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Objectives: Innovative precision dietary procedures are required to promote healthy aging. This study aimed to evaluate the effects of a personalised strategy based on the inclusion of individualised foods and digital tools on overall health status and quality of life within a follow-up of 3 months in older adults with overweight or obesity. Methods: 127 men and women aged between 50 and 80 years with overweight/obesity participated in the study—between January 2020 and September 2020 at the Center for Nutrition Research-University of Navarra and IMDEA-ALIMENTACIÓN—and were randomly assigned to a usual-care group (standard recommendations) or precision group (precision nutrition strategy based on the inclusion of individualised foods and a mobile application). Anthropometry, body fat percentage, biochemical parameters, diet, and quality of life (SF-36 Health Survey) were assessed at baseline and after 3 months. Results: Both strategies were found to improve overall metabolic health; however, the precision approach demonstrated significantly better outcomes. The precision strategy reduced body weight at 3 months (−4.3 kg; p

Leading a healthy lifestyle significantly reduces the risk of developing Non-Communicable Diseases (NCD). However, defining and monitoring healthy eating behaviour depends on multiple factors and usually requires the intervention of experts. On the other hand, nowadays millions of images are shared on social media and web platforms. In particular, many of them are food images taken from a smartphone over time, providing information related to the individual’s diet. Consequently, exploiting recent advances in image processing and Artificial Intelligence (AI), this scenario represents an excellent opportunity to: i) create new methods that analyse the individuals’ health from what they eat, and ii) develop personalised recommendations to improve nutrition and diet under specific circumstances (e.g., obesity or COVID). This article introduces the AI4Food-NutritionFW, a framework that facilitates the creation of food image datasets tailored to configurable eating behaviours. The framework considers various aspects such as region and lifestyle, simulating a user-friendly scenario where individuals capture food images using their smartphones. The study also presents a novel food image dataset comprising 4,800 diverse weekly diets from 15 distinct profiles, ranging from healthy eating habits to unhealthy ones. Finally, we evaluate the healthy eating behaviours through a score based on the Normalised Mahalanobis Distance (NMD), achieving promising results (99.53% and 99.60% accuracy and sensitivity, respectively). We also release to the research community a software implementation of our proposed AI4Food-NutritionFW (https://github.com/BiDAlab/AI4Food-NutritionFW) and the mentioned food image dataset created with it.

Fasting has been reported to protect from chemotherapy-associated toxicity. Here, the authors show that fatty acid profiles in erythrocyte membranes and gene expression from peripheral blood mononuclear cells are associated to the fasting-mediated benefits during cancer treatment in mice and patients.

Background Online health data collection has gained a reputation over the last years to record and process information about health issues for implementing digital health. Objective The research aim was to appraise two online methods (open and rewarded) to collect information about HRQoL and nutritional well-being and to compare the results between both surveyed populations. Methods This cross-sectional study is framed on the NUTRiMDEA project. Online data through two different web-based methods (open survey and rewarded survey) were retrieved to assemble data related to sociodemographic, lifestyle (diet, physical activity and sleep patterns) and general health aspects, as well as HRQoL by an evidence-based form such as the SF-12 questionnaire, the IPAQ survey, and MEDAS-14, participants were adults (>18 years old). Results Overall, 17,332 participants responded to the open survey (OS, n = 11,883) or the rewarded survey (RS, n = 5449). About 65.1% of the participants were female, while the mean age was in the range of 40–70 years. There were significant differences ( p

Viral infections activate the innate immune response and the secretion of inflammatory cytokines. They also alter oxidative stress markers, which potentially can have an involvement in the pathogenesis of the disease. The aim of this research was to study the role of the oxidative stress process assessed through lactate dehydrogenase (LDH) on the severity of COVID-19 measured by oxygen saturation (SaO2) and the putative interaction with inflammation. The investigation enrolled 1808 patients (mean age of 68 and 60% male) with COVID-19 from the HM Hospitals database. To explore interactions, a regression model and mediation analyses were performed. The patients with lower SaO2 presented lymphopenia and higher values of neutrophils-to-lymphocytes ratio and on the anisocytosis coefficient. The regression model showed an interaction between LDH and anisocytosis, suggesting that high levels of LDH (>544 U/L) and an anisocytosis coefficient higher than 10% can impact SaO2 in COVID-19 patients. Moreover, analysis revealed that LDH mediated 41% (p value = 0.001) of the effect of anisocytosis on SaO2 in this cohort. This investigation revealed that the oxidative stress marker LDH and the interaction with anisocytosis have an important role in the severity of COVID-19 infection and should be considered for the management and treatment of the oxidative phenomena concerning this within a precision medicine strategy.

Abstract Background Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumors. In this work, we identified a new set of gene markers for CRC associated to prognosis and risk using a large unified cohort of patients with transcriptomic profiles and survival information. Results We built an integrated dataset with 1273 human colorectal samples, which provides a homogeneous robust framework to analyse genome-wide expression and survival data. Using this dataset we identified two sets of genes that are candidate prognostic markers for CRC in stages III and IV, showing either up-regulation correlated with poor prognosis or up-regulation correlated with good prognosis. The top 10 up-regulated genes found as survival markers of poor prognosis (i.e. low survival) were: DCBLD2, PTPN14, LAMP5, TM4SF1, NPR3, LEMD1, LCA5, CSGALNACT2, SLC2A3 and GADD45B. The stability and robustness of the gene survival markers was assessed by cross-validation, and the best-ranked genes were also validated with two external independent cohorts: one of microarrays with 482 samples; another of RNA-seq with 269 samples. Up-regulation of the top genes was also proved in a comparison with normal colorectal tissue samples. Finally, the set of top 100 genes that showed overexpression correlated with low survival was used to build a CRC risk predictor applying a multivariate Cox proportional hazards regression analysis. This risk predictor yielded an optimal separation of the individual patients of the cohort according to their survival, with a p-value of 8.25e-14 and Hazard Ratio 2.14 (95% CI: 1.75–2.61). Conclusions The results presented in this work provide a solid rationale for the prognostic utility of a new set of genes in CRC, demonstrating their potential to predict colorectal tumor progression and evolution towards poor survival stages. Our study does not provide a fixed gene signature for prognosis and risk prediction, but instead proposes a robust set of genes ranked according to their predictive power that can be selected for additional tests with other CRC clinical cohorts.

Sport performance is influenced by several factors, including genetic susceptibility. In the past years, specific single nucleotide polymorphisms have been associated to sport performance; however, these effects should be considered in multivariable prediction systems since they are related to a polygenic inheritance. The aim of this study was to design a genetic endurance prediction score (GES) of endurance performance and analyze its association with anthropometric, nutritional and sport efficiency variables in a cross-sectional study within fifteen male cyclists. A statistically significant positive relationship between GES and the VO2 maximum (P = 0.033), VO2 VT1 (P = 0.049) and VO2 VT2 (P < 0.001) was observed. Moreover, additional remarkable associations between genotype and the anthropometric, nutritional and sport performance variables, were achieved. In addition, an interesting link between the habit of consuming caffeinated beverages and the GES was observed. The outcomes of the present study indicate a potential use of this genetic prediction algorithm in the sports’ field, which may facilitate the finding of genetically talented athletes, improve their training and food habits, as well as help in the improvement of physical conditions of amateurs.

An abnormal acyl-CoA synthetase/stearoyl-CoA desaturase (ACSL/SCD) lipid network fuels colon cancer progression, endowing cells with invasive and migratory properties. Therapies against this metabolic network may be useful to improve clinical outcomes. Because micro-RNAs (miRNAs/miRs) are important epigenetic regulators, we investigated novel miRNAs targeting this pro-tumorigenic axis; hence to be used as therapeutic or prognostic miRNAs. Thirty-one putative common miRNAs were predicted to simultaneously target the three enzymes comprising the ACSL/SCD network. Target validation by quantitative RT-PCR, Western blotting, and luciferase assays showed miR-544a, miR-142, and miR-19b-1 as major regulators of the metabolic axis, ACSL/SCD. Importantly, lower miR-19b-1 expression was associated with a decreased survival rate in colorectal cancer (CRC) patients, accordingly with ACSL/SCD involvement in patient relapse. Finally, miR-19b-1 regulated the pro-tumorigenic axis, ACSL/SCD, being able to inhibit invasion in colon cancer cells. Because its expression correlated with an increased survival rate in CRC patients, we propose miR-19b-1 as a potential noninvasive biomarker of disease-free survival and a promising therapeutic miRNA in CRC.

Chronobiological aspects controlled by CLOCK genes may influence obesity incidence. Although there are studies that show an association between the expression of these genes and energy intake, waist circumference or abdominal obesity phenotypes, interactions with appetite have been insufficiently investigated in relation to chrononutrition. The objective was to identify interactions between CLOCK genetic variants involved in appetite status. A total of 442 subjects (329 women, 113 men; aged 18 to 65 years) were recruited. Anthropometric, dietary and lifestyle data were collected by trained nutritionists. Participants were classified according to their appetite feelings with a Likert scale. Multiple linear regression models were used to examine associations of the type genotype x appetite status on adiposity-related variables. p values were corrected by the Bonferroni method. A significant influence was found concerning the effects of appetite on waist circumference with respect to rs3749474 CLOCK polymorphism (p < 0.001). An additive model analysis (adjusted by age, gender, exercise and energy intake) showed that risk allele carriers, increased the waist circumference around 14 cm (β = 14.1, CI = 6.3–22.0) by each increment in the level of appetite. The effects of appetite on waist circumference may be partly modulated by the rs3749474 CLOCK polymorphism.

Metabolic syndrome (MetS) is established as the combination of central obesity and different metabolic disturbances, such as insulin resistance, hypertension and dyslipidemia. This cluster of factors affects approximately 10%–50% of adults worldwide and the prevalence has been increasing in epidemic proportions over the last years. Thus, dietary strategies to treat this heterogenic disease are under continuous study. In this sense, diets based on negative-energy-balance, the Mediterranean dietary pattern, n-3 fatty acids, total antioxidant capacity and meal frequency have been suggested as effective approaches to treat MetS. Furthermore, the type and percentage of carbohydrates, the glycemic index or glycemic load, and dietary fiber content are some of the most relevant aspects related to insulin resistance and impaired glucose tolerance, which are important co-morbidities of MetS. Finally, new studies focused on the molecular action of specific nutritional bioactive compounds with positive effects on the MetS are currently an objective of scientific research worldwide. The present review summarizes some of the most relevant dietary approaches and bioactive compounds employed in the treatment of the MetS to date.

BACKGROUND:The Kennedy pathway generates phosphocoline and phosphoethanolamine through its two branches. Choline Kinase (ChoK) is the first enzyme of the Kennedy branch of synthesis of phosphocholine, the major component of the plasma membrane. ChoK family of proteins is composed by ChoKalpha and ChoKbeta isoforms, the first one with two different variants of splicing. Recently ChoKalpha has been implicated in the carcinogenic process, since it is over-expressed in a variety of human cancers. However, no evidence for a role of ChoKbeta in carcinogenesis has been reported. METHODOLOGY/PRINCIPAL FINDINGS:Here we compare the in vitro and in vivo properties of ChoKalpha1 and ChoKbeta in lipid metabolism, and their potential role in carcinogenesis. Both ChoKalpha1 and ChoKbeta showed choline and ethanolamine kinase activities when assayed in cell extracts, though with different affinity for their substrates. However, they behave differentially when overexpressed in whole cells. Whereas ChoKbeta display an ethanolamine kinase role, ChoKalpha1 present a dual choline/ethanolamine kinase role, suggesting the involvement of each ChoK isoform in distinct biochemical pathways under in vivo conditions. In addition, while overexpression of ChoKalpha1 is oncogenic when overexpressed in HEK293T or MDCK cells, ChoKbeta overexpression is not sufficient to induce in vitro cell transformation nor in vivo tumor growth. Furthermore, a significant upregulation of ChoKalpha1 mRNA levels in a panel of breast and lung cancer cell lines was found, but no changes in ChoKbeta mRNA levels were observed. Finally, MN58b, a previously described potent inhibitor of ChoK with in vivo antitumoral activity, shows more than 20-fold higher efficiency towards ChoKalpha1 than ChoKbeta. CONCLUSION/SIGNIFICANCE:This study represents the first evidence of the distinct metabolic role of ChoKalpha and ChoKbeta isoforms, suggesting different physiological roles and implications in human carcinogenesis. These findings constitute a step forward in the design of an antitumoral strategy based on ChoK inhibition.

Background: Identification of biomarkers associated with the prognosis of different cancer subtypes is critical to achieve better therapeutic assistance. In colorectal cancer (CRC) the discovery of stable and consistent survival markers remains a challenge due to the high heterogeneity of this class of tumors. In this work, we identified a new set of gene markers for CRC associated to prognosis and risk using a large unified cohort of patients with transcriptomic profiles and survival information. Results: We built an integrated dataset with 1273 human colorectal samples, which provides a homogeneous robust framework to analyse genome-wide expression and survival data. Using this dataset we identified two sets of genes that are candidate prognostic markers for CRC in stages III and IV, showing either up-regulation correlated with poor prognosis or up-regulation correlated with good prognosis. The top 10 up-regulated genes found as survival markers of poor prognosis (i.e. low survival) were: DCBLD2, PTPN14, LAMP5, TM4SF1, NPR3, LEMD1, LCA5, CSGALNACT2, SLC2A3 and GADD45B. The stability and robustness of the gene survival markers was assessed by cross-validation, and the best-ranked genes were also validated with two external independent cohorts: one of microarrays with 482 samples; another of RNA-seq with 269 samples. Up-regulation of the top genes was also proved in a comparison with normal colorectal tissue samples. Finally, the set of top 100 genes that showed overexpression correlated with low survival was used to build a CRC risk predictor applying a multivariate Cox proportional hazards regression analysis. This risk predictor yielded an optimal separation of the individual patients of the cohort according to their survival, with a p-value of 8.25e-14 and Hazard Ratio 2.14 (95% CI: 1.75–2.61). Conclusions: The results presented in this work provide a solid rationale for the prognostic utility of a new set of genes in CRC, demonstrating their potential to predict colorectal tumor progression and evolution towards poor survival stages. Our study does not provide a fixed gene signature for prognosis and risk prediction, but instead proposes a robust set of genes ranked according to their predictive power that can be selected for additional tests with other CRC clinical cohorts. [ABSTRACT FROM AUTHOR]