. However, only K18-hACE2 mice exhibited elevated viral RNA loads and infectious titers in the brain at 3 days post-infection, accompanied by neuropathological injury and weight loss. GO analysis of infected K18-hACE2 brain tissue revealed significant dysregulation of genes associated with innate immunity and antiviral defense responses, including type I interferons, pro-inflammatory cytokines, Toll-like receptor signaling components, and interferon-stimulated genes. Neuroinflammation was evident, alongside activation of apoptotic and pyroptotic pathways. Furthermore, altered neural cell marker expression suggested viral-induced neuroglial activation, resulting in caspase 4 and lipocalin 2 release and disruption of neuronal molecular networks. CONCLUSION These findings elucidate mechanisms of neuropathogenicity associated with the SARS-CoV-2 beta variant and highlight therapeutic targets to mitigate COVID-19-related neurological dysfunction.
Animals ; COVID-19/genetics* ; Mice ; Brain/metabolism* ; Apoptosis ; Mice, Inbred C57BL ; SARS-CoV-2/physiology* ; Pyroptosis ; Gene Expression Profiling ; Transcriptome ; Male ; Female

Objective:To analyze the efficacy and influencing factors of cyclosporine(CsA)alone in the treatment of children with acquired aplastic anemia(AA).Methods:The clinical data of children diagnosed with AA and treated with CsA alone from January 1,2016 to December 31,2020 in the Children's Hospital of Chongqing Medical University were collected,and the efficacy and influencing factors of CsA treatment were evaluated.Results:Among the 119 patients,there were 62 male and 57 female,with a median age of 7 years and 1 month.There were 45 cases of very severe AA(VSAA),47 cases of severe AA(SAA),and 27 cases of non-severe AA(NSAA).At 6 months after treatment,the efficacy of VSAA was lower than that of SAA and NSAA,and there was a statistical difference(P＜0.01).6 cases died early,16 cases relapsed,2 cases progressed to AML and ALL.The results of univariate analysis showed that the high proportion of lymphocyte in the bone marrow at 6 months was an adverse factor for the efficacy of CsA,while high PLT count was a protective factor(P=0.008,P=0.002).The ROC curve showed that the cut-off values of PLT count and the proportion of bone marrow lymphocyte at 6 months were 16.5 × 109/L,68.5％,respectively.Multivariate analysis showed that the high proportion of lymphocyte in bone marrow at 6 months was an independent adverse factor for IST(P=0.020,OR=0.062),and high PLT count was a protective factor(P=0.044,OR=1.038).At 3 months of treatment,CsA response and NSAA were the risk factor for recurrence(P=0.001,0.031).Conclusion:The efficacy of NSAA was higher than that of SAA and VSAA after 6 months of treatment with CsA alone.A high PLT count at the initial diagnosis was a good factor for the effectiveness of CsA,and a high proportion of bone marrow lymphocyte was an unfavorable factor.CsA response at 3 months and NSAA were risk factors for recurrence.

Objective To investigate the cumulative incidence of recurrence(CIR)in children with acute lymphoblastic leukemia(ALL)after treatment with the Chinese Children's Cancer Group ALL-2015(CCCG-ALL-2015)protocol and the risk factors for recurrence.Methods A retrospective analysis was conducted on the clinical data of 852 children who were treated with the CCCG-ALL-2015 protocol from January 2015 to December 2019.CIR was calculated,and the risk factors for the recurrence of B-lineage acute lymphoblastic leukemia(B-ALL)were analyzed.Results Among the 852 children with ALL,146(17.1%)experienced recurrence,with an 8-year CIR of 19.8%±1.6%.There was no significant difference in 8-year CIR between the B-ALL group and the acute T lymphocyte leukemia group(P>0.05).For the 146 children with recurrence,recurrence was mainly observed in the very early stage(n=62,42.5%)and the early stage(n=46,31.5%),and there were 42 children with bone marrow recurrence alone(28.8%)in the very early stage and 27 children with bone marrow recurrence alone(18.5%)in the early stage.The Cox proportional-hazards regression model analysis showed that positive MLLr fusion gene(HR=4.177,95%CI:2.086-8.364,P<0.001)and minimal residual disease≥0.01%on day 46(HR=2.013,95%CI:1.163-3.483,P=0.012)were independent risk factors for recurrence in children with B-ALL after treatment with the CCCG-ALL-2015 protocol.Conclusions There is still a relatively high recurrence rate in children with ALL after treatment with the CCCG-ALL-2015 protocol,mainly bone marrow recurrence alone in the very early stage and the early stage,and minimal residual disease≥0.01%on day 46 and positive MLLr fusion gene are closely associated with the recurrence of B-ALL.

Aim To explore the role of SIRT1/Nrf2 / HO-1 in alleviating the cognitive function impairment by sevoflurane treatment in a mouse model of postoperative cerebral reperfusion. Methods C57BL/6J mice were randomly divided into five groups: sham operation group, hemorrhagic shock reperfusion group, sevoflurane postconditioning group, sevoflurane postcondition-ing + SIRT1 inhibitor group and sevoflurane postconditioning + Nrf2 inhibitor group. Mice were subjected to Morris water maze test after cerebral ischemia reperfusion. The ATP, superoxide dismutase (SOD), ROS and MDA contents in tissue of mice were detected. SIRT1, Nrf2 and HO-1 proteins in tissue were detected by Western blot. Results After hemorrhagic shock, the learning and memory ability of mice was reduced.ATP and SOD concentration in hippocampus was reduced , MDA and ROS concentration increased, and the SIRT, Nrf2 and HO-1 concentration was reduced. Sevoflurane improved the cognitive dysfunction and oxi-dative damage in postoperative mice, and the neuro-protective effect of sevoflurane on hemorrhagic shock and resuscitation mice was weakened followed with SIRT1 and Nrf2 inhibitors. Conclusion Sevoflurane probably alleviates the oxidative reaction damage and cognitive impairment caused by cerebral reperfusion in mice through SIRT1/Nrf2/H0-1 pathway.

Thyroglobulin(Tg)is a glycoprotein with large molecular weight,which is synthesized and secreted into the bloodstream by thyroid follicular cells.The concentration level of Tg in blood is one of the important biomarkers for diagnosis of thyroid diseases such as differentiated thyroid cancer(DTC),subacute thyroiditis,etc..Radioimmunoassay(RIA),immunoradiometric assay(IRMA),and immunochemiluminescence assay(ICMA)are the main clinical methods for detecting Tg.Recently,for meeting the requirement of detecting low concentration of Tg in blood after thyroid clearance surgery,researchers have developed various high-performance analysis methods for detecting Tg concentration in blood samples,providing new assays for thyroid disease screening and efficacy evaluation.This review summarized the analysis methods of Tg,especially the new progresses in the biosensors for monitoring low concentration of Tg in blood during the past five years.The current technical challenges of these methods in clinical applications were briefly discussed,which might provide useful information for developing new liquid biopsy methods of DTC.

Objectives: Telemedicine is firmly established in the healthcare landscape of many countries. Acute respiratory infections are the most common reason for telemedicine consultations. A throat examination is important for diagnosing bacterial pharyngitis, but this is challenging for doctors during a telemedicine consultation. A solution could be for patients to upload images of their throat to a web application. This study aimed to develop a deep learning model for the automated diagnosis of exudative pharyngitis. Thereafter, the model will be deployed online. Methods: We used 343 throat images (139 with exudative pharyngitis and 204 without pharyngitis) in the study. ImageDataGenerator was used to augment the training data. The convolutional neural network models of MobileNetV3, ResNet50, and EfficientNetB0 were implemented to train the dataset, with hyperparameter tuning. Results: All three models were trained successfully; with successive epochs, the loss and training loss decreased, and accuracy and training accuracy increased. The EfficientNetB0 model achieved the highest accuracy (95.5%), compared to MobileNetV3 (82.1%) and ResNet50 (88.1%). The EfficientNetB0 model also achieved high precision (1.00), recall (0.89) and F1-score (0.94). Conclusions We trained a deep learning model based on EfficientNetB0 that can diagnose exudative pharyngitis. Our model was able to achieve the highest accuracy, at 95.5%, out of all previous studies that used machine learning for the diagnosis of exudative pharyngitis. We have deployed the model on a web application that can be used to augment the doctor’s diagnosis of exudative pharyngitis.

Objective: To describe the distribution characteristics of hypertension among adult twins in the Chinese National Twin Registry (CNTR) and to provide clues for exploring the role of genetic and environmental factors on hypertension. Methods: A total of 69 220 (34 610 pairs) of twins aged 18 and above with hypertension information were selected from CNTR registered from 2010 to 2018. Random effect models were used to describe the population and regional distribution of hypertension in twins. To estimate the heritability, the concordance rates of hypertension were calculated and compared between monozygotic twins (MZ) and dizygotic twins (DZ). Results: The age of all participants was (34.1±12.4) years. The overall self-reported prevalence of hypertension was 3.8%(2 610/69 220). Twin pairs who were older, living in urban areas, married, overweight or obese, current smokers or ex-smokers, and current drinkers or abstainers had a higher self-reported prevalence of hypertension (P<0.05). Analysis within the same-sex twin pairs found that the concordance rate of hypertension was 43.2% in MZ and 27.0% in DZ, and the difference was statistically significant (P<0.001). The heritability of hypertension was 22.1% (95%CI: 16.3%- 28.0%). Stratified by gender, age, and region, the concordance rate of hypertension in MZ was still higher than that in DZ. The heritability of hypertension was higher in female participants. Conclusions: There were differences in the distribution of hypertension among twins with different demographic and regional characteristics. It is indicated that genetic factors play a crucial role in hypertension in different genders, ages, and regions, while the magnitude of genetic effects may vary.
Adult ; Female ; Humans ; Male ; Alcohol Drinking ; Diseases in Twins/genetics* ; Hypertension/genetics* ; Twins, Dizygotic/genetics* ; Twins, Monozygotic/genetics*

Objective: To describe the distribution characteristics of hyperlipidemia in adult twins in the Chinese National Twin Registry (CNTR) and explore the effect of genetic and environmental factors on hyperlipidemia. Methods: Twins recruited from the CNTR in 11 project areas across China were included in the study. A total of 69 130 (34 565 pairs) of adult twins with complete information on hyperlipidemia were selected for analysis. The random effect model was used to characterize the population and regional distribution of hyperlipidemia among twins. The concordance rates of hyperlipidemia were calculated in monozygotic twins (MZ) and dizygotic twins (DZ), respectively, to estimate the heritability. Results: The age of all participants was (34.2±12.4) years. This study's prevalence of hyperlipidemia was 1.3% (895/69 130). Twin pairs who were men, older, living in urban areas, married,had junior college degree or above, overweight, obese, insufficient physical activity, current smokers, ex-smokers, current drinkers, and ex-drinkers had a higher prevalence of hyperlipidemia (P<0.05). In within-pair analysis, the concordance rate of hyperlipidemia was 29.1% (118/405) in MZ and 18.1% (57/315) in DZ, and the difference was statistically significant (P<0.05). Stratified by gender, age, and region, the concordance rate of hyperlipidemia in MZ was still higher than that in DZ. Further, in within-same-sex twin pair analyses, the heritability of hyperlipidemia was 13.04% (95%CI: 2.61%-23.47%) in the northern group and 18.59% (95%CI: 4.43%-32.74%) in the female group, respectively. Conclusions: Adult twins were included in this study and were found to have a lower prevalence of hyperlipidemia than in the general population study, with population and regional differences. Genetic factors influence hyperlipidemia, but the genetic effect may vary with gender and area.
Adult ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; China/epidemiology* ; Diseases in Twins/genetics* ; Hyperlipidemias/genetics* ; Metabolic Diseases ; Twins, Dizygotic ; Twins, Monozygotic/genetics*

Objective: To establish a comprehensive diagnostic classification model of lateral cephalograms based on artificial intelligence (AI) to provide reference for orthodontic diagnosis. Methods: A total of 2 894 lateral cephalograms were collected in Department of Orthodontics, Capital Medical University School of Stomatology from January 2015 to December 2021 to construct a data set, including 1 351 males and 1 543 females with a mean age of (26.4± 7.4) years. Firstly, 2 orthodontists (with 5 and 8 years of orthodontic experience, respectively) performed manual annotation and calculated measurement for primary classification, and then 2 senior orthodontists (with more than 20 years of orthodontic experience) verified the 8 diagnostic classifications including skeletal and dental indices. The data were randomly divided into training, validation, and test sets in the ratio of 7∶2∶1. The open source DenseNet121 was used to construct the model. The performance of the model was evaluated by classification accuracy, precision rate, sensitivity, specificity and area under the curve (AUC). Visualization of model regions of interest through class activation heatmaps. Results: The automatic classification model of lateral cephalograms was successfully established. It took 0.012 s on average to make 8 diagnoses on a lateral cephalogram. The accuracy of 5 classifications was 80%-90%, including sagittal and vertical skeletal facial pattern, mandibular growth, inclination of upper incisors, and protrusion of lower incisors. The acuracy rate of 3 classifications was 70%-80%, including maxillary growth, inclination of lower incisors and protrusion of upper incisors. The average AUC of each classification was ≥0.90. The class activation heat map of successfully classified lateral cephalograms showed that the AI model activation regions were distributed in the relevant structural regions. Conclusions: In this study, an automatic classification model for lateral cephalograms was established based on the DenseNet121 to achieve rapid classification of eight commonly used clinical diagnostic items.
Male ; Female ; Humans ; Young Adult ; Adult ; Artificial Intelligence ; Deep Learning ; Cephalometry ; Maxilla ; Mandible/diagnostic imaging*