Multi-generational dispersal and dynamic patch occupancy reveals spatial and temporal stability of seascapes.

The success of non-native species (NNS) invasions depends on patterns of dispersal and connectivity, which underpin genetic diversity, population establishment and growth. In the marine environment, both global environmental change and increasing anthropogenic activity can alter hydrodynamic patterns, leading to significant inter-annual variability in dispersal pathways. Despite this, multi-generational dispersal is rarely explicitly considered in attempts to understand NNS spread or in the design of management interventions. Here, we present a novel approach to quantifying species spread that considers range expansion and network formation across time using the non-native Pacific oyster, Magallana gigas (Thunberg 1793), as a model. We combined biophysical modelling, dynamic patch occupancy models, consideration of environmental factors, and graph network theory to model multi-generational dispersal in northwest Europe over 13 generations. Results revealed that M. gigas has a capacity for rapid range expansion through the creation of an ecological network of dispersal pathways that remains stable through time. Maximum network size was achieved in four generations, after which connectivity patterns remained temporally stable. Multi-generational connectivity could therefore be divided into two periods: network growth (2000-2003) and network stability (2004-2012). Our study is the first to examine how dispersal trajectories affect the temporal stability of ecological networks across biogeographic scales, and provides an approach for the assignment of site-based prioritisation of non-native species management at different stages of the invasion timeline. More broadly, the framework we present can be applied to other fields (e.g. Marine Protected Area design, management of threatened species and species range expansion due to climate change) as a means of characterising and defining ecological network structure, functioning and stability.

Offshore oil and gas infrastructure plays a minor role in marine metapopulation dynamics.

Decommissioning consequences of offshore oil and gas infrastructure removal on marine population dynamics, including connectivity, are not well understood. We modelled the connectivity and metapopulation dynamics of three fish and two benthic invertebrate species inhabiting the natural rocky reefs and offshore oil and gas infrastructure located in the Bass Strait, south-east Australia. Using a network approach, we found that platforms are not major sources, destinations, or stepping-stones for most species, yet act as modest sources for connectivity of Corynactis australis (jewel anemone). In contrast, sections of subsea pipelines appear to act as stepping-stones, source and destination habitats of varying strengths for all study species, except for Centrostephanus rodgersii (long-spined sea urchin). Natural reefs were the main stepping-stones, local source, and destination habitats for all study species. These reefs were largely responsible for the overall metapopulation growth of all study species (average of 96 % contribution across all species), with infrastructure acting as a minor contributor (<2 % average contribution). Full or partial decommissioning of platforms should have a very low or negligible impact on the overall metapopulation dynamics of the species explored, except C. australis, while full removal of pipelines could have a low impact on the metapopulation dynamics of benthic invertebrate species and a moderate impact on fish species (up to 34.1 % reduction in the metapopulation growth). We recommend that the decision to remove offshore infrastructure, either in full or in-part, be made on a platform-by-platform basis and consider contributions of pipelines to connectivity and metapopulation dynamics.

Robustness of carbon-ion radiotherapy against DNA damage repair associated radiosensitivity variation based on a biophysical model.

BACKGROUND: Interpatient variation of tumor radiosensitivity is rarely considered during the treatment planning process despite its known significance for the therapeutic outcome. PURPOSE: To apply our mechanistic biophysical model to investigate the biological robustness of carbon ion radiotherapy (CIRT) against DNA damage repair interference (DDRi) associated patient-to-patient variability in radiosensitivity and its potential clinical advantages against conventional radiotherapy approaches. METHODS AND MATERIALS: The "UNIfied and VERSatile bio response Engine" (UNIVERSE) was extended by carbon ions and its predictions were compared to a panel of in vitro and in vivo data including various endpoints and DDRi settings within clinically relevant dose and linear energy transfer (LET) ranges. The implications of UNIVERSE predictions were then assessed in a clinical patient scenario considering DDRi variance. RESULTS: UNIVERSE tests well against the applied benchmarks. While in vitro survival curves were predicted with an R2 > 0.92, deviations from in vivo RBE data were less than 5.6% The conducted paradigmatic patient plan study implies a markedly reduced significance of DDRi based radiosensitivity variability in CIRT (13% change of D 50 ${{D}_{50}}$ in target) compared to conventional radiotherapy (62%) and that boosting the LET within the target further amplifies this robustness of CIRT (8%). In the case of heightened tumor radiosensitivity, a dose de-escalation strategy for photons allows a reduction of the maximum effective dose within the normal tissue (NT) from a D 2 ${{D}_2}$ of 2.65 to 1.64 Gy, which lies below the level found for CIRT ( D 2 ${{D}_2}$  = 2.41 Gy) for the analyzed plan and parameters. However, even after de-escalation, the integral effective dose in the NT is found to be substantially higher for conventional radiotherapy in comparison to CIRT ( D m e a n ${{D}_{mean}}$ of 0.75, 0.46, and 0.24 Gy for the conventional plan, its de-escalation and CIRT, respectively). CONCLUSIONS: The framework offers adequate predictions of in vitro and in vivo radiation effects of CIRT while allowing the consideration of DRRi based solely on parameters derived from photon data. The results of the patient planning study underline the potential of CIRT to minimize important sources of interpatient divergence in therapy outcome, especially when combined with techniques that allow to maximize the LET within the tumor. Despite the potential of de-escalation strategies for conventional radiotherapy to reduce the maximum effective dose in the NT, CIRT appears to remain a more favorable option due to its ability to reduce the integral effective dose within the NT.

Combining population genomics and biophysical modelling to assess connectivity patterns in an Antarctic fish.

Connectivity is a fundamental process of population dynamics in marine ecosystems. In the last decade, with the emergence of new methods, combining different approaches to understand the patterns of connectivity among populations and their regulation has become increasingly feasible. The Western Antarctic Peninsula (WAP) is characterized by complex oceanographic dynamics, where local conditions could act as barriers to population connectivity. Here, the notothenioid fish Harpagifer antarcticus, a demersal species with a complex life cycle (adults with poor swim capabilities and pelagic larvae), was used to assess connectivity along the WAP by combining biophysical modelling and population genomics methods. Both approaches showed congruent patterns. Areas of larvae retention and low potential connectivity, observed in the biophysical model output, coincide with four genetic groups within the WAP: (1) South Shetland Islands, (2) Bransfield Strait, (3) the central and (4) the southern area of WAP (Marguerite Bay). These genetic groups exhibited limited gene flow between them, consistent with local oceanographic conditions, which would represent barriers to larval dispersal. The joint effect of geographic distance and larval dispersal by ocean currents had a greater influence on the observed population structure than each variable evaluated separately. The combined effect of geographic distance and a complex oceanographic dynamic would be generating limited levels of population connectivity in the fish H. antarcticus along the WAP. Based on this, population connectivity estimations and priority areas for conservation were discussed, considering the marine protected area proposed for this threatened region of the Southern Ocean.

Biophysical model of muscle spindle encoding.

Muscle spindles encode mechanosensory information by mechanisms that remain only partially understood. Their complexity is expressed in mounting evidence of various molecular mechanisms that play essential roles in muscle mechanics, mechanotransduction and intrinsic modulation of muscle spindle firing behaviour. Biophysical modelling provides a tractable approach to achieve more comprehensive mechanistic understanding of such complex systems that would be difficult/impossible by more traditional, reductionist means. Our objective here was to construct the first integrative biophysical model of muscle spindle firing. We leveraged current knowledge of muscle spindle neuroanatomy and in vivo electrophysiology to develop and validate a biophysical model that reproduces key in vivo muscle spindle encoding characteristics. Crucially, to our knowledge, this is the first computational model of mammalian muscle spindle that integrates the asymmetric distribution of known voltage-gated ion channels (VGCs) with neuronal architecture to generate realistic firing profiles, both of which seem likely to be of great biophysical importance. Results predict that particular features of neuronal architecture regulate specific characteristics of Ia encoding. Computational simulations also predict that the asymmetric distribution and ratios of VGCs is a complementary and, in some instances, orthogonal means to regulate Ia encoding. These results generate testable hypotheses and highlight the integral role of peripheral neuronal structure and ion channel composition and distribution in somatosensory signalling.

Methods for assessing cardiac myofilament calcium sensitivity.

Myofilament calcium (Ca2+) sensitivity is one of several mechanisms by which force production of cardiac muscle is modulated to meet the ever-changing demands placed on the heart. Compromised Ca2+ sensitivity is associated with pathologies, which makes it a parameter of interest for researchers. Ca2+ Sensitivity is the ratio of the association and dissociation rates between troponin C (TnC) and Ca2+. As it is not currently possible to measure these rates in tissue preparations directly, methods have been developed to infer myofilament sensitivity, typically using some combination of force and Ca2+ measurements. The current gold-standard approach constructs a steady-state force-Ca2+ relation by exposing permeabilised muscle samples to a range of Ca2+ concentrations and uses the half-maximal concentration as a proxy for sensitivity. While a valuable method for steady-state investigations, the permeabilisation process makes the method unsuitable when examining dynamic, i.e., twitch-to-twitch, changes in myofilament sensitivity. The ability of the heart to transiently adapt to changes in load is an important consideration when evaluating the impact of disease states. Alternative methods have been proffered, including force-Ca2+ phase loops, potassium contracture, hybrid experimental-modelling and conformation-based fluorophore approaches. This review provides an overview of the mechanisms underlying myofilament Ca2+ sensitivity, summarises existing methods, and explores, with modelling, whether any of them are suited to investigating dynamic changes in sensitivity. We conclude that a method that equips researchers to investigate the transient change of myofilament Ca2+ sensitivity is still needed. We propose that such a method will involve simultaneous measurements of cytosolic Ca2+ and TnC activation in actively twitching muscle and a biophysical model to interpret these data.

Cool shade and not-so-cool shade: How habitat loss may accelerate thermal stress under current and future climate.

Worldwide habitat loss, land-use changes, and climate change threaten biodiversity, and we urgently need models that predict the combined impacts of these threats on organisms. Current models, however, overlook microhabitat diversity within landscapes and so do not accurately inform conservation efforts, particularly for ectotherms. Here, we built and field-parameterized a model to examine the effects of habitat loss and climate change on activity and microhabitat selection by a diurnal desert lizard. Our model predicted that lizards in rock-free areas would reduce summer activity levels (e.g. foraging, basking) and that future warming will gradually decrease summer activity in rocky areas, as even large rocks become thermally stressful. Warmer winters will enable more activity but will require bushes and small rocks as shade retreats. Hence, microhabitats that may seem unimportant today will become important under climate change. Modelling frameworks should consider the microhabitat requirements of organisms to improve conservation outcomes.

Preservation of thalamocortical circuitry is essential for good recovery after cardiac arrest.

Continuous electroencephalographam (EEG) monitoring contributes to prediction of neurological outcome in comatose cardiac arrest survivors. While the phenomenology of EEG abnormalities in postanoxic encephalopathy is well known, the pathophysiology, especially the presumed role of selective synaptic failure, is less understood. To further this understanding, we estimate biophysical model parameters from the EEG power spectra from individual patients with a good or poor recovery from a postanoxic encephalopathy. This biophysical model includes intracortical, intrathalamic, and corticothalamic synaptic strengths, as well as synaptic time constants and axonal conduction delays. We used continuous EEG measurements from hundred comatose patients recorded during the first 48 h postcardiac arrest, 50 with a poor neurological outcome [cerebral performance category ( CPC = 5 ) ] and 50 with a good neurological outcome ( CPC = 1 ). We only included patients that developed (dis-)continuous EEG activity within 48 h postcardiac arrest. For patients with a good outcome, we observed an initial relative excitation in the corticothalamic loop and corticothalamic propagation that subsequently evolved towards values observed in healthy controls. For patients with a poor outcome, we observed an initial increase in the cortical excitation-inhibition ratio, increased relative inhibition in the corticothalamic loop, delayed corticothalamic propagation of neuronal activity, and severely prolonged synaptic time constants that did not return to physiological values. We conclude that the abnormal EEG evolution in patients with a poor neurological recovery after cardiac arrest may result from persistent and selective synaptic failure that includes corticothalamic circuitry and also delayed corticothalamic propagation.

Linking cortex and contraction-Integrating models along the corticomuscular pathway.

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.

Heterogeneity of absorbed dose distribution in kidney tissues and dose-response modelling of nephrotoxicity in radiopharmaceutical therapy with beta-particle emitters: A review.

Absorbed dose heterogeneity in kidney tissues is an important issue in radiopharmaceutical therapy. The effect of absorbed dose heterogeneity in nephrotoxicity is, however, not fully understood yet, which hampers the implementation of treatment optimization by obscuring the interpretation of clinical response data and the selection of optimal treatment options. Although some dosimetry methods have been developed for kidney dosimetry to the level of microscopic renal substructures, the clinical assessment of the microscopic distribution of radiopharmaceuticals in kidney tissues currently remains a challenge. This restricts the anatomical resolution of clinical dosimetry, which hinders a thorough clinical investigation of the impact of absorbed dose heterogeneity. The potential of absorbed dose-response modelling to support individual treatment optimization in radiopharmaceutical therapy is recognized and gaining attraction. However, biophysical modelling is currently underexplored for the kidney, where particular modelling challenges arise from the convolution of a complex functional organization of renal tissues with the function-mediated dose distribution of radiopharmaceuticals. This article reviews and discusses the heterogeneity of absorbed dose distribution in kidney tissues and the absorbed dose-response modelling of nephrotoxicity in radiopharmaceutical therapy. The review focuses mainly on the peptide receptor radionuclide therapy with beta-particle emitting somatostatin analogues, for which the scientific literature reflects over two decades of clinical experience. Additionally, detailed research perspectives are proposed to address various identified challenges to progress in this field.

Oceanographic connectivity explains the intra-specific diversity of mangrove forests at global scales.

The distribution of mangrove intra-specific biodiversity can be structured by historical demographic processes that enhance or limit effective population sizes. Oceanographic connectivity (OC) may further structure intra-specific biodiversity by preserving or diluting the genetic signatures of historical changes. Despite its relevance for biogeography and evolution, the role of oceanographic connectivity in structuring the distribution of mangrove's genetic diversity has not been addressed at global scale. Here we ask whether connectivity mediated by ocean currents explains the intra-specific diversity of mangroves. A comprehensive dataset of population genetic differentiation was compiled from the literature. Multigenerational connectivity and population centrality indices were estimated with biophysical modeling coupled with network analyses. The variability explained in genetic differentiation was tested with competitive regression models built upon classical isolation-by-distance (IBD) models considering geographic distance. We show that oceanographic connectivity can explain the genetic differentiation of mangrove populations regardless of the species, region, and genetic marker (significant regression models in 95% of cases, with an average R-square of 0.44 ± 0.23 and Person's correlation of 0.65 ± 0.17), systematically improving IBD models. Centrality indices, providing information on important stepping-stone sites between biogeographic regions, were also important in explaining differentiation (R-square improvement of 0.06 ± 0.07, up to 0.42). We further show that ocean currents produce skewed dispersal kernels for mangroves, highlighting the role of rare long-distance dispersal events responsible for historical settlements. Overall, we demonstrate the role of oceanographic connectivity in structuring mangrove intra-specific diversity. Our findings are critical for mangroves' biogeography and evolution, but also for management strategies considering climate change and genetic biodiversity conservation.

A multivariate approach to synthetize large amount of connectivity matrices for management decisions: Application to oyster population restocking in the pearl farming context of Tuamotu Archipelago semi-closed atolls.

In applied ecology, numerical biophysical modelling allows running numerous simulations of spatial connectivity between source and destination locations. To characterize population connectivity, larval dispersal and resulting connectivity matrices can be computed for various forcing conditions of wind, density of spawners, or pelagic larval durations. Here, we investigate a methodology to synthetize meaningfully all numerical experiments performed for three atoll lagoons in the Tuamotu Archipelago pearl farming context. The objective is to identify the best restocking locations that consistently maximize the spread of pearl oyster larval dispersal, considering all forcing conditions. A multivariate generic approach is used to process and synthesize time-series of connectivity matrices and identify afterward with contextual criteria the spawning locations that match a variety of specific connectivity, logistical and ecological criteria. Similar synthesis of large volume of connectivity matrices will likely gain momentum considering the increasing use of numerical models for applied science and population management.

A Mission to Mars: Prediction of GCR Doses and Comparison with Astronaut Dose Limits.

Long-term human space missions such as a future journey to Mars could be characterized by several hazards, among which radiation is one the highest-priority problems for astronaut health. In this work, exploiting a pre-existing interface between the BIANCA biophysical model and the FLUKA Monte Carlo transport code, a study was performed to calculate astronaut absorbed doses and equivalent doses following GCR exposure under different shielding conditions. More specifically, the interface with BIANCA allowed us to calculate both the RBE for cell survival, which is related to non-cancer effects, and that for chromosome aberrations, related to the induction of stochastic effects, including cancer. The results were then compared with cancer and non-cancer astronaut dose limits. Concerning the stochastic effects, the equivalent doses calculated by multiplying the absorbed dose by the RBE for chromosome aberrations ("high-dose method") were similar to those calculated using the Q-values recommended by ICRP. For a 650-day mission at solar minimum (representative of a possible Mars mission scenario), the obtained values are always lower than the career limit recommended by ICRP (1 Sv), but higher than the limit of 600 mSv recently adopted by NASA. The comparison with the JAXA limits is more complex, since they are age and sex dependent. Concerning the deterministic limits, even for a 650-day mission at solar minimum, the values obtained by multiplying the absorbed dose by the RBE for cell survival are largely below the limits established by the various space agencies. Following this work, BIANCA, interfaced with an MC transport code such as FLUKA, can now predict RBE values for cell death and chromosome aberrations following GCR exposure. More generally, both at solar minimum and at solar maximum, shielding of 10 g/cm2 Al seems to be a better choice than 20 g/cm2 for astronaut protection against GCR.

Differential patterns of connectivity in Western Pacific hydrothermal vent metapopulations: A comparison of biophysical and genetic models.

Hydrothermal ecosystems face threats from planned deep-seabed mining activities, despite the fact that patterns of realized connectivity among vent-associated populations and communities are still poorly understood. Since populations of vent endemic species depend on larval dispersal to maintain connectivity and resilience to habitat changes, effective conservation strategies for hydrothermal ecosystems should include assessments of metapopulation dynamics. In this study, we combined population genetic methods with biophysical models to assess strength and direction of gene flow within four species of the genus Alviniconcha (A. boucheti, A. kojimai, A. strummeri and A. hessleri) that are ecologically dominant taxa at Western Pacific hydrothermal vents. In contrast to predictions from dispersal models, among-basin migration in A. boucheti occurred predominantly in an eastward direction, while populations within the North Fiji Basin were clearly structured despite the absence of oceanographic barriers. Dispersal models and genetic data were largely in agreement for the other Alviniconcha species, suggesting limited between-basin migration for A. kojimai, lack of genetic structure in A. strummeri within the Lau Basin and restricted gene flow between northern and southern A. hessleri populations in the Mariana back-arc as a result of oceanic current conditions. Our findings show that gene flow patterns in ecologically similar congeneric species can be remarkably different and surprisingly limited depending on environmental and evolutionary contexts. These results are relevant to regional conservation planning and to considerations of similar integrated analyses for any vent metapopulations under threat from seabed mining.

Mapping and exploring the organoid state space using synthetic biology.

The functional relevance of an organoid is dependent on the differentiation, morphology, cell arrangement and biophysical properties, which collectively define the state of an organoid. For an organoid culture, an individual organoid or the cells that compose it, these state variables can be characterised, most easily by transcriptomics and by high-content image analysis. Their states can be compared to their in vivo counterparts. Current evidence suggests that organoids explore a wider state space than organs in vivo due to the lack of niche signalling and the variability of boundary conditions in vitro. Using data-driven state inference and in silico modelling, phase diagrams can be constructed to systematically sort organoids along biochemical or biophysical axes. These phase diagrams allow us to identify control strategies to modulate organoid state. To do so, the biochemical and biophysical environment, as well as the cells that seed organoids, can be manipulated.

Modeling secondary cancer risk ratios for proton versus carbon ion beam therapy: A comparative study based on the local effect model.

BACKGROUND: Ion beam therapy allows for substantial sparing of normal tissues. Besides deterministic normal-tissue complications, stochastic long-term effects like secondary cancer (SC) induction are of importance when comparing different treatment modalities. PURPOSE: To develop a modeling approach for comparison of SC risk in proton and carbon ion therapy. METHODS AND MATERIALS: The local effect model (LEM) is used to predict the relative biological effectiveness (RBE) of SC induction after particle therapy. A key feature of the new approach is the double use of the LEM, reflecting the competition between the two processes of mutation induction (leading to cancer development) and cell inactivation (leading to suppression of cancer development). Based on previous investigations, treatment plans were in this work analyzed for an idealized geometry in order to assess the underlying systematic dependencies of cancer induction. In a further step, relative SC risks were predicted for proton and carbon ion treatment plans prepared for 10 prostate cancer patients. RESULTS: We investigated the impact of factors such as treatment plan geometry, fractionation scheme, and tissue radiosensitivity to photon irradiation on the ion beam SC risk. Our model studies do not result in a clear preference for either protons or carbon ions, but rather indicate a complex interplay of different aspects. Reduced lateral scattering leads to a lower SC risk for carbon ions compared to protons at the lateral field margins in the entrance channel, while an increased risk was found closely behind the tumor due to projectile fragmentation. The fractionation scheme had little impact on the expected risk ratio. With respect to sensitivity parameters, those characterizing RBE for cell killing of potentially cancerous cells as well as of the primary tumor had the most significant impact. The observed general systematic dependencies are in agreement with results from previous model studies. The prostate patient study reveals reduced SC risks predictions for skin and bones for carbon ions as compared to protons, but higher mean risks for bladder and rectum. CONCLUSION: The methods established in this work provide a basis for further investigating treatment optimizing strategies for ion beam therapy with regard to SC risk comparisons.

Radiobiological damage by space radiation: extension of the BIANCA model to heavy ions up to iron, and pilot application to cosmic ray exposure.

Space research seems to be object of a renewed interest, also considering that human missions to the Moon, and possibly Mars, are being planned. Among the risks affecting such missions, astronauts' exposure to space radiation is a major concern. In this work, the question of the evaluation of biological damage by Galactic Cosmic Rays (GCR) was addressed by a biophysical model called BIophysical ANalysis of Cell death and chromosome Aberrations (BIANCA), which simulates the induction of cell death and chromosome aberrations by different ions. While previously BIANCA has been validated for calculating cell death along hadrontherapy beams up to oxygen, herein the approach was extended up to Fe ions. Specifically, experimental survival curves available in literature for V79 cells irradiated by Si-, Ne-, Ar- and Fe-ions were reproduced, and a reference radiobiological database describing V79 cell survival as a function of ion type (1 ⩽Z⩽ 26), energy and dose was constructed. Analogous databases were generated for Chinese hamster ovary hamster cells and human skin fibroblasts, finding good agreement between simulations and data. Concerning chromosome aberrations, which are regarded as radiation risk biomarkers, dicentric data in human lymphocytes irradiated by heavy ions up to iron were reproduced, and a radiobiological database allowing calculation of lymphocyte dicentric yields as a function of dose, ion type (1 ⩽Z⩽ 26) and energy was constructed. Following interface between BIANCA and the FLUKA Monte Carlo transport code, a feasibility study was performed to calculate the relative biological effectiveness (RBE) of different GCR spectrum components, for both dicentrics and cell death. Fe-ions, although representing only 10% of the total absorbed dose, were found to be responsible for about 35%-40% of the RBE-weighted dose. Interestingly, the RBE for dicentrics was higher than that for cell survival. More generally, this work shows that BIANCA can calculate RBE values for cell death and lymphocyte dicentrics not only for ion therapy, but also for space radiation.

Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes.

Advances in biological imaging have accelerated our understanding of human physiology in both health and disease. As these advances have developed, the opportunities gained by integrating with cutting-edge mathematical models have become apparent yet remain challenging. Combined imaging-modelling approaches provide unprecedented opportunity to correlate data on tissue architecture and function, across length and time scales, to better understand the mechanisms that underpin fundamental biology and also to inform clinical decisions. Here we discuss the opportunities and challenges of such approaches, providing literature examples across a range of organ systems. Given the breadth of the field we focus on the intersection of continuum modelling and in vivo imaging applied to the vasculature and blood flow, though our rationale and conclusions extend widely. We propose three key research pillars (image acquisition, image processing, mathematical modelling) and present their respective advances as well as future opportunity via better integration. Multidisciplinary efforts that develop imaging and modelling tools concurrently, and share them open-source with the research community, provide exciting opportunity for advancing these fields.

Mathematical models in GnRH research.

Mathematical modelling is an indispensable tool in modern biosciences, enabling quantitative analysis and integration of biological data, transparent formulation of our understanding of complex biological systems, and efficient experimental design based on model predictions. This review article provides an overview of the impact that mathematical models had on GnRH research. Indeed, over the last 20 years mathematical modelling has been used to describe and explore the physiology of the GnRH neuron, the mechanisms underlying GnRH pulsatile secretion, and GnRH signalling to the pituitary. Importantly, these models have contributed to GnRH research via novel hypotheses and predictions regarding the bursting behaviour of the GnRH neuron, the role of kisspeptin neurons in the emergence of pulsatile GnRH dynamics, and the decoding of GnRH signals by biochemical signalling networks. We envisage that with the advent of novel experimental technologies, mathematical modelling will have an even greater role to play in our endeavour to understand the complex spatiotemporal dynamics underlying the reproductive neuroendocrine system.

Seascape genomics identify adaptive barriers correlated to tidal amplitude in the shore crab Carcinus maenas.

Most marine invertebrates disperse during a planktonic larval stage that may drift for weeks with ocean currents. A challenge for larvae of coastal species is to return to coastal nursery habitats. Shore crab (Carcinus maenas L.) larvae are known to show tidal rhythmicity in vertical migration in tidal areas and circadian rhythmicity in microtidal areas, which seems to increase successful coastal settlement. We studied genome-wide differentiation based on 24,000 single nucleotide polymorphisms of 12 native populations of shore crab sampled from a large tidal amplitude gradient from macrotidal (~8 m) to microtidal (~0.2 m). Dispersal and recruitment success of larvae was assessed with a Lagrangian biophysical model, which showed a strong effect of larval behaviour on long-term connectivity, and dispersal barriers that partly coincided with different tidal environments. The genetic population structure showed a subdivision of the samples into three clusters, which represent micro-, meso- and macrotidal areas. The genetic differentiation was mostly driven by 0.5% outlier loci, which showed strong allelic clines located at the limits between the three tidal areas. Demographic modelling suggested that the two genetic barriers have different origins. Differential gene expression of two clock genes (cyc and pdp1) further highlighted phenotypic differences among genetic clusters that are potentially linked to the differences in larval behaviour. Taken together, our seascape genomic study suggests that tidal regime acts as a strong selection force on shore crab population structure, consistent with larval behaviour affecting dispersal and recruitment success.