Aggregation-diffusion in heterogeneous environments.

Aggregation-diffusion equations are foundational tools for modelling biological aggregations. Their principal use is to link the collective movement mechanisms of organisms to their emergent space use patterns in a concrete mathematical way. However, most existing studies do not account for the effect of the underlying environment on organism movement.

Understanding and predicting animal movements and distributions in the Anthropocene.

Predicting animal movements and spatial distributions is crucial for our comprehension of ecological processes and provides key evidence for conserving and managing populations, species and ecosystems. Notwithstanding considerable progress in movement ecology in recent decades, developing robust predictions for rapidly changing environments remains challenging. To accurately predict the effects of anthropogenic change, it is important to first identify the defining features of human-modified environments and their consequences on the drivers of animal movement.

Variations in non-local interaction range lead to emergent chase-and-run in heterogeneous populations.

In a chase-and-run dynamic, the interaction between two individuals is such that one moves towards the other (the chaser), while the other moves away (the runner). Examples can be found in both interacting cells and animals. Here, we investigate the behaviours that can emerge at a population level, for a heterogeneous group that contains subpopulations of chasers and runners.

Distinguishing Between Long-Transient and Asymptotic States in a Biological Aggregation Model.

Aggregations are emergent features common to many biological systems. Mathematical models to understand their emergence are consequently widespread, with the aggregation-diffusion equation being a prime example. Here we study the aggregation-diffusion equation with linear diffusion in one spatial dimension.

Nonviral Liver Disease Burden in People Living With HIV and Elevated Transaminases: A Cross-Sectional Study.

Introduction: Because of improved life expectancy in people living with HIV (PLWH), liver disease is increasingly being recognized. We assessed nonviral chronic liver disease burden in PLWH.

Methods: The HIV non-virAL liver disease study (2014-2021) prospectively recruited PLWH with elevated serum alanine aminotransferase levels and negative hepatitis serology.

How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection.

Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly active area of research. This study focuses on a particular strand of research in this area, based around step selection analysis (SSA).

Detecting minimum energy states and multi-stability in nonlocal advection-diffusion models for interacting species.

Deriving emergent patterns from models of biological processes is a core concern of mathematical biology. In the context of partial differential equations, these emergent patterns sometimes appear as local minimisers of a corresponding energy functional. Here we give methods for determining the qualitative structure of local minimum energy states of a broad class of multi-species nonlocal advection-diffusion models, recently proposed for modelling the spatial structure of ecosystems.

Highlighting when animals expend excessive energy for travel using dynamic body acceleration.

Travel represents a major cost for many animals so there should be selection pressure for it to be efficient - at minimum cost. However, animals sometimes exceed minimum travel costs for reasons that must be correspondingly important. We use Dynamic Body Acceleration (DBA), an acceleration-based metric, as a proxy for movement-based power, in tandem with vertical velocity (rate of change in depth) in a shark () to derive the minimum estimated power required to swim at defined vertical velocities.

Energy-based step selection analysis: Modelling the energetic drivers of animal movement and habitat use.

The energetic gains from foraging and costs of movement are expected to be key drivers of animal decision-making, as their balance is a large determinant of body condition and survival. This fundamental perspective is often missing from habitat selection studies, which mainly describe correlations between space use and environmental features, rather than the mechanisms behind these correlations. To address this gap, we present a novel parameterisation of step selection functions (SSFs), that we term the energy selection function (ESF).

Diagnostic accuracy and interobserver agreement of digital single-operator cholangioscopy for indeterminate biliary strictures.

Background And Aims: Digital single-operator cholangioscopy (d-SOC) with cholangioscopic biopsy sampling has shown promise in the evaluation of indeterminate biliary strictures. Some studies have suggested higher sensitivity for visual impression compared with biopsy sampling, although assessors were not blinded to previous investigations. We aimed to investigate the diagnostic accuracy and interobserver agreement (IOA) of d-SOC in the visual appraisal of biliary strictures when blinded to additional information.

Mechanistic home range analysis reveals drivers of space use patterns for a non-territorial passerine.

Home ranging is a near-ubiquitous phenomenon in the animal kingdom. Understanding the behavioural mechanisms that give rise to observed home range patterns is thus an important general question, and mechanistic home range analysis (MHRA) provides the tools to address it. However, such analysis has hitherto been principally restricted to scent-marking territorial animals, so its potential breadth of application has not been tested.

An "orientation sphere" visualization for examining animal head movements.

Animal behavior is elicited, in part, in response to external conditions, but understanding how animals perceive the environment and make the decisions that bring about these behavioral responses is challenging.Animal heads often move during specific behaviors and, additionally, typically have sensory systems (notably vision, smell, and hearing) sampling in defined arcs (normally to the front of their heads). As such, head-mounted electronic sensors consisting of accelerometers and magnetometers, which can be used to determine the movement and directionality of animal heads (where head "movement" is defined here as changes in heading [azimuth] and/or pitch [elevation angle]), can potentially provide information both on behaviors in general and also clarify which parts of the environment the animals might be prioritizing ("environmental framing").

Optimizing the use of biologgers for movement ecology research.

The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored. Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF). We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology.

Spatial Memory and Taxis-Driven Pattern Formation in Model Ecosystems.

Mathematical models of spatial population dynamics typically focus on the interplay between dispersal events and birth/death processes. However, for many animal communities, significant arrangement in space can occur on shorter timescales, where births and deaths are negligible. This phenomenon is particularly prevalent in populations of larger, vertebrate animals who often reproduce only once per year or less.

Making sense of ultrahigh-resolution movement data: A new algorithm for inferring sites of interest.

Decomposing the life track of an animal into behavioral segments is a fundamental challenge for movement ecology. The proliferation of high-resolution data, often collected many times per second, offers much opportunity for understanding animal movement. However, the sheer size of modern data sets means there is an increasing need for rapid, novel computational techniques to make sense of these data.

imaging of hepatic neutrophil migration in severe alcoholic hepatitis with In-radiolabelled leucocytes.

The study's aim was to image severe alcoholic hepatitis (SAH) using In-labelled leucocytes with two objectives in mind: firstly for non-invasive diagnosis and secondly to provide a platform for experimental therapies aiming to inhibit intrahepatic neutrophil migration. In-leucocyte scintigraphy was performed 30 min and 24 h post-injection in 19 patients with SAH, 14 abstinent patients with alcohol-related cirrhosis and 11 normal controls. Eleven with SAH and seven with cirrhosis also had Tc-nanocolloid scintigraphy.

Fortune favours the brave: Movement responses shape demographic dynamics in strongly competing populations.

Animal movement is a key mechanism for shaping population dynamics. The effect of interactions between competing animals on a population's survival has been studied for many decades. However, interactions also affect an animal's subsequent movement decisions.

Partial differential equation techniques for analysing animal movement: A comparison of different methods.

Recent advances in animal tracking have allowed us to uncover the drivers of movement in unprecedented detail. This has enabled modellers to construct ever more realistic models of animal movement, which aid in uncovering detailed patterns of space use in animal populations. Partial differential equations (PDEs) provide a popular tool for mathematically analysing such models.

Circulating granulocyte lifespan in compensated alcohol-related cirrhosis: a pilot study.

Although granulocyte dysfunction is known to occur in cirrhosis, in vivo studies of granulocyte lifespan have not previously been performed. The normal circulating granulocyte survival half-time (G - t½), determined using indium-111 ((111)In)-radiolabeled granulocytes, is ~7 h. In this pilot study, we aimed to measure the in vivo G - t½ in compensated alcohol-related cirrhosis.

Flexible characterization of animal movement pattern using net squared displacement and a latent state model.

Background: Characterizing the movement patterns of animals is an important step in understanding their ecology. Various methods have been developed for classifying animal movement at both coarse (e.g.

How memory of direct animal interactions can lead to territorial pattern formation.

Mechanistic home range analysis (MHRA) is a highly effective tool for understanding spacing patterns of animal populations. It has hitherto focused on populations where animals defend their territories by communicating indirectly, e.g.

Spatial Patterning of Prey at Reproduction to Reduce Predation Risk: What Drives Dispersion from Groups?

Group living is a widespread behavior thought to be an evolutionary adaptation for reducing predation risk. Many group-living species, however, spend a portion of their life cycle as dispersed individuals, suggesting that the costs and benefits of these opposing behaviors vary temporally. Here, we evaluated mechanistic hypotheses for explaining individual dispersion as a tactic for reducing predation risk at reproduction (i.

Predicting local and non-local effects of resources on animal space use using a mechanistic step selection model.

Predicting space use patterns of animals from their interactions with the environment is fundamental for understanding the effect of habitat changes on ecosystem functioning. Recent attempts to address this problem have sought to unify resource selection analysis, where animal space use is derived from available habitat quality, and mechanistic movement models, where detailed movement processes of an animal are used to predict its emergent utilization distribution. Such models bias the animal's movement towards patches that are easily available and resource-rich, and the result is a predicted probability density at a given position being a function of the habitat quality at that position.