SARS-CoV-2 infection in multiple sclerosis patients: interaction with treatments, adjuvant therapies, and vaccines against COVID-19.

The SARS-CoV-2 pandemic has raised particular concern for people with Multiple Sclerosis, as these people are believed to be at increased risk of infection, especially those being treated with disease-modifying therapies. Therefore, the objective of this review was to describe how COVID-19 affects people who suffer from Multiple Sclerosis, evaluating the risk they have of suffering an infection by this virus, according to the therapy to which they are subjected as well as the immune response of these patients both to infection and vaccines and the neurological consequences that the virus can have in the long term. The results regarding the increased risk of infection due to treatment are contradictory. B-cell depletion therapies may cause patients to have a lower probability of generating a detectable neutralizing antibody titer. However, more studies are needed to help understand how this virus works, paying special attention to long COVID and the neurological symptoms that it causes.

COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain.

Many types of research have been carried out with the aim of combating the COVID-19 pandemic since the first outbreak was detected in Wuhan, China. Anticipating the evolution of an outbreak helps to devise suitable economic, social and health care strategies to mitigate the effects of the virus. For this reason, predicting the SARS-CoV-2 transmission rate has become one of the most important and challenging problems of the past months. In this paper, we apply a two-stage mid and long-term forecasting framework to the epidemic situation in eight districts of Andalusia, Spain. First, an analytical procedure is performed iteratively to fit polynomial curves to the cumulative curve of contagions. Then, the extracted information is used for estimating the parameters and structure of an evolutionary artificial neural network with hybrid architectures (i.e., with different basis functions for the hidden nodes) while considering single and simultaneous time horizon estimations. The results obtained demonstrate that including polynomial information extracted during the training stage significantly improves the mid- and long-term estimations in seven of the eight considered districts. The increase in average accuracy (for the joint mid- and long-term horizon forecasts) is 37.61% and 35.53% when considering the single and simultaneous forecast approaches, respectively.

Melatonin and multiple sclerosis: antioxidant, anti-inflammatory and immunomodulator mechanism of action.

BACKGROUND: Melatonin is an indole hormone secreted primarily by the pineal gland that showing anti-oxidant, anti-inflammatory and anti-apoptotic capacity. It can play an important role in the pathophysiological mechanisms of various diseases. In this regard, different studies have shown that there is a relationship between Melatonin and Multiple Sclerosis (MS). MS is a chronic immune-mediated disease of the Central Nervous System. AIM: The objective of this review was to evaluate the mechanisms of action of melatonin on oxidative stress, inflammation and intestinal dysbiosis caused by MS, as well as its interaction with different hormones and factors that can influence the pathophysiology of the disease. RESULTS: Melatonin causes a significant increase in the levels of catalase, superoxide dismutase, glutathione peroxidase, glutathione and can counteract and inhibit the effects of the NLRP3 inflammasome, which would also be beneficial during SARS-CoV-2 infection. In addition, melatonin increases antimicrobial peptides, especially Reg3ß, which could be useful in controlling the microbiota. CONCLUSION: Melatonin could exert a beneficial effect in people suffering from MS, running as a promising candidate for the treatment of this disease. However, more research in human is needed to help understand the possible interaction between melatonin and certain sex hormones, such as estrogens, to know the potential therapeutic efficacy in both men and women.

Real world evidence of calcifediol or vitamin D prescription and mortality rate of COVID-19 in a retrospective cohort of hospitalized Andalusian patients.

COVID-19 is a major worldwide health problem because of acute respiratory distress syndrome, and mortality. Several lines of evidence have suggested a relationship between the vitamin D endocrine system and severity of COVID-19. We present a survival study on a retrospective cohort of 15,968 patients, comprising all COVID-19 patients hospitalized in Andalusia between January and November 2020. Based on a central registry of electronic health records (the Andalusian Population Health Database, BPS), prescription of vitamin D or its metabolites within 15-30 days before hospitalization were recorded. The effect of prescription of vitamin D (metabolites) for other indication previous to the hospitalization was studied with respect to patient survival. Kaplan-Meier survival curves and hazard ratios support an association between prescription of these metabolites and patient survival. Such association was stronger for calcifediol (Hazard Ratio, HR = 0.67, with 95% confidence interval, CI, of [0.50-0.91]) than for cholecalciferol (HR = 0.75, with 95% CI of [0.61-0.91]), when prescribed 15 days prior hospitalization. Although the relation is maintained, there is a general decrease of this effect when a longer period of 30 days prior hospitalization is considered (calcifediol HR = 0.73, with 95% CI [0.57-0.95] and cholecalciferol HR = 0.88, with 95% CI [0.75, 1.03]), suggesting that association was stronger when the prescription was closer to the hospitalization.

Implementing Personalized Medicine in COVID-19 in Andalusia: An Opportunity to Transform the Healthcare System.

The COVID-19 pandemic represents an unprecedented opportunity to exploit the advantages of personalized medicine for the prevention, diagnosis, treatment, surveillance and management of a new challenge in public health. COVID-19 infection is highly variable, ranging from asymptomatic infections to severe, life-threatening manifestations. Personalized medicine can play a key role in elucidating individual susceptibility to the infection as well as inter-individual variability in clinical course, prognosis and response to treatment. Integrating personalized medicine into clinical practice can also transform health care by enabling the design of preventive and therapeutic strategies tailored to individual profiles, improving the detection of outbreaks or defining transmission patterns at an increasingly local level. SARS-CoV2 genome sequencing, together with the assessment of specific patient genetic variants, will support clinical decision-makers and ultimately better ways to fight this disease. Additionally, it would facilitate a better stratification and selection of patients for clinical trials, thus increasing the likelihood of obtaining positive results. Lastly, defining a national strategy to implement in clinical practice all available tools of personalized medicine in COVID-19 could be challenging but linked to a positive transformation of the health care system. In this review, we provide an update of the achievements, promises, and challenges of personalized medicine in the fight against COVID-19 from susceptibility to natural history and response to therapy, as well as from surveillance to control measures and vaccination. We also discuss strategies to facilitate the adoption of this new paradigm for medical and public health measures during and after the pandemic in health care systems.