- 作者列表："Alfaro R","Doty T","Narayanan A","Lugar H","Hershey T","Pepino MY
BACKGROUND:Wolfram syndrome is a rare genetic disease characterized by insulin-dependent diabetes, optic nerve atrophy, sensorineural hearing loss and neurodegeneration. Although olfactory dysfunction, a classical clinical marker of neurodegenerative processes, has been reported in Wolfram syndrome, its use as a clinical marker in Wolfram is limited due to data scarcity. In addition, it is unknown whether Wolfram syndrome affects the sense of taste. METHODS:Smell and taste perception were assessed in participants with Wolfram syndrome (n = 40) who were 15.1 ± 6.0 years of age (range: 5.1-28.7 years) and two sex- and age-matched control groups: one group with type 1 diabetes mellitus (T1D; n = 25) and a healthy control group (HC; n = 29). Smell sensitivity was assessed by measuring n-butanol detection thresholds and smell identification by using the University of Pennsylvania Smell Identification Test (UPSIT). Taste function was assessed using NIH Toolbox, which includes the assessment of sucrose (sweet) taste preference, and perceived intensity of sucrose, sodium chloride (salty), and quinine hydrochloride (bitter) both in the tip of the tongue (regional test) and the whole mouth. RESULTS:Smell sensitivity was not significantly different among groups; however, smell identification was impaired in Wolfram syndrome, as reflected by significantly lower UPSIT scores in Wolfram syndrome compared to HC and T1D (P < 0.001). Compared to participants in the control groups, participants with Wolfram syndrome had a blunted perception of sweetness and saltiness when taste stimuli were applied regionally (P < 0.05), but differences in perceived intensity were no longer significant among groups when taste stimuli were tasted with the whole mouth. Groups preferred similar sucrose concentrations. CONCLUSION:Wolfram syndrome was associated with olfactory dysfunction. However, the olfactory dysfunction was qualitative (related to smell identification) and not secondary to olfactory insensitivity or diabetes, suggesting is arising from dysfunction in central olfactory brain regions. In contrast to olfaction, and despite decreased perception of taste intensity in the anterior tongue, the sense of taste was overall well-conserved in individuals with Wolfram syndrome. Future longitudinal studies of taste and smell perception in Wolfram syndrome will be important to determine the use of the chemical senses as clinical markers of disease progression.
背景: Wolfram 综合征是一种罕见的遗传性疾病，以胰岛素依赖型糖尿病、视神经萎缩、感音神经性聋和神经退行性病变为特征。虽然 Wolfram 综合征报道了嗅觉障碍，一种神经退行性疾病的经典临床标志物，但由于数据稀缺，其作为 Wolfram 临床标志物的使用受到限制。此外，还不知道 Wolfram 综合征是否会影响味觉。 方法: 在年龄为 15.1 ± 6.0 岁 (范围: 5.1-28.7 岁) 的 Wolfram 综合征 (n = 40) 参与者中评估嗅觉和味觉和两个性别和年龄匹配的对照组: 1 组 1 型糖尿病 (T1D; n = 25) 和健康对照组 (HC; n = 29)。通过测量正丁醇检测阈值和使用宾夕法尼亚大学气味鉴定试验 (UPSIT) 进行气味敏感性评估。使用 NIH 工具箱评估味觉功能，包括评估蔗糖 (甜) 味觉偏好，以及蔗糖、氯化钠 (咸) 和盐酸奎宁 (苦) 的感知强度无论是在舌尖 (区域测试) 和整个口。 结果: 各组间嗅觉敏感性无显著差异; 然而，Wolfram 综合征的嗅觉识别受损，表现为 Wolfram 综合征的 UPSIT 评分显著低于 HC 和 T1D (p
METHODS:Aims We aimed to develop a prediction model based on clinical and biochemical variables for gestational diabetes mellitus (GDM) based on the 2013 World Health Organization (WHO) criteria. Methods A total of 1843 women from a Belgian multi-centric prospective cohort study underwent universal screening for GDM. Using multivariable logistic regression analysis, a model to predict GDM was developed based on variables from early pregnancy. The performance of the model was assessed by receiver-operating characteristic (AUC) analysis. To account for over-optimism, an eightfold cross-validation was performed. The accuracy was compared with two validated models (van Leeuwen and Teede). Results A history with a first degree relative with diabetes, a history of smoking before pregnancy, a history of GDM, Asian origin, age, height and BMI were independent predictors for GDM with an AUC of 0.72 [95% confidence interval (CI) 0.69–0.76)]; after cross-validation, the AUC was 0.68 (95% CI 0.64–0.72). Adding biochemical variables, a history of a first degree relative with diabetes, a history of GDM, non-Caucasian origin, age, height, weight, fasting plasma glucose, triglycerides and HbA_1c were independent predictors for GDM, with an AUC of the model of 0.76 (95% CI 0.72–0.79); after cross-validation, the AUC was 0.72 (95% CI 0.66–0.78), compared to an AUC of 0.67 (95% CI 0.63–0.71) using the van Leeuwen model and an AUC of 0.66 (95% CI 0.62–0.70) using the Teede model. Conclusions A model based on easy to use variables in early pregnancy has a moderate accuracy to predict GDM based on the 2013 WHO criteria.
METHODS:Leveraging the availability of nationwide electronic health records from over 500,000 pregnancies in Israel, a machine-learning approach offers an alternative means of predicting gestational diabetes at high accuracy in the early stages of pregnancy. Gestational diabetes mellitus (GDM) poses increased risk of short- and long-term complications for mother and offspring^ 1 – 4 . GDM is typically diagnosed at 24–28 weeks of gestation, but earlier detection is desirable as this may prevent or considerably reduce the risk of adverse pregnancy outcomes^ 5 , 6 . Here we used a machine-learning approach to predict GDM on retrospective data of 588,622 pregnancies in Israel for which comprehensive electronic health records were available. Our models predict GDM with high accuracy even at pregnancy initiation (area under the receiver operating curve (auROC) = 0.85), substantially outperforming a baseline risk score (auROC = 0.68). We validated our results on both a future validation set and a geographical validation set from the most populated city in Israel, Jerusalem, thereby emulating real-world performance. Interrogating our model, we uncovered previously unreported risk factors, including results of previous pregnancy glucose challenge tests. Finally, we devised a simpler model based on just nine questions that a patient could answer, with only a modest reduction in accuracy (auROC = 0.80). Overall, our models may allow early-stage intervention in high-risk women, as well as a cost-effective screening approach that could avoid the need for glucose tolerance tests by identifying low-risk women. Future prospective studies and studies on additional populations are needed to assess the real-world clinical utility of the model.
METHODS::Repurposing of currently approved medications is an attractive option for the development of novel treatment strategies against physiological and infectious diseases. The antidiabetic sulfonylurea glyburide has demonstrated off-target capacity to inhibit activation of the NLRP3 inflammasome in a variety of disease models, including vaginal candidiasis, caused primarily by the fungal pathogen Candida albicans Therefore, we sought to determine which of the currently approved sulfonylurea drugs prevent the release of interleukin 1β (IL-1β), a major inflammasome effector, during C. albicans challenge of the human macrophage-like THP1 cell line. Findings revealed that the second-generation antidiabetics (glyburide, glisoxepide, gliquidone, and glimepiride), which exhibit greater antidiabetic efficacy than prior iterations, demonstrated anti-inflammatory effects with various degrees of potency as determined by calculation of 50% inhibitory concentrations (IC50s). These same compounds were also effective in reducing IL-1β release during noninfectious inflammasome activation (e.g., induced by lipopolysaccharide [LPS] plus ATP), suggesting that their anti-inflammatory activity is not specific to C. albicans challenge. Moreover, treatment with sulfonylurea drugs did not impact C. albicans growth and filamentation or THP1 viability. Finally, the use of ECE1 and Candidalysin deletion mutants, along with isogenic NLRP3-/- cells, demonstrated that both Candidalysin and NLRP3 are required for IL-1β secretion, further confirming that sulfonylureas suppress inflammasome signaling. Moreover, challenge of THP1 cells with synthetic Candidalysin peptide demonstrated that this toxin is sufficient to activate the inflammasome. Treatment with the experimental inflammasome inhibitor MCC950 led to similar blockade of IL-1β release, suggesting that Candidalysin-mediated inflammasome activation can be inhibited independently of potassium efflux. Together, these results demonstrate that the second-generation antidiabetic sulfonylureas retain anti-inflammatory activity and may be considered for repurposing against immunopathological diseases, including vaginal candidiasis.