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Abstract Obesity arises from an imbalance between energy consumption and energy expenditure, and thyroid hormone levels serve as a determinant of energy expenditure. We conducted experiments at the animal and cellular levels and combined those findings with clinical data to elucidate the role of triiodothyronine (T3) in facilitating the browning of white adipose tissue (WAT) and its underlying mechanism. The results showed (i) the impaired metabolic function of local WAT and the compensatory elevation of systemic thermogenesis in obesity; (ii) T3 treatment of white adipocytes in vitro and local WAT in vivo induced a shift towards a morphologically “brown” phenotype, accompanied by upregulation of mRNA and protein expression of browning-related and mitochondrial function markers, which suggest that T3 intervention promotes the browning of WAT; and (iii) the aforementioned processes could be modulated through inhibition of the PI3K/AKT signalling pathway; however, whether T3 affects the PI3K/AKT signalling pathway by affecting insulin signalling remains to be studied and clarified. The results of our study indicate that T3 treatment promotes browning of WAT through inhibition of the PI3K/AKT signalling pathway; these findings offer novel perspectives regarding the potential of localised therapies for addressing WAT volume in individuals with obesity.

ABSTRACT Aims/Introduction Research has suggested that vitamin D deficiency is associated with diabetic retinopathy (DR). Our study aimed to determine whether vitamin D deficiency is the cause of diabetic retinopathy or if diabetic retinopathy reduces vitamin D levels. Materials and Methods Participants with type‐2 diabetes were recruited for this prospective observational clinical study and were divided into a diabetic group without retinopathy and a diabetic group with retinopathy, with additional healthy volunteers serving as a control group. The differences in clinical characteristics among the three groups were also compared. Patients without retinopathy were then followed for 1 year to monitor the incidence of diabetic retinopathy. After follow‐up, participants were divided into subgroups based on whether diabetic retinopathy occurred. The baseline data of the subgroups were compared, and the independent risk factors were analyzed. Results Vitamin D levels were generally low. Participants with diabetic retinopathy had significantly lower vitamin D levels than did those without retinopathy (P

Background: Graves' disease (GD) is a common autoimmune thyroid disorder. The pathogenesis of GD involves an autoimmune response to the A subunit of the human thyrotropin receptor (hTSHR), although the specific mechanisms are not fully elucidated. Methods: This study established a GD model by immunizing BALB/c mice with a recombinant adenovirus expressing the hTSHR A subunit. Spleen tissues were collected and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed peptides (DEPs). Gene Ontology (GO) analysis and KEGG pathway analysis were further utilized to annotate the functions of these DEPs. Additionally, peptide bioactivity prediction and molecular docking studies were conducted using Alphafold and Pymol software, respectively, to assess the binding affinity of specific peptides to the hTSHR A subunit. Results: The GD mouse model was successfully established, and 1,428 DEPs were identified in the spleen, with 368 upregulated and 1,060 downregulated. Functional analysis indicated that these DEPs are mainly involved in cellular endocytosis, regulation of gene expression, and nucleocytoplasmic transport. Notably, molecular docking studies revealed that the abnormally highly expressed peptide HG2A-24aa demonstrated potential bioactivity and strong binding affinity with hTSHR-289aa. Conclusion: The specific bioactive peptides may play key roles in the pathogenesis of GD, particularly HG2A-24aa, which may have a significant role in the MHC II antigen presentation pathway mediated by the hTSHR A subunit.

Background To analyse changes in lipid levels during the development of intrahepatic cholestasis of pregnancy (ICP) and identify new biomarkers for predicting ICP.Methods A retrospective case-control study was conducted to analyse 473 pregnant women who underwent regular prenatal examinations and delivered at the Women and Children’s Hospital, School of Medicine, Xiamen University, between June 2020 and June 2023, including 269 normal pregnancy controls and 204 pregnant women with cholestasis.Results Patients with ICP with gestational diabetes mellitus (GDM) have lower high-density lipoprotein (HDL) levels than in those without GDM. Total bile acid (TBA) levels were significantly higher in pregnant women with GDM than those without. The apolipoprotein A (APOA) level was lower in patients with ICP and hypothyroidism than those without hypothyroidism. TBA levels were significantly higher in pregnant women with hypothyroidism than those without. Triglyceride (TG) levels were significantly higher in patients with preeclampsia (PE) than those without. HDL and APOA levels were lower in women with ICP complicated by preterm delivery than those with normal delivery. The AUC (area under the curve) of the differential diagnosis of cholestasis of pregnancy for the APOA/APOB (apolipoprotein B) ratio was 0.727, with a sensitivity of 85.9% and specificity of 47.5%.Conclusions The results suggested that dyslipidaemia is associated with an increased risk of ICP and its complications. The timely detection of blood lipid and bile acid levels can assist in the diagnosis of ICP and effectively prevent ICP and other complications.

BackgroundT-cell exhaustion (Tex) can be beneficial in autoimmune diseases, but its role in Graves’ disease (GD), an autoimmune disorder of the thyroid, remains unknown. This study investigated Tex-related gene expression in GD patients to discern the potential contributions of these genes to GD pathogenesis and immune regulation.MethodsThrough gene landscape analysis, a protein–protein interaction network of 40 Tex-related genes was constructed. mRNA expression levels were compared between GD patients and healthy control (HCs). Unsupervised clustering categorized GD cases into subtypes, revealing distinctions in gene expression, immune cell infiltration, and immune responses. Weighted gene co-expression network analysis and differential gene expression profiling identified potential therapeutic targets. RT-qPCR validation of candidate gene expression was performed using blood samples from 112 GD patients. Correlations between Tex-related gene expression and clinical indicators were analyzed.ResultsExtensive Tex-related gene interactions were observed, with six genes displaying aberrant expression in GD patients. This was associated with atypical immune cell infiltration and regulation. Cluster analysis delineated two GD subtypes, revealing notable variations in gene expression and immune responses. Screening efforts identified diverse drug candidates for GD treatment. The Tex-related gene CBL was identified for further validation and showed reduced mRNA expression in GD patients, especially in cases of relapse. CBL mRNA expression was significantly lower in patients with moderate-to-severe thyroid enlargement than in those without such enlargement. Additionally, CBL mRNA expression was negatively correlated with the disease-specific indicator thyrotropin receptor antibodies.ConclusionTex-related genes modulate GD pathogenesis, and their grouping aids subtype differentiation and exploration of therapeutic targets. CBL represents a potential marker for GD recurrence.

Abstract Background Glycemic control for patients with diabetes in the surgical department is often unsatisfactory. Compounding this issue is the fact that conventional glucose management models are often inefficient and difficult to monitor over time. Objective To investigate the impact of inpatient glucose team-based management on glycemic control and hospital days in surgical patients with diabetes. Methods A retrospective analysis was conducted on 4156 patients with diabetes in the surgical department who received inpatient management of diabetes at a tertiary medical center from June 2020 to May 2022. Based on whether they received inpatient glucose team-based management, the surgical patients with diabetes were divided into two groups: the inpatient glucose team-based management (GM group, consisting of 1698 participants) and the conventional blood glucose management group (control group, consisting of 2458 participants). We compared the two groups in terms of glycemic control, hospital days, and health-care costs. Multiple logistic regression analysis was performed to build the hospital days prediction model and nomogram. Finally, the performance of the model was evaluated. Results The rate of glucose detection was higher in the GM group at 2 h postprandial (P

Abstract Aims Carbohydrate antigen 199 (CA199) is a standard tumor marker, and recent studies have found elevated in CA199 levels in patients with diabetes. However, there is no systematic measurement and comparison of serum CA199 levels in patients with diabetes and cancer. Here, a detailed description of the changes in serum CA199 levels in patients with type 2 diabetes and various cancers was explored. Methods A total of 5,641 participants were screened for clinical laboratory test results of serum CA199 levels over the past three years (2020–2023). This study included 2,464 healthy controls, 688 patients with type 2 diabetes, and 2,489 patients with 16 different types of cancer. Each type of cancer had more than 30 independent serum CA199 level test results. The serum CA199 levels were compared between cancer groups, type 2 diabetes patients, and healthy controls. Additionally, the CA199 levels of cancer patients were compared with those of patients with type 2 diabetes. Results The serum CA199 levels of esophagus cancer, lung cancer, pancreatic cancer, ovarian cancer, breast cancer, rectum cancer, prostate cancer, bladder cancer, liver cancer, gastric cancer, cervical cancer, colon cancer, lymphoma, thyroid cancer, intracranial tumors, and nasopharyngeal laryngeal cancer were found to be elevated compared to healthy controls (P

Abstract Research suggests that fibrinogen was related to diabetic retinopathy (DR). Then, the relationship between functional indices of fibrinogen and detailed staging of DR has not been explored. Type 2 diabetic and healthy control subjects (n = 960) were recruited in a cross-sectional study. Participants with type 2 diabetes mellitus were categorized into five stages according to their fundus lesions, and fibrinogen (Fib) and its functional indices (angle α and k value) were measured. The angle α levels increased in diabetic subjects with retinopathy compared with those without, and it was significantly elevated early in retinopathy. In contrast, the k value levels slightly decreased. Despite observing an increase in angle α levels and a decrease in k value levels during the later stages of retinopathy compared to the earlier stages, there was no statistically significant difference in the later stages. The association of the angle α and k value with DR was independent of the hyperglycaemic state and other potential confounders (OR = 1.672, 95% CI 1.489–1.876, P

Abstract Background Diabetic peripheral neuropathy (DPN) is a common complication of Type 2 diabetes mellitus (T2DM), which frequently results in disabling neuropathic pain and lower‐limb amputation. The identification of noninvasive biomarkers for DPN may help early detection and individualized treatment of DPN. Methods In this study, we identified differentially expressed genes (DEGs) between DPN and the control based on blood‐source (GSE95849) and tissue‐source gene expression profiles (GSE143979) from the Gene Expression Omnibus (GEO) database using limma, edgeR, and DESeq2 approaches. KEGGG and GO functional enrichments were performed. Hub genes and their correlation with infiltrating immune cells were analyzed. Real‐time quantitative polymerase chain reaction (RT‐qPCR) was used to quantify hub gene expression. Results In total, 144 DEGs between DPN and the control were identified. Functional enrichment revealed that the DEGs were mainly enriched in immune‐related pathways like the Fc epsilon receptor Ig signaling pathway. By protein–protein interaction (PPI) network analysis, FCER1G, SYK, ITGA4, F13A1, MS4A2, and PTK2B were screened as hub genes with higher expression in DPN patients, among which half were immune genes (FCER1G, PTK2B, and SYK). RT‐qPCR demonstrated that mRNA expression of FCER1G, PTK2B, and SYK was significantly increased in patients with DPN compared with both diabetic nonperipheral neuropathy (DNN) and normal subjects. The area under the receiver operating characteristic (ROC) curve of FCER1G, PTK2B, and SYK was 0.84, 0.81, and 0.73, respectively, suggesting their great advantages as diagnostic biomarkers to predict the progression of neuropathy in T2DM. Further analysis indicated that the expression of FCER1G, PTK2B, and SYK was negatively correlated with the cell proportion of significantly altered resting natural killer cells, T follicular helper cells, and activated mast cells, but positively correlated with monocytes. Conclusions Our findings demonstrated FCER1G, PTK2B, and SYK are potential diagnostic biomarkers and therapeutic targets for DPN, which provides new insight into DPN pathogenesis and therapies.

Abstract Background Osteoporosis (OP) is one of the diseases that endanger the health of the elderly population. Klotho protein is a hormone with anti-aging effects. A few studies have discussed the relationship between Klotho and OP. However, there is still a lack of research on larger populations. This study aims to evaluate the association between OP and Klotho in American postmenopausal women. Methods This is a retrospective study. We searched the National Health and Nutrition Examination Survey (NHANES) database and collected data of 3 survey cycles, finally involving 871 postmenopausal women over 50 years old in the present study. All participants took dual-energy X-ray absorptiometry examination and serum Klotho testing at the time of investigation. After adjusting the possible confounding variables, a multivariate regression model was employed to estimate the relationship between OP and Klotho proteins. Besides, the P for trend and restricted cubic spline (RCS) were applied to examine the threshold effect and calculate the inflection point. Results Factors influencing the occurrence of OP included age, ethnicity, body mass index and Klotho levels. Multivariate regression analysis indicated that the serum Klotho concentration was lower in OP patients than that in participants without OP (OR[log2Klotho] = 0.568, P = 0.027). The C-index of the prediction model built was 0.765, indicating good prediction performance. After adjusting the above-mentioned four variables, P values for trend showed significant differences between groups. RCSs revealed that when the Klotho concentration reached 824.09 pg/ml, the risk of OP decreased drastically. Conclusion Based on the analysis of the data collected from the NHANES database, we propose a correlation between Klotho and postmenopausal OP. A higher serum Klotho level is related to a lower incidence of OP. The findings of the present study can provide guidance for research on diagnosis and risk assessment of OP.

Abstract Aims Long noncoding RNAs (lncRNAs) may be associated with the development of type 2 diabetes mellitus and its complications; however, the findings remain controversial. We aimed to synthesize the available data to assess the diagnostic utility of lncRNAs for identification of type 2 diabetes mellitus and its consequences. Materials and Methods We performed a systematic review and meta‐analysis, searching PubMed, Embase, and Web of Science for articles published from September 11, 2015 to December 27, 2022. We evaluated human case–control or cohort studies on differential lncRNA expression in type 2 diabetes mellitus or its associated comorbidities. We excluded studies if they were non‐peer reviewed or published in languages other than English. From 2387 identified studies, we included 17 (4685 participants). Results Analysis of the pooled data showed that lncRNAs had a diagnostic area under the curve (AUC) of 0.84 (95% CI: 0.80–0.87), with a sensitivity of 0.79 (95% CI: 0.74–0.83) and a specificity of 0.75 (95% CI: 0.69–0.80). LncRNAs had an AUC of 0.65 for the diagnosis of prediabetes, with 82% sensitivity and 65% specificity. Conclusions LncRNAs may be promising diagnostic markers for type 2 diabetes mellitus and its complications.

ObjectiveTo screen for predictive obesity factors in overweight populations using an optimal and interpretable machine learning algorithm.MethodsThis cross-sectional study was conducted between June 2011 and January 2012. The participants were randomly selected using a simple random sampling technique. Seven commonly used machine learning methods were employed to construct obesity risk prediction models. A total of 5,236 Chinese participants from Ningde City, Fujian Province, Southeast China, participated in this study. The best model was selected through appropriate verification and validation and suitably explained. Subsequently, a minimal set of significant predictors was identified. The Shapley additive explanation force plot was used to illustrate the model at the individual level.ResultsMachine learning models for predicting obesity have demonstrated strong performance, with CatBoost emerging as the most effective in both model validity and net clinical benefit. Specifically, the CatBoost algorithm yielded the highest scores, registering 0.91 in the training set and an impressive 0.83 in the test set. This was further corroborated by the area under the curve (AUC) metrics, where CatBoost achieved 0.95 for the training set and 0.87 for the test set. In a rigorous five-fold cross-validation, the AUC for the CatBoost model ranged between 0.84 and 0.91, with an average AUC of ROC at 0.87 ± 0.022. Key predictors identified within these models included waist circumference, hip circumference, female gender, and systolic blood pressure.ConclusionCatBoost may be the best machine learning method for prediction. Combining Shapley’s additive explanation and machine learning methods can be effective in identifying disease risk factors for prevention and control.

Abstract Aims/Introduction To compare the application value of different machine learning (ML) algorithms for diabetes risk prediction. Materials and Methods This is a 3‐year retrospective cohort study with a total of 3,687 participants being included in the data analysis. Modeling variable screening and predictive model building were carried out using logistic regression (LR) analysis and 10‐fold cross‐validation, respectively. In total, six different ML algorithms, including random forests, light gradient boosting machine, extreme gradient boosting, adaptive boosting (AdaBoost), multi‐layer perceptrons and gaussian naive bayes were used for model construction. Model performance was mainly evaluated by the area under the receiver operating characteristic curve. The best performing ML model was selected for comparison with the traditional LR model and visualized using Shapley additive explanations. Results A total of eight risk factors most associated with the development of diabetes were identified by univariate and multivariate LR analysis, and they were visualized in the form of a nomogram. Among the six different ML models, the random forests model had the best predictive performance. After 10‐fold cross‐validation, its optimal model has an area under the receiver operating characteristic value of 0.855 (95% confidence interval [CI] 0.823–0.886) in the training set and 0.835 (95% CI 0.779–0.892) in the test set. In the traditional LR model, its area under the receiver operating characteristic value is 0.840 (95% CI 0.814–0.866) in the training set and 0.834 (95% CI 0.785–0.884) in the test set. Conclusions In the real‐world epidemiological research, the combination of traditional variable screening and ML algorithm to construct a diabetes risk prediction model has satisfactory clinical application value.

Abstract Background Research suggests that fibrinogen (Fib) is related to mild cognitive impairment (MCI) and diabetic peripheral neuropathy (DPN) and the risk of MCI in patients with DPN is greatly increased, although no studies have evaluated the predictive value of Fib for the risk of MCI in patients with DPN. Methods This prospective observational clinical study enrolled 207 type 2 diabetes mellitus (T2DM) patients, who were divided into diabetes with no neuropathy (102 cases) and diabetes with neuropathy (105 cases) groups. Meanwhile, 90 healthy unrelated subjects were recruited as controls. The incidence of MCI in the DPN patients was followed up for 2 years. Divide patients in the DPN group into subgroups according to whether MCI occur, use multivariate logistic regression to analyze independent factors of MCIs in DPN patients within 2 years, and use ROC curve to analyze the predictive value of Fib for MCI in DPN patients. Results Fib levels were significantly higher in diabetic subjects with neuropathy compared with those without (P

Background: Graves’ disease is a common autoimmune disease. Cytokines and their signalling pathways play a major part in the pathogenesis of Gr aves’ disease; however, the underlying mechanism needs to be clarified. Aims: The aim of this study was to explore whether circular RNAs par ticipate in the immunological pathology of Graves’ disease via cytokine-related signalling pathways. Methods: Bioinformatics analysis was performed to identify differentially expressed circular RNAs and their targets and associated pathways. A tota l of three patients with Graves’ disease and three sex- and age-matched healthy controls were enrolled for validation with microarray analysis and real-time quantitative PCR (qPCR). An additional 24 patients with Graves’ disease and 24 gender- and age-matched controls were included for validation by real-time fluorescent qPCR. Flow cyto metry and CCK8 assays were used to detect the apoptotic and proliferative levels of J urkat cells (T lymphocytes) with the silenced expression of circRNA. ELISA was performed to detect the growth and apoptosis-related proteins. The competition mechanism of en dogenous RNA was explored by real-time fluorescence qPCR. Results: A total of 366 significantly differentially expressed circular RN As were identified in the Graves’ disease group compared to healthy cont rols. The level of hsa_circ_0090364 was elevated in Graves’ disease patients and p ositively correlated with thyroid-stimulating hormone receptor antibodies. Further analyses suggested that hsa_ circ_0090364 may regulate the JAK-STAT pathway via the hsa-miR- 378a-3p/IL-6ST/IL21R axis to promote cell growth. Conclusions: These results provide novel clues into the pathophysiological m echanisms of Graves’ disease and potential targets for drug treatment.

Keypoints What is already known? Bariatric surgery (BS) in obese individuals has become increasingly popular. BS can result in many complications, including osteoporosis. There are many reasons for this, including malabsorption and hormonal disorders. It is necessary to investigate the association between BS and bone density. What does this study add? BS had a certain impact on many parts of the body, such as the femoral neck, lumbar spine and whole body. The impact of metabolic surgery on bone density becomes more significant in participants aged 40 or older. The impact of BS on bone density becomes greater in the patients with a postsurgical time of greater than 12 months. How might your results change the direction of research or the focus of clinical practice? BS had a certain impact on many parts of the body, particularly in patients over 40 years of age and individuals with a postsurgical time of greater than 12 months. These patients should pay attention to bone density screening and osteoporosis prevention. Further research is needed to analyze the variations over a longer period.

Manipulation of flowering time to develop cultivars with desired maturity dates is fundamental in plant breeding. It is desirable to generate polyploid rapeseed (Brassica napus L.) germplasm with varying flowering time controlled by a few genes. In the present study, BnaSVP, a rapeseed homolog of the Arabidopsis SVP (Short Vegetative Phase) gene, was characterized and a set of mutants was developed using a CRISPR/Cas9-based gene-editing tool. A single construct targeting multiple sites was successfully applied to precisely mutate four copies of BnaSVP. The induced mutations in these copies were stably transmitted to subsequent generations. Homozygous mutants with loss-of-function alleles and free transgenic elements were generated across the four BnaSVP homologs. All mutant T1 lines tested in two environments (summer and winter growing seasons) showed early-flowering phenotypes. The decrease in flowering time was correlated with the number of mutated BnaSVP alleles. The quadruple mutants showed the shortest flowering time, with a mean decrease of 40.6%–50.7% in length relative to the wild type under the two growth conditions. Our study demonstrates the quantitative involvement of BnaSVP copies in the regulation of flowering time and provides valuable resources for rapeseed breeding.

Objective: To establish a rapid, cost-effective, accurate, and acceptable osteoporosis (OP) screening model for the Chinese male population (age ≥ 40 years) based on data mining technology. Materials and methods: This was a 3-year retrospective cohort study, which belonged to the sub-cohort of the Chinese Reaction Study. The research period was from March 2011 to December 2014. A total of 1834 subjects who did not hav e OP at the baseline and completed a 3-year follow-up were included in this study. All subjects underwent quantitative ultrasound examinations for calcaneus at the baseline and follow-ups that lasted for 3 years. We utilized the least absolute shrinkage and selection operator (LASSO) regression model to select feature variables. The chara cteristic variables selected in the LASSO regression were analyzed by multivariable logistic regression (MLR) to construct the predictive model. This predictive model was displayed through a nomogram. We used the receiver operating characteristic (ROC) curve, C-index, calibration curve, and clinical decision curve analysis (DCA) to evaluate model performance and the bootstrapping validation to internally validate the model. Results: The predictive factors included in the prediction model were age, neck circumference, waist-to-height ratio, BMI, triglyceride, impaired fasting glucose, dyslipidemia, osteopenia, smoking history, and strenuous exercise. The area under the ROC (AUC) curve of the risk nomogram was 0.882 (95% CI, 0.8 58–0.907), exhibiting good predictive ability and performance. The C-index for the risk nomogram was 0.882 in the prediction model, which presented good refinement. In add ition, the nomogram calibration curve indicated that the prediction model was consistent. The DCA showed that when the threshold probability was between 1 and 100%, the nomogram had a good clinical application value. More importantly, the internal ly verified C-index of the nomogram was still very high, at 0.870. Conclusions: This novel nomogram can effectively predict the 3-year inciden ce risk of OP in the male population. It also helps clinicians to identify group s at high risk of OP early and formulate personalized intervention measures.

Papillary thyroid carcinoma (PTC) is the most common form of thyroid cancer. Several studies have proposed serum microRNAs (miRNAs) as novel biomarkers for diagnosing PTC. In this study, we conducted a meta-analysis aiming to investigate the overall diagnostic accuracy of serum miRNAs in PTC detection. Three online databases including PubMed, EMBASE and Cochrane Library were searched up to 1 May 2021. We systematically reviewed studies evaluating the value of serum miRNAs in diagnosing PTC, and then summarized the area under receiver operating characteristics curve (AUROC), sensitivity, specificity, and diagnostic odds ratio to assess the accuracy of serum miRNAs for the discrimination between patients with PTC and patients with benign thyroid nodules and healthy controls. We included 32 studies from 6 articles. Overall, there were 463 PTC patients, 334 patients with benign thyroid nodules, and 104 healthy controls. The results showed that the summary sensitivity and specificity were 76% (95% confidence interval [CI]: 68%‒83%) and 86% (95% CI: 80%‒91%), respectively, and that the summary AUROC was 0.89 (95% CI: 0.86‒0.91), when serum miRNAs were used for discriminating between PTC patients and those with benign nodules. On the other hand, the summary sensitivity and specificity of serum miRNAs for discriminating between PTC patients and healthy controls were 82% (95% CI: 77%‒86%) and 84% (95% CI: 76%‒90%), respectively, and the summary AUROC was 0.89 (95% CI: 0.86‒0.92). We found that serum miRNAs have good diagnostic performance for the discrimination between patients with PTC and patients with benign nodules and healthy controls, and thus have considerable potential as novel minimally invasive tools for detecting PTC.

BackgroundDiabetic peripheral neuropathy (DPN) is the most common diabetes-associated complication and imposes a significant burden to healthcare systems. Thus, early diagnosis of DPN is extremely critical for management and outcome of diabetic patients. Supersonic Shear Wave Imaging (SSI) enables the noninvasive measurement of nerve stiffness. However, previous studies on SSI in the diagnosis of DPN were limited in sample sizes and reported various results. In this meta-analysis, we aimed to obtain comprehensive evidence on the value of tibial nerve stiffness measurement by SSI in the diagnosis of DPN.MethodsA comprehensive literature search in English and Chinese electronic database was conducted for studies (published until January 25, 2022) that investigated the diagnostic performance of tibial nerve stiffness measurement by SSI for detecting DPN. Summary receiver operating characteristics (SROC) modelling was constructed to conduct the meta-analysis of diagnostic accuracy of SSI for detecting DPN.ResultsFinally, a total of 12 eligible studies with 1325 subjects were included for evaluation, and a meta-analysis was conducted to evaluate the diagnostic performance of tibial nerve stiffness measurement by SSI for detecting DPN. For tibial nerve stiffness measurement by SSI, the summary sensitivity and specificity for the diagnosis of DPN were 80% (95% confidence interval [CI]: 73%–86%) and 86% (95% CI: 82%–89%), respectively. The summary area under the ROC curve (AUROC) value of the SROC was 0.90 (95% CI: 0.87–0.92), for diagnosing DPN. A subgroup analysis of 11 SSI studies from China revealed similar diagnostic performance, with a summary sensitivity of 79% (95% CI: 72%–85%), specificity of 86% (95% CI: 82%–89%) and summary AUROC value of the SROC of 0.90 (95% CI: 0.87–0.92) for diagnosing DPN.ConclusionsOur meta-analysis suggests that a tibial nerve stiffness measurement by SSI shows good performance in diagnosing DPN and has considerable potential as a noninvasive tool for detecting DPN.

Type 2 diabetes mellitus(T2DM) is regarded as one of the most severe chronic metabolic diseases worldwide, which poses a great threat to human safety and health. The main feature of T2DM is the deterioration of pancreatic beta-cell function. More and more studies have shown that the decline of pancreatic beta-cell function in T2DM can be attributable to beta-cell apoptosis, but the exact mechanisms of beta-cell apoptosis in T2DM are not yet fully clarified. Therefore, in this review, we will focus on the current status and progress of research on the mechanism of pancreatic beta-cell apoptosis in T2DM, to provide new ideas for T2DM treatment strategies.

Graves’ ophthalmopathy (GO), also known as thyroid-associated ophthalmopathy, is a common potentially vision-threatening organ-specific autoimmune disease and the most common extrathyroidal manifestation of Graves’ disease. It can happen to those who have hyperthyroidism or euthyroidism. At present, the pathogenesis of GO has not been fully elucidated, and the majority of clinical treatments are symptomatic. Therefore, we are eager to discover any new therapeutic strategies that target the etiology of GO. To provide fresh ideas for the creation of new therapeutic techniques, this study primarily discusses the research state and progress of GO-related pathogenesis from the perspectives of GO’s cellular immunity, autoantigens, non-coding RNAs, and exosomes.

Human infection with highly pathogenic H5N1 influenza virus causes severe respiratory diseases. Currently, the drugs against H5N1 are limited to virus-targeted inhibitors. However, drug resistance caused by these inhibitors is becoming a serious threat to global public health. An alternative strategy to reduce the resistance risk is to develop antiviral drugs targeting host cell proteins. In this study, we demonstrated that cytochrome c oxidase subunit 4 isoform 1 (COX41) of host cell plays an important role in H5N1 infection. Overexpression of COX41 promoted viral replication, which was inhibited by silencing or knockout the expression of COX41 in the host cell. The ribonucleoproteins (RNPs) of H5N1 were retained in the cell nucleus after knockout cellular COX41. Strikingly, inhibition of cellular COX41 by lycorine, a small-molecule compound isolated from Amaryllidaceae plants, reduced the levels of COX41-induced ROS and phosphorylation of extracellular signal-regulated kinase (ERK) in cells, thus resulting in the blockage of nuclear export of vRNP and inhibition of viral replication. In H5N1-infected mice that were treated with lycorine, we observed a reduction of viral titers and inhibition of pathological changes in the lung and trachea tissues. Importantly, no resistant virus was generated after culturing the virus with the continuous treatment of lycorine. Collectively, these findings suggest that COX41 is a positive regulator of H5N1 replication and might serve as an alternative target for anti-influenza drug development.

BackgroundThis study aimed to establish and verify an effective machine learning (ML) model to predict the prognosis of follicular thyroid cancer (FTC), and compare it with the eighth edition of the American Joint Committee on Cancer (AJCC) model.MethodsKaplan-Meier method and Cox regression model were used to analyze the risk factors of cancer-specific survival (CSS). Propensity-score matching (PSM) was used to adjust the confounding factors of different surgeries. Nine different ML algorithms,including eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Random Forests (RF), Logistic Regression (LR), Adaptive Boosting (AdaBoost), Gaussian Naive Bayes (GaussianNB), K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP),were used to build prognostic models of FTC.10-fold cross-validation and SHapley Additive exPlanations were used to train and visualize the optimal ML model.The AJCC model was built by multivariate Cox regression and visualized through nomogram. The performance of the XGBoost model and AJCC model was mainly assessed using the area under the receiver operating characteristic (AUROC).ResultsMultivariate Cox regression showed that age, surgical methods, marital status, T classification, N classification and M classification were independent risk factors of CSS. Among different surgeries, the prognosis of one-sided thyroid lobectomy plus isthmectomy (LO plus IO) was the best, followed by total thyroidectomy (hazard ratios: One-sided thyroid LO plus IO, 0.086[95% confidence interval (CI),0.025-0.290], P

BackgroundThe ongoing coronavirus disease 2019 (COVID-19) pandemic has forced the development of vaccines. Reports have suggested that vaccines play a role in inducing autoimmune diseases (AIDs). Scattered cases have reported that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines may promote thyroid disease, including Graves’ disease (GD). However, the effect of inactivated SARS-CoV-2 vaccine on GD remains unclear. The aim of the present study was to investigate the response of thyrotropin receptor antibody (TRAB) to inactivated SARS-COV-2 vaccines.MethodsWe conducted a retrospective study to observe the differences in thyroid function and TRAB trends between pre-vaccination (n=412) and post-vaccination (n=231) groups at an interval of 2 months. We then retrospectively observed the differences in serum thyroid function and TRAB levels at 3 months before (n=280), 1 month before (n=294), 1 month after (n=306), and 3 months after (n=250) vaccination. Subsequently, 173 GD patients who were not vaccinated with inactivated SARS-COV-2 vaccines were selected for a prospective study. Thyroid function and TRAB assessment were performed before 3 and 1 months and 1 and 3 months after the first dose of vaccination and were then compared by repeated measures ANOVA to explore their dynamic changes.ResultsA retrospective study preliminarily observed that the trend of TRAB post-vaccination was opposite of that pre-vaccination (p=0.000), serum TRAB levels decreased before vaccination and increased after vaccination. In this prospective study, repeated measures ANOVA indicated significant differences in serum FT3 (p=0.000), FT4 (p=0.000), TSH (p=0.000), and TRAB (p=0.000) levels at different time points before and after vaccination. Serum TRAB levels showed dynamic changes that decreased significantly at 1 month before vaccination (p=0.000), no significant differences at 1 month after vaccination (p=0.583), and reflected an upward trend at 3 months after vaccination (p=0.034). Serum FT3 and FT4 levels showed similar trends to serum TRAB levels before and after vaccination. Instead, the serum TSH levels showed a continuous upward trend over time.ConclusionBased on the results obtained in both retrospective and prospective studies, we concluded that serum TRAB levels decreased less after inactivated SARS-CoV-2 vaccination and showed an upward trend, which may be related to humoral immunity induced by vaccination.

Abstract Aims/Introduction The incidence of type 2 diabetes mellitus is increasing worldwide, and it might partly cause metabolic disorder and type 2 diabetes mellitus susceptibility in patients’ offspring through epigenetic modification. However, the underlying mechanisms remain largely unclear. Recent studies have shown a potential link between deoxyribonucleic acid methylation in paternal sperm and susceptibility to type 2 diabetes mellitus in offspring, so this article focuses on whether the whole‐genome methylation profiles of spermatozoa in type 2 diabetes mellitus patients have changed. Materials and Methods We investigated the genome‐wide deoxyribonucleic acid methylation profiles in spermatozoa by comparing eight individuals with type 2 diabetes mellitus and nine non‐diabetic controls using whole‐genome bisulfite sequencing method. Results First, we found that the proportion of methylated cytosine in the whole genome of the type 2 diabetes mellitus group was slightly lower than that of the control group. Interestingly, the proportion of methylated cytosines in the CG context decreased, and the proportion of methylated cytosines in the CHG context (H = A, T or C) increased in the type 2 diabetes mellitus group, but the proportion of methylated cytosines in the CHH context (H = A, T or C) barely changed. The methylated cytosines in the CG context were mainly distributed at the high methylated level, whereas methylated cytosines in the CHG context and methylated cytosines in the CHH context were mainly distributed at the low and middle methylated level in both groups. Second, functional enrichment analysis showed that differentially methylated genes played a significant role in nervous system development and cell metabolism. Finally, we identified 10 top type 2 diabetes mellitus‐related differentially methylated genes, including IRS1, PRKCE, FTO, PPARGC1A, KCNQ1, ATP10A, GHR, CREB1, PRKAR1A and HNF1B. Conclusions Our study provides the first evidence for deoxyribonucleic acid methylation reprogramming in spermatozoa of type 2 diabetes mellitus patients, and provides a new basis for explaining the complex mechanism of type 2 diabetes mellitus susceptibility in offspring.

ObjectiveMicroalbuminuria (MAU) occurs due to universal endothelial damage, which is strongly associated with kidney disease, stroke, myocardial infarction, and coronary artery disease. Screening patients at high risk for MAU may aid in the early identification of individuals with an increased risk of cardiovascular events and mortality. Hence, the present study aimed to establish a risk model for MAU by applying machine learning algorithms.MethodsThis cross-sectional study included 3,294 participants ranging in age from 16 to 93 years. R software was used to analyze missing values and to perform multiple imputation. The observed population was divided into a training set and a validation set according to a ratio of 7:3. The first risk model was constructed using the prepared data, following which variables with P

Organosulfur natural products (NPs) refer to the different kinds of small molecular-containing sulfur (S) elements. Sulfur-containing NPs tightly link to the biochemical processes and play an important role in the pharmaceutical industry. The majority of S-containing NPs are generally isolated from Alliaceae plants or bacteria, and those from fungi are still relatively rare. In recent years, an increasing number of S-containing metabolites have been discovered in marine and terrestrial fungi, but there is no comprehensive and targeted review to summarize the studies. In order to make it more straightforward to better grasp the fungal-derived S-containing NPs and understand the particularity of marine S-containing NPs compared to those from terrestrial fungi, we summarized the chemical structures and biological activities of 89 new fungal-derived S-containing metabolites from 1929 when the penicillin was discovered to the present in this current review. The structural and bioactive diversity of these S-containing metabolites were concluded in detail, and the preliminary mechanism for C-S bond formation in fungi was also discussed briefly.

Circular RNAs (circRNAs) participate in the development of various kinds of diseases. However, the function and roles of circRNAs in obstructive sleep apnea (OSA)-induced cardiovascular disease remain poorly understood. Therefore, we sought to explore the circRNA expression profiles and predict their functions in OSA-induced cardiac injury with the use of bioinformatics analysis. The model of OSA was established in mouse treated by chronic intermittent hypoxia (CIH) exposure. Then, we screened the circRNA profile using circRNA microarray. By comparing circRNA expression in three matched pairs of CIH-treated cardiac tissues and controls, differentially expressed circRNAs were identified in the CIH groups. Comparison of the selected circRNAs expression levels was performed between qRT-PCR and microarray. Meanwhile, we employed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to predict the functions of these selected circRNAs. Finally, we constructed a circRNA-miRNA-mRNA network based on the target prediction. It was found that a total of 124 circRNAs were differentially expressed in CIH-treated cardiac tissues (p ≤ 0.05, fold-change ≥ 1.5). Among them, 23 circRNAs were significantly down-regulated, and the other 101 were up-regulated. Then, ten circRNAs were randomly selected to validate the reliability of the microarray results by using qRT-PCR. Next, we conducted the GO and KEGG pathway analysis to explore the parental genes functions of differentially expressed circRNA. Finally, two significantly differentially expressed circRNAs (mmu_circRNA_014309 and mmu_circRNA_21856) were further selected to create a circRNA-miRNA-mRNA regulation network. Our study did first reveal that the differentially expressed circRNAs played a vital role in the pathogenesis of OSA-induced cardiac damage. Thus, our findings bring us closer to unraveling the pathophysiologic mechanisms and eliciting novel therapeutic targets for the treatment of OSA-associated cardiovascular diseases.

Background: Mechanically ventilated patients in the intensive care unit (ICU) have high mortality rates. There are multiple prediction scores, such as the Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), and Sequential Organ Failure Assessment (SOFA), widely used in the general ICU population. We aimed to establish prediction scores on mechanically ventilated patients with the combination of these disease severity scores and other features available on the first day of admission.Methods: A retrospective administrative database study from the Medical Information Mart for Intensive Care (MIMIC-III) database was conducted. The exposures of interest consisted of the demographics, pre-ICU comorbidity, ICU diagnosis, disease severity scores, vital signs, and laboratory test results on the first day of ICU admission. Hospital mortality was used as the outcome. We used the machine learning methods of k-nearest neighbors (KNN), logistic regression, bagging, decision tree, random forest, Extreme Gradient Boosting (XGBoost), and neural network for model establishment. A sample of 70% of the cohort was used for the training set; the remaining 30% was applied for testing. Areas under the receiver operating characteristic curves (AUCs) and calibration plots would be constructed for the evaluation and comparison of the models' performance. The significance of the risk factors was identified through models and the top factors were reported.Results: A total of 28,530 subjects were enrolled through the screening of the MIMIC-III database. After data preprocessing, 25,659 adult patients with 66 predictors were included in the model analyses. With the training set, the models of KNN, logistic regression, decision tree, random forest, neural network, bagging, and XGBoost were established and the testing set obtained AUCs of 0.806, 0.818, 0.743, 0.819, 0.780, 0.803, and 0.821, respectively. The calibration curves of all the models, except for the neural network, performed well. The XGBoost model performed best among the seven models. The top five predictors were age, respiratory dysfunction, SAPS II score, maximum hemoglobin, and minimum lactate.Conclusion: The current study indicates that models with the risk of factors on the first day could be successfully established for predicting mortality in ventilated patients. The XGBoost model performs best among the seven machine learning models.

Background: Depression is prevalent in patients with all stages of CKD and is associated with adverse outcome. Abnormally elevated GFR, or hyperfiltration, may play a crucial role in the initiation and progression of CKD. However, the association between depression and hyperfiltration is not known. The aim of this study is to investigate the relationship between depression and hyperfiltration. Methods: This was an observational cross-sectional study. A total of 3,716 volunteers (1,303 males and 2,413 females) aged 40–75 years without CKD from a community in China were included for the study. Depressive symptoms and the presence of a minor or major depressive episode were assessed with the 9-item Patient Health Questionnaire (PHQ-9) and Diagnostic and Statistical Manual of Mental Disorders (4th edition)-based structured interview, respectively. Results: The mean age of the participants in the present study was 53.8 ± 9.0 years. 115 participants had clinically relevant depression, and 122 participants had a minor or major depressive episode. In a multivariable logistic regression analysis adjusted for potential confounders, the association between clinically relevant depression and renal hyperfiltration remained significant in men but not in women. As compared with men without depression (PHQ

Abstract Background Thyroid dysfunction is one of the prevalent endocrine disorders. The relationship between lifestyle factors and thyroid dysfunction was not clear and some of the factors seemed paradoxical. Methods We conducted this population-based study using data from 5154 She ethnic minority people who had entered into the epidemic survey of diabetes between July 2007 to September 2009. Life style information was collected using a standard questionnaire. Body mass index (BMI), Blood pressure and serum TSH, TPOAb, triglycerides (TG), total cholesterol (TC) and high–density lipoprotein cholesterol (HDL) were collected. Results The study showed that people who drank, had higher education or suffered from insomnia have lower incidence of hyperthyroidism. On the other hand, smoking, alcohol consumption, exercise, undergoing weight watch and chronic headache were associated with decreased incidence of hypothyroidism. Using multivariable logistic regression analysis, we found that alcohol consumption was associated with decreased probability of hyperthyroidism, hypothyroidism, as well as positive TPOAb. The amounts of cigarettes smoked daily displayed a positive correlation with hyperthyroidism among smokers. Accordingly, smoking seemed to be associated with decreased risk for hypothyroidism and positive TPOAb. Exercise and maintaining a healthy weight might have a beneficial effect on thyroid health. Interestingly, daily staple amount showed an inverse correlation with incidence of positive TPOAb. Conclusions Within the Chinese She ethnic minority, we found associations between different lifestyle factors and the incidence of different thyroid diseases. Understanding the nature of these associations requires further investigations.

Abstract Background Catecholamines are commonly used in septic shock but face limitations of their hypo-responsiveness and adverse events due to high dose. Terlipressin is a synthetic vasopressin analog with greater selectivity for the V1-receptor. A meta-analysis was conducted to evaluate the efficacy and safety of terlipressin in septic shock. Methods We searched for relevant studies in PubMed, Embase, and the Cochrane database from inception up to July 15, 2018. Randomized controlled trials (RCTs) were included if they reported data on any of the predefined outcomes in patients with septic shock and managed with terlipressin or any catecholamines. Results were expressed as risk ratio (RR) or mean difference (MD) with accompanying 95% confidence interval (CI). Heterogeneity, subgroup analysis, sensitivity analysis, and publication bias were explored. Results Ten studies with 928 patients were included. Despite the shorter duration of mechanical ventilation, use of terlipressin did not reduce the risk of mortality (RR = 0.94; 95% CI, 0.85 to 1.05; I 2 = 0%; P = 0.28) when compared with control. This finding was confirmed by further subgroup and sensitivity analyses. In addition, lactate clearance, length of stay in ICU or hospital, total adverse events, digital ischemia, and arrhythmia were also similar between groups, while terlipressin was associated with shorter duration of mechanical ventilation and less norepinephrine requirements. Conclusions Current results suggest terlipressin did not show added survival benefit in septic shock therapy when compared with catecholamines.

Background: Delirium is a commonly found comorbidity in hospitalized patients and is associated with adverse outcomes. Melatonin is an endogenous hormone that exerts multiple biological effects, mainly in regulating diurnal rhythms and in inflammatory process and immune responses. We aimed to assess the efficacy of exogenous melatonergics in the prevention of delirium.Methods: We conducted a search to identify relevant randomized controlled studies (RCTs) in PubMed, Cochrane Library, and EMBASE databases that had been published up to December 2019. Hospitalized adult patients administered melatonergics were included. The primary outcome measure was the incidence of delirium. The secondary outcome measure was the length of stay in intensive care unit (ICU-LOS). The pooled effects were analyzed as the risk ratio (RR) for delirium incidence, weighted mean difference (WMD) for ICU-LOS, and 95% confidence intervals (CIs).Results: Nine RCTs with 1,210 patients were included. The forest plots showed that melatonergics were associated with a decreasing incidence of delirium (RR, 0.51; 95% CI, 0.30–0.85; I2 = 70%; p = 0.01). There was no significant difference in ICU-LOS (WMD, −0.08; 95% CI, −0.19–0.03; I2 = 0; p = 0.17).Conclusion: Administration of exogenous melatonergics to hospitalized patients seems to be associated with a decreasing incidence of delirium.PROSPERO registration number: CRD42019138863.

Hyperthyroidism can cause glucose metabolism disorders and insulin resistance. Insulin resistance in muscle and adipose tissues has been extensively studied, whereas investigations on β-cell insulin resistance are limited. This study preliminarily explored the effects of high T3 levels on β-cell line (MIN6) insulin resistance, as well as the roles of endoplasmic reticulum stress (ERS). In this study, we treated β-cell line with T3, with or without an inhibitor of phosphotyrosine phosphatases (PTPs, sodium vanadate) or ERS inhibitor (4-PBA). The results indicated that high levels of T3 significantly inhibited insulin secretion in β-cell line. In addition, we observed an upregulation of p-IRS-1ser307 and downregulation of Akt. These results can be corrected by sodium vanadate. Moreover, high T3 levels upregulate the ERS-related proteins PERK, IRE1, ATF6, and GRP78, as well as ERS-related apoptosis CHOP and caspase-12. Similarly, this change can be corrected by 4-PBA. These results suggest that high T3 levels can induce insulin resistance in β-cell line by activating ERS and the apoptotic pathway.

Objective. It has been testified that iodine regulates thyroid function by controlling thyroid-restricted genes expression and is closely related to diffuse goiter and thyroid dysfunction. However, the effects of follicular lumen iodine, the main form of iodine reserve in the body, on thyroid-restricted genes in nodular goiter are poorly understood. In this study, correlations between follicular lumen iodine and the expressions of thyroid stimulating hormone receptor (TSHR), its transcription factors TTF-1, and PAX8 in nodular goiter were investigated. Patients. In this study, 30 resection specimens clinically histopathologically confirmed to have nodular goiter and 30 normal thyroid specimens from adjacent tissues of nodular goiter are used. Measurement. Western blot immunohistochemistry was performed to assay TSHR, TTF-1, and PAX8 in thyrocytes of nodular goiter as well as in extranodular normal thyroid tissues. Meanwhile, follicular lumen iodine of both nodular goiter and extranodular normal thyroid tissues was detected as well. Results. The TSHR, TTF-1, and PAX8 in nodular goiter were significantly higher than those in the controls. The iodine content in nodular goiter was significantly lower than those in control tissues. Conclusion. Upregulation of TSHR, TTF-1, and PAX8 is associated with low follicular lumen iodine content in nodular goiter.

OBJECTIVE: To compare important outcomes between early tracheostomy (ET) and late tracheostomy (LT) or prolonged intubation (PI) for critically ill patients receiving long-term ventilation during their treatment. METHOD: We performed computerized searches for relevant articles on PubMed, EMBASE, and the Cochrane register of controlled trials (up to July 2013). We contacted international experts and manufacturers. We included in the study randomized controlled trials (RCTs) that compared ET (performed within 10 days after initiation of laryngeal intubation) and LT (after 10 days of laryngeal intubation) or PI in critically ill adult patients admitted to intensive care units (ICUs). Two investigators evaluated the articles; divergent opinions were resolved by consensus. RESULTS: A meta-analysis was evaluated from nine randomized clinical trials with 2,072 participants. Compared to LT/PI, ET did not significantly reduce short-term mortality [relative risks (RR) = 0.91; 95% confidence intervals (CIs) = 0.81-1.03; p = 0.14] or long-term mortality (RR = 0.90; 95% CI = 0.76-1.08; p = 0.27). Additionally, ET was not associated with a markedly reduced length of ICU stay [weighted mean difference (WMD) = -4.41 days; 95% CI = -13.44-4.63 days; p = 0.34], ventilator-associated pneumonia (VAP) (RR = 0.88; 95% CI = 0.71-1.10; p = 0.27) or duration of mechanical ventilation (MV) (WMD = - 2.91 days; 95% CI = -7.21-1.40 days; p = 0.19). CONCLUSION: Among the patients requiring prolonged MV, ET showed no significant difference in clinical outcomes compared to that of the LT/PI group. But more rigorously designed and adequately powered RCTs are required to confirm it in future.

OBJECTIVE: To explore the associations of green tea and rock tea consumption with risk of impaired fasting glucose (IFG) and impaired glucose tolerance (IGT). METHODS: A multistage, stratified, cluster, random-sampling method was used to select a representative sample from Fujian Province in China. In total, 4808 subjects without cardiovascular disease, hypertension, cancer, or pancreatic, liver, kidney, or gastrointestinal diseases were enrolled in the study. A standard questionnaire was used to gather data on tea (green, rock, and black) consumption and other relevant factors. The assessment of impaired glucose regulation (IGR) was using 75-g oral glucose tolerance test (OGTT), the diagnostic criteria of normal glucose tolerance was according to American Diabetes Association. RESULTS: Green tea consumption was associated with a lower risk of IFG, while rock tea consumption was associated with a lower risk of IGT. The adjusted odds ratios for IFG for green tea consumption of 30 cups per week were 1.0 (reference), 0.42 (95% confidence intervals (CI) 0.27-0.65), 0.23 (95% CI, 0.12-0.46), and 0.41 (95% CI, 0.17-0.93), respectively. The adjusted odds ratios for IGT for rock tea consumption of 30 cups per week were 1.0 (reference), 0.69 (95% CI, 0.48-0.98), 0.59 (95% CI, 0.39-0.90), and 0.64 (95% CI, 0.43-0.97), respectively. A U-shaped association was observed, subjects who consumed 16-30 cups of green or rock tea per week having the lowest odds ratios for IFG or IGT. CONCLUSIONS: Consumption of green or rock tea may protect against the development of type 2 diabetes mellitus in Chinese men and women, particularly in those who drink 16-30 cups per week.