A Machine Learning Based Dose Prediction of Lutein Supplements for Individuals With Eye Fatigue

Visual fatigue a comprehensive review of mechanisms of occurrence, animal model design and nutritional intervention strategies

When the eyes work intensively, it is easy to have eye discomfort such as blurred vision, soreness, dryness, and tearing, that is, visual fatigue. Visual fatigue not only affects work and study efficiency, but long-term visual fatigue can also easily affect physical and mental health. In recent years, with the popularization of electronic products, although it has brought convenience to the office and study, it has also caused more frequent visual fatigue among people who use electronic devices. Moreover, studies have reported that the number of people with visual fatigue is showing a trend of increasing year by year. The range of people involved is also extensive, especially students, people who have been engaged in computer work and fine instruments (such as microscopes) for a long time, and older adults with aging eye function. More and more studies have proposed that supplementation with the proper nutrients can effectively relieve visual fatigue and promote eye health. This review discusses the physiological mechanisms of visual fatigue and the design ideas of animal experiments from the perspective of modern nutritional science. Functional food ingredients with the ability to alleviate visual fatigue are discussed in detail.

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

Lutein-Rich Beverage Alleviates Visual Fatigue in the Hyperglycemia Model of Sprague-Dawley Rats

Asthenopia is a syndrome based on the symptoms of eye discomfort that has become a chronic disease that interferes with and harms people's physical and mental health. Lutein is an internationally recognized "eye nutrient", and studies have shown that it can protect the retina and relieve visual fatigue. In this study, lutein was extracted from marigold (Tagetes erecta L.) and saponified. The purified lutein concentration measured by HPLC was 50.12 mg/100 g. Then, purified lutein was modified to be water-soluble by nanoscale modification and microencapsulation technology. Water-soluble lutein was then mixed with a leaching solution of Chinese wolfberry and chrysanthemum to make a functional beverage. The effects of this beverage on hepatic antioxidant enzymes and the alleviation of visual fatigue in a rat model of diabetes were investigated for 4 weeks. Lutein intake of 0.72 (medium-lutein beverage group) and 1.44 mg/mL (high-lutein beverage group) relieved visual fatigue, ameliorated turbidity symptoms of impaired crystalline lenses, reduced hepatic MDA concentration, increased hepatic GSH concentration, and significantly increased the activities of the hepatic antioxidant enzymes SOD, CAT, GSH-Px, and GR in rats. These data suggest that a lutein-rich beverage is an effective and harmless way to increase the total anti-oxidation capacity of lenses and alleviate visual fatigue.

Development and validation to predict visual acuity and keratometry two years after corneal crosslinking with progressive keratoconus by machine learning

Purpose

To explore and validate the utility of machine learning (ML) methods using a limited sample size to predict changes in visual acuity and keratometry 2 years following corneal crosslinking (CXL) for progressive keratoconus.

Methods

The study included all consecutive patients with progressive keratoconus who underwent CXL from July 2014 to December 2020, with a 2 year follow-up period before July 2022 to develop the model. Variables collected included patient demographics, visual acuity, spherical equivalence, and Pentacam parameters. Available case data were divided into training and testing data sets. Three ML models were evaluated based on their performance in predicting case corrected distance visual acuity (CDVA) and maximum keratometry (Kmax) changes compared to actual values, as indicated by average root mean squared error (RMSE) and R-squared (R2) values. Patients followed from July 2022 to December 2022 were included in the validation set.

Results

A total of 277 eyes from 195 patients were included in training and testing sets and 43 eyes from 35 patients were included in the validation set. The baseline CDVA (26.7%) and the ratio of steep keratometry to flat keratometry (K2/K1; 13.8%) were closely associated with case CDVA changes. The baseline ratio of Kmax to mean keratometry (Kmax/Kmean; 20.9%) was closely associated with case Kmax changes. Using these metrics, the best-performing ML model was XGBoost, which produced predicted values closest to the actual values for both CDVA and Kmax changes in testing set (R2 = 0.9993 and 0.9888) and validation set (R2 = 0.8956 and 0.8382).

Conclusion

Application of a ML approach using XGBoost, and incorporation of identifiable parameters, considerably improved variation prediction accuracy of both CDVA and Kmax 2 years after CXL for treatment of progressive keratoconus.

Personalized nutrition: A review of genotype-based nutritional supplementation

Nutritional disorders have become a major public health issue, requiring increased targeted approaches. Personalized nutrition adapted to individual needs has garnered dramatic attention as an effective way to improve nutritional balance and maintain health. With the rapidly evolving fields of genomics and nutrigenetics, accumulation of genetic variants has been indicated to alter the effects of nutritional supplementation, suggesting its indispensable role in the genotype-based personalized nutrition. Additionally, the metabolism of nutrients, such as lipids, especially omega-3 polyunsaturated fatty acids, glucose, vitamin A, folic acid, vitamin D, iron, and calcium could be effectively improved with related genetic variants. This review focuses on existing literatures linking critical genetic variants to the nutrient and the ways in which these variants influence the outcomes of certain nutritional supplementations. Although further studies are required in this direction, such evidence provides valuable insights for the guidance of appropriate interventions using genetic information, thus paving the way for the smooth transition of conventional generic approach to genotype-based personalized nutrition.