AI4FoodDB: a database for personalized e-Health nutrition and lifestyle through wearable devices and artificial intelligence

The increasing prevalence of diet-related diseases calls for an improvement in nutritional advice. Personalized nutrition aims to solve this problem by adapting dietary and lifestyle guidelines to the unique circumstances of each individual. With the latest advances in technology and data science, researchers can now automatically collect and analyze large amounts of data from a variety of sources, including wearable and smart devices. By combining these diverse data, more comprehensive insights of the human body and its diseases can be achieved. However, there are still major challenges to overcome, including the need for more robust data and standardization of methodologies for better subject monitoring and assessment. Here, we present the AI4Food database (AI4FoodDB), which gathers data from a nutritional weight loss intervention monitoring 100 overweight and obese participants during 1 month. Data acquisition involved manual traditional approaches, novel digital methods and the collection of biological samples, obtaining: (i) biological samples at the beginning and the end of the intervention, (ii) anthropometric measurements every 2 weeks, (iii) lifestyle and nutritional questionnaires at two different time points and (iv) continuous digital measurements for 2 weeks. To the best of our knowledge, AI4FoodDB is the first public database that centralizes food images, wearable sensors, validated questionnaires and biological samples from the same intervention. AI4FoodDB thus has immense potential for fostering the advancement of automatic and novel artificial intelligence techniques in the field of personalized care. Moreover, the collected information will yield valuable insights into the relationships between different variables and health outcomes, allowing researchers to generate and test new hypotheses, identify novel biomarkers and digital endpoints, and explore how different lifestyle, biological and digital factors impact health. The aim of this article is to describe the datasets included in AI4FoodDB and to outline the potential that they hold for precision health research. Database URL https://github.com/AI4Food/AI4FoodDB.

Non-Coding and Regulatory RNAs as Epigenetic Remodelers of Fatty Acid Homeostasis in Cancer

Cancer cells commonly display metabolic fluctuations. Together with the Warburg effect and the increased glutaminolysis, alterations in lipid metabolism homeostasis have been recognized as a hallmark of cancer. Highly proliferative cancer cells upregulate de novo synthesis of fatty acids (FAs) which are required to support tumor progression by exerting multiple roles including structural cell membrane composition, regulators of the intracellular redox homeostasis, ATP synthesis, intracellular cell signaling molecules, and extracellular mediators of the tumor microenvironment. Epigenetic modifications have been shown to play a crucial role in human development, but also in the initiation and progression of complex diseases. The study of epigenetic processes could help to design new integral strategies for the prevention and treatment of metabolic disorders including cancer. Herein, we first describe the main altered intracellular fatty acid processes to support cancer initiation and progression. Next, we focus on the most important regulatory and non-coding RNAs (small noncoding RNA-sncRNAs-long non-coding RNAs-lncRNAs-and other regulatory RNAs) which may target the altered fatty acids pathway in cancer.

A more physiological approach to lipid metabolism alterations in cancer: CRC-like organoids assessment

Precision medicine might be the response to the recent questioning of the use of metformin as an anticancer drug in colorectal cancer (CRC). Thus, in order to establish properly its benefits, metformin application needs to be assayed on the different progression stages of CRC. In this way, intestinal organoids imply a more physiological tool, representing a new therapeutic opportunity for CRC personalized treatment to assay tumor stage-dependent drugs. The previously reported lipid metabolism-related axis, Acyl-CoA synthetases/ Stearoyl-CoA desaturase (ACSLs/SCD), stimulates colon cancer progression and metformin is able to rescue the invasive and migratory phenotype conferred to cancer cells upon this axis overexpression. Therefore, we checked ACSL/SCD axis status, its regulatory miRNAs and the effect of metformin treatment in intestinal organoids with the most common acquired mutations in a sporadic CRC (CRC-like organoids) as a model for specific and personalized treatment. Despite ACSL4 expression is upregulated progressively in CRC-like organoids, metformin is able to downregulate its expression, especially in the first two stages (I, II). Besides, organoids are clearly more sensitive in the first stage (Apc mutated) to metformin than current chemotherapeutic drugs such as fluorouracil (5-FU). Metformin performs an independent "Warburg effect" blockade to cancer progression and is able to reduce crypt stem cell markers expression such as LGR5+. These results suggest a putative increased efficiency of the use of metformin in early stages of CRC than in advanced disease.

Targeting the lipid metabolic axis ACSL/SCD in colorectal cancer progression by therapeutic miRNAs: miR-19b-1 role

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.

A link between lipid metabolism and epithelial-mesenchymal transition provides a target for colon cancer therapy

The alterations in carbohydrate metabolism that fuel tumor growth have been extensively studied. However, other metabolic pathways involved in malignant progression, demand further understanding. Here we describe a metabolic acyl-CoA synthetase/stearoyl-CoA desaturase ACSL/SCD network causing an epithelial-mesenchymal transition (EMT) program that promotes migration and invasion of colon cancer cells. The mesenchymal phenotype produced upon overexpression of these enzymes is reverted through reactivation of AMPK signaling. Furthermore, this network expression correlates with poorer clinical outcome of stage-II colon cancer patients. Finally, combined treatment with chemical inhibitors of ACSL/SCD selectively decreases cancer cell viability without reducing normal cells viability. Thus, ACSL/SCD network stimulates colon cancer progression through conferring increased energetic capacity and invasive and migratory properties to cancer cells, and might represent a new therapeutic opportunity for colon cancer treatment.