Percutaneous nephrolithotomy guided by 5G-powered robot-assisted teleultrasound diagnosis system: first clinical experience with a novel tele-assistance approach (IDEAL stage 1).

BACKGROUND: To demonstrate the technical feasibility of percutaneous nephrolithotomy (PCNL) guided by 5G-powered robot-assisted teleultrasound diagnosis system (RTDS) in a complex kidney-stone (CKS) cohort and present our preliminary outcomes. PCNL is highly skill-required, which hinders it popularization in primary medical units of remote regions. We designed an innovative tele-assistance approach to make PCNL easy to be operated by inexperienced surgeons. METHODS: This was a prospective proof-of-concept study (IDEAL phase 1) on intraoperative tele-assistance provided by online urological experts via a 5G-powered RTDS. Total 15 CKS patients accepted this technology. Online experts manipulated a simulated probe to assist unskilled local operators by driving a patient-side robot-probe to guide and monitor the steps of access establishment and finding residual stones. RESULTS: Median total delay was 177ms despite one-way network-connecting distance > 5,800 km. No perceptible delay of audio-visual communication, driving robot-arm or dynamic ultrasound images was fed back. Successful tele-assistance was obtained in all cases. The first-puncture access-success rate was 78.6% with a one-session SF rate of 71.3% and without complications of grade III-V. CONCLUSIONS: The current technology based on 5G-powered RTDS can provide high-quality intraoperative tele-assistance, which has preliminarily shown satisfactory outcomes and reliable safety. It will break down a personal competence-based barrier to endow PCNL with more popular utilization. TRIAL REGISTRATION: The study was approved by ethics committee of the Xinjiang Kezhou People's Hospital and ethics committee of the First Affiliated Hospital of Nanjing Medical University and was registered on http://www.chictr.org.cn (ChiCTR2200065849, 16/11/2022).

Comparison of the diagnostic effectiveness of ultrasound imaging coupled with three mathematical models for discriminating thyroid nodules.

BACKGROUND: The overlapping nature of thyroid lesions visualized on ultrasound (US) images could result in misdiagnosis and missed diagnoses in clinical practice. PURPOSE: To compare the diagnostic effectiveness of US coupled with three mathematical models, namely logistic regression (Logistics), partial least-squares discriminant analysis (PLS-DA), and support vector machine (SVM), in discriminating between malignant and benign thyroid nodules. MATERIAL AND METHODS: A total of 588 thyroid nodules (287 benign and 301 malignant) were collected, among which 80% were utilized for constructing the mathematical models and the remaining 20% were used for internal validation. In addition, an external validation cohort comprising 160 nodules (80 benign and 80 malignant) was employed to validate the accuracy of these mathematical models. RESULTS: Our study demonstrated that all three models exhibited effective predictive capabilities for distinguishing between benign and malignant nodules, whose diagnostic effectiveness surpassed that of the TI-RADS classification, particularly in terms of true negative diagnoses. SVM achieved a higher diagnostic rate for malignant thyroid nodules (93.8%) compared to Logistics (91.5%) and PLS-DA (91.6%). PLS-DA exhibited higher diagnostic rates for benign thyroid nodules (91.9%) compared to Logistics (86.7%) and SVM (88.7%). Both the area under the receiver operating characteristic curve (AUC) values of PLS-DA (0.917) and SVM (0.913) were higher than that of Logistics (0.891). CONCLUSION: Our findings indicate that SVM had significantly higher rates of true positive diagnoses and PLS-DA exhibited significantly higher rates of true negative diagnoses. All three models outperformed the TI-RADS classification in discriminating between malignant and benign thyroid nodules.

Predicting the malignancy of extremity soft-tissue tumors by an ultrasound-based radiomics signature.

BACKGROUND: Accurate differentiation of extremity soft-tissue tumors (ESTTs) is important for treatment planning. PURPOSE: To develop and validate an ultrasound (US) image-based radiomics signature to predict ESTTs malignancy. MATERIAL AND METHODS: A dataset of US images from 108 ESTTs were retrospectively enrolled and divided into the training cohort (78 ESTTs) and validation cohort (30 ESTTs). A total of 1037 radiomics features were extracted from each US image. The most useful predictive radiomics features were selected by the maximum relevance and minimum redundancy method, least absolute shrinkage, and selection operator algorithm in the training cohort. A US-based radiomics signature was built based on these selected radiomics features. In addition, a conventional radiologic model based on the US features from the interpretation of two experienced radiologists was developed by a multivariate logistic regression algorithm. The diagnostic performances of the selected radiomics features, the US-based radiomics signature, and the conventional radiologic model for differentiating ESTTs were evaluated and compared in the validation cohort. RESULTS: In the validation cohort, the area under the curve (AUC), sensitivity, and specificity of the US-based radiomics signature for predicting ESTTs malignancy were 0.866, 84.2%, and 81.8%, respectively. The US-based radiomics signature had better diagnostic predictability for predicting ESTT malignancy than the best single radiomics feature and the conventional radiologic model (AUC = 0.866 vs. 0.719 vs. 0.681 for the validation cohort, all P <0.05). CONCLUSION: The US-based radiomics signature could provide a potential imaging biomarker to accurately predict ESTT malignancy.

Preoperative Contrast-Enhanced Ultrasound Predicts Microvascular Invasion in Hepatocellular Carcinoma as Accurately as Contrast-Enhanced MR.

OBJECTIVES: Both contrast-enhanced ultrasound (CEUS) and contrast-enhanced magnetic resonance (CEMR) are important imaging methods for hepatocellular carcinoma (HCC). This study aimed to establish a model using preoperative CEUS parameters to predict microvascular invasion (MVI) in HCC, and compare its predictive efficiency with that of CEMR model. METHODS: A total of 93 patients with HCC (39 cases in MVI positive group and 54 cases in MVI negative group) who underwent surgery in our hospital from January 2020 to June 2021 were retrospectively analyzed. Their clinical and imaging data were collected to establish CEUS and CEMR models for predicting MVI. The predictive efficiencies of both models were compared. RESULTS: By the univariate and multivariate regression analyses of patients' clinical information, preoperative CEUS static and dynamic images, we found that serrated edge and time to peak were independent predictors of MVI. The CEUS prediction model achieved a sensitivity of 92.3%, a specificity of 83.3%, and an accuracy of 84.6% (Az: 0.934). By analyzing the clinical and CEMR information, we found that tumor morphology, fast-in and fast-out, peritumoral enhancement, and capsule were independent predictors of MVI. The CEMR prediction model achieved a sensitivity of 97.4%, a specificity of 77.8%, and an accuracy of 83.2% (Az: 0.900). The combination of the two models achieved a sensitivity of 84.6%, a specificity of 87.0%, and an accuracy of 86.2% (Az: 0.884). There was no significant statistical difference in the areas under the ROC curve of the three models. CONCLUSION: The CEUS model and the CEMR model have similar predictive efficiencies for MVI of HCC. CEUS is also an effective method to predict MVI before operation.

Pretreatment ultrasound-based deep learning radiomics model for the early prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

OBJECTIVES: To investigate the predictive performance of the deep learning radiomics (DLR) model integrating pretreatment ultrasound imaging features and clinical characteristics for evaluating therapeutic response after neoadjuvant chemotherapy (NAC) in patients with breast cancer. METHODS: A total of 603 patients who underwent NAC were retrospectively included between January 2018 and June 2021 from three different institutions. Four different deep convolutional neural networks (DCNNs) were trained by pretreatment ultrasound images using annotated training dataset (n = 420) and validated in a testing cohort (n = 183). Comparing the predictive performance of these models, the best one was selected for image-only model structure. Furthermore, the integrated DLR model was constructed based on the image-only model combined with independent clinical-pathologic variables. Areas under the curve (AUCs) of these models and two radiologists were compared by using the DeLong method. RESULTS: As the optimal basic model, Resnet50 achieved an AUC and accuracy of 0.879 and 82.5% in the validation set. The integrated DLR model, yielding the highest classification performance in predicting response to NAC (AUC 0.962 and 0.939 in the training and validation cohort), outperformed the image-only model and the clinical model and also performed better than two radiologists' prediction (all p < 0.05). In addition, predictive efficacy of the radiologists was improved under the assistance of the DLR model significantly. CONCLUSION: The pretreatment US-based DLR model could hold promise as a clinical guidance for predicting NAC response of patients with breast cancer, thereby providing benefit of timely treatment strategy adjustment to potential poor NAC responders. KEY POINTS: • Multicenter retrospective study showed that deep learning radiomics (DLR) model based on pretreatment ultrasound image and clinical parameter achieved satisfactory prediction of tumor response to neoadjuvant chemotherapy (NAC) in breast cancer. • The integrated DLR model could become an effective tool to guide clinicians in identifying potential poor pathological responders before chemotherapy. • The predictive efficacy of the radiologists was improved under the assistance of the DLR model.

Association between time in range 70-180 mg/dl in early stage and severity with in patients acute pancreatitis.

BACKGROUND: It is not well understood whether glucose control in the early stage of acute pancreatitis(AP) is related to outcome. This study aimed to investigate the association between blood glucose time in range (TIR) of 70-180 mg/dL in the first 72 h(h) on admission and the progression of AP. METHODS: Individuals admitted with AP to the Gastroenterology Department of the Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University between January 2017 and December 2021 were included and retrospectively evaluated. The percentage of TIR between 70 and 180 mg/dL in the first 72 h was calculated. According to the progress of AP at discharge, patients were divided into mild pancreatitis(MAP), and moderately severe acute pancreatitis (MSAP), or severe acute pancreatitis (SAP) groups. We examined the association between TIR or TIR ≥ 70% and AP severity using logistic regression models stratified by a glycosylated hemoglobin (HbA1c) level of 6.5%. Receiver operating characteristic (ROC) curves were generated to assess the ability of the TIR to predict MSAP or SAP. RESULTS: A total of 298 individuals were included, of whom 35 developed MSAP or SAP. Logistic regression analyses indicated that TIR was independently associated with the incidence of more serious AP (odds ratio [OR] = 0.962, 95% CI = 0.941-0.983, p = 0.001). This association remained significant in individuals with HbA1c levels ≤ 6.5% (OR = 0.928, 95% CI = 0.888-0.969, p = 0.001). A TIR ≥ 70% was independently associated with reduced severity only in people with well-antecedent controls (OR = 0.238; 95% CI = 0.071-0.802; p = 0.020). TIR was not powerful enough to predict the severity of AP in both patients with poor antecedent glucose control (AUC = 0.641) or with HbA1c < 6.5% (AUC = 0.668). CONCLUSIONS: TIR was independently associated with severity in patients with AP, particularly those with good antecedent glucose control.

A multiparametric clinic-ultrasomics nomogram for predicting extremity soft-tissue tumor malignancy: a combined retrospective and prospective bicentric study.

OBJECTIVE: We aimed at building and testing a multiparametric clinic-ultrasomics nomogram for prediction of malignant extremity soft-tissue tumors (ESTTs). MATERIALS AND METHODS: This combined retrospective and prospective bicentric study assessed the performance of the multiparametric clinic-ultrasomics nomogram to predict the malignancy of ESTTs, when compared with a conventional clinic-radiologic nomogram. A dataset of grayscale ultrasound (US), color Doppler flow imaging (CDFI), and elastography images for 209 ESTTs were retrospectively enrolled from one hospital, and divided into the training and validation cohorts. A multiparametric ultrasomics signature was built based on multimodal ultrasomic features extracted from the grayscale US, CDFI, and elastography images of ESTTs in the training cohort. Another conventional radiologic score was built based on multimodal US features as interpreted by two experienced radiologists. Two nomograms that integrated clinical risk factors and the multiparameter ultrasomics signature or conventional radiologic score were respectively developed. Performance of the two nomograms was validated in the retrospective validation cohort, and tested in a prospective dataset of 51 ESTTs from the second hospital. RESULTS: The multiparametric ultrasomics signature was built based on seven grayscale ultrasomic features, three CDFI ultrasomic features, and one elastography ultrasomic feature. The conventional radiologic score was built based on five multimodal US characteristics. Predictive performance of the multiparametric clinic-ultrasomics nomogram was superior to that of the conventional clinic-radiologic nomogram in the training (area under the receiver operating characteristic curve [AUC] 0.970 vs. 0.890, p = 0.006), validation (AUC: 0.946 vs. 0.828, p = 0.047) and test (AUC: 0.934 vs. 0.842, p = 0.040) cohorts, respectively. Decision curve analysis of combined training, validation and test cohorts revealed that the multiparametric clinic-ultrasomics nomogram had a higher overall net benefit than the conventional clinic-radiologic model. CONCLUSION: The multiparametric clinic-ultrasomics nomogram can accurately predict the malignancy of ESTTs.

Comparison of an online versus conventional multidisciplinary collaborative weight loss programme in type 2 diabetes mellitus: A randomized controlled trial.

AIM: The aim of this study was to examine the effect of an online multidisciplinary weight loss management programme. METHODS: Between July 2016 and July 2017 this randomized controlled trial recruited patients in Nanjing, China who were living with type 2 diabetes mellitus and who were obese or overweight and randomized them to online versus conventional groups. All participants were managed by a multidisciplinary team. The experimental group was managed using the Why Wait WeChat Platform for Weight Reduction Management. RESULTS: There were 55 and 52 participants in the online and conventional groups, respectively. The decreases in fasting blood glucose (-4.26 vs. -2.99 mmol/L), 2-h postprandial blood glucose (-4.48 vs. -2.68 mmol/L) and glycated haemoglobin (-22.11 vs. -6.21 mmol/mol) were more pronounced in the online compared to conventional group (all P < 0.05). After the intervention, self-management ability parameters, including diet control, foot care and total score, were improved in the online group compared with the conventional group, as well as all indexes of quality of life (all P < 0.05). CONCLUSION: The online multidisciplinary weight loss management programme improved blood glucose in obese or overweight patients living with type 2 diabetes mellitus. Self-management ability parameters (including diet control, foot care and total score) and quality of life were improved in the online group compared with the conventional group.

Thrombin injection under B-flow and ultrasound guidance: A safe and effective treatment of pseudoaneurysms.

PURPOSE: To evaluate the method of thrombin injection under B-flow and ultrasound guidance (BUGTI) for the treatment of pseudoaneurysms. MATERIALS AND METHODS: Twenty-one patients suffering from pseudoaneurysm (PSA) were retrospectively reviewed at the First Affiliated Hospital of Nanjing Medical University in Nanjing, China, from January 2018 to August 2019. The patients were treated using an ultrasound-guided injection of thrombin (500 IU/mL) combined with B-mode blood flow imaging (B-flow). The information on the PSA, including the size of the arterial rupture and sac, flow rate, thrombin dose, and treatment outcome, was recorded during the procedure. Follow-up evaluation was performed at 1, 3, and 6 months after the treatment. Pearson's correlation analysis was performed among the characteristics of PSA and the dose of thrombin. RESULT: The age of patients ranged from 34 to 80 years and averaged 62.8 years. The maximum cross-sectional area of PSA ranged from 208 to 1148 mm2. All patients were treated with thrombin injections. The dose of thrombin ranged from 300 to 1667 IU. No reperfusions were detected at follow-up 6 months, and the BUGTI treatment was successful in all 21 cases. Pearson's correlation analysis demonstrated that the dose of thrombin was positively correlated with the width (r = 0.449, p < .05) and maximum cross-sectional area (r = 0.504, p < .05) of PSA. CONCLUSION: Thrombin injection under B-flow and ultrasound guidance is a rapid and effective treatment for PSA. Additionally, the sac size could be used to estimate the dose of thrombin.

Management of Sonographically Suspicious Thyroid Nodules 1 cm or Smaller and Candidacy for Active Surveillance: Experience of a Tertiary Center in China.

OBJECTIVE: Our objective was to investigate the management of patients with asymptomatic suspicious thyroid nodules ≤1 cm. METHODS: We retrospectively reviewed medical records of patients with sonographically suspicious thyroid nodules ≤1 cm and without distant metastases, suspicious lymph node metastasis (LNM), or extrathyroidal extension (ETE). RESULTS: Of the 386 enrolled patients, 174 (45.1%) had immediate surgery (IS), while 212 (54.9%) underwent active surveillance (AS). In the IS group, 166 (95.4%) patients were confirmed as having papillary thyroid microcarcinoma. LNM and ETE were observed in 24.7% and 2.4% cases, respectively. In the AS group, nodule size increased by ≥3 mm in 11 (5.2%) patients and 39 (18.4%) had a >50% increase in nodule volume after a median follow-up of 12 months. Nodules with smaller volume at diagnosis were more likely to increase in volume later. Newly suspicious LNM was detected in 23 (10.8%) patients. Delayed surgery (DS) was performed in 101 patients, with 27 showing disease progression. ETE and LNM were detected in 3% and 36%, respectively, of patients with papillary thyroid microcarcinoma. Compared with IS, tumors in the DS group more frequently showed lateral LNM and capsular invasion (P < .05). No patient had recurrence or died of thyroid cancer during postoperative follow-up (median 26 [4-60] months). CONCLUSIONS: IS or DS of patients with asymptomatic suspicious thyroid nodules ≤1 cm was relatively high in China. The inertia of low-risk nodules and the effectiveness of DS for those that progressed make AS a feasible strategy.

Application of multi-label classification models for the diagnosis of diabetic complications.

BACKGROUND: Early diagnosis for the diabetes complications is clinically demanding with great significancy. Regarding the complexity of diabetes complications, we applied a multi-label classification (MLC) model to predict four diabetic complications simultaneously using data in the modern electronic health records (EHRs), and leveraged the correlations between the complications to further improve the prediction accuracy. METHODS: We obtained the demographic characteristics and laboratory data from the EHRs for patients admitted to Changzhou No. 2 People's Hospital, the affiliated hospital of Nanjing Medical University in China from May 2013 to June 2020. The data included 93 biochemical indicators and 9,765 patients. We used the Pearson correlation coefficient (PCC) to analyze the correlations between different diabetic complications from a statistical perspective. We used an MLC model, based on the Random Forest (RF) technique, to leverage these correlations and predict four complications simultaneously. We explored four different MLC models; a Label Power Set (LP), Classifier Chains (CC), Ensemble Classifier Chains (ECC), and Calibrated Label Ranking (CLR). We used traditional Binary Relevance (BR) as a comparison. We used 11 different performance metrics and the area under the receiver operating characteristic curve (AUROC) to evaluate these models. We analyzed the weights of the learned model and illustrated (1) the top 10 key indicators of different complications and (2) the correlations between different diabetic complications. RESULTS: The MLC models including CC, ECC and CLR outperformed the traditional BR method in most performance metrics; the ECC models performed the best in Hamming loss (0.1760), Accuracy (0.7020), F1_Score (0.7855), Precision (0.8649), F1_micro (0.8078), F1_macro (0.7773), Recall_micro (0.8631), Recall_macro (0.8009), and AUROC (0.8231). The two diabetic complication correlation matrices drawn from the PCC analysis and the MLC models were consistent with each other and indicated that the complications correlated to different extents. The top 10 key indicators given by the model are valuable in medical application. CONCLUSIONS: Our MLC model can effectively utilize the potential correlation between different diabetic complications to further improve the prediction accuracy. This model should be explored further in other complex diseases with multiple complications.

Echocardiographic Changes in Newly Diagnosed Type 2 Diabetes Mellitus Patients with and without Hypertension.

BACKGROUND Whether type 2 diabetes mellitus (T2DM) is independently associated with structural heart abnormalities is controversial because of confounders associated with T2DM. This study aimed to investigate echocardiographic features in patients with newly diagnosed T2DM, exploring changes in cardiac structure and function. MATERIAL AND METHODS This was a retrospective study of new T2DM cases treated at the Second People's Hospital Affiliated to Nanjing Medical University (Changzhou) in 2014-2016. In all, 128 T2DM cases were included (62 hypertensive and 66 non-hypertensive individuals). Controls were selected among individuals who underwent examination at the same department/period. Interventricular septal thickness (IVST), left ventricular end-diastolic diameter (LVEDD), posterior left ventricular wall thickness (PWTD), left ventricle mass (LVM), end-diastolic thickness of left ventricular posterior wall (Dd), aortic root diameter, left atrial diameter (LAd), left atrial diameter fraction-shortening values, and left ventricular ejection fraction (LVEF) were determined routinely. RESULTS IVST, LVEDD, PWTD, Dd, LAd, and left atrial diameter fraction-shortening values were larger in patients with T2DM (all P<0.05 vs. controls). LVM was higher in T2DM patients (median, 57.12 vs. 54.77 g, P=0.001). There were no differences in aortic root diameter and EF (both P>0.05). Multivariable analysis showed that IVST (OR=1.33, 95% CI: 1.01-1.76, P=0.04), LAd (OR=1.16, 95% CI: 1.07-1.25, P<0.001), TGs (OR=1.34, 95% CI: 1.09-1.63, P=0.005), and HDL (OR=1.46, 95% CI: 1.02-2.08, P=0.04) were independently associated with hypertension in patients with T2DM. CONCLUSIONS Patients with newly diagnosed T2DM already display structural heart abnormalities. LAd and IVST are independently associated with hypertension in these patients, probably contributing to increased cardiovascular risk.

Oxalomalate regulates the apoptosis and insulin secretory capacity in streptozotocin-induced pancreatic ß-cells.

Diabetes mellitus (DM) is a kind of metabolic disorder characterized by long-term hyperglycemia. Oxidative stress is involved in inducing the apoptosis of pancreatic ß-cells and promoting the development of DM. Oxalomalate (OMA) is a competitive inhibitor of two classes of NADP+-dependent isocitrate dehydrogenase isoenzymes that are the main nicotinamide adenine dinucleotide phosphate (NADPH) producers to scavenge cellular reactive oxygen species (ROS). However, the role of OMA in DM remains unclear. The present study aimed to investigate the protective effects of OMA on streptozotocin (STZ)-induced ß-cell damage and its underlying mechanisms. The viability of rat insulinoma cell line (INS-1) and the contents of ROS, nitric oxide and NAPDH were examined after cells being treated with STZ. After treatment with OMA in STZ-stimulated INS-1, the cell viability, apoptosis, and apoptosis-related proteins were measured. Meanwhile, the levels of oxidative stress-related factors and the changes of insulin secretion were determined. The results revealed that OMA significantly increased the cell viability (p < .05), reduced the apoptotic rate (p < .001), and altered the expression levels of Bcl-2, Bax, cleaved caspase3, and cleaved-caspase9 (p < .05 or p < .01) in STZ-induced INS-1 cells. Moreover, OMA enhanced the activities of superoxide dismutase, catalase, glutathione peroxidase (p < .01), whereas reduced the levels of ROS, malondialdehyde and lactic dehydrogenase (p < .001). Furthermore, OMA improved the ability of insulin secretion. These results indicated that OMA might have antioxidative stress and anti-apoptosis effects to protect INS-1 cells from STZ-induced cell damage.

Determining the optimal fasting glucose target for patients with type 2 diabetes: Results of the multicentre, open-label, randomized-controlled FPG GOAL trial.

The optimal fasting blood glucose (FBG) target of achieving HbA1c less than 7.0% in type 2 diabetes (T2D) patients remains controversial. This open-label trial randomized (1:3:3) 947 adults with uncontrolled T2D (HbA1c >7% to ≤10.5%) who were using one to three oral antidiabetic drugs to achieve an FBG target of 3.9 < FBG ≤5.6 mmol/L (Group 1), 3.9 < FBG ≤6.1 mmol/L (Group 2) or of 3.9 < FBG ≤7.0 mmol/L (Group 3). Targets were achieved using a pre-defined insulin glargine 100 U/mL titration scheme. The primary endpoint was proportion of patients achieving HbA1c <7.0% at 24 weeks. At 24 weeks, 44.4%, 46.1% and 37.7% of patients achieved HbA1c <7.0% in Groups 1, 2 and 3, respectively (P = 0.017; Group 2 vs Group 3). Alert hypoglycaemia (glucose ≤3.9 mmol/L) was significantly more frequent in Group 1 than in Group 3 (38.9 vs 23.3%; P < 0.001) but was not in Group 2 vs Group 3 (27.5% vs 23.3%; P = 0.177). Clinically important hypoglycaemia (glucose ≤3.0 mmol/L) was reported in 4.8%, 2.0% and 3.8% of patients in Groups 1, 2 and 3, respectively. In conclusion, the optimal FBG target for most Chinese patients with T2D appears to be 3.9-6.1 mmol/L.

[Association between obesity and sleep disorders among children in Lanzhou, China].

OBJECTIVE: To investigate the prevalence of obesity and sleep disorders and the association between them among children in Lanzhou, China. METHODS: The stratified cluster random sampling method was used to select 3 283 primary school students in four districts of Lanzhou of Gansu province. Physical examination and sleep questionnaire were conducted to screen out the children who met the criteria for sleep disorders or obesity as subjects. Among the 3 283 children, 200 healthy children without sleep disorders or obesity were enrolled as the control group. RESULTS: The prevalence rate of obesity among the 3 283 children was 5.76% (189/3 283). Among these 189 obese children, 80 (42.3%) had sleep disorders. The prevalence rate of sleep disorders was 16.24% (533/3 283), and the prevalence rate of obesity among the children with sleep disorders was 24.6% (131/533). Snoring was the most common sleep disorder in obese children. The prevalence rate of obstructive sleep apnea hypopnea syndrome was 45% (36/80) among obese children with sleep disorders. The obese children had a significantly higher prevalence rate of sleep disorders than the children with normal body weight [42.3% (80/189) vs 20% (40/200), P<0.01]. CONCLUSIONS: There is a close relationship between obesity and sleep disorders in children in Lanzhou, China.

Analysis of Oral Microbiota Revealed High Abundance of Prevotella Intermedia in Gout Patients.

BACKGROUND/AIMS: Microbes reside in a number of body sites, including the oral cavity, and are associated with the progression of many systemic diseases. In this study, we aimed to investigate the effects of gout and hyperuricemia (HUA) on the composition of oral microbiomes. METHODS: Analysis of the oral microbiota from 12 gout patients, 11 HUA patients, and 19 healthy control subjects was performed using a deep sequencing approach, and validation of significant changes in Prevotella intermedia and Serratia marcescens in new patient cohorts was performed using quantitative PCR (qPCR). RESULTS: Our analysis indicated that both gout and HUA significantly altered the composition of the oral microbiome in patients. Patients with gout or HUA had significantly greater levels of salivary Prevotella intermedia but significantly lower levels of Serratia marcescens than healthy control subjects. CONCLUSION: We demonstrated the association between the oral microbiome and gout and HUA for the first time. In particular, 16S sequencing and qPCR analysis revealed significantly higher levels of oral Prevotella intermedia in gout/HUA patients, which suggests that these patients might be at risk for the development of periodontitis.

Egr2 enhances insulin resistance via JAK2/STAT3/SOCS-1 pathway in HepG2 cells treated with palmitate.

Insulin resistance is generally responsible for the pathogenesis of type 2 diabetes mellitus (T2DM). Early growth response proteins-2 (Egr2) has been reported to be able to increase the expression of the suppressors of cytokine signaling-1 (SOCS-1), and impair insulin signaling pathway through suppression of insulin receptor substrates (IRS), including IRS-1 and IRS-2. However, whether Egr2 is directly involved in the development of insulin resistance, and how its potential contributions to insulin resistance still remain unknown. Here, our present investigation found that the expression levels of Egr2 were up-regulated when insulin resistance occurs, and knockdown of Egr2 abolished the effect of insulin resistance in HepG2 cells induced with palmitate (PA). Importantly, inhibition of Egr2 decreased the expression of SOCS-1 as well as reduced phosphorylation of JAK2 and STAT3. And, our data indicated that silencing of Egr2 accelerated hepatic glucose uptake and reversed the impaired lipid metabolism upon insulin resistance. In summary, the present study confirms that Egr2 could deteriorate insulin resistance via the pathway of JAK2/STAT3/SOCS-1 and may shed light on resolving insulin resistance and further the pathogenesis of T2DM.

CtBP2 ameliorates palmitate-induced insulin resistance in HepG2 cells through ROS mediated JNK pathway.

Oxidative stress plays a significant role in the development of hepatic insulin resistance, but the underlying molecular mechanisms remain poorly understood. In this study, we discovered that C-terminal-binding protein 2 (CtBP2) level was decreased in insulin resistance. Taking into account the relationship between CtBP family protein (ANGUSTIFOLIA) and reactive oxygen species (ROS) accumulation, we conjectured CtBP2 was involved in insulin resistance through ROS induced stress. In order to verify this hypothesis, we over-expressed CtBP2 in palmitate (PA) treated HepG2 cells. Here, we found that over-expression of CtBP2 ameliorated insulin sensitivity by increasing phosphorylation of glycogen synthase kinase 3ß (GSK3ß) and protein kinase B (AKT). These data suggest that CtBP2 plays a critical role in the development of insulin resistance. Moreover, CtBP2 reversed the effects of PA on ROS level, lipid accumulation, hepatic glucose uptake and gluconeogenesis. We also found that over-expression of CtBP2 could suppress PA induced c-jun NH2 terminal kinase (JNK) activation. Furthermore, JNK inhibitor SP600125 was shown to promote the effect of CtBP2 on insulin signaling. Thus, we demonstrated that CtBP2 ameliorated PA-induced insulin resistance via ROS-dependent JNK pathway.

Liver X Receptor Gene Expression is Enhanced in Children with Obstructive Sleep Apnea-Hyperpnoea Syndrome and Cyclooxygenase-2 (COX-2) is Correlated with Severity of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS).

BACKGROUND Liver X receptor (LXR) is a nuclear receptor presenting in macrophages; it works indispensably in lipid metabolism control and also negatively regulates the expression of inflammatory genes in macrophages. There are many LXR-related studies in adults with metabolic syndrome but rare reports in obese children with obstructive sleep apnea-hypopnea syndrome (OSAHS). The aim of this study was to investigate the expression of LXR, cholesterol ester transfer protein (CETP), and cyclooxygenase-2 (COX-2) genes in obese children with OSAHS compared with obese children without OSAHS and non-obese children. MATERIAL AND METHODS Sleep monitoring was conducted in 80 obese children with sleep disorders. Fasting morning blood samples from the 80 obese children and 51 normal children were collected and separated, so that macrophages were obtained after culture. Fluorescence quantitative real-time PCR (RT-PCR) was used to detect expression levels of the LXR, CETP, and COX-2 genes. RESULTS LXR, COX-2, and CETP levels in the OSAHS group were higher than those in the other two groups (P<0.05), and the LXR levels in the group of obese children without OSAHS were higher than those in control group (P<0.05). COX-2 expression in the group with moderate to severe OSAHS was higher than that in the group with mild OSAHS (P<0.05). Meanwhile, there were no significant differences in the LXR and CETP levels between the moderate to severe OSAHS group and the mild OSAHS group (P>0.05). CONCLUSIONS LXR gene expression was significantly increased in obese children with OSAHS. The severity of OSAHS was positively correlated with COX-2 levels.

Predictors of High Cardiovascular Risk Among Nonobese Patients with Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease in a Chinese Population.

Purpose: This study aims to investigate cardiovascular risk factors in nonobese patients with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD) and to determine whether they might be used to predict high-risk individuals effectively. Patients and Methods: This cross-sectional study included 245 nonobese patients with T2DM who underwent FibroTouch in the National Metabolic Management Center of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University from January 2021 to December 2022. All individuals were divided into NAFLD and non-NAFLD groups. Patients with NAFLD were further grouped by UAP tertiles (T1, T2 and T3). We created a Cardiovascular Score (total scale: 0-5 points; ≥3 points was defined as high-risk individual) based on baPWV, carotid ultrasound, and urinary microalbumin creatinine ratio (UA/CR) to assess the risk of cardiovascular disease in non-obese T2DM patients with NAFLD. Risk factors were evaluated using univariate and multivariate analysis. The performance of risk factors was compared according to the area under the receiver operating characteristic (ROC) curve. Results: Atherogenic index of plasma (AIP), atherosclerosis index (AI), prevalence of hypertension, body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR) were higher in the NAFLD group compared to the non-NAFLD group. In T3 group, AIP, AI, BMI and HOMA-IR were higher than those of T1 group. Multivariate logistic regression showed that age, systolic blood pressure, low-density lipoprotein-cholesterol (LDL-C) and AIP were risk factors for cardiovascular disease among nonobese patients with T2DM and NAFLD. The area under the ROC curve for age, systolic blood pressure, LDL-C and AIP were 0.705, 0.688, 0.738 and 0.642, respectively. The area under the ROC curve was 0.895 when combining them. Conclusion: Age, systolic blood pressure, AIP and LDL-C are all independent risk factors for cardiovascular disease in non-obese individuals with T2DM and NAFLD, which can be combined to identify high-risk populations and carry out intervention.