Clinically pure PLS can be defined by isolated UMN signs 4 years after symptom onset, and is a syndrome of slow progression with high levels of function. Prior to the fourth year, the diagnosis of PLS cannot be made with certainty because many patients develop LMN signs. UMN-dominant ALS, defined by predominantly UMN disease with minor LMN signs, has disability similar to ALS, but slower progression.

Acute facial nerve disease leading to peripheral facial paralysis is commonly associated with viral infections. COVID-19 may be a potential cause of peripheral facial paralysis and neurological symptoms could be the first and only manifestation of the disease. We report a case of a term pregnancy diagnosed with COVID-19 after presenting with isolated peripheral facial palsy.

Accurate contextual decision-making strategies are important in social environments. Specific areas in the brain are tasked to process these complex interactions and generate correct follow-up responses. The dorsolateral and dorsomedial parts of the telencephalon in the teleost fish brain are neural substrates modulated by the neurotransmitter dopamine (DA), and are part of an important neural circuitry that drives animal behaviour from the most basic actions such as learning to search for food, to properly choosing partners and managing decisions based on context. The Indo-Pacific cleaner wrasse Labroides dimidiatus is a highly social teleost fish species with a complex network of interactions with its 'client' reef fish. We asked if changes in DA signalling would affect individual learning ability by presenting cleaner fish two ecologically different tasks that simulated a natural situation requiring accurate decisionmaking. We demonstrate that there is an involvement of the DA system and D 1 receptor pathways on cleaners' natural abilities to learn both tasks. Our results add significantly to the growing literature on the physiological mechanisms that underlie and facilitate the expression of cooperative abilities.

Infectious diseases, such as tuberculosis (TB) and the novel coronavirus (COVID-19) relate to environmental factors, understanding of which is essential to inform policy and practice and tackle them effectively. The review follows the conceptual framework offered by the World Health Organization Commission on Social Determinants of Health (defined as “all those material, psychological and behavioural circumstances linked to health and generically indicated as risk factors’ in the conventional epidemiological language”). It describes the social factors behind TB and COVID-19, the commonalities between the two diseases, and what can be learned so far from the published best practices. The social determinants sustaining TB and COVID-19 underline the importance of prioritising health and allocating adequate financial and human resources to achieve universal health coverage and health-related social protection while addressing the needs of vulnerable populations. Rapid and effective measures against poverty and other major social determinants and sources of inequality are urgently needed to develop better health in the post-COVID-19 world.

Higher GDF-15 associated with worse prognosis in acute HF independently of BNP. When both biomarkers GDF-15 and BNP were elevated at discharge, the 2-year mortality risk increased over four-fold. Biomarkers related to different pathophysiological pathways can provide incremental prognostic information in acute HF.

Physical exercise (PE) has become an essential tool for different rehabilitation programs. High-intensity exercises (HIEs) have been demonstrated to provide better results in general health conditions, compared with low and moderate-intensity exercises. In this context, monitoring of a patients’ condition is essential to avoid extreme fatigue conditions, which may cause physical and physiological complications. Different methods have been proposed for fatigue estimation, such as: monitoring the subject’s physiological parameters and subjective scales. However, there is still a need for practical procedures that provide an objective estimation, especially for HIEs. In this work, considering that the sit-to-stand (STS) exercise is one of the most implemented in physical rehabilitation, a computational model for estimating fatigue during this exercise is proposed. A study with 60 healthy volunteers was carried out to obtain a data set to develop and evaluate the proposed model. According to the literature, this model estimates three fatigue conditions (low, moderate, and high) by monitoring 32 STS kinematic features and the heart rate from a set of ambulatory sensors (Kinect and Zephyr sensors). Results show that a random forest model composed of 60 sub-classifiers presented an accuracy of 82.5% in the classification task. Moreover, results suggest that the movement of the upper body part is the most relevant feature for fatigue estimation. Movements of the lower body and the heart rate also contribute to essential information for identifying the fatigue condition. This work presents a promising tool for physical rehabilitation.

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