Mistakes that affect others: An fMRI study on processing of own errors in a social context

In social contexts, errors have a special significance and often bear consequences for others. Thinking about others and drawing social inferences in interpersonal games engages the mentalizing system. We used neuroimaging to investigate the differences in brain activations between errors that affect only agents themselves and errors that additionally influence the payoffs of interaction partners. Activation in posterior medial frontal cortex (pMFC) and bilateral insula was increased for all errors, whereas errors that implied consequences for others specifically activated medial prefrontal cortex (mPFC), an important part of the mentalizing system. The results demonstrate that performance monitoring in social contexts involves additional processes and brain structures compared with individual performance monitoring where errors only have consequences for the person committing them. Taking into account how one’s behavior may affect others is particularly crucial for adapting behavior in interpersonal interactions and joint action

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models

Risk of COVID-19-related death among patients with chronic obstructive pulmonary disease or asthma prescribed inhaled corticosteroids: an observational cohort study using the OpenSAFELY platform

BACKGROUND: Early descriptions of patients admitted to hospital during the COVID-19 pandemic showed a lower prevalence of asthma and chronic obstructive pulmonary disease (COPD) than would be expected for an acute respiratory disease like COVID-19, leading to speculation that inhaled corticosteroids (ICSs) might protect against infection with severe acute respiratory syndrome coronavirus 2 or the development of serious sequelae. We assessed the association between ICS and COVID-19-related death among people with COPD or asthma using linked electronic health records (EHRs) in England, UK. METHODS: In this observational study, we analysed patient-level data for people with COPD or asthma from primary care EHRs linked with death data from the Office of National Statistics using the OpenSAFELY platform. The index date (start of follow-up) for both cohorts was March 1, 2020; follow-up lasted until May 6, 2020. For the COPD cohort, individuals were eligible if they were aged 35 years or older, had COPD, were a current or former smoker, and were prescribed an ICS or long-acting β agonist plus long-acting muscarinic antagonist (LABA-LAMA) as combination therapy within the 4 months before the index date. For the asthma cohort, individuals were eligible if they were aged 18 years or older, had been diagnosed with asthma within 3 years of the index date, and were prescribed an ICS or short-acting β agonist (SABA) only within the 4 months before the index date. We compared the outcome of COVID-19-related death between people prescribed an ICS and those prescribed alternative respiratory medications: ICSs versus LABA-LAMA for the COPD cohort, and low-dose or medium-dose and high-dose ICSs versus SABAs only in the asthma cohort. We used Cox regression models to estimate hazard ratios (HRs) and 95% CIs for the association between exposure categories and the outcome in each population, adjusted for age, sex, and all other prespecified covariates. We calculated e-values to quantify the effect of unmeasured confounding on our results. FINDINGS: We identified 148 557 people with COPD and 818 490 people with asthma who were given relevant respiratory medications in the 4 months before the index date. People with COPD who were prescribed ICSs were at increased risk of COVID-19-related death compared with those prescribed LABA-LAMA combinations (adjusted HR 1·39 [95% CI 1·10-1·76]). Compared with those prescribed SABAs only, people with asthma who were prescribed high-dose ICS were at an increased risk of death (1·55 [1·10-2·18]), whereas those given a low or medium dose were not (1·14 [0·85-1·54]). Sensitivity analyses showed that the apparent harmful association we observed could be explained by relatively small health differences between people prescribed ICS and those not prescribed ICS that were not recorded in the database (e value lower 95% CI 1·43). INTERPRETATION: Our results do not support a major role for regular ICS use in protecting against COVID-19-related death among people with asthma or COPD. Observed increased risks of COVID-19-related death can be plausibly explained by unmeasured confounding due to disease severity. FUNDING: UK Medical Research Council

A Spoonful of Math Helps the Medicine Go Down: An Illustration of How Healthcare can Benefit from Mathematical Modeling and Analysis

<p>Abstract</p> <p>Objectives</p> <p>A recent joint report from the Institute of Medicine and the National Academy of Engineering, highlights the benefits of--indeed, the need for--mathematical analysis of healthcare delivery. Tools for such analysis have been developed over decades by researchers in Operations Research (OR). An OR perspective typically frames a complex problem in terms of its essential mathematical structure. This article illustrates the use and value of the tools of operations research in healthcare. It reviews one OR tool, queueing theory, and provides an illustration involving a hypothetical drug treatment facility.</p> <p>Method</p> <p>Queueing Theory (QT) is the study of waiting lines. The theory is useful in that it provides solutions to problems of waiting and its relationship to key characteristics of healthcare systems. More generally, it illustrates the strengths of modeling in healthcare and service delivery.</p> <p>Queueing theory offers insights that initially may be hidden. For example, a queueing model allows one to incorporate randomness, which is inherent in the actual system, into the mathematical analysis. As a result of this randomness, these systems often perform much worse than one might have guessed based on deterministic conditions. Poor performance is reflected in longer lines, longer waits, and lower levels of server utilization.</p> <p>As an illustration, we specify a queueing model of a representative drug treatment facility. The analysis of this model provides mathematical expressions for some of the key performance measures, such as average waiting time for admission.</p> <p>Results</p> <p>We calculate average occupancy in the facility and its relationship to system characteristics. For example, when the facility has 28 beds, the average wait for admission is 4 days. We also explore the relationship between arrival rate at the facility, the capacity of the facility, and waiting times.</p> <p>Conclusions</p> <p>One key aspect of the healthcare system is its complexity, and policy makers want to design and reform the system in a way that affects competing goals. OR methodologies, particularly queueing theory, can be very useful in gaining deeper understanding of this complexity and exploring the potential effects of proposed changes on the system without making any actual changes.</p

Synergistic binding of transcription factors to cell-specific enhancers programs motor neuron identity

Efficient transcriptional programming promises to open new frontiers in regenerative medicine. However, mechanisms by which programming factors transform cell fate are unknown, preventing more rational selection of factors to generate desirable cell types. Three transcription factors, Ngn2, Isl1 and Lhx3, were sufficient to program rapidly and efficiently spinal motor neuron identity when expressed in differentiating mouse embryonic stem cells. Replacement of Lhx3 by Phox2a led to specification of cranial, rather than spinal, motor neurons. Chromatin immunoprecipitation–sequencing analysis of Isl1, Lhx3 and Phox2a binding sites revealed that the two cell fates were programmed by the recruitment of Isl1-Lhx3 and Isl1-Phox2a complexes to distinct genomic locations characterized by a unique grammar of homeodomain binding motifs. Our findings suggest that synergistic interactions among transcription factors determine the specificity of their recruitment to cell type–specific binding sites and illustrate how a single transcription factor can be repurposed to program different cell types.Project ALS FoundationNational Institutes of Health (U.S.) (Grant P01 NS055923

Major histocompatibility complex class I molecules protect motor neurons from astrocyte-induced toxicity in amyotrophic lateral sclerosis

Astrocytes isolated from individuals with amyotrophic lateral sclerosis (ALS) are toxic to motor neurons (MNs) and play a non–cell autonomous role in disease pathogenesis. The mechanisms underlying the susceptibility of MNs to cell death remain unclear. Here we report that astrocytes derived from either mice bearing mutations in genes associated with ALS or human subjects with ALS reduce the expression of major histocompatibility complex class I (MHCI) molecules on MNs; reduced MHCI expression makes these MNs susceptible to astrocyte-induced cell death. Increasing MHCI expression on MNs increases survival and motor performance in a mouse model of ALS and protects MNs against astrocyte toxicity. Overexpression of a single MHCI molecule, HLA-F, protects human MNs from ALS astrocyte–mediated toxicity, whereas knockdown of its receptor, the killer cell immunoglobulin-like receptor KIR3DL2, on human astrocytes results in enhanced MN death. Thus, our data indicate that, in ALS, loss of MHCI expression on MNs renders them more vulnerable to astrocyte-mediated toxicity

The Explosion Mechanism of Core-Collapse Supernovae and Its Observational Signatures

The death of massive stars is shrouded in many mysteries. One of them is the mechanism that overturns the collapse of the degenerate iron core into an explosion, a process that determines the supernova explosion energy, properties of the surviving compact remnant, and the nucleosynthetic yields. The number of core-collapse supernova observations has been growing with an accelerating pace thanks to modern time-domain astronomical surveys and new tests of the explosion mechanism are becoming possible. We review predictions of parameterized supernova explosion models and compare them with explosion properties inferred from observed light curves, spectra, and neutron star masses.Comment: Reviews in Frontiers of Modern Astrophysics; From Space Debris to Cosmology, edited by Kab\'ath, Petr; Jones, David; Skarka, Marek. ISBN: 978-3-030-38509-5. Cham: Springer International Publishing, 2020, pp. 189-21

The Management of Disclosure in Children’s Accounts of Domestic Violence: Practices of Telling and Not Telling

Children and young people who experience domestic violence are often represented as passive witnesses, too vulnerable to tell the stories of their own lives. This article reports on findings from a 2 year European research project (Understanding Agency and Resistance Strategies, UNARS) with children and young people in Greece, Italy, Spain and the UK, who had experienced domestic violence. It explores children and young people’s understandings of their own capacity to reflect on and disclose their experiences Extracts from individual interviews with 107 children and young people (age 8–18) were analysed. Three themes are presented, that illustrate children and young people’s strategies for managing disclosure: (1) “Being silenced or choosing silence?”, explores children and young people’s practices of self-silencing; (2) “Managing disclosures: Finding ways to tell” outlines how children and young people value self-expression, and the strategies they use to disclose safely; and in (3) “Speaking with many voices” considers how children and young people’s accounts of their experiences are constituted relationally, and are often polyvocal. The article concludes that children and young people can be articulate, strategic and reflexive communicators, and that good support for families struggling with domestic violence must enable space for children and young people’s voice to be heard. This is possible only in an integrated framework able to encompass multiple layers and perspectives, rather than privileging the adult point of view. Practitioners who work with families affected by domestic violence need to recognize that children and young people are able to reflect on and speak about their experiences. This requires that attention is paid to the complexity of children and young people’s communication practices, and the relational context of those communications