Regulations & exemptions during the COVID-19 pandemic for new medical technology, health services & data

The rapid evolution of the COVID-19 pandemic has sparked a large unmet need for new or additional medical technology and healthcare services to be made available urgently. Healthcare, Academic, Government and Industry organizations and individuals have risen to this challenge by designing, developing, manufacturing or implementing innovation. However, both they and healthcare stakeholders are hampered as it is unclear how to introduce and deploy the products of this innovation quickly and legally within the healthcare system. Our paper outlines the key regulations and processes innovators need to comply with, and how these change during a public health emergency via dedicated exemptions. Our work includes references to the formal documents regarding UK healthcare regulation and governance, and is meant to serve as a guide for those who wish to act quickly but are uncertain of the legal and regulatory pathways that allow new a device or service to be fast-tracked

The management of the painful bipartite patella: a systematic review

Purpose: This study aimed to identify the most effective method for the treatment of the symptomatic bipartite patella. Methods: A systematic review of the literature was completed, and all studies assessing the management of a bipartite patella were included. Owing to the paucity of randomised controlled trials, a narrative review of 22 studies was completed. A range of treatments were assessed: conservative measures, open and arthroscopic fixation or excision and soft tissue release and excision. Results: All of the methods provided results ranging from good to excellent, with acceptable complication rates. Conclusions: This is a poorly answered treatment question. No firm guidance can be given as to the most appropriate method of treating the symptomatic bipartite patella. This study suggests that there are a number of effective treatments with acceptable complication rates and it may be that treatments that conserve the patella are more appropriate for larger fragments

A nonlinear updating algorithm captures suboptimal inference in the presence of signal-dependent noise

Bayesian models have advanced the idea that humans combine prior beliefs and sensory observations to optimize behavior. How the brain implements Bayes-optimal inference, however, remains poorly understood. Simple behavioral tasks suggest that the brain can flexibly represent probability distributions. An alternative view is that the brain relies on simple algorithms that can implement Bayes-optimal behavior only when the computational demands are low. To distinguish between these alternatives, we devised a task in which Bayes-optimal performance could not be matched by simple algorithms. We asked subjects to estimate and reproduce a time interval by combining prior information with one or two sequential measurements. In the domain of time, measurement noise increases with duration. This property takes the integration of multiple measurements beyond the reach of simple algorithms. We found that subjects were able to update their estimates using the second measurement but their performance was suboptimal, suggesting that they were unable to update full probability distributions. Instead, subjects’ behavior was consistent with an algorithm that predicts upcoming sensory signals, and applies a nonlinear function to errors in prediction to update estimates. These results indicate that the inference strategies employed by humans may deviate from Bayes-optimal integration when the computational demands are high

The Extracellular Matrix Component Psl Provides Fast-Acting Antibiotic Defense in Pseudomonas aeruginosa Biofilms

Bacteria within biofilms secrete and surround themselves with an extracellular matrix, which serves as a first line of defense against antibiotic attack. Polysaccharides constitute major elements of the biofilm matrix and are implied in surface adhesion and biofilm organization, but their contributions to the resistance properties of biofilms remain largely elusive. Using a combination of static and continuous-flow biofilm experiments we show that Psl, one major polysaccharide in the Pseudomonas aeruginosa biofilm matrix, provides a generic first line of defense toward antibiotics with diverse biochemical properties during the initial stages of biofilm development. Furthermore, we show with mixed-strain experiments that antibiotic-sensitive “non-producing” cells lacking Psl can gain tolerance by integrating into Psl-containing biofilms. However, non-producers dilute the protective capacity of the matrix and hence, excessive incorporation can result in the collapse of resistance of the entire community. Our data also reveal that Psl mediated protection is extendible to E. coli and S. aureus in co-culture biofilms. Together, our study shows that Psl represents a critical first bottleneck to the antibiotic attack of a biofilm community early in biofilm development.National Institutes of Health (U.S.). National Institute of Environmental Health Sciences (Training Grant in Toxicology 5 T32 ES7020-37

Prenatal Excess Glucocorticoid Exposure and Adult Affective Disorders:A Role for Serotonergic and Catecholamine Pathways

Fetal glucocorticoid exposure is a key mechanism proposed to underlie prenatal ‘programming’ of adult affective behaviours such as depression and anxiety. Indeed, the glucocorticoid metabolising enzyme 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2), which is highly expressed in the placenta and the developing fetus, acts as a protective barrier from the high maternal glucocorticoids which may alter developmental trajectories. The programmed changes resulting from maternal stress or bypass or from the inhibition of 11β-HSD2 are frequently associated with alterations in the hypothalamic-pituitary-adrenal (HPA) axis. Hence, circulating glucocorticoid levels are increased either basally or in response to stress accompanied by CNS region-specific modulations in the expression of both corticosteroid receptors (mineralocorticoid and glucocorticoid receptors). Furthermore, early-life glucocorticoid exposure also affects serotonergic and catecholamine pathways within the brain, with changes in both associated neurotransmitters and receptors. Indeed, global removal of 11β-HSD2, an enzyme that inactivates glucocorticoids, increases anxiety‐ and depressive-like behaviour in mice; however, in this case the phenotype is not accompanied by overt perturbation in the HPA axis but, intriguingly, alterations in serotonergic and catecholamine pathways are maintained in this programming model. This review addresses one of the potential adverse effects of glucocorticoid overexposure in utero, i.e. increased incidence of affective behaviours, and the mechanisms underlying these behaviours including alteration of the HPA axis and serotonergic and catecholamine pathways

mTOR: from growth signal integration to cancer, diabetes and ageing

In all eukaryotes, the target of rapamycin (TOR) signalling pathway couples energy and nutrient abundance to the execution of cell growth and division, owing to the ability of TOR protein kinase to simultaneously sense energy, nutrients and stress and, in metazoans, growth factors. Mammalian TOR complex 1 (mTORC1) and mTORC2 exert their actions by regulating other important kinases, such as S6 kinase (S6K) and Akt. In the past few years, a significant advance in our understanding of the regulation and functions of mTOR has revealed the crucial involvement of this signalling pathway in the onset and progression of diabetes, cancer and ageing.National Institutes of Health (U.S.)Howard Hughes Medical InstituteWhitehead Institute for Biomedical ResearchJane Coffin Childs Memorial Fund for Medical Research (Postdoctoral Fellowship)Human Frontier Science Program (Strasbourg, France

Self versus Environment Motion in Postural Control

To stabilize our position in space we use visual information as well as non-visual physical motion cues. However, visual cues can be ambiguous: visually perceived motion may be caused by self-movement, movement of the environment, or both. The nervous system must combine the ambiguous visual cues with noisy physical motion cues to resolve this ambiguity and control our body posture. Here we have developed a Bayesian model that formalizes how the nervous system could solve this problem. In this model, the nervous system combines the sensory cues to estimate the movement of the body. We analytically demonstrate that, as long as visual stimulation is fast in comparison to the uncertainty in our perception of body movement, the optimal strategy is to weight visually perceived movement velocities proportional to a power law. We find that this model accounts for the nonlinear influence of experimentally induced visual motion on human postural behavior both in our data and in previously published results

Learning Priors for Bayesian Computations in the Nervous System

Our nervous system continuously combines new information from our senses with information it has acquired throughout life. Numerous studies have found that human subjects manage this by integrating their observations with their previous experience (priors) in a way that is close to the statistical optimum. However, little is known about the way the nervous system acquires or learns priors. Here we present results from experiments where the underlying distribution of target locations in an estimation task was switched, manipulating the prior subjects should use. Our experimental design allowed us to measure a subject's evolving prior while they learned. We confirm that through extensive practice subjects learn the correct prior for the task. We found that subjects can rapidly learn the mean of a new prior while the variance is learned more slowly and with a variable learning rate. In addition, we found that a Bayesian inference model could predict the time course of the observed learning while offering an intuitive explanation for the findings. The evidence suggests the nervous system continuously updates its priors to enable efficient behavior

Bayesian Inference Underlies the Contraction Bias in Delayed Comparison Tasks

Delayed comparison tasks are widely used in the study of working memory and perception in psychology and neuroscience. It has long been known, however, that decisions in these tasks are biased. When the two stimuli in a delayed comparison trial are small in magnitude, subjects tend to report that the first stimulus is larger than the second stimulus. In contrast, subjects tend to report that the second stimulus is larger than the first when the stimuli are relatively large. Here we study the computational principles underlying this bias, also known as the contraction bias. We propose that the contraction bias results from a Bayesian computation in which a noisy representation of a magnitude is combined with a-priori information about the distribution of magnitudes to optimize performance. We test our hypothesis on choice behavior in a visual delayed comparison experiment by studying the effect of (i) changing the prior distribution and (ii) changing the uncertainty in the memorized stimulus. We show that choice behavior in both manipulations is consistent with the performance of an observer who uses a Bayesian inference in order to improve performance. Moreover, our results suggest that the contraction bias arises during memory retrieval/decision making and not during memory encoding. These results support the notion that the contraction bias illusion can be understood as resulting from optimality considerations

The Second-Agent Effect: Communicative Gestures Increase the Likelihood of Perceiving a Second Agent

Background: Beyond providing cues about an agent’s intention, communicative actions convey information about the presence of a second agent towards whom the action is directed (second-agent information). In two psychophysical studies we investigated whether the perceptual system makes use of this information to infer the presence of a second agent when dealing with impoverished and/or noisy sensory input. Methodology/Principal Findings: Participants observed point-light displays of two agents (A and B) performing separate actions. In the Communicative condition, agent B’s action was performed in response to a communicative gesture by agent A. In the Individual condition, agent A’s communicative action was replaced with a non-communicative action. Participants performed a simultaneous masking yes-no task, in which they were asked to detect the presence of agent B. In Experiment 1, we investigated whether criterion c was lowered in the Communicative condition compared to the Individual condition, thus reflecting a variation in perceptual expectations. In Experiment 2, we manipulated the congruence between A’s communicative gesture and B’s response, to ascertain whether the lowering of c in the Communicative condition reflected a truly perceptual effect. Results demonstrate that information extracted from communicative gestures influences the concurrent processing of biological motion by prompting perception of a second agent (second-agent effect). Conclusions/Significance: We propose that this finding is best explained within a Bayesian framework, which gives