Vulnerability and Protective Factors for PTSD and Depression Symptoms Among Healthcare Workers During COVID-19: A Machine Learning Approach

Background: Healthcare workers are at high risk for developing mental health problems during the COVID-19 pandemic. There is an urgent need to identify vulnerability and protective factors related to the severity of psychiatric symptoms among healthcare workers to implement targeted prevention and intervention programs to reduce the mental health burden worldwide during COVID-19. // Objective: The present study aimed to apply a machine learning approach to predict depression and PTSD symptoms based on psychometric questions that assessed: (1) the level of stress due to being isolated from one's family; (2) professional recognition before and during the pandemic; and (3) altruistic acceptance of risk during the COVID-19 pandemic among healthcare workers. // Methods: A total of 437 healthcare workers who experienced some level of isolation at the time of the pandemic participated in the study. Data were collected using a web survey conducted between June 12, 2020, and September 19, 2020. We trained two regression models to predict PTSD and depression symptoms. Pattern regression analyses consisted of a linear epsilon-insensitive support vector machine (ε-SVM). Predicted and actual clinical scores were compared using Pearson's correlation coefficient (r), the coefficient of determination (r2), and the normalized mean squared error (NMSE) to evaluate the model performance. A permutation test was applied to estimate significance levels. // Results: Results were significant using two different cross-validation strategies to significantly decode both PTSD and depression symptoms. For all of the models, the stress due to social isolation and professional recognition were the variables with the greatest contributions to the predictive function. Interestingly, professional recognition had a negative predictive value, indicating an inverse relationship with PTSD and depression symptoms. // Conclusions: Our findings emphasize the protective role of professional recognition and the vulnerability role of the level of stress due to social isolation in the severity of posttraumatic stress and depression symptoms. The insights gleaned from the current study will advance efforts in terms of intervention programs and public health messaging

Clinical practice. Diagnosis and treatment of cow’s milk allergy

Introduction Cow's milk allergy (CMA) is thought to affect 2-3% of infants. The signs and symptoms are nonspecific and may be difficult to objectify, and as the diagnosis requires cow's milk elimination followed by challenge, often, children are considered cow's milk allergic without proven diagnosis. Diagnosis Because of the consequences, a correct diagnosis of CMA is pivotal. Open challenges tend to overestimate the number of children with CMA. The only reliable way to diagnose CMA is by double-blind, placebo-controlled challenge (DBPCFC). Therapy At present, the only proven treatment consists of elimination of cow's milk protein from the child's diet and the introduction of formulas based on extensively hydrolysed whey protein or casein; amino acid-based formula is rarely indicated. The majority of children will regain tolerance to cow's milk within the first 5 years of life. Conclusions Open challenges can be used to reject CMA, but for adequate diagnosis, DBPCFC is mandatory. In most children, CMA can be adequately treated with extensively hydrolysed whey protein or casein formulas

Limited effect of chronic valproic acid treatment in a mouse model of Machado-Joseph disease

Machado-Joseph disease (MJD) is an inherited neurodegenerative disease, caused by a CAG repeat expansion within the coding region of ATXN3 gene, and which currently lacks effective treatment. In this work we tested the therapeutic efficacy of chronic treatment with valproic acid (VPA) (200mg/kg), a compound with known neuroprotection activity, and previously shown to be effective in cell, fly and nematode models of MJD. We show that chronic VPA treatment in the CMVMJD135 mouse model had limited effects in the motor deficits of these mice, seen mostly at late stages in the motor swimming, beam walk, rotarod and spontaneous locomotor activity tests, and did not modify the ATXN3 inclusion load and astrogliosis in affected brain regions. However, VPA chronic treatment was able to increase GRP78 protein levels at 30 weeks of age, one of its known neuroprotective effects, confirming target engagement. In spite of limited results, the use of another dosage of VPA or of VPA in a combined therapy with molecules targeting other pathways, cannot be excluded as potential strategies for MJD therapeuticsPM received funding from Ataxia UK Grant (Project: Pharmacologic therapy for Machado-Joseph disease: from a C. elegans drug screen to a mouse model validation). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio