Mathematical models of neuronal growth

The establishment of a functioning neuronal network is a crucial step in neural development. During this process, neurons extend neurites—axons and dendrites—to meet other neurons and interconnect. Therefore, these neurites need to migrate, grow, branch and find the correct path to their target by processing sensory cues from their environment. These processes rely on many coupled biophysical effects including elasticity, viscosity, growth, active forces, chemical signaling, adhesion and cellular transport. Mathematical models offer a direct way to test hypotheses and understand the underlying mechanisms responsible for neuron development. Here, we critically review the main models of neurite growth and morphogenesis from a mathematical viewpoint. We present different models for growth, guidance and morphogenesis, with a particular emphasis on mechanics and mechanisms, and on simple mathematical models that can be partially treated analytically.

Global cooling induced by biophysical effects of bioenergy crop cultivation

Bioenergy crop with carbon capture and storage (BECCS) is a key negative emission technology to meet carbon neutrality. However, the biophysical effects of widespread bioenergy crop cultivation on temperature remain unclear. Here, using a coupled atmosphere-land model with an explicit representation of lignocellulosic bioenergy crops, we find that after 50 years of large-scale bioenergy crop cultivation following plausible scenarios, global air temperature decreases by 0.03~0.08 °C, with strong regional contrasts and interannual variability. Over the cultivated regions, woody crops induce stronger cooling effects than herbaceous crops due to larger evapotranspiration rates and smaller aerodynamic resistance. At the continental scale, air temperature changes are not linearly proportional to the cultivation area. Sensitivity tests show that the temperature change is robust for eucalypt but more uncertain for switchgrass among different cultivation maps. Our study calls for new metrics to take the biophysical effects into account when assessing the climate mitigation capacity of BECCS.

Computational Compensatory Mutation Discovery Approach: Predicting a PARP1 Variant Rescue Mutation

The prediction of protein mutations that affect function may be exploited for multiple uses. In the context of disease variants, the prediction of compensatory mutations that reestablish functional phenotypes could aid in the development of genetic therapies. In this work, we present an integrated approach that combines coevolutionary analysis and molecular dynamics (MD) simulations to discover functional compensatory mutations. This approach is employed to investigate possible rescue mutations of a poly(ADP-ribose) polymerase 1 (PARP1) variant, PARP1 V762A, associated with lung cancer and follicular lymphoma. MD simulations show PARP1 V762A exhibits noticeable changes in structural and dynamical behavior compared with wild type PARP1. Our integrated approach predicts A755E as a possible compensatory mutation based on coevolutionary information, and molecular simulations indicate that the PARP1 A755E/V762A double mutant exhibits similar structural and dynamical behavior to WT PARP1. Our methodology can be broadly applied to a large number of systems where SNPs have been identified as connected to disease and can shed light on the biophysical effects of such changes as well as provide a way to discover potential mutants that could restore wild type-like functionality. This can in turn be further utilized in the design of molecular therapeutics that aim to mimic such compensatory effect.

Evaluation of coupled regional climate models in representing the local biophysical effects of afforestation over continental China

Regional climate models have been widely used to examine the biophysical effects of afforestation, but their performances in this respect have rarely been evaluated. To fill this knowledge gap, an evaluation method based on the “space for time” strategy is proposed here. Using this method, we validate the performances of three regional models, the Regional Climate Model (RegCM), Weather Research and Forecasting (WRF) model and the WRF model run at a convection-permitting resolution (WRF-CP), in representing the local biophysical effects of afforestation over continental China against satellite observations. The results show that WRF and WRF-CP can not accurately describe afforestation-induced changes in surface biophysical properties, e.g. albedo or leaf area index. Second, all models exhibit poor simulations of afforestation-induced changes in latent and sensible heat fluxes. In particular, the observed increase in the summer latent heat due to afforestation is substantially underestimated by all models. Third, the models are basically reasonable in representing the biophysical impact of afforestation on temperature. The cooling of the daily mean surface temperature and 2-meter temperature in summer are reproduced well. Nevertheless, the mechanism driving the cooling effect may be improperly represented by the models. Moreover, the models perform relatively poorly in representing the response of the daily minimum surface temperature to afforestation. This highlights the necessity of evaluating the representation of the biophysical effects by a model before the model is employed to carry out afforestation experiments. This study serves as a test bed for validating regional model performance in this respect.

Lipoprotein-Induced Increases in Cholesterol and 7-Ketocholesterol Result in Opposite Molecular-Scale Biophysical Effects on Membrane Structure

Under hypercholesterolemic conditions, exposure of cells to lipoproteins results in a subtle membrane increase in the levels of cholesterol and 7-ketocholesterol, as compared to normal conditions. The effect of these physiologically relevant concentration increases on multicomponent bilayer membranes was investigated using coarse-grained molecular dynamics simulations. Significant changes in the structural and dynamic properties of the bilayer membranes resulted from these subtle increases in sterol levels, with both sterol species inducing decreases in the lateral area and inhibiting lateral diffusion to varying extents. Cholesterol and 7-ketocholesterol, however, exhibited opposite effects on lipid packing and orientation. The results from this study indicate that the subtle increases in membrane sterol levels induced by exposure to lipoproteins result in molecular-scale biophysical perturbation of membrane structure.

Biophysical effects, safety and efficacy of raspberry leaf use in pregnancy: a systematic integrative review

Background Childbearing women have been using various herbs to assist with pregnancy, labour and birth for centuries. One of the most common is raspberry leaf. The evidence base for the use of raspberry leaf is however under-developed. It is incumbent on midwives and other maternity care providers to provide women with evidence-based information so they can make informed choices. The aim of this study was to review the research literature to identify the evidence base on the biophysical effects, safety and efficacy of raspberry leaf in pregnancy. Methods A systematic, integrative review was undertaken. Six databases were searched to identify empirical research papers published in peer reviewed journals including in vitro, in vivo, human and animal studies. The search included the databases CINAHL, MEDLINE, Cochrane Library, Scopus and Web of Science Core Collection and AMED. Identified studies were appraised independently by two reviewers using the MMAT appraisal instrument. An integrative approach was taken to analysis. Results Thirteen studies were included. Five were laboratory studies using animal and human tissue, two were experiments using animals, and six were human studies. Included studies were published between 1941 and 2016. Raspberry leaf has been shown to have biophysical effects on animal and human smooth muscle including the uterus. Toxity was demonstrated when high doses were administered intravenously or intaperitoneally in animal studies. Human studies have not shown any harm or benefit though one study demonstrated a clinically meaningful (though non-statistically significant) reduction in length of second stage and augmentation of labour in women taking raspberry leaf. Conclusions Many women use raspberry leaf in pregnancy to facilitate labour and birth. The evidence base supporting the use of raspeberry leaf in pregnancy is weak and further research is needed to address the question of raspberry leaf’s effectiveness.