Coronaviruses (CoVs), enveloped positive-sense RNA viruses, are a group of viruses that cause infections in the human respiratory tract, which can be characterized clinically from mild to fatal. The severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) is the virus responsible. The global spread of COVID‑19 can be described as the worst pandemic in humanity in the last century. To date, COVID‑19 has infected more than 3,000,000 people worldwide and killed more than 200,000 people. All age groups can be infected from the virus, but more serious symptoms that can possibly result in death are observed in older people and those with underlying medical conditions such as cardiovascular and pulmonary disease. Novel data report more severe symptoms and even a negative prognosis for the obese patients. A growing body of evidence connects obesity with COVID‑19 and a number of mechanisms from immune system activity attenuation to chronic inflammation are implicated. Lipid peroxidation creates reactive lipid aldehydes which in a patient with metabolic disorder and COVID‑19 will affect its prognosis. Finally, pregnancy‑associated obesity needs to be studied further in connection to COVID‑19 as this infection could pose high risk both to pregnant women and the fetus.

The lifestyle adopted by most people in Western societies has an important impact on the propensity to metabolic disorders (e.g., diabetes, cancer, cardiovascular disease, neurodegenerative diseases). This is often accompanied by chronic low-grade inflammation, driven by the activation of various molecular pathways such as STAT3 (signal transducer and activator of transcription 3), IKK (IκB kinase), MMP9 (matrix metallopeptidase 9), MAPK (mitogen-activated protein kinases), COX2 (cyclooxigenase 2), and NF-Kβ (nuclear factor kappa-light-chain-enhancer of activated B cells). Multiple intervention studies have demonstrated that lifestyle changes can lead to reduced inflammation and improved health. This can be linked to the concept of real-life risk simulation, since humans are continuously exposed to dietary factors in small doses and complex combinations (e.g., polyphenols, fibers, polyunsaturated fatty acids, etc.). Inflammation biomarkers improve in patients who consume a certain amount of fiber per day; some even losing weight. Fasting in combination with calorie restriction modulates molecular mechanisms such as m-TOR, FOXO, NRF2, AMPK, and sirtuins, ultimately leads to significantly reduced inflammatory marker levels, as well as improved metabolic markers. Moving toward healthier dietary habits at the individual level and in publicly-funded institutions, such as schools or hospitals, could help improving public health, reducing healthcare costs and improving community resilience to epidemics (such as COVID-19), which predominantly affects individuals with metabolic diseases.

Fasting is increasingly practiced to improve health and general well-being, as well as for its cytoprotective effects. Changes in blood redox status, linked to the development of a variety of metabolic diseases, have been recently documented during calorie restriction and intermittent fasting, but not with long-term fasting (LF). We investigated some parameters of the blood redox profile in 109 subjects before and after a 10-day fasting period. Fasting resulted in a significant reduction in body weight, improved well-being and had a beneficial modulating effect on blood lipids and glucose regulation. We observed that fasting decreased lipid peroxidation (TBARS) and increased total antioxidant capacity (TAC) in plasma, concomitant with a uric acid elevation, known to be associated with fasting and did not cause gout attacks. Reduced glutathione (GSH), glutathione reductase (GR), glutathione peroxidase (GPx) and catalase in erythrocytes did not show significant changes. In addition, reduction in body weight, waist circumference, and glucose levels were associated to a reduced lipid peroxidation. Similar results were obtained by grouping subjects on the basis of the changes in their GSH levels, showing that a period of 10 days fasting improves blood redox status regardless of GSH status in the blood.

Imbalance between oxidative stress burden and antioxidant capacity is implicated in the course of atherosclerosis among type 2 diabetic patients. We addressed the effects of insulin, glucagon-like peptide-1 receptor agonists (GLP1-RA), sodium-glucose cotransporter-2 inhibitors (SGLT-2i), and their combination on levels of oxidant and antioxidant biomarkers. We recruited a total of 160 type 2 diabetics, who received insulin (n = 40), liraglutide (n = 40), empagliflozin (n = 40), or their combination (GLP-1RA+SGLT-2i) (n = 40). We measured at baseline, at 4 and at 12 months of treatment: (a) Thiobarbituric Acid Reactive Substances (TBARS), (b) Malondialdehyde (MDA), (c) Reducing Power (RP), (d) 2,2¢-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) radical (ABTS) and (e) Total Antioxidant Capacity TAC). Dual treatment resulted in significant improvement of TBARS, MDA, and ABTS at four months compared with the other groups (p < 0.05 for all comparisons). At twelve months, all participants improved TBARS, MDA, and ABTS (p < 0.05). At 12 months, GLP1-RA and GLP-1RA+SGLT2-i provided a greater reduction of TBARS (−8.76% and −9.83%) compared with insulin or SGLT2i (−0.5% and 3.22%), (p < 0.05). GLP1-RA and GLP-1RA+SGLT-2i showed a greater reduction of MDA (−30.15% and −31.44%) compared with insulin or SGLT2i (4.72% and −3.74%), (p < 0.05). SGLT2i and GLP-1RA+SGLT2-i showed increase of ABTS (12.87% and 14.13%) compared with insulin or GLP1-RA (2.44% and −3.44%), (p < 0.05). Only combined treatment resulted in increase of TAC compared with the other groups after 12 months of treatment (p < 0.05).12-month treatment with GLP1-RA and SGLT2i resulted in reduction of biomarkers responsible for oxidative modifications and increase of antioxidant biomarker, respectively. The combination treatment was superior and additive to each separate agent and also the beneficial effects appeared earlier.

In this research, a model for the estimation of antioxidant content in cherry fruits from multispectral imagery acquired from drones was developed, based on machine learning methods. For two consecutive cultivation years, the trees were sampled on different dates and then analysed for their fruits’ radical scavenging activity (DPPH) and Folin–Ciocalteu (FCR) reducing capacity. Multispectral images from unmanned aerial vehicles were acquired on the same dates with fruit sampling. Soil samples were collected throughout the study fields at the end of the season. Topographic, hydrographic and weather data also were included in modelling. First-year data were used for model-fitting, whereas second-year data for testing. Spatial autocorrelation tests indicated unbiased sampling and, moreover, allowed restriction of modelling input parameters to a smaller group. The optimum model employs 24 input variables resulting in a 6.74 root mean square error. Provided that soil profiles and other ancillary data are known in advance of the cultivation season, capturing drone images in critical growth phases, together with contemporary weather data, can support site- and time-specific harvesting. It could also support site-specific treatments (precision farming) for improving fruit quality in the long-term, with analogous marketing perspectives.