State-level tracking of COVID-19 in the United States

As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available deathdata within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on therate of transmission of SARS-CoV-2. We estimate thatRtwas only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals

Finding the “Dark Matter” in Human and Yeast Protein Network Prediction and Modelling

Accurate modelling of biological systems requires a deeper and more complete knowledge about the molecular components and their functional associations than we currently have. Traditionally, new knowledge on protein associations generated by experiments has played a central role in systems modelling, in contrast to generally less trusted bio-computational predictions. However, we will not achieve realistic modelling of complex molecular systems if the current experimental designs lead to biased screenings of real protein networks and leave large, functionally important areas poorly characterised. To assess the likelihood of this, we have built comprehensive network models of the yeast and human proteomes by using a meta-statistical integration of diverse computationally predicted protein association datasets. We have compared these predicted networks against combined experimental datasets from seven biological resources at different level of statistical significance. These eukaryotic predicted networks resemble all the topological and noise features of the experimentally inferred networks in both species, and we also show that this observation is not due to random behaviour. In addition, the topology of the predicted networks contains information on true protein associations, beyond the constitutive first order binary predictions. We also observe that most of the reliable predicted protein associations are experimentally uncharacterised in our models, constituting the hidden or “dark matter” of networks by analogy to astronomical systems. Some of this dark matter shows enrichment of particular functions and contains key functional elements of protein networks, such as hubs associated with important functional areas like the regulation of Ras protein signal transduction in human cells. Thus, characterising this large and functionally important dark matter, elusive to established experimental designs, may be crucial for modelling biological systems. In any case, these predictions provide a valuable guide to these experimentally elusive regions

Recognition and diagnosis of sleep disorders in Parkinson's disease

Contains fulltext : 109296.pdf (publisher's version ) (Open Access)Sleep disturbances are among the most frequent and incapacitating non-motor symptoms of Parkinson's disease (PD), and are increasingly recognized as an important determinant of impaired quality of life. Here we review several recent developments regarding the recognition and diagnosis of sleep disorders in PD. In addition, we provide a practical and easily applicable approach to the diagnostic process as a basis for tailored therapeutic interventions. This includes a stepwise scheme that guides the clinical interview and subsequent ancillary investigations. In this scheme, the various possible sleep disorders are arranged not in order of prevalence, but in a 'differential diagnostic' order. We also provide recommendations for the use of sleep registrations such as polysomnography. Furthermore, we point out when a sleep specialist could be consulted to provide additional diagnostic and therapeutic input. This structured approach facilitates early detection of sleep disturbances in PD, so treatment can be initiated promptly

Mechanisms and therapeutic applications of electromagnetic therapy in Parkinson's disease

© 2015 Vadalà et al. Electromagnetic therapy is a non-invasive and safe approach for the management of several pathological conditions including neurodegenerative diseases. Parkinson's disease is a neurodegenerative pathology caused by abnormal degeneration of dopaminergic neurons in the ventral tegmental area and substantia nigra pars compacta in the midbrain resulting in damage to the basal ganglia. Electromagnetic therapy has been extensively used in the clinical setting in the form of transcranial magnetic stimulation, repetitive transcranial magnetic stimulation, high-frequency transcranial magnetic stimulation and pulsed electromagnetic field therapy which can also be used in the domestic setting. In this review, we discuss the mechanisms and therapeutic applications of electromagnetic therapy to alleviate motor and non-motor deficits that characterize Parkinson's disease

Adipose-derived stem cells; selecting for translational success

We have witnessed a rapid expansion of in vitro characterization and differentiation of adipose-derived stem cells, with increasing translation to both in vivo models and a breadth of clinical specialties. However, an appreciation of the truly heterogeneous nature of this unique stem cell group has identified a need to more accurately delineate subpopulations by any of a host of methods, to include functional properties or surface marker expression. Cells selected for improved proliferative, differentiative, angiogenic or ischemia-resistant properties are but a few attributes that could prove beneficial for targeted treatments or therapies. Optimizing cell culture conditions to permit re-introduction to patients is critical for clinical translation

Arterial injuries at the elbow carry a high risk of muscle necrosis and warrant urgent revascularisation

INTRODUCTION: Revascularisation following axial arterial system injury is effective in upper limb salvage but necrosis of muscle, the tissue most sensitive to ischaemia, may still occur. We examined the frequency of necrosis, its related factors and its functional significance. METHODS: The clinical findings and operative management of 13 patients with injuries at the elbow referred to 2 plastic surgical hand surgery units over a 30-month period were reviewed. Good outcome was defined as minimal impairment with return to previous occupation, intermediate outcome as moderate impairment with change in occupation and poor outcome as major functional loss preventing work. RESULTS: Seven patients injured the brachial and six injured both the radial and ulnar arteries. Concomitant injuries were severe with nerve injuries in 11 and muscle damage in 12 patients. Functional outcome was good in four cases, intermediate in four and poor in five. Muscle necrosis developed in four brachial artery injuries. In all four cases, initial successful revascularisation failed post-operatively. Case review revealed delayed recognition in three cases where pain heralded ischaemia but distal skin circulation and pulses were adequate. Of patients with necrosis, three had a poor outcome and one had an intermediate outcome. CONCLUSIONS: The risk of muscle necrosis must be considered when managing these injuries, particularly if initial revascularisation is unsuccessful. Every effort should be made to optimise repair technique and post-operative monitoring. Limb salvage is no longer enough. Fully viable muscle is necessary to restore function and livelihoods