Network development in biological gels: role in lymphatic vessel development

In this paper, we present a model that explains the prepatterning of lymphatic vessel morphology in collagen gels. This model is derived using the theory of two phase rubber material due to Flory and coworkers and it consists of two coupled fourth order partial differential equations describing the evolution of the collagen volume fraction, and the evolution of the proton concentration in a collagen implant; as described in experiments of Boardman and Swartz (Circ. Res. 92, 801–808, 2003). Using linear stability analysis, we find that above a critical level of proton concentration, spatial patterns form due to small perturbations in the initially uniform steady state. Using a long wavelength reduction, we can reduce the two coupled partial differential equations to one fourth order equation that is very similar to the Cahn–Hilliard equation; however, it has more complex nonlinearities and degeneracies. We present the results of numerical simulations and discuss the biological implications of our model

Refined Interfaces for Compositional Verification

The compositional verification approach of Graf & Steffen aims at avoiding state space explosion for individual processes of a concurrent system. It relies on interfaces that express the behavioural constraints imposed on each process by synchronization with the other processes, thus preventing the exploration of states and transitions that would not be reachable in the global state space. Krimm & Mounier, and Cheung & Kramer proposed two techniques to generate such interfaces automatically. In this report, we propose a refined interface generation technique that derives the interface of a process automatically from the examination of (a subset of) concurrent processes. This technique is applicable to formalisms where concurrent processes are composed either using synchronization vectors or process algebra parallel composition operators (including those of CCS, CSP, muCRL, LOTOS, and E-LOTOS). We implemented this approach in the EXP.OPEN 2.0 tool of the CADP toolbox. Several experiments indicate state space reductions by more than two orders of magnitude for the largest processes

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Diagnosis of crop secondary and micro-nutrient deficiencies in sub-Saharan Africa

Published online: 10 Jan 2019Crop production in sub-Saharan Africa has numerous biotic and abiotic constraints, including nutrient deficiencies. Information on crop response to macronutrients is relatively abundant compared with secondary and micronutrients (SMN). Data from 1339 trial replicates of 280 field trials conducted from 2013 to 2016 in 11 countries were analyzed for the diagnosis of SMN deficiencies. The diagnostic data included relative yield response (RYR) and soil and foliar test results. The RYR to application of a combination of Mg, S, Zn, and B (Mg–S–Zn–B) relative to a comparable N–P–K treatment was a > 5% increase for 35% of the legume blocks and 60% of the non-legume blocks. The frequencies of soil test Zn, Cu, and B being below their critical level were 28, 2 and 10% for eastern and southern Africa, respectively, and 55, 58 and 89% for western Africa, while low levels for other SMN were less frequent. The frequency of foliar results indicating low availability were 58% for Zn, 16% for S and less for other SMN. The r2 values for relationships between soil test, foliar test and RYR results were < 0.035 with little complementarity except for soil test Zn and B with cassava (Manihot esculenta L. Crantz) RYR in Ghana, and foliar Zn with cereal RYR in Uganda. Positive RYR is powerful diagnostic information and indicative of good profit potential for well-targeted and well-specified SMN application. Geo-referenced RYR, soil analysis and foliar analysis results for diagnosis of SMN deficiencies in 11 countries of sub-Saharan Africa were generally not complementary