The Utilization of Machine Learning Algorithms for Assisting Physicians in the Diagnosis of Diabetes.

This paper investigates the use of machine learning algorithms to aid medical professionals in the detection and risk assessment of diabetes. The research employed a dataset gathered from individuals with type 2 diabetes in Ninh Binh, Vietnam. A variety of classification algorithms, including Decision Tree Classifier, Logistic Regression, SVC, Ada Boost Classifier, Gradient Boosting Classifier, Random Forest Classifier, and K Neighbors Classifier, were utilized to identify the most suitable algorithm for the dataset. The results of the present study indicate that the Random Forest Classifier algorithm yielded the most promising results, exhibiting a cross-validation score of 0.998 and an accuracy rate of 100%. To further evaluate the effectiveness of the selected model, it was subjected to a testing phase involving a new dataset comprising 67 patients that had not been previously seen. The performance of the algorithm on this dataset resulted in an accuracy rate of 94%, especially the study's notable finding is the algorithm's accurate prediction of the probability of patients developing diabetes, as indicated by the class 1 (diabetes) probabilities. This innovative approach offers a meticulous and quantifiable method for diabetes detection and risk evaluation, showcasing the potential of machine learning algorithms in assisting clinicians with diagnosis and management. By communicating the diabetes score and probability estimates to patients, the comprehension of their disease status can be enhanced. This information empowers patients to make informed decisions and motivates them to adopt healthier lifestyle habits, ultimately playing a crucial role in impeding disease progression. The study underscores the significance of leveraging machine learning in healthcare to optimize patient care and improve long-term health outcomes.

Acetylcholinesterase inhibitory activities of some flavonoids from the root bark of Pinus krempfii Lecomte: in vitro and in silico study.

From the root bark of Pinus krempfii Lecomte, four flavonoids were isolated and evaluated for their inhibitory activities against AChE and BChE enzymes in vitro and in silico. Tectochrysin (1) was found to inhibit AChE with an IC50 value of 33.69 ± 2.80 µM. The docking study results also showed agreement with the in vitro test results. All four compounds also showed the best binding affinity for the AChE enzyme, characterised by binding energy (ΔG) values as low as -8.1 to -9.3 kcal/mol, in which, the compound tectochrysin had the best binding affinity for the AChE protein with a ΔG value of -9.329 kcal/mol. Tectochrysin (1) was also bound to the amino acid Phe295 of AChE with a bond length of 2.8 Å, similar to the control dihydrotanshinone-I. Galangin (2) also showed its in vitro inhibitory activity against BChE with an IC50 value of 82.21 ± 2.70 µM. In silico, it also had the best binding energy value of -9.072 kcal/mol with BChE and formed hydrogen bonds with the His438 (2.85 Å) residues of BChE like the positive control (tacrine). The steered molecular dynamics (SMD) simulation results of these two complexes revealed a mechanistic insight that the protein-ligand complexes showed stable trajectories throughout the 20 and 150 ns simulations. Moreover, the drug likeliness suggested that both flavonoids (1 and 2) were expected to be drug-like and have an LD50 toxicity level of 5. This study has contributed new results for drug discovery and the development of substances with neuroprotective effects, especially for the treatment of Alzheimer's disease.Communicated by Ramaswamy H. Sarma.

Lower Extremity Nerve Conduction Abnormalities in Vietnamese Patients with Type 2 Diabetes: A Cross-Sectional Study on Peripheral Neuropathy and Its Correlation with Glycemic Control and Renal Function.

Peripheral neuropathy is a common complication of type 2 diabetes mellitus (T2DM) that results in nerve conduction abnormalities. This study aimed to investigate the parameters of nerve conduction in lower extremities among T2DM patients in Vietnam. A cross-sectional study was conducted on 61 T2DM patients aged 18 years and older, diagnosed according to the American Diabetes Association's criteria. Data on demographic characteristics, duration of diabetes, hypertension, dyslipidemia, neuropathy symptoms, and biochemical parameters were collected. Nerve conduction parameters were measured in the tibial and peroneal nerves, including peripheral motor potential time, response amplitude M, and motor conduction speed, as well as sensory conduction in the shallow nerve. The study found a high rate of peripheral neuropathy among T2DM patients in Vietnam, with decreased conduction rate, motor response amplitude, and nerve sensation. The incidence of nerve damage was highest in the right peroneal nerve and left peroneal nerve (86.7% for both), followed by the right tibial nerve and left tibial nerve (67.2% and 68.9%, respectively). No significant differences were found in the rate of nerve defects between different age groups, body mass index (BMI) groups, or groups with hypertension or dyslipidemia. However, a statistically significant association was found between the rate of clinical neurological abnormalities and the duration of diabetes (p < 0.05). Patients with poor glucose control and/or decreased renal function also had a higher incidence of nerve defects. The study highlights the high incidence of peripheral neuropathy among T2DM patients in Vietnam and the association between nerve conduction abnormalities and poor glucose control and/or decreased renal function. The findings underscore the importance of early diagnosis and management of neuropathy in T2DM patients to prevent serious complications.

Caffeic Acid Phenethyl Ester Inhibits Basal Lipolysis by Activating PPAR-Gamma and Increasing Lipid Droplet-Associated Perilipin in Mature Rat Adipocytes.

Abnormal lipolysis is correlated with metabolic syndrome. Caffeic acid phenethyl ester (CAPE), a natural product from honeybee hives, has been reported to improve metabolic syndrome. However, the effects of CAPE on lipolysis and perilipin-1 (the major lipid droplet-associated protein) in mature adipocytes were not clarified. In this study, mature adipocytes were isolated from the epididymal fat pads of male rats and incubated with CAPE to estimate lipolysis by measuring glycerol release. It was found that the basal lipolysis was inhibited by CAPE in a dose- and time-dependent manner. The lipid droplet-associated perilipin-1 and phosphorylated peroxisome proliferator-activated receptor (PPAR) gamma levels increased following CAPE treatment by Western blot analysis. Moreover, a specific PPAR-gamma inhibitor (T0070907) could partly reverse the effect of CAPE on basal lipolysis. Furthermore, treatment of adipocytes with dibutyryl-cAMP (db-cAMP) or isoproterenol (ISO) increased lipolysis, but the drug-induced lipolysis was abrogated by combination treatment with CAPE. The lipid droplet-associated perilipin-1 level was also decreased in the drug-induced groups but increased when combined treatment with CAPE. In conclusion, our results revealed that a decrease in basal lipolysis and an increase in lipid droplet-associated perilipin-1 levels induced by CAPE may be involved in the regulation of lipid metabolism through activation of PPAR-gamma in mature adipocytes.

FTO-rs9939609 Polymorphism is a Predictor of Future Type 2 Diabetes: A Population-Based Prospective Study.

The study aimed to evaluate the contribution of the FTO A/T polymorphism (rs9939609) to the prediction of the future type 2 diabetes (T2D). A population-based prospective study included 1443 nondiabetic subjects at baseline, and they were examined for developing T2D after 5-year follow-up. Cox proportional hazards model was used to evaluate the hazard ratio (HR) of rs9939609 to the future T2D in the models adjusted for the confounding factors including socio-economic status, lifestyle factors (smoking and drinking history, sporting habits, and leisure time), and clinical patterns (obese status, blood pressures, and dyslipidemia) at baseline. The area under receiver operating characteristic curve (AUC) was used to measure the power to predict individuals with T2D. The FTO-rs9939609 polymorphism was a significant predictor of future T2D in the model unadjusted, and it remained significant in the final model after adjustment for the confounding factors, showing an additive effect of the A-allele (HR = 1.35, 95% CI = 1.02-1.78, P = 0.036, AUC = 0.676). For normoglycemic subjects at baseline, the similar final adjusted model reported the increased HR per A-allele (HR = 1.50, 95% CI = 1.09-2.07, P = 0.012, AUC = 0.697). Five-year changes in BMI, waist circumference, and systolic blood pressure did not remove the contribution of rs9939609 to increased HR of T2D. The population attributable risk for risk genotype was 13.6%. In conclusion, the study indicates that the FTO-rs9939609 polymorphism is an important genetic predictor for future T2D in Vietnamese population.

First Report on Association of Hyperuricemia with Type 2 Diabetes in a Vietnamese Population.

BACKGROUND: Uric acid is a powerful free-radical scavenger in humans, but hyperuricemia may induce insulin resistance and beta-cell dysfunction. The study aimed to evaluate the association between hyperuricemia and hyperglycemia, considering the confounding factors in a Vietnamese population. METHODS: A population-based cross-sectional study recruited 1542 adults aged 50 to 70 years to collect data on socioeconomic status, lifestyle factors, and clinical patterns. Associations between hyperuricemia and hyperglycemia (isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), combined IFG-IGT, and type 2 diabetes (T2D)) were evaluated by multinomial logistic regression analysis in several models, adjusting for the confounding factors including socioeconomic status, lifestyle factors, and clinical measures. RESULTS: Uric acid values were much higher in IFG, IFG-IGT, and T2D groups compared to those in the normal glucose tolerance (NGT) group. The significant association of hyperuricemia with IFG, IFG-IGT, and T2D was found in the model unadjusted and remained consistently in several models adjusted for socioeconomic status, lifestyle factors, and clinical patterns. In the final model, the consistent hyperglycemia risk was found in total sample (OR = 2.23 for IFG, OR = 2.29 for IFG-IGT, and 1.75 for T2D, P ≤ 0.006) and in women (OR = 2.90 for IFG, OR = 3.96 for IFG-IGT, and OR = 2.49 for T2D, P < 0.001) but not in men. CONCLUSIONS: It is the first report in Vietnamese population suggesting the significant association of hyperuricemia with IFG, IFG-IGT, and T2D; and the predominant association was found in women than in men, taken into account the confounding factors.

Metabolic syndrome among a middle-aged population in the Red River Delta region of Vietnam.

BACKGROUND: Metabolic syndrome (MetS) is a clustering of metabolic risk factors for cardiovascular diseases and type 2 diabetes. The study aimed to estimate the prevalence of MetS, its components, and their associations among rural middle-aged population in Vietnam. METHODS: A cross-sectional study with a representative sample (n = 2443) was conducted to collect data on demographic, socioeconomic, anthropometric, lifestyles, plasma glucose, and lipid profile. The age- and sex-adjusted prevalences of MetS and its components were calculated using the direct standardization. Associations of risk factors with MetS were evaluated using logistic regression, taken into account the confounding factors. RESULTS: The total age- and sex-adjusted prevalence (95% CI) of MetS was 16.3% (14.0 - 18.6). The most frequent component of MetS was high triglycerides (43.2%), followed by low HDL-C (42.0%), elevated blood pressure (29.2%), high plasma glucose (14.3%), and central obesity (12.3%). Of the total population, only 17.6% did not have any component of MetS and more than 40% had at least two MetS components. The association of MetS with residence, age, body mass index, marital status, and siesta time per day was statistically significant in univariate analysis and replicated in multivariate analysis. CONCLUSION: The MetS prevalence and its components are common and major public health burden in the middle-aged adults in Vietnam. Habitants living in urban, being never-married, having an increase in age, BMI, and siesta time per day are significantly associated with MetS, and they should be paid much more attention for screening and implementing preventive activities.