The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

AIM To establish a UPLC-MS/MS method for the simultaneouscontent determination of notoginsenosides R1,Fc,Fe,ginsenosides Re,Rg1,Rf,F3,Rg2,Ra2,Rb1,Ro,Rc,F1,Ra1,Rb2,Rb3,Rd,F2,Rg5,chikusetsusaponin Ⅳ a,20(S)-ginsenoside Rg3 and 20(R)-ginsenoside Rg3 in Dengzhan Shengmai Capsules.METHODS The analysis was performed on a 35 ℃ thermostatic Accucore Phenyl Hexyl column(2.1 mm×100 mm,2.6 μm),with the mobile phase comprising of 0.1％formic acid-acetonitrile flowing at 0.4 mL/min in a gradient elution manner,and heated electrospray ionization source was adopted in negative ion scanning with parallel reaction monitoring mode.Subsequently,cluster analysis,principal component analysis and partial least squares discriminant analysis were adopted.RESULTS Twenty-two saponins showed good linear relationships within their own ranges(r ≥ 0.996 4),whose average recoveries were 98.5％-101.6％with the RSDs of 1.3％-5.2％.Ten batches of samples were clustered into four types,three principal components demonstrated the accumulative variance contribution rate of 90.265％,ginsenosides Rb1,Rg2,Rb2,Rd,Rg1,Ro,Rf,Re,Rg5,Rc were taken as potential quality markers.CONCLUSION This simple,efficient,accurate and sensitive method can be used for the quality control of Dengzhan Shengmai Capsules.

Objective To establish a classification tree model for non-alcoholic fatty liver disease(NAFLD)among aircrews,screen for influencing factors of NAFLD,so as to provide scientific basis for prevention and intervention decisions for NAFLD.Methods Aircrews who underwent recuperation at a sanatorium from January 2019 to December 2023 were selected as the research objects.Their annual physical examination data were collected and the NAFLD detection rate was calculated.Age,body mass index(BMI),blood pressure,waist circumference,blood routine,biochemistry indexes,and thyroid function were incorporated,and a NAFLD risk model was constructed using classification regression tree method.The predictive performance of the NAFLD classification tree model was evaluated through model misclassification matrix,risk statistics,and receiver operating characteristic curve.Results A total of 4088 aircrews were included in the study,and NAFLD was detected in 380 persons(380/4088,9.30%).The NAFLD model consisted of three layers,and five explanatory variables affecting the onset of NAFLD were extracted,including BMI,triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),alanine aminotransferase(ALT),and total bilirubin(TBIL).BMI was located at the top of the classification tree and was the most important risk factor for NAFLD in aircrews.The area under the curve(AUC)of the model was 0.853.The predictive accuracy of NAFLD was 90.9%,indicating that the model has good accuracy and fitting effect.Conclusion In this study,the detection rate of NAFLD in aircrews was 9.30%.BMI,TG,HDL-C,ALT,and TBIL are risk factors for the onset of NAFLD.NAFLD is mainly related to weight gain and lipid metabolism disorders caused by unhealthy lifestyles.

Objective To investigate the expression of T cell immunoglobulin and mucin domain-containing protein 3(TIM-3)in peripheral blood mononuclear cells and its relationship with non-small cell lung cancer(NSCLC).Methods TIM-3 expression in monocytes from the peripheral blood of 116 NSCLC patients and 37 healthy volunteers was analyzed via flow cytometry.The expression of TIM-3 in macrophages from tissues was detected via multiplex immunohistochemical staining.Transwell migration experiments were used to detect the migration ability of monocytes.Real-time PCR and ELISA were used to detect the mRNA and protein expression of TIM-3 in monocytes.Results Compared with that in healthy volunteers,TIM-3 expression was upregulated in the peripheral blood monocytes of NSCLC patients(P＜0.05).TIM-3 was expressed mainly in macrophages in adjacent tissues and positively correlated with its expression in monocytes in NSCLC patients(P＜0.05).Furthermore,high TIM-3 expression promoted monocyte migration in NSCLC patients(P＜0.05),and high TIM-3 expression in peripheral blood monocytes indicated poor prognosis(P＜0.05).Conclusion TIM-3 expression in peripheral blood monocytes may be a useful indicator of the disease prognosis of NSCLC patients and TIM-3 could be a new target for immunotherapeutic strategies.

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms

Objective:To investigate the differences in clinical outcomes of septic children with varying serum zinc levels,and to analyze the relationship between reduced serum zinc levels and organ dysfunction as well as 28-day mortality in septic children.Methods:This study conducted a retrospective analysis of clinical data from pediatric patients diagnosed with sepsis or septic shock in the Department of critical care medicine of the children's Hospital of Soochow University between January 2017 and December 2022.Clinical characteristics,organ dysfunction,and prognosis were compared between two groups:children with low serum zinc levels and those with normal zinc levels.Results:The serum zinc level of septic children within 24 hours of admission was 9.60(5.52,13.80)μmol/L,with 50.54%(94/186)of the children exhibiting low serum zinc levels(<10.07 μmol/L).Compared to the normal serum zinc group,the low serum zinc group had a significantly lower Pediatric Critical Illness Score(PCIS)[(78.71±9.35)vs.(85.12±8.51),P=0.005]and higher 28-day mortality(46.80%vs.14.13%,P<0.001).The low serum zinc group also had a higher proportion of invasive mechanical ventilation(64.89%vs.47.82%,P=0.019),renal replacement therapy(15.59%vs.3.26%,P=0.003),and use of vasoactive drugs(56.38%vs.30.43%,P<0.001).The rate of underlying conditions in the low serum zinc group was significantly higher than that in the normal serum zinc group(57.44%vs.36.95%,P=0.005).Additionally,the low serum zinc group had a higher incidence of disseminated intravascular coagulation(DIC),respiratory failure,acute kidney injury,shock,and multiple organ dysfunction syndrome(MODS)compared to the normal serum zinc group(P<0.05).Serum zinc levels had predictive value for 28-day mortality in septic children(AUC=0.813;95%CI:0.725～0.902;P<0.001).A serum zinc level of less than 6.950 μmol/L predicted the death of septic children with a sensitivity of 0.618 and a specificity of 0.902.Conclusion:Sepsis in children is commonly associated with low serum zinc levels,especially in those with underlying conditions such as hematologic and oncologic disorders.Sepsis patients hypozincemia with a higher incidence of DIC,respiratory failure,acute kidney injury,shock,and MODS.A serum zinc level below 6.95 μmol/L serves as a significant predictor of 28-day mortality in children with severe sepsis.

Objective:To investigate the effects and mechanisms of cyclic adenosine monophosphate (cAMP) on cisplatin-induced acute kidney injury (AKI).Methods:GSE227970 dataset derived from human renal tubular epithelial cells (HK-2 cells) in the GEO database was downloaded, and Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis were performed in normal and cisplatin-damaged cells. Eighteen 8-week-old male C57BL/6J mice with body weight of (22±2) g were randomly divided into normal group, cisplatin group and cAMP group according to random number table method, with 6 mice in each group. cAMP group was intraperitoneally injected with 30 mg/kg glumine cyclic adenosine monophosphate, while normal group and cisplatin group were intraperitoneally injected with the same volume of 0.9% sodium chloride solution for 10 consecutive days. The cisplatin and cAMP groups were intraperitoneally injected with 20 mg/kg cisplatin once on the 8th day. The body weight and kidney weight of mice were weighed, and kidney weight to body weight ratio was calculated. The blood urea nitrogen (BUN) and serum creatinine (Scr) in mice were detected. HE staining was used to evaluate the degree of renal injury. Western blotting was used to detect the protein expression of AMP-activated protein kinase (AMPK)/acetyl-CoA carboxylase (ACC) signaling pathway in renal tissues. In vitro experiments, HK-2 cells were set up in normal group, cisplatin group, cAMP group and cAMP+AMPK inhibitor group. Immunofluorescence was used to detect the protein expression of phosphorylated (p)-AMPK in HK-2 cells. Adenosine triphosphate content and ratio of NAD + to NADH in cells were detected. Flow cytometry was used to detect cell apoptosis. Results:Biological signal analysis showed that axon guidance, Ras-related protein 1 signaling pathway and cAMP signaling pathway were significantly changed in cisplatin group. The body weight, kidney weight and kidney weight/body weight ratio in cisplatin group were significantly lower than those in normal group (all P<0.05). However, after cAMP treatment, kidney weight was significantly higher compared with cisplatin group ( P<0.05), and body weight and kidney weight/body weight ratio also increased, but the differences were not statistically significant (both P>0.05). BUN, Scr and renal tubular injury score in cisplatin group were significantly higher than those in normal group (all P<0.05). After cAMP treatment, BUN, Scr and renal tubular injury score were significantly lower than those in cisplatin group (all P<0.05). Western blotting results showed that cAMP treatment could significantly increase the decreased AMPK/ACC signaling pathway protein in the renal tissues of cisplatin-induced mice (all P<0.05). In vitro experiments, immunofluorescence detection showed that the expression of p-AMPK protein in cisplatin-induced HK-2 cells decreased, and the addition of cAMP increased the expression of p-AMPK protein in cisplatin-induced HK-2 cells (all P<0.05). cAMP treatment could alleviate cisplatin-induced injury in HK-2 cells, restore the reduction of adenosine triphosphate content and NAD +/NADH ratio, and reduce the apoptosis induced by cisplatin (all P<0.05), while AMPK inhibitor could eliminate the protective effect of cAMP on cisplatin-induced injury in HK-2 cells. Conclusion:cAMP can play a protective role in renal injury caused by cisplatin, and its mechanism may be related to activation of AMPK/ACC signaling pathway.

Objective:To evaluate the efficacy and safety of peri-diaphragmatic hydrodissection in assisting microwave ablation（MWA）of right subphrenic colorectal liver metastasis（CRLM）.Methods:A retrospective analysis was conducted on 101 patients with right subphrenic CRLMs（206 lesions）who underwent percutaneous ultrasound-guided MWA at the Sixth Affiliated Hospital，Sun Yat-sen University from June 2020 to June 2023. Patients were divided into contrast-enhanced ultrasound（CEUS）with hydrodissection group（ n=63）and artificial ascites/pleural effusion group（ n=38，there were 17 patients with artificial pleural effusion，21 patients with artificial ascites）. In the CEUS with hydrodissection group，the peri-diaphragmatic water dissection was established during the post-vascular phase of CEUS. Lesion detection rates，visualization scores，local tumor progression（LTP），and complications were compared between the two groups. Results:In both the CEUS with hydrodissection group and the artificial ascites/pleural effusion group，the lesion detection rates（96.9% and 98.7%）and visualization scores［（3.7 ± 1.3）points and（4.6 ± 0.7）points］improved with water dissection assistance compared to conventional ultrasound［detection rates of 57.5% and 55.7%，visualization scores of（1.9 ± 1.0）points and（2.6 ± 1.5）points］and CEUS alone［detection rates of 78.0% and 78.5%，visualization scores of（3.1 ± 1.5）points and（3.7 ± 1.6）points］（all P<0.001）. The CEUS with hydrodissection group achieved comparable success rates（96.8% vs. 97.4%， P>0.99）but required less saline［60（30，90）ml vs. 500（500，1 000）ml， P<0.001］than artificial ascites/pleural effusion group. No significant differences were observed in LTP rates，complications，or pain scores（all P>0.05）. Conclusions:CEUS combined with peri-diaphragmatic hydrodissection improves detection rates and visualization of right subphrenic CRLM while reducing fluid volume compared to artificial hydrothorax/ascites，serving as a safe and effective adjunct for percutaneous MWA.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To investigate the effect of tissue-resident memory T cells(TRM)on imiquimod-induced psoriatic-like skin lesions in mice,and to elucidate the underlying mechanisms of TRM involvement in this process.Methods Forty female BALB/c mice were procured and randomly allocated into four groups:ten in the blank control group,and thirty for the establishment of a psoriasis mouse model.Following successful modeling,the thirty mice were further randomized into three groups:the model control group,the methotrexate-treated group,and the imiquimod-treated group,with ten mice in each group.Mice in the blank control group and model control group were uniformly treated with Vaseline for intervention.The methotrexate group and the imiquimod group were treated with 62.5mg of 5％imiquimod cream.The methotrexate group was administered by gavage at a dose of 1 mg/kg,and the gavage volume of each group was 10 mL/kg.The model control group,blank group and imiquimod group were gavaged with the same volume of normal saline.Treatment was conducted over six consecutive days.Subsequently,comparisons were made across groups regarding the psoriasis area and severity index(PASI),histopathological findings,inflammatory cytokine levels,and TRM cell levels.Results(1)The imiquimod group exhibited signifi-cantly lower scores for erythema(2.54±0.32),skin thickening(2.59±0.25),and scaling(2.52±0.29)compared to the methotrexate group,model control group,and blank control group(P<0.05).Additionally,the methotrexate group demonstrated reduced scores for erythema,skin thickening,and scaling compared to the model control group(P<0.05).(2)Hematoxylin-eosin(HE)staining revealed that the epidermis in the methotrexate group became thin-ner,with fewer parakeratotic cells and increased hair follicles.Conversely,the imiquimod group displayed abnor-mal cell morphology and relatively thicker white skin after modeling.(3)The imiquimod group showed significantly lower levels of TNF-α(51.63±4.39 pg/mL),IL-1β(35.53±4.15 pg/mL),IFN-γ(23.43±3.41 pg/mL),and IL-23(15.24±2.95 pg/mL)compared to the methotrexate and model control groups(P<0.05).Similarly,the methotrexate group exhibited reduced levels of TNF-α,IL-1β,IFN-γ,and IL-23 compared to the model control group(P<0.05).(4)The imiquimod group had significantly lower levels of CD8+CD103+cells(15.39±2.31)than the methotrexate and model control groups(P<0.05).Furthermore,the methotrexate group demonstrated lower levels of CD8+CD103+cells compared to the model control group(P<0.05).Conclusion Miquimod induces heavier skin lesions,faster response,and more epidermal thickening in psoriasis like mice.CD8+CD103+TRM cells and inflammatory factors may be involved in the recurrence of psoriasis.