The relationship between dietary inflammatory index and metabolic syndrome and its components: a case study in Kashi urban, Xinjiang.

Introduction: This paper examines the association between the dietary inflammatory index (DII) and the risk of metabolic syndrome (MS) and its components among Uygur adults in Kashi, Xinjiang. Methods: The study used the multi-stage random cluster sampling method to investigate the adult residents of Uighu aged over 18 years old in one county and one township/street of three cities in Kashi between May and June 2021. All dietary data collected were analyzed for energy and nutrient intake with a nutritional analysis software, followed by a calculation of DII. Logistic regression was used to estimate the association between DII and the risks of MS and its components. Results: The maximum DII value across our 1,193 respondents was 4.570 to 4.058, with an average value of 0.256. When we analyzed the DII as a continuous variable, we determined the anti-inflammatory diet has been identified as a mitigating factor for metabolic syndrome (OR = 0.586, 95% CI = 0.395-0.870), obesity (OR = 0.594, 95% CI = 0.395-0.870), elevated fasting glucose levels (OR = 0.422, 95% CI = 0.267-0.668), and hypertension (OR = 0.698, 95% CI = 0.488-0.996). When the model was adjusted by sex, age, and occupation, we found a significant correlation between high- and low-density lipoproteinemia and DII (OR = 1.55, 95% CI = 1.040-2.323). The present study identified four distinct dietary patterns among the population under investigation. There was a linear trend in the incidence of MS and hypertension across low, middle, and high levels of fruits and milk dietary pattern model (p = 0.027; p = 0.033), within this dietary pattern may serve as protective factors against MS and hypertension, suggesting that fruits and milk within this dietary pattern may serve as protective factors against MS and hypertension. And the linear trend in the incidence of elevated fasting glucose and obesity across the low, medium, and high scores of meet and eggs dietary pattern (p = 0.006; p < 0.001), suggest that a diet rich in meat may potentially contribute to an increased risk of developing elevated fasting glucose levels and obesity. An observed linear trend in the incidence rate of high fasting blood glucose across low, moderate, and high scores of dried fruits and nuts dietary pattern (p = 0.014), indicating that increased consumption of nuts acted as a protective factor against elevated fasting blood glucose levels and contributed to their reduction. Discussion: The dietary inflammation index was integrated with the findings from the study on the dietary patterns of the sampled population, revealing that an anti-inflammatory diet demonstrated a protective effect against metabolic syndrome, obesity, high fasting blood glucose, and hypertension in this specific population. laying the foundation for further research.

Chronic disease prevention literacy and its influence on behavior and lifestyle: a cross-sectional study in Xinjiang, China.

OBJECTIVE: To understand the status and influencing factors of Kyrgyz chronic disease prevention literacy, and to explore the impact of chronic disease prevention literacy on behavior and living habits. METHOD: Using stratified sampling method, Kyrgyz residents aged ≥ 18 years in Artush City, Aheqi County and Ucha County were surveyed by questionnaire. RESULTS: A total of 10,468 subjects were investigated, and the literacy rate of chronic disease prevention in Kyrgyz was 11.2%. The results of Logistic regression analysis showed that the literacy rate of chronic disease prevention was low among people with low education level, herdsmen, low income, urban and chronic disease (P < 0.05). Residents with chronic disease prevention literacy were more inclined to not smoke, not drink alcohol, drink milk every day, eat soy products every month, eat whole grains every day (P < 0.05). CONCLUSION: The literacy level of chronic disease prevention of Kyrgyz residents in Kezhou has been improved, but it is still at a low level compared with another subcategories. The behavioral lifestyle is related to the literacy level of chronic disease prevention. Therefore, local health promotion strategies should be developed to improve the literacy level of chronic disease prevention and promote the formation of good behavioral and living habits.

Influenza vaccine effectiveness against influenza A during the delayed 2022/23 epidemic in Shihezi, China.

After the temporary end of COVID-19 in China in February 2023, the influenza epidemic peaked in March across many Chinese places. We recruited a total of 258 all-age subjects presenting influenza-like illness (ILI) in Shihezi city, China from January 1 to March 16, 2023, and tested for influenza virus infection. Using a test-negative design, we assessed influenza vaccine effectiveness (VE) of 56.3% (95% CrI: 13.6, 73.6) against medically attended, influenza illness during the delayed 2022/23 influenza epidemic. The findings contributed to the continuous monitoring of the influenza vaccine performance across the world, especially in the "post-COVID" pandemic era.

Prediction Model of hospitalization time of COVID-19 patients based on Gradient Boosted Regression Trees.

When an outbreak of COVID-19 occurs, it will cause a shortage of medical resources and the surge of demand for hospital beds. Predicting the length of stay (LOS) of COVID-19 patients is helpful to the overall coordination of hospital management and improves the utilization rate of medical resources. The purpose of this paper is to predict LOS for patients with COVID-19, so as to provide hospital management with auxiliary decision-making of medical resource scheduling. We collected the data of 166 COVID-19 patients in a hospital in Xinjiang from July 19, 2020, to August 26, 2020, and carried out a retrospective study. The results showed that the median LOS was 17.0 days, and the average of LOS was 18.06 days. Demographic data and clinical indicators were included as predictive variables to construct a model for predicting the LOS using gradient boosted regression trees (GBRT). The MSE, MAE and MAPE of the model are 23.84, 4.12 and 0.76 respectively. The importance of all the variables involved in the prediction of the model was analyzed, and the clinical indexes creatine kinase-MB (CK-MB), C-reactive protein (CRP), creatine kinase (CK), white blood cell count (WBC) and the age of patients had a higher contribution to the LOS. We found our GBRT model can accurately predict the LOS of COVID-19 patients, which will provide good assistant decision-making for medical management.

Shift work is associated with an increased risk of type 2 diabetes and elevated RBP4 level: cross sectional analysis from the OHSPIW cohort study.

BACKGROUND: Shift work, with its growing prevalence globally, disrupts the body's inherent circadian rhythm. This disruption may escalate the risk of chronic diseasesxacerbate chronic disease risk by dysregulating physiological, behavioral, and psychosocial pathways. This study aimed to evaluate the effect of shift work on type 2 diabetes (T2DM) and Retinol binding protein 4 (RBP4) level. METHODS: The current study employed a multi-stage stratified cluster sampling technique, examining 1499 oilfield workers from the OHSPIW cohort who participated in occupational health assessments between March 2017 and June 2018.The evaluation involved shift work, sleep quality, T2DM status with questionnaires and plasma RBP4 levels in blood samples. Statistical analysis includes, Chi-square tests, t-tests, multivariate logistic regression analyses, and multivariate linear mixed models. RESULTS: The prevalence rate of T2DM in shift workers (6.56%) was significantly higher than in day workers (4.21%) (OR = 1.60, 95% CI: 1.01-2.53), with no significant difference found in the family history of diabetes, hypertension, or other chronic heart diseases (P = 0.378). The shift worker (6.89 ± 3.35) also exhibited distinctly higher PSQI scores than day workers (5.99 ± 2.87) (P < 0.001). Adjusting the age, gender, BMI, family income, tobacco smoking, alcohol drinking and PSQI, hailed shift work as a risk factor for T2DM (OR = 1.91, 95% CI: 1.17-3.14). The pairwise comparison revealed significant differences in RBP4 levels across different groups: shift and non-shift workers both with and without T2DM (P < 0.001). The RBP4 level of the shift group without T2DM was higher than the non-shift group without T2DM (P < 0.05). The levels of RBP4 level in shift and non-shift groups with T2DM was higher than those without T2DM (P < 0.05). The multivariate linear mixed model showed that when age, gender, BMI, diabetes, PSQI, family income, smoking and drinking remained unchanged, the RBP4 level of the shift workers increased by an average of 9.51 µg/mL compared with the day workers. CONCLUSIONS: Shift work is associated with an increased risk of T2DM and high levels of RBP4. Follow-up of RBP4 could facilitateearly detection of T2DM among shift workers.

The Effect of the Interaction between Abnormal Body Mass Index and Hypertension on the Risk of Type 2 Diabetes.

Objective: Many patients with type 2 diabetes have an abnormal body mass index (BMI) and hypertension together, but few studies on the interaction of the two on the risk of T2DM are reported. We aim to explore the effect of the interaction between abnormal BMI and hypertension on the risk of type 2 diabetes mellitus (T2DM) in Uyghur residents. Methods and Results: Based on the physical examination data of 27,4819 Uygur residents in Moyu County, a logistic regression model was used to analyze the correlation between BMI abnormality, hypertension, and T2DM disease, and then, the effect of their interaction on the risk of T2DM was evaluated by an additive model and a multiplicative model. The results showed that the detectable rate of T2DM was 5.58%, the proportion of abnormal BMI was 59.49%, and the proportion of hypertension was 25.14%. The risk of T2DM in people with an abnormal BMI and hypertension was higher than that in people with a normal weight and without hypertension, and the difference was statistically significant (P < 0.05). The additive model showed that after adjusting for confounding factors such as gender, age, family history of diabetes, abdominal obesity, and alcohol consumption, abnormal BMI and hypertension had a synergistic effect on the risk of T2DM and the evaluation indicators RERI, AP, and S were 0.90 (0.32∼1.49), 0.20 (0.11∼0.30), and 1.36 (1.17∼1.57), respectively. But there was no multiplicative interaction between the two (OR = 0.97, (95% CI: 0.89∼1.06). 3). Conclusion: The interaction between abnormal BMI and hypertension can increase the risk of T2DM, and improving BMI and controlling blood pressure within the normal range can effectively reduce the risk of T2DM.

Long non-coding RNA screening and identification of potential biomarkers for type 2 diabetes.

BACKGROUND: To investigate new lncRNAs as molecular markers of T2D. METHODS: We used microarrays to identify differentially expressed lncRNAs and mRNAs from five patients with T2D and paired controls. Through bioinformatics analysis, qRT-PCR validation, ELISA, and receiver operating characteristic (ROC) curve analysis of 100 patients with T2D and 100 controls to evaluate the correlation between lncRNAs and T2D, and whether lncRNAs could be used in the diagnosis of T2D patients. RESULTS: We identified 68 and 74 differentially expressed lncRNAs and mRNAs, respectively. The top five upregulated lncRNAs are ENST00000381108.3, ENST00000515544.1, ENST00000539543.1, ENST00000508174.1, and ENST00000564527.1, and the top five downregulated lncRNAs are TCONS_00017539, ENST00000430816.1, ENST00000533203.1, ENST00000609522.1, and ENST00000417079.1. The top five upregulated mRNAs are Q59H50, CYP27A1, DNASE1L3, GRIP2, and lnc-TMEM18-12, and the top five downregulated mRNAs are GSTM4, PODN, GLYATL2, ZNF772, and CLTC. Examination of lncRNA-mRNA interaction pairs indicated that the target gene of lncRNA XR_108954.2 is E2F2. Multiple linear regression analysis showed that XR_108954.2 (r = 0.387, p < 0.01) and E2F2 (r = 0.368, p < 0.01) expression levels were positively correlated with glucose metabolism indicators. Moreover, E2F2 was positively correlated with lipid metabolism indicators (r = 0.333, p < 0.05). The area under the ROC curve was 0.704 (95% CI: 0.578-0.830, p = 0.05) for lncRNA XR_108954.2 and 0.653 (95% CI: 0.516-0.790, p = 0.035) for E2F2. CONCLUSIONS: This transcriptome analysis explored the aberrantly expressed lncRNAs and identified E2F2 and lncRNA XR_108954.2 as potential biomarkers for patients with T2D.

The relationship between polymorphism of insulin-like growth factor I gene and susceptibility to type 2 diabetes in Uygur population, Xinjiang, China.

BACKGROUND: Type 2 diabetes (T2DM) susceptibility varies among different populations and is affected by gene single nucleotide polymorphism (SNP). Insulin-like growth factor (IGF)-1 gene, which has many SNP loci, is involved in T2DM pathogenesis. However, the relationship of IGF-1 gene polymorphism with T2DM in Uyghur population is less studied. OBJECTIVE: To investigate the relationship between T2DM susceptibility and polymorphism of IGF-1 gene in Uyghur population of Xinjiang, China. METHODS: This study enrolled 220 cases (122 males (55.46%) and 98 females (44.54%); mean age of 53.40 ± 10.94 years) of T2DM patients (T2DM group) and 229 (124 males (54.15%) and 105 females (45.85%); mean age of 51.64 ± 10.48 years) healthy controls (control group). Biochemical indexes were determined. IGF-1 gene polymorphism was analyzed by SNP genotyping. RESULTS: The levels of TG, HDL, LDL, BUN, and Cr were statistically significant between the T2DM group and the control group. In terms of IGF-1 polymorphism, T2DM group had higher frequency of AA genotype (OR = 2.40, 95% CI = 1.19-4.84) and allele A (OR = 1.55, 95% CI = 1.17-2.06) of rs35767 loci, suggesting that rs35767 is related to the occurrence of T2DM. A total of 5 gene interaction models was obtained through analyzing the interaction of 5 SNP loci with the GMDR method. Among them, the two-factor model that included rs35767 locus and rs5742694 locus had statistical difference with a large cross-validation consistency (10/10). The combination of GG/CC, GA/AA, AA/AA, and AA/AC genotype was in high-risk group, whereas the combination of GG/AA, GG/AC, GA/AC and GA/CC genotype was in the low-risk group. The risk of T2DM in the high-risk group was 2.165 times than that of the low-risk group (OR = 2.165, 95% CI = 1.478-3.171). CONCLUSION: TG, HDL, LDL, BUN, and Cr are influencing factors of T2DM in Uyghur population. The rs35767 locus of IGF-1 gene may be associated with T2DM in Uyghur population. The high-risk group composing of rs35767 locus and rs5742694 locus has a higher risk of T2DM.

Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China.

OBJECTIVE: A simple type 2 diabetes mellitus (T2DM) screening model was established preciously based on easily available variables for identifying high-risk individuals in western Xinjiang, China. METHODS: A total of 458,153 cases participating in the national health examination were recruited. Logistic regression and the least absolute shrinkage and selection operator (LASSO) models were used for univariate analysis, factors selection, and the establishment of prediction model. Receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test and clinical decision curve (CDA) were applied for evaluating the discrimination, calibration and clinical validity, respectively. The optimal threshold for predicting risk factors for T2DM has been estimated as well. RESULTS: The nomogram depicted the risk of T2DM based on different genders, the factors mainly consisted of age, family history of T2DM (FHOT), waist circumference (WC), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDLc), body mass index (BMI), high-density lipoprotein cholesterol (HDLc), etc. The area under ROC of men and women was 0.864 and 0.816 in the development group, similarly in the validation group, which was 0.865 and 0.815, respectively. The calibration curve showed that the nomogram was accurate for predicting the risk of T2DM, and the CDA proved great clinical application value of the nomogram. Threshold values of the age, WC, TC, TG, HDLc, BMI in different genders were 52.5 years old (men) and 48.5 years old (women), 85.50 cm (men) and 89.9 cm (women), 4.94 mmol/L (men) and 4.94mmol/L (women), 1.26mmol/L (men) and 1.67mmol/L (women), 1.40mmol/L (men) and 1.40mmol/L (women), 24.70kg/m2 (men) and 24.95kg/m2 (women), respectively. CONCLUSION: Our results give a clue that the nomogram may be useful for identifying adults who have high risk for diabetes, which is simple, affordable, with high credibility and can be widely implemented. Further studies are needed to evaluate the utility and feasibility of this model in various settings.

Correlations between FTO Gene Polymorphisms and TSH Level in Uyghur Chinese Patients with Type 2 Diabetes.

OBJECTIVE: The aim of this study was to investigate the correlation between polymorphisms in the FTO gene and TSH level in Uyghur patients with type 2 diabetes in the Xinjiang region. Material and Methods. This cohort was made up of 498 Uyghur patients with type 2 diabetes who underwent genotype screening for rs8050136 and rs9939609 using the Sequenom MassARRAY system. The distribution frequencies of the genotypes and alleles at rs8050136 and rs993960 were compared between two patient groups, those with TSH < 2.5 mU/L and those with TSH ≥ 2.5 mU/L group. We further evaluated the relationships between these different genotypes and FT3, FT4, TSH, FPG, and HbA1c expression. RESULTS: The results suggested the TSH level was 2.281 times higher in rs8050136 CC+CA carriers than in AA genotype (95%CI = 1.024~5.080, P = 0.044) and was 2.417 times higher in rs9939609 TT+TA carriers than in AA genotype (95%CI = 1.257~4.649, P = 0.008) after adjusting for age, sex, and BMI under the recessive model. TSH levels were significantly different between T2DM patients with different FTO genotypes, rs8050136 (P = 0.008) and rs9939609 (P = 0.003), with TSH levels in rs8050136 CC genotype carriers showing a significant increase compared to those in the AA genotype carriers (P = 0.005). Additionally, rs9939609 TT and TA genotype carriers had a significant increase in the TSH level when compared to AA genotype carriers (P = 0.001 and P = 0.031, respectively). The TSH level was also significantly different in these male patients with different genotypes of rs8050136 (P = 0.026) and rs9939609 (P = 0.019). And TSH levels in rs8050136 CC genotype male carriers showing a significant increase compared to those in the AA genotype carriers (P = 0.013) and rs9939609 TT genotype male carriers had a significant increase in TSH level when compared to AA genotype carriers (P = 0.004). CONCLUSION: The polymorphisms at rs8050136 and rs9939609 are associated with changes in the TSH level with rs8050136 CC and rs9939609 TT genotypes identified as potential risk factors for increased TSH levels in these male patients.

A Non-Invasive Prediction Model for Non-Alcoholic Fatty Liver Disease in Adults with Type 2 Diabetes Based on the Population of Northern Urumqi, China.

BACKGROUND: High prevalence of non-alcoholic fatty liver disease (NAFLD) occurs in type 2 diabetes mellitus (T2DM), and about 13% of diabetic patients eventually die of liver cirrhosis or liver cancer. The purpose of our research was to develop a non-invasive predictive model of NAFLD in adults with T2DM. PATIENTS AND METHODS: Adult patients diagnosed with T2DM during physical examination in 2018 in Urumqi were recruited, in total 40,921 cases. We chose questionnaire and physical measurement variables to build a simple, low-cost model. Variables were selected by the least absolute shrinkage and selection operator regression (LASSO). The features chosen by LASSO were used to build the nomogram prediction model of NAFLD. The receiver operating curve (ROC) and calibration were used for model validation. RESULTS: Determinants in the nomogram included age, ethnicity, sex, exercise, smoking, dietary ratio, heart rate, systolic blood pressure (SBP), BMI, waist circumference, and atherosclerotic vascular disease (ASCVD). The area under ROC of developing group and validation group was 0.756 (95% confidence interval 0.750-0.761) and 0.755 (95% confidence interval 0.746-0.763), respectively, and the P values of the two calibration curves were 0.694 and 0.950, suggesting that the nomogram had good disease recognition ability and calibration. CONCLUSION: A nomogram constructed with accuracy can calculate the possibility of NAFLD in adults with T2DM. If validated externally, this tool could be utilized as a non-invasive method to diagnose non-alcoholic fatty liver in adults with T2DM.

Prevalence and Correlation of Metabolic Syndrome: A Cross-Sectional Study of Nearly 10 Million Multi-Ethnic Chinese Adults.

PURPOSE: This study aimed to examine the prevalence and correlates of metabolic syndrome (MetS) in multi-ethnic populations of Northwest China based on Large-scale provincial health checking data. PATIENTS AND METHODS: A total of 9,745,640 Chinese aged ≥18 years in Xinjiang, the largest autonomous region of multi-ethnic in China, were enrolled from Feb. to Sep. 2019. MetS was defined by modified Adult Treatment Panel (ATP III) criteria. RESULTS: The overall prevalence of MetS was 20.85% [Sex: 20.06% female, 21.56% male; Age: 39.22% 60-years and above, 26.32% 40- to 59-years and 9.56% 18- to 39-years; Ethnicity: 28.19% Hui followed by Han (26.39%), Uyghur (18.56%), Other (18.61%), Kazak (17.98%), Mongolian (17.87%), Kyrgyz (14.44%)]. People living in cities and towns (23.03%) or North (24.78%) had higher prevalence of MetS than rural (19.94%) and South (17.66%). Although the prevalence of hypertension, smoking, drinking and lack of physical activity were higher in Kyrgyz, Mongolian and Kazak than those of other ethnic groups, the risk of MetS was lower. CONCLUSION: The results indicated that a high prevalence of MetS in Hui and Han groups and people living in cities and towns. Living in North Xinjiang and elder population tend to have higher prevalence of MetS. The prevention and management of MetS in these populations should be prioritized.

Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas. METHODS: A total of 584,168 adult subjects who have participated in the national physical examination were enrolled in this study. The risk factors for type II diabetes mellitus (T2DM) were identified by p values and odds ratio, using logistic regression (LR) based on variables of physical measurement and a questionnaire. Combined with the risk factors selected by LR, we used a decision tree, a random forest, AdaBoost with a decision tree (AdaBoost), and an extreme gradient boosting decision tree (XGBoost) to identify individuals with T2DM, compared the performance of the four machine learning classifiers, and used the best-performing classifier to output the degree of variables' importance scores of T2DM. RESULTS: The results indicated that XGBoost had the best performance (accuracy = 0.906, precision = 0.910, recall = 0.902, F-1 = 0.906, and AUC = 0.968). The degree of variables' importance scores in XGBoost showed that BMI was the most significant feature, followed by age, waist circumference, systolic pressure, ethnicity, smoking amount, fatty liver, hypertension, physical activity, drinking status, dietary ratio (meat to vegetables), drink amount, smoking status, and diet habit (oil loving). CONCLUSIONS: We proposed a classifier based on LR-XGBoost which used fourteen variables of patients which are easily obtained and noninvasive as predictor variables to identify potential incidents of T2DM. The classifier can accurately screen the risk of diabetes in the early phrase, and the degree of variables' importance scores gives a clue to prevent diabetes occurrence.

Acarbose-metformin is more effective in glycemic variability control than repaglinide-metformin in T2DM patients inadequately controlled with metformin: a retrospective cohort study.

BACKGROUND: Acarbose and repaglinide are widely used either by themselves or in combination with other medications. However, their efficacy in diabetes control has not been compared when used in combination with metformin. METHODS: The present study aimed to compare their effects on glycemic variability (GV) control when taken with metformin for type 2 diabetes mellitus (T2DM) inadequately controlled with metformin alone. In this retrospective cohort study, T2DM patients who were treated with either acarbose-metformin or repaglinide-metformin combination were recruited. Either acarbose 100 mg or repaglinide 2 mg triple daily was taken for the subsequent 12 weeks in combination with metformin. Demographic data, biochemical data and 7-point glycemic self-monitoring conducted with capillary blood (SMBG) data were reviewed after one week and 12 weeks. The primary outcome including glucose control and changes in GV as well as other factors affecting GV and the incidence of hypoglycemia were also analyzed. RESULTS: Of the 305 T2DM patients enrolled, data from 273 subjects, 136 in the acarbose-metformin group (M+A) and 137 in the repaglinide-metformin group (M+R) were analyzed. Both regimens improved glycemic control at 12 weeks post commencement of new medications. GV, expressed as the mean amplitude of plasma glycemic excursions (MAGE, 5.0 ± 2.6 vs. 2.8 ± 1.6 mmol/L, p < 0.001 in M+A; 5.1 ± 2.5 vs. 2.9 ± 1.3 mmol/L, p < 0.001 in M+R), standard deviation of blood glucose (SDBG, 3.6 ± 1.3 vs. 2.0 ± 0.9 mmol/L, p < 0.001 in M+A; 3.7 ± 1.3 vs. 2.4 ± 1.3 p < 0.001 in M+R), coefficient of variation of blood glucose (CVBG, (0.30 ± 0.09 vs. 0.21 ± 0.1, p < 0.001 in M+A; 0.31 ± 0.09 vs. 0.24 ± 0.12, p < 0.001 in M+R), postprandial amplitude of glycemic excursions (PPGE, 5.2 ± 2.6 vs. 2.8 ± 1.6 mmol/L, p < 0.001 in M+A; 5.3 ± 2.5 vs. 2.9 ± 1.3 mmol/L, p < 0.001 in M+R) or largest amplitude of glycemic excursions (LAGE, 9.8 ± 3.6 vs. 5.4 ± 2.4 mmol/L, p < 0.001 in M+A; 10.1 ± 3.4 vs. 6.3 ± 3.2 mmol/L, p < 0.001 in M+R) decreased significantly after the addition of acarbose or repaglinide (p < 0.05 respectively). Compared with repaglinide-metformin, acarbose-metformin was more effective in GV control at 12 weeks post commencement of new medications (p < 0.05). This study indicates that both acarbose-metformin and repaglinide-metformin combinations could effectively reduce GV and the acarbose-metformin combination seems to be more effective than the repaglinide-metformin combination. However, this conclusion should be confirmed by future large-scaled and more comprehensive studies due to the limitations of the present study.

Rho-kinase inhibition by Fasudil promotes tumor maturation and apoptosis in small-cell lung cancer.

Small-cell lung cancer (SCLC) is a poorly differentiated neuroendocrine neoplasm with inadequate therapeutic options. Fasudil is a Rho-associated protein kinase 1 and 2 (ROCK1/2) inhibitor whose clinical indications remain limited in cardiocerebrovascular diseases. This study aimed to report a possible implication of Fasudil for SCLC. The expression and prognostic value of ROCK1/2 were investigated immunohistochemically in surgical specimens. The positive rates of ROCK1 (77/113, 68.1%) and ROCK2 (94/113, 83.2%) were distinctly higher in SCLC than in other lung neuroendocrine tumors. The high expression level of ROCK1 was related to the poor long-term survival of patients, especially in the classic SCLC subtype. In vitro, SCLC cell line treated with Fasudil exhibited synapse-like morphologic change, accompanied by a reduction in the expression levels of c-myc and cyclin D1. Cell cycle arrest was further demonstrated, accompanied by sensitivity to starvation-induced apoptosis, indicating tumor maturation. In addition, RNA-seq identified hundreds of differentially expressed genes involved in the positive regulation of neuron differentiation, stem cell differentiation, cell development, and nervous system development. Finally, Fasudil inhibited SCLC growth, promoted structural maturity, and induced apoptosis in BALB/c nude mice xenograft model. In conclusion, these results indicated a potential and novel application of Fasudil for SCLC treatment.

A simple nomogram score for screening patients with type 2 diabetes to detect those with hypertension: A cross-sectional study based on a large community survey in China.

OBJECTIVES: Compared with unaffected individuals, patients with type 2 diabetes (T2DM) have higher risk of hypertension, and diabetes combined with hypertension can lead to server cardiovascular disease. Therefore, the purpose of this study was to establish a simple nomogram model to identify the determinants of hypertension in patients with T2DM and to quickly calculate the probability of hypertension in individuals with T2DM. MATERIALS AND METHODS: A total of 643,439 subjects participating in the national physical examination has been recruited in this cross-sectional study. After excluding unqualified subjects, 30,507 adults with T2DM were included in the final analysis. 21,355 and 9,152 subjects were randomly assigned to the model developing group and validation group, respectively, with a ratio of 7:3. The potential risk factors used in this study to assess hypertension in patients with T2DM included questionnaire investigation and physical measurement variables. We used the least absolute shrinkage and selection operator models to optimize feature selection, and the multivariable logistic regression analysis was for predicting model. Discrimination and calibration were assessed using the receiver operating curve (ROC) and calibration curve. RESULTS: The results showed that the major determinants of hypertension in patients with T2DM were age, gender, drinking, exercise, smoking, obesity and atherosclerotic vascular disease. The area under ROC curve of developing group and validation group are both 0.814, indicating that the prediction model owns high disease recognition ability. The p values of the two calibration curves are 0.625 and 0.445, suggesting that the nomogram gives good calibration. CONCLUSION: The individualized nomogram model can facilitate improved screening and early identification of patients with hypertension in T2DM. This procedure will be useful in developing regions with high epidemiological risk and poor socioeconomic status just like Urumqi, in Northern China.

A nomogram model for screening the risk of diabetes in a large-scale Chinese population: an observational study from 345,718 participants.

Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and gallbladder disease. The area under ROC was 0.811 for development group and 0.814 for validation group, and the p values of the two calibration curves were 0.053 and 0.438, the improvement of net reclassification and integrated discrimination are significant in our model. Our results give a clue that the screening models we conducted may be useful for identifying Chinses adults at high risk for diabetes. Further studies are needed to evaluate the utility and feasibility of this model in various settings.

Studies on the Inhibitory Effects of Nano-Hydroxyapatite-Loaded As2O3 on Hepatoma Cells.

A stable monodisperse hydroxyapatite (HAP) nanoparticle suspension was prepared by chemical method-assisted ultrasound irradiation. HAP nanoparticles were characterized by atomic force microscopy (AFM) and particle size potentiometry. The effects of HAP nanoparticles on BEL-7402 human hepatocarcinoma cells were studied by MTT colorimetric assay and morphological observation. The mechanism of HAP nanoparticles was studied by analyzing single cell fluorescence element microregion, the change of ultrastructure and cell cycle. The experimental results show that HAP nanoparticles have an obvious inhibitory effect on BEL-7402 human hepatocarcinoma cells in vitro. By entering the cancer cells and blocking the progress of cell cycle, HAP nanoparticles induce the accumulation of cells in G1 phase, which leads to cancer cell swelling and apoptosis.

PPARγ gene Pro12Ala variants reduce the risk of obese individuals to non-alcoholic fatty liver: A study in Uygur Chinese population residing in Northwestern China.

OBJECTIVE: To investigate the association of polymorphisms of Pro12Ala of peroxisome proliferator-activated receptor gamma (PPARγ) gene with clinical and biochemical parameters in Uygur Chinese population with non-alcoholic fatty liver (NAFLD) METHODS: In this case-control study, we recruited 467 NAFLD cases and 524 controls. Examination of abdominal ultrasound, clinical and biochemical profiles, as well as polymerase chain reaction-restriction fragment length polymorphisms of Pro12Ala of PPARγ gene were performed. The association of PPARγ gene Pro12Ala variants with clinical and biochemical parameters was analyzed. RESULTS: There was no statistically significant difference between NAFLD and control groups in the frequencies of genotypic and allele distribution (P>0.05), while significantly difference of genotypic (P=0.032) and allele (P=0.015) distribution was found between NAFLD and control groups in the obese. Using logistics multivariate regression analysis by adjusting age, sex, body mass index, diabetes, hyperuricemia and dyslipidemia, both Pro12Ala and Ala12Ala polymorphisms were not associated with the presence of NAFLD. However, above two polymorphisms were found to be related to NAFLD in obesity group (odds ratio=0.442, P=0.031 and odds ratio=0.039, P=0.010, respectively) CONCLUSION: In Uygur Chinese population, PPARr gene Ala variants reduce the risk of NAFLD in obese individuals.

Estimates of beta cell function adjusted by anthropometric markers in patients with T2DM.

We sought to determine whether adjusting the indices used to assess beta cell function by anthropometric markers of obesity improves their clinical value in a diabetic population. We conducted a cross-sectional survey of 3732 diabetic patients who underwent a 100 g carbohydrate meal test. Insulin secretion was estimated using HOMA-B of steady state as well as △C0-30 /△G0-30 , △AUCc30-120 /△AUCG30-120 and CPIn for dynamic state. Body weight index, waist circumference, waist-hip ratio and body surface area were recorded. The final analysis included 2873 T2DM patients. Correlation analyses showed that there was a poor correlation between diabetic duration and CPI30 (r = -.040, P < .05), and there were no remarkable changes in the correlation coefficient after CPI30 was divided by BMI, WC, WHR, or body surface area, respectively. The same was found for the correlation between HbA1c and CPI120 with these measures. The main determinants of diabetic duration were age (ß = 0.388, P < .001), log HOMA-IR (ß = -0.328, P < .001), CPI30 (ß = -0.045, P = .011). There were no remarkable changes in ß weights between diabetic duration and CPI30 when it was corrected with anthropometric markers in the multiple stepwise linear regression analyses. The same was found between HbA1c and CPI120 . CPI30 and CPI120 are more practical indexes. Correcting the indices used to estimate the beta cell function by anthropometric markers of obesity may not improve their correlations with diabetic duration or HbA1c in a diabetic population.