UNASSIGNED: This study aims to elucidate the association between glycemia and the occurrence of multi-vessel lesions in participants undergoing coronary angiography.
UNASSIGNED: We analyzed 2,533 patients with coronary artery disease who underwent coronary angiography. Of these, 1,973 patients, identified by the endpoint of multi-vessel lesions, were examined using univariate and multivariate logistic regression analyses to determine the relationship between glycemia levels and multi-vessel lesion occurrence.
UNASSIGNED: The analysis included 1,973 participants, among whom 474 patients were identified with coronary multi-vessel lesions. Univariate logistic regression analysis demonstrated a positive correlation between glycemia and the occurrence of coronary multi-vessel lesions (OR 1.04; 95% CI 1.01-1.08; p = 0.02). The adjusted model indicated that for each unit increase in glycemia, the risk of developing coronary multi-vessel lesions increased by 4%, showing a significant correlation (p < 0.05). Subgroup analyses revealed that the impact of glycemia on multi-vessel lesions in patients with PCI varied according to gender, age, and smoking status, with the effect being more pronounced in men, older patients, and smokers.
UNASSIGNED: Our findings establish a significant association between glycemia and the incidence of multi-vessel lesions, particularly pronounced in male patients, individuals over 45, and smokers.

Human adenovirus-36 (HAdV-36) infection has been linked to obesity, low lipid levels, and improvements in blood glucose levels and insulin sensitivity in animal models and humans, although epidemiological studies remain controversial. Therefore, this study investigated the relationship between HAdV-36 seropositivity and glycemic control in youths. This observational study examined 460 youths (246 with normal weight and 214 obese subjects). All participants underwent assessments for anthropometry, blood pressure, circulating fasting levels of glucose, lipids, insulin, and anti-HAdV-36 antibodies; additionally, the homeostatic model assessment of insulin resistance (HOMA-IR) was calculated. In all, 57.17% of the subjects were HAdV-36 seropositive. Moreover, HAdV-36 seroprevalence was higher in obese subjects compared to their normal weight counterparts (59% vs. 55%). BMI (33.1 vs. 32.3 kg/m2, p = 0.03), and waist circumference (107 vs. 104 cm, p = 0.02), insulin levels (21 vs. 16.3 µU/mL, p = 0.003), and HOMA-IR (4.6 vs. 3.9, p = 0.02) were higher in HAdV-36-positive subjects with obesity compared to seronegative subjects. In the obese group, HAdV-36 seropositivity was associated with a reducing effect in blood glucose levels in a model adjusted for total cholesterol, triglyceride levels, age and sex (β = -10.44, p = 0.014). Furthermore, a statistically significant positive relationship was observed between HAdV-36 seropositivity and insulin levels in the obesity group. These findings suggest that natural HAdV-36 infection improves glycemic control but does not ameliorate hyperinsulinemia in obese subjects.

Aim: This study evaluated the levels of anti-insulin antibodies (AIAs) and the influence of some antidiabetic medications on AIA in diabetes mellitus (DM) patients with retinopathy. Patient & methods: An observational cross-sectional study. Results: A lower titer of AIA IgG was observed in the diabetic retinopathy (DR) and DM-only study categories compared with the control group [DR = 86 (5-560), DM-only = 50 (5-500), versus control = 200 (7-565); p = 0.017]. Taking nifedipine and metformin were negatively correlated (r = -0.32, p = 0.04) with the levels of AIA IgE in the DR group. Conclusion: A decreased titer of circulating AIAs was observed in the DR study category, suggesting that AIA may not contribute to the pathogenesis of DR.
Diabetic retinopathy (DR) is the main reason people lose their sight in countries with few resources. Anti-insulin antibodies, or AIAs, help the body fight off infections and may play a role in the development of DR. The study looked at how much AIA was in DR patients and how some diabetes drugs affected AIA levels. There was a negative link between nifedipine and one AIA (IgE) in people with DR, but a positive link between metformin and another AIA (IgG). AIA levels were lower in the DR study group, which suggests that AIA may not cause DR.

Smallanthus sonchifolius, popularly known as yacon, is a member of the Asteraceae family. Due to its medicinal and edible value, yacon is consumed by different populations. Yacon is unique due to its high fructo-oligosaccharide and inulin content, as well as flavonoids, sesquiterpene lactones, and phenolic acids. Roots can be used to produce flour, which is less perishable and can be applied in various industrial products. This systematic review focuses on the effects of yacon flour on metabolic parameters. PubMed, Cochrane, Embase, Science Direct, Scopus, Web of Science, and Google Scholar databases were consulted, and PRISMA guidelines were followed in the selection of the studies. In total, 526 articles were found in the databases, and of these, only 28 full texts were eligible for inclusion. After applying the inclusion and exclusion criteria, seven studies were finally included. The results showed that the use of yacon flour can reduce glycemia, HbA1c, advanced glycation ends, plasma lipids, body fat mass, body weight, and waist circumference and improve intestinal microbiota and the antioxidant status. Further exploration of the effects of yacon flour is warranted, and additional clinical trials are necessary to determine the optimal daily consumption levels required to assist in improving metabolic parameters.

Hypoglycemia is the most common metabolic alteration in the clinical routine of newborn dogs, acting as a predictor of mortality in these patients. The neonatal dog shows hepatic insufficiency and homeostatic mechanisms not yet fully developed, with limited glycogen reserves and limited capacity to perform glycogenolysis and gluconeogenesis. These physiological particularities make newborn dogs particularly susceptible to hypoglycemia when of fasting, even for short periods. Several maternal and neonatal factors may be related to a higher risk of developing hypoglycemia in neonates. This paper reviews glycemic homeostasis, the pathophysiology of neonatal hypoglycemia, the main causes involved and the diagnostic and therapeutic approaches to this condition.

Background: The Mexican population exhibits several cardiovascular risk factors (CVRF) including high blood pressure (HBP), dysglycemia, dyslipidemia, overweight, and obesity. This study is an extensive observation of the most important CVFRs in six of the most populated cities in Mexico. Methods: In a cohort of 297,370 participants (54% female, mean age 43 ± 12.6 years), anthropometric (body mass index (BMI)), metabolic (glycemia and total cholesterol (TC)), and blood pressure (BP) data were obtained. Results: From age 40, 40% and 30% of the cohort\'s participants were overweight or obese, respectively. HBP was found in 27% of participants. However, only 8% of all hypertensive patients were controlled. Fifty percent of the subjects 50 years and older were hypercholesterolemic. Glycemia had a constant linear relation with age. BMI had a linear correlation with SBP, glycemia, and TC, with elevated coefficients in all cases and genders. The β1 coefficient for BMI was more significant in all equations than the other β, indicating that it greatly influences the other CVRFs. Conclusions: TC, glycemia, and SBP, the most critical atherogenic factors, are directly related to BMI.

BACKGROUND: Therapeutic interventions for diabetes are most effective when administered in the newly onset phase, yet determining the exact onset moment can be elusive in practice. Spontaneous autoimmune diabetes among NOD mice appears randomly between 12 and 32 weeks of age with an incidence range from 60 to 90%. Furthermore, the disease often progresses rapidly to severe diabetes within days, resulting in a very short window of newly onset phase, that poses significant challenge in early diagnosis. Conventionally, extensive blood glucose (BG) testing is typically required on large cohorts throughout several months to conduct prospective survey. We incorporated ultrasensitive urine glucose (UG) testing into an ordinary BG survey process, initially aiming to elucidate the lag period required for excessive glucose leaking from blood to urine during diabetes progression in the mouse model.
RESULTS: The observations unexpectedly revealed that small amounts of glucose detected in the urine often coincide with, sometimes even a couple days prior than elevated BG is diagnosed. Accordingly, we conducted the UG-based survey protocol in another cohort that was validated to accurately identified every individual near onset, who could then be confirmed by following few BG tests to fulfill the consecutive BG + criteria. This approach required fewer than 95 BG tests, compared to over 700 tests with traditional BG survey, to diagnose all the 37-38 diabetic mice out of total 60. The average BG level at diagnosis was slightly below 350 mg/dl, lower than the approximately 400 mg/dl observed with conventional BG monitoring.
CONCLUSIONS: We demonstrated a near perfect correlation between BG + and ultrasensitive UG + results in prospective survey with no lag period detected under twice weekly of testing frequency. This led to the refined protocol based on surveying with noninvasive UG testing, allowing for the early identification of newly onset diabetic mice with only a few BG tests required per mouse. This protocol significantly reduces the need for extensive blood sampling, lancet usage, labor, and animal distress, aligning with the 3Rs principle. It presents a convenient, accurate, and animal-friendly alternative for early diabetes diagnosis, facilitating research on diagnosis, pathogenesis, prevention, and treatment.

UNASSIGNED: The amount and type of food consumed impacts the glycemic response and insulin needs of people with type 1 diabetes mellitus (T1DM). Daily variability in consumption, reflected in diet quality, may acutely impact glycemic levels and insulin needs.
UNASSIGNED: Type 1 Diabetes Exercise Initiative (T1DEXI) data were examined to evaluate the impact of daily diet quality on near-term glycemic control and interaction with exercise.
UNASSIGNED: Using the Remote Food Photography Method, ≤8 d of dietary intake data were analyzed per participant. Diet quality was quantified with the Healthy Eating Index-2015 (HEI), where a score of 100 indicates the highest-quality diet. Each participant day was classified as low HEI (≤57) or high HEI (>57) based on the mean of nationally reported HEI data. Within participants, the relationship between diet quality and subsequent glycemia measured by continuous glucose monitoring (CGM) and total insulin dose usage was evaluated using a paired t-test and robust regression models.
UNASSIGNED: Two hundred twenty-three adults (76% female) with mean ± SD age, HbA1c, and body mass index (BMI) of 37 ± 14 y, 6.6% ± 0.7%, and 25.1 ± 3.6 kg/m2, respectively, were included in these analyses. The mean HEI score was 56 across all participant days. On high HEI days (mean, 66 ± 4) compared with low HEI days (mean, 47 ± 5), total time in range (70-180 mg/dL) was greater (77.2% ± 14% compared with 75.7% ± 14%, respectively, P = 0.01), whereas time above 180 mg/dL (19% ± 14% compared with 21% ± 15%, respectively, P = 0.004), mean glucose (143 ± 22 compared with 145 ± 22 mg/dL, respectively, P = 0.02), and total daily insulin dose (0.52 ± 0.18 compared with 0.54 ± 0.18 U/kg/d, respectively, P = 0.009) were lower. The interaction between diet quality and exercise on glycemia was not significant.
UNASSIGNED: Higher HEI scores correlated with improved glycemia and lower insulin needs, although the impact of diet quality was modest and smaller than the previously reported impact of exercise.

(1) Aims: Gut microbiota metabolites may play integral roles in human metabolism and disease progression. However, evidence for associations between metabolites and cardiometabolic risk factors is sparse, especially in high-risk Hispanic populations. We aimed to evaluate the cross-sectional and longitudinal relationships between gut microbiota related metabolites and measures of glycemia, dyslipidemia, adiposity, and incident type 2 diabetes in two Hispanic observational cohorts. (2) Methods: We included data from 670 participants of the Boston Puerto Rican Health Study (BPRHS) and 999 participants of the San Juan Overweight Adult Longitudinal Study (SOALS). Questionnaires and clinical examinations were conducted over 3 years of follow-up for SOALS and 6 years of follow-up for BPRHS. Plasma metabolites, including L-carnitine, betaine, choline, and trimethylamine N-oxide (TMAO), were measured at baseline in both studies. We used multivariable linear models to evaluate the associations between metabolites and cardiometabolic risk factors and multivariable logistic and Poisson regressions to assess associations with prevalent and incident type 2 diabetes, adjusted for potential confounding factors. Cohort-specific analyses were combined using a fixed-effects meta-analysis. (3) Results: Higher plasma betaine was prospectively associated with lower fasting glucose [-0.97 mg/dL (95% CI: -1.59, -0.34), p = 0.002], lower HbA1c [-0.02% (95% CI: -0.04, -0.01), p = 0.01], lower HOMA-IR [-0.14 (95% CI: -0.23, -0.05), p = 0.003], and lower fasting insulin [-0.27 mcU/mL (95% CI: -0.51, -0.03), p = 0.02]. Betaine was also associated with a 22% lower incidence of type 2 diabetes (IRR: 0.78, 95% CI: 0.65, 0.95). L-carnitine was associated with lower fasting glucose [-0.68 mg/dL (95% CI: -1.29, -0.07), p = 0.03] and lower HbA1c at follow-up [-0.03% (95% CI: -0.05, -0.01), p < 0.001], while TMAO was associated with higher fasting glucose [0.83 mg/dL (95% CI: 0.22, 1.44), p = 0.01] and higher triglycerides [3.52 mg/dL (95% CI: 1.83, 5.20), p < 0.0001]. Neither choline nor TMAO were associated with incident type 2 diabetes. (4) Conclusions: Higher plasma betaine showed consistent associations with a lower risk of glycemia, insulinemia, and type 2 diabetes. However, TMAO, a metabolite of betaine, was associated with higher glucose and lipid concentrations. These observations demonstrate the importance of gut microbiota metabolites for human cardiometabolic health.

The use of continuous glucose monitors (CGMs) in individuals living without diabetes is increasing. The purpose of this study was to profile various CGM metrics around nutritional intake, sleep and exercise in a large cohort of physically active men and women living without any known metabolic disease diagnosis to better understand the normative glycemic response to these common stimuli. A total of 12,504 physically active adults (age 40 ± 11 years, BMI 23.8 ± 3.6 kg/m2; 23% self-identified as women) wore a real-time CGM (Abbott Libre Sense Sport Glucose Biosensor, Abbott, USA) and used a smartphone application (Supersapiens Inc., Atlanta, GA, USA) to log meals, sleep and exercise activities. A total of >1 M exercise events and 274,344 meal events were analyzed. A majority of participants (85%) presented an overall (24 h) average glucose profile between 90 and 110 mg/dL, with the highest glucose levels associated with meals and exercise and the lowest glucose levels associated with sleep. Men had higher mean 24 h glucose levels than women (24 h-men: 100 ± 11 mg/dL, women: 96 ± 10 mg/dL). During exercise, the % time above >140 mg/dL was 10.3 ± 16.7%, while the % time <70 mg/dL was 11.9 ± 11.6%, with the remaining % within the so-called glycemic tight target range (70-140 mg/dL). Average glycemia was also lower for females during exercise and sleep events (p < 0.001). Overall, we see small differences in glucose trends during activity and sleep in females as compared to males and higher levels of both TAR and TBR when these active individuals are undertaking or competing in endurance exercise training and/or competitive events.