Massive gravity from bimetric gravity

We discuss the subtle relationship between massive gravity and bimetric gravity, focusing particularly on the manner in which massive gravity may be viewed as a suitable limit of bimetric gravity. The limiting procedure is more delicate than currently appreciated. Specifically, this limiting procedure should not unnecessarily constrain the background metric, which must be externally specified by the theory of massive gravity itself. The fact that in bimetric theories one always has two sets of metric equations of motion continues to have an effect even in the massive gravity limit, leading to additional constraints besides the one set of equations of motion naively expected. Thus, since solutions of bimetric gravity in the limit of vanishing kinetic term are also solutions of massive gravity, but the contrary statement is not necessarily true, there is not complete continuity in the parameter space of the theory. In particular, we study the massive cosmological solutions which are continuous in the parameter space, showing that many interesting cosmologies belong to this class.Comment: v1: 25 pages; v2: 6 references added, discussion streamlined; v3: 24 pages, 20 references added, section 2 summarized, new comments added to section 3, conclusions improved but unchanged. This version accepted for publication in Classical and Quantum Gravit

An Overview of the Management of Flexor Tendon Injuries

Flexor tendon injuries still remain a challenging condition to manage to ensure optimal outcome for the patient. Since the first flexor tendon repair was described by Kirchmayr in 1917, several approaches to flexor tendon injury have enabled successful repairs rates of 70-90%. Primary surgical repair results in better functional outcome compared to secondary repair or tendon graft surgery. Flexor tendon injury repair has been extensively researched and the literature demonstrates successful repair requires minimal gapping at the repair site or interference with tendon vascularity, secure suture knots, smooth junction of tendon end and having sufficient strength for healing. However, the exact surgical approach to achieve success being currently used among surgeons is still controversial. Therefore, this review aims to discuss the results of studies demonstrating the current knowledge regarding the optimal approach for flexor tendon repair. Post-operative rehabilitation for flexor tendon surgery is another area, which has caused extensive debate in hand surgery. The trend to more active mobilisation protocols seems to be favoured but further study in this area is needed to find the protocol, which achieves function and gliding but avoids rupture of the tendons. Lastly despite success following surgery complications commonly still occur post surgery, including adhesion formation, tendon rupture and stiffness of the joints. Therefore, this review aims to discuss the appropriate management of these difficulties post surgery. New techniques in management of flexor tendon will also be discussed including external laser devices, addition of growth factors and cytokines

Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10−6). Novel reciprocal case–control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present

Machine-learning Prognostic Models from the 2014-16 Ebola Outbreak: Data-harmonization Challenges, Validation Strategies, and mHealth Applications.

Ebola virus disease (EVD) plagues low-resource and difficult-to-access settings. Machine learning prognostic models and mHealth tools could improve the understanding and use of evidence-based care guidelines in such settings. However, data incompleteness and lack of interoperability limit model generalizability. This study harmonizes diverse datasets from the 2014-16 EVD epidemic and generates several prognostic models incorporated into the novel Ebola Care Guidelines app that provides informed access to recommended evidence-based guidelines. Multivariate logistic regression was applied to investigate survival outcomes in 470 patients admitted to five Ebola treatment units in Liberia and Sierra Leone at various timepoints during 2014-16. We generated a parsimonious model (viral load, age, temperature, bleeding, jaundice, dyspnea, dysphagia, and time-to-presentation) and several fallback models for when these variables are unavailable. All were externally validated against two independent datasets and compared to further models including expert observational wellness assessments. Models were incorporated into an app highlighting the signs/symptoms with the largest contribution to prognosis. The parsimonious model approached the predictive power of observational assessments by experienced clinicians (Area-Under-the-Curve, AUC = 0.70-0.79, accuracy = 0.64-0.74) and maintained its performance across subcohorts with different healthcare seeking behaviors. Age and viral load contributed > 5-fold the weighting of other features and including them in a minimal model had a similar AUC, albeit at the cost of specificity. Clinically guided prognostic models can recapitulate clinical expertise and be useful when such expertise is unavailable. Incorporating these models into mHealth tools may facilitate their interpretation and provide informed access to comprehensive clinical guidelines. Howard Hughes Medical Institute, US National Institutes of Health, Bill & Melinda Gates Foundation, International Medical Corps, UK Department for International Development, and GOAL Global