The deterioration of brain glucose metabolism predates the clinical onset of Alzheimer’s disease (AD). Medium-chain triglycerides (MCTs) and docosahexaenoic acid (DHA) positively improve brain glucose metabolism and decrease the expression of AD-related proteins. However, the effects of the combined intervention are unclear. The present study explored the effects of the supplementation of MCTs combined with DHA in improving brain glucose metabolism and decreasing AD-related protein expression levels in APP/PS1 mice. The mice were assigned into four dietary treatment groups: the control group, MCTs group, DHA group, and MCTs + DHA group. The corresponding diet of the respective groups was fed to mice from the age of 3 to 11 months. The results showed that the supplementation of MCTs combined with DHA could increase serum octanoic acid (C8:0), decanoic acid (C10:0), DHA, and β-hydroxybutyrate (β-HB) levels; improve glucose metabolism; and reduce nerve cell apoptosis in the brain. Moreover, it also aided with decreasing the expression levels of amyloid beta protein (Aβ), amyloid precursor protein (APP), β-site APP cleaving enzyme-1 (BACE1), and presenilin-1 (PS1) in the brain. Furthermore, the supplementation of MCTs + DHA was significantly more beneficial than that of MCTs or DHA alone. In conclusion, the supplementation of MCTs combined with DHA could improve energy metabolism in the brain of APP/PS1 mice, thus decreasing nerve cell apoptosis and inhibiting the expression of Aβ.

Background: The physical abilities of older adults decline with age, making them more susceptible to micronutrient deficiency, which may affect their sleep quality. Objectives: This study aimed to construct a risk correlative model for sleep disorders in Chinese older adults based on blood micronutrient levels. Methods: In this matched case-control study, we recruited 124 participants with sleep disorders and 124 matched controls from the Tianjin Elderly Nutrition and Cognition cohort in China. Micronutrient levels in whole blood were measured using the dried blood spot technique. We compared the differences in micronutrient levels between the two groups and also constructed a receiver operating characteristic (ROC) model and nomogram for sleep disorders. Results: In comparison to the control group, the sleep disorders group showed lower levels of blood vitamin A, vitamin E (VE), folate, magnesium, copper, iron, and selenium (Se) in the univariate analysis (p < 0.05). The ROC curve analysis indicated that the combination of VE + folate + Se may have an excellent diagnostic effect on sleep disorders, with an area under the curve of 0.964. This VE + folate + Se was integrated into a nomogram model to demonstrate their relationship with sleep disorders. The consistency index of the model was 0.88, suggesting that the model assessed sleep disorders well. Conclusions: The sleep disorders risk correlative model constructed by the levels of VE, folate, and Se in whole blood might show good performance in assessing the risk of sleep disorders in older adults.

The reference intervals (RIs) for venous whole blood micronutrients are instrumental in evaluating nutritional status within populations. However, research on establishing micronutrient RIs using the simple and efficient dried blood spot (DBS) technique remains scarce. Consequently, this study aims to establish RIs for venous whole blood micronutrients among healthy Chinese older individuals via DBS. Participants were recruited from the general community of Baodi District, Tianjin, northern China. Healthy populations were identified based on the recommendations of the Clinical and Laboratory Standards Institute guidelines, physical signs (body mass index and waist circumference), and blood biochemical parameters (serum lipid status and hemoglobin). The micronutrient levels were measured via the DBS technique. For normally distributed data, the RI was calculated as the mean ± 2SD. For non-normally distributed data, the RI is calculated as the 2.5th to 97.5th percentiles. This study established RIs for 8 vitamins (vitamins A, D, E, B₁, B₂, B₃, B₆, B₉) and 5 minerals (Mg, Cu, Fe, Zn, Se) in healthy older adults. For males, the RIs are as follows: VA (157.76-828.81 ng/mL); VD (8.89-58.32 ng/mL); VE (1.84-13.78 μg/mL); VB₁ (0.19-5.36 ng/mL); VB₂ (0.53-13.84 ng/mL); VB₃ (4.43-13.70 μg/mL); VB₆ (1.09-26.00 ng/mL); VB₉ (1.02-9.48 ng/mL); Mg (27.54-52.99 mg/L); Cu (0.57-1.64 mg/L); Fe (287.00-708.60 mg/L); Zn (4.10-20.85 mg/L); Se (70.57-167.63 μg/L). For females: VA (142.62-755.78 ng/mL); VD (10.10-66.20 ng/mL); VE (1.87-13.43 ng/mL); VB₁ (0.15-4.20 ng/mL); VB₂ (0.61-12.81 ng/mL); VB₃ (4.51-15.53 ng/mL); VB₆ (1.82-24.05 ng/mL); VB₉ (0.60-9.62 ng/mL); Mg (25.73-51.94 mg/L); Cu (0.58-1.41 mg/L); Fe (236.75-599.81 mg/L); Zn (3.93-22.22 mg/L); Se (70.57-167.63 μg/L). This study presents venous whole blood micronutrient parameters that can facilitate nutrition-related epidemiological research and inform personalized intervention strategies, thereby enhancing the quality of healthcare for elderly individuals in China.

Purpose: Adequate micronutrients play a crucial role in cognitive health. Identifying relevant micronutrients and constructing risk prediction models can guide the prevention of mild cognitive impairment (MCI) in older adults. This study aimed to assess the associations of MCI with whole blood micronutrient levels and develop a nomogram for personalized MCI risk prediction in older adults. Methods: In the matched case–control study, 100 MCI patients and 100 matched controls by age, sex and education from Baodi District, Tianjin, China were recruited. MCI was determined by a modified version of the Petersen criteria. Whole blood levels of 9 vitamins and 5 minerals were measured using the dried blood spot technique. Weighted quantile sum regression was employed to identify the most significant micronutrients associated with cognitive function. Receiver operating characteristic (ROC) curves were constructed, and a nomogram for predicting MCI risk was developed. Results: High levels of vitamins (vitamin A, vitamin B₂, vitamin B₆, vitamin B₉) and minerals (magnesium, selenium) were significantly associated with lower MCI prevalence, in which vitamin B₂, vitamin B₉ and selenium were ranked as the most significant contributors to cognitive function. The ROC curves for vitamin B₂ and vitamin B₉ (area under the curve = 0.855) have superior diagnostic accuracy compared to individual assessments (p < 0.05). Based on these findings, a nomogram was developed using these two micronutrients to predict MCI risk. Conclusion: The nomogram based on vitamin B₂ and vitamin B₉ can be effectively used to detect MCI early and guide preventive strategies in older adults.