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Fish are good for your health in more ways than you may expect. For one, eating fish is a common dietary recommendation for a healthy diet. However, fish have much more to provide than omega‐3 fatty acids to your circulatory system. Some fish species now serve as important and innovative model systems for diabetes research, providing novel and unique advantages compared with classical research models. Not surprisingly, the largest share of diabetes research in fish occurs in the laboratory workhorse among fish, the zebrafish (Danio rerio). Established as a genetic model system to study development, these small cyprinid fish have eventually conquered almost every scientific discipline and, over the past decade, have emerged as an important model system for metabolic diseases, including diabetes mellitus. In this review we highlight the practicability of using zebrafish to study diabetes and hyperglycemia, and summarize some of the recent research and breakthroughs made using this model. Equally exciting is the appearance of another emerging discipline, one that is taking advantage of evolution by studying cases of naturally occurring insulin resistance in fish species. We briefly discuss two such models in this review, namely the rainbow trout (Oncorhynchus mykiss) and the cavefish (Astyanax mexicanus). HighlightsDifferent fish species are becoming increasingly attractive as models for the study of hyperglycemia and diabetes due to the ease of generating and maintaining large numbers of animals.Some fish species exhibit unique physiological and evolutionary features that could be used to gain further insights into vertebrate glucose homeostasis and dysregulation. [ABSTRACT FROM AUTHOR]

Background Saudi Arabia is a community thrilled by sudden social and economical changes, leading to a sharp increase in the prevalence of abnormal glucose metabolism. Age-specific diabetes and impaired fasting glucose prevalence is the focus of this study with the expected risk factors. Methods A nationwide, household, randomized, population based cohort of 18 034 participants aged ≥30 years was selected to test for abnormal glucose metabolism using fasting plasma glucose ( FPG) according to American Diabetes Association ( ADA) criteria. Results The prevalence of diabetes was 25.4% with 40.3% being unaware of their disease, while impaired fasting glucose ( IFG) affected 25.5% of the total sample. IFG to diabetes ratio was one in this study, decreasing with age and increasing with body weight. Age ≥45 years, hypertension, history of gestational diabetes mellitus ( GDM), and high triglycerides are the strongest risk factors in diabetic patients, while history of GDM, dyslipidemia, obesity, and high triglycerides are the most significant risk factors in IFG participants. Conclusions Abnormal glucose metabolism has reached an epidemic level in this society, where half of adults and older are affected. Risk factors are behind this epidemic and the quick shift from IFG to diabetes in this society. [ABSTRACT FROM AUTHOR]

Background The sensitivity of HbA1c is not optimal for the screening of patients with latent diabetes. We hypothesize that simple healthcare information could improve accuracy. Methods We retrospectively analyzed data, including HbA1c, from multiple years from the National Health and Nutrition Examination Survey ( NHANES) database (2005-2010). The data were used to create a logistic regression classification model for screening purposes. Results The study evaluated data for 5381 participants, including 404 with undiagnosed diabetes. The HbA1c screening data were supplemented with information about age, waist circumference, and physical activity in the HbA1c+ model. Alone, HbA1c alone had a receiver operating characteristics ( ROC) curve for the area under the curve ( AUC) of 0.808 (95% confidence interval [ CI] 0.792-0.834). The HbA1c+ model had an ROC AUC of 0.851 (95% CI 0.843-0.872). There was a significant difference in the AUC between our model and using HbA1c without supplementary information ( P < 0.05). Conclusions We have developed a novel screening model that could help improve screening for type 2 diabetes with HbA1c. It seems beneficial to systematically add additional patient healthcare information in the process of screening with HbA1c. [ABSTRACT FROM AUTHOR]

Background Syphilis, a sexually transmitted disease, is commonly referred to as the 'great imitator' because of its wide-ranging clinical presentations. Recently, we noticed that patients with neurosyphilis ( NS) seemed to be more susceptible to complications of diabetes mellitus ( DM). This is an interesting phenomenon, but it also puzzles clinicians because of scant knowledge about this situation. Methods A case-control study was conducted to explore the association between NS and DM. Clinical data and the prevalence of DM among NS patients, patients with syphilis but not NS (syphilis/non- NS), non-syphilis patients, and healthy controls were analyzed. In addition, we explored the time of occurrence of NS and DM. Results Fasting plasma glucose and HbA1c levels in NS patients were significantly higher than in syphilis/non- NS patients, non-syphilis patients, and healthy controls ( P < 0.05). In all, 45 of 149 NS patients (30.2%) were diagnosed with DM. The prevalence of DM in NS patients was significantly higher than in the other three groups ( P < 0.05). There was no relationship between the prevalence of DM and the type of NS (e.g. asymptomatic NS, syphilitic meningitis, meningovascular NS, general paresis, and tabes dosalis). In the study population, 57.8% of NS patients were diagnosed with DM at the same time, whereas 80.0% were diagnosed with DM within 5 years of their diagnosis of NS. Conclusions Based on the results of the present study, DM is not merely an occasional chance occurrence in NS patients. There is an association between NS and DM. [ABSTRACT FROM AUTHOR]