The integrative framework for the behavioural sciences has already been discovered, and it is the adaptationist approach

The adaptationist framework is necessary and sufficient for unifying the social and natural sciences. Gintis’s “beliefs, preferences, and constraints” (BPC) model compares unfavorably to this framework because it lacks criteria for determining special design, incorrectly assumes that standard evolutionary theory predicts individual rationality maximisation, does not adequately recognize the impact of psychological mechanisms on culture, and is mute on the behavioural implications of intragenomic conflict

Innovation and Borrower Discouragement in SMEs

In this paper, we investigate whether innovative small and medium sized enterprises (SMEs) are more likely to be discouraged from applying for external finance than non-innovators. These so-called discouraged borrowers are credit worthy SMEs who choose not to apply for external finance despite the fact that this is needed. We find that SMEs undertaking pure product and joint product and process innovation have a significantly higher incidence of borrower discouragement than non-innovative counterparts. Moreover, radical and incremental product innovators are more likely to be discouraged relative to non-innovative counterparts. Innovative activity can increase borrower discouragement for a myriad of reasons including fear of rejection, reluctance to take on additional risk, negative perceptions of the funding application process and perceived negative economic conditions. Overall, our results suggest a need for targeted policy interventions in order to alleviate borrower discouragement of innovative SMEs, as well as a closer alignment between innovation and SME finance policy

Optimizing the identification of risk-relevant mutations by multigene panel testing in selected hereditary breast/ovarian cancer families

The introduction of multigene panel testing for hereditary breast/ovarian cancer screening has greatly improved efficiency, speed, and costs. However, its clinical utility is still debated, mostly due to the lack of conclusive evidences on the impact of newly discovered genetic variants on cancer risk and lack of evidence-based guidelines for the clinical management of their carriers. In this pilot study, we aimed to test whether a systematic and multiparametric characterization of newly discovered mutations could enhance the clinical utility of multigene panel sequencing. Out of a pool of 367 breast/ovarian cancer families Sanger-sequenced for BRCA1 and BRCA2 gene mutations, we selected a cohort of 20 BRCA1/2-negative families to be subjected to the BROCA-Cancer Risk Panel massive parallel sequencing. As a strategy for the systematic characterization of newly discovered genetic variants, we collected blood and cancer tissue samples and established lymphoblastoid cell lines from all available individuals in these families, to perform segregation analysis, loss-of-heterozygosity and further molecular studies. We identified loss-of-function mutations in 6 out 20 high-risk families, 5 of which occurred on BRCA1, CHEK2 and ATM and are esteemed to be risk-relevant. In contrast, a novel RAD50 truncating mutation is most likely unrelated to breast cancer. Our data suggest that integrating multigene panel testing with a pre-organized, multiparametric characterization of newly discovered genetic variants improves the identification of risk-relevant alleles impacting on the clinical management of their carriers

Increased proportion of alcohol-related trauma in a South London Major Trauma Centre during lockdown: A cohort study

Purpose Alcohol has been associated with 10%–35% trauma admissions and 40% trauma-related deaths globally. In response to the COVID-19 pandemic, the United Kingdom (UK) entered a state of “lockdown” on 23rd March 2020. Restrictions were most significantly eased on 1st June 2020, when shops and schools re-opened. The purpose of this study was to quantify the effect of lockdown on alcohol-related trauma admissions. Methods All adult patients admitted as “trauma calls” to a London Major Trauma Centre during April 2018 and April 2019 (pre-lockdown, n=316), and 1st April–31st May 2020 (lockdown, n=191) had electronic patient records analysed retrospectively. Patients’ blood alcohol level and records of intoxication were used to identify alcohol-related trauma. Trauma admissions from pre- and post-lockdown cohorts were compared using multiple regression analyses. Results Alcohol-related trauma was present in a significantly higher proportion of adult trauma calls during lockdown (lockdown 60/191 (31.4%), vs. pre-lockdown 62/316 (19.6%); (odds ratio (OR): 0.83, 95% CI: 0.38–1.28, p0.05). Conclusions UK lockdown was independently associated with an increased proportion of alcohol-related trauma. Trauma admissions were increased during the weekend when staffing levels are reduced. With the possibility of further global “waves” of COVID-19, the long-term repercussions of dangerous alcohol-related behaviour to public health must be addressed

Numerical solution of the eXtended Pom-Pom model for viscoelastic free surface flows

In this paper we present a finite difference method for solving two-dimensional viscoelastic unsteady free surface flows governed by the single equation version of the eXtended Pom-Pom (XPP) model. The momentum equations are solved by a projection method which uncouples the velocity and pressure fields. We are interested in low Reynolds number flows and, to enhance the stability of the numerical method, an implicit technique for computing the pressure condition on the free surface is employed. This strategy is invoked to solve the governing equations within a Marker-and-Cell type approach while simultaneously calculating the correct normal stress condition on the free surface. The numerical code is validated by performing mesh refinement on a two-dimensional channel flow. Numerical results include an investigation of the influence of the parameters of the XPP equation on the extrudate swelling ratio and the simulation of the Barus effect for XPP fluids

Social Deprivation, Inequality, and the Neighborhood-Level Incidence of Psychotic Syndromes in East London

licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited

Etiology of Severe Non-malaria Febrile Illness in Northern Tanzania: A Prospective Cohort Study.

The syndrome of fever is a commonly presenting complaint among persons seeking healthcare in low-resource areas, yet the public health community has not approached fever in a comprehensive manner. In many areas, malaria is over-diagnosed, and patients without malaria have poor outcomes. We prospectively studied a cohort of 870 pediatric and adult febrile admissions to two hospitals in northern Tanzania over the period of one year using conventional standard diagnostic tests to establish fever etiology. Malaria was the clinical diagnosis for 528 (60.7%), but was the actual cause of fever in only 14 (1.6%). By contrast, bacterial, mycobacterial, and fungal bloodstream infections accounted for 85 (9.8%), 14 (1.6%), and 25 (2.9%) febrile admissions, respectively. Acute bacterial zoonoses were identified among 118 (26.2%) of febrile admissions; 16 (13.6%) had brucellosis, 40 (33.9%) leptospirosis, 24 (20.3%) had Q fever, 36 (30.5%) had spotted fever group rickettsioses, and 2 (1.8%) had typhus group rickettsioses. In addition, 55 (7.9%) participants had a confirmed acute arbovirus infection, all due to chikungunya. No patient had a bacterial zoonosis or an arbovirus infection included in the admission differential diagnosis. Malaria was uncommon and over-diagnosed, whereas invasive infections were underappreciated. Bacterial zoonoses and arbovirus infections were highly prevalent yet overlooked. An integrated approach to the syndrome of fever in resource-limited areas is needed to improve patient outcomes and to rationally target disease control efforts

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning