120-years of ecological monitoring data shows that the risk of overhunting is increased by environmental degradation for an isolated marine mammal population: The Baltic grey seal.

The Baltic Sea is home to a genetically isolated and morphologically distinct grey seal population. This population has been the subject of 120-years of careful documentation, from detailed records of bounty statistics to annual monitoring of health and abundance. It has also been exposed to a range of well-documented stressors, including hunting, pollution and climate change. To investigate the vulnerability of marine mammal populations to multiple stressors, data series relating to the Baltic grey seal population size, hunt and health were compiled, vital demographic rates were estimated, and a detailed population model was constructed. The Baltic grey seal population fell from approximately 90,000 to as few as 3000 individuals during the 1900s as the result of hunting and pollution. Subsequently, the population has recovered to approximately 55,000 individuals. Fertility levels for mature females have increased from 9% in the 1970s to 86% at present. The recovery of the population has led to demands for increased hunting, resulting in a sudden increase in annual quotas from a few hundred to 3550 in 2020. Simultaneously, environmental changes, such as warmer winters and reduced prey availability due to overfishing, are likely impacting fecundity and health. Future population development is projected for a range of hunting and environmental stress scenarios, illustrating how hunting, in combination with environmental degradation, can lead to population collapse. The current combined hunting quotas of all Baltic Nations caused a 10% population decline within three generations in 100% of simulations. To enable continued recovery of the population, combined annual quotas of less than 1900 are needed, although this quota should be re-evaluated annually as monitoring of population size and seal health continues. Sustainable management of long-lived slowly growing species requires an understanding of the drivers of population growth and the repercussions of management decisions over many decades. The case of the Baltic grey seal illustrates how long-term ecological time series are pivotal in establishing historical baselines in population abundance and demography to inform sustainable management.

SARS-CoV-2 elicits non-sterilizing immunity and evades vaccine-induced immunity: implications for future vaccination strategies.

Neither vaccination nor natural infection result in long-lasting protection against SARS-COV-2 infection and transmission, but both reduce the risk of severe COVID-19. To generate insights into optimal vaccination strategies for prevention of severe COVID-19 in the population, we extended a Susceptible-Exposed-Infectious-Removed (SEIR) mathematical model to compare the impact of vaccines that are highly protective against severe COVID-19 but not against infection and transmission, with those that block SARS-CoV-2 infection. Our analysis shows that vaccination strategies focusing on the prevention of severe COVID-19 are more effective than those focusing on creating of herd immunity. Key uncertainties that would affect the choice of vaccination strategies are: (1) the duration of protection against severe disease, (2) the protection against severe disease from variants that escape vaccine-induced immunity, (3) the incidence of long-COVID and level of protection provided by the vaccine, and (4) the rate of serious adverse events following vaccination, stratified by demographic variables.

Persistent symptoms of fatigue, neuropathy and role-functioning impairment among indolent non-Hodgkin lymphoma survivors: A longitudinal PROFILES registry study.

Little is known about the long-term health-related quality of life (HRQoL) and persistence of symptoms among patients with indolent non-Hodgkin lymphoma (iNHL). This large population-based longitudinal study therefore investigated the long-term HRQoL and persistence of symptoms and identified associated sociodemographic, clinical and psychological factors. Patients diagnosed between 1999 and 2014 and four or more months after diagnosis were invited to participate in a longitudinal survey. Sociodemographic and clinical data were obtained from the Netherlands Cancer Registry. The EORTC QLQ-C30 and CLL-16 were completed by 669 patients (74% response rate). Patients completed on average four questionnaires. Primary treatment was active surveillance (52%), systemic therapy (31%) or radiotherapy (13%). Respectively, 36% reported persistent fatigue, 33% persistent neuropathy and 25% persistent role-functioning impairment. This was 2-3 times higher than in the age- and sex-matched normative population. Up to 10 years after diagnosis, scores remained relatively stable without clinically relevant changes. Comorbidities, psychological distress, shorter time since diagnosis, systemic therapy, younger age, education level and having no partner were associated with worse outcomes (all ps < 0.05). Up to a third of patients with iNHL experience long-term persistent symptoms which do not improve over time. Early recognition of symptoms will help in providing tailored supportive care for those in need.

Adaptation to distinct habitats is maintained by contrasting selection at different life stages in sunflower ecotypes.

Conspecific populations living in adjacent but contrasting microenvironments represent excellent systems for studying natural selection. These systems are valuable because gene flow is expected to force genetic homogeneity except at loci experiencing divergent selection. A history of reciprocal transplant and common garden studies in such systems, and a growing number of genomic studies, have contributed to understanding how selection operates in natural populations. While selection can vary across different fitness components and life stages, few studies have investigated how this ultimately affects allele frequencies and the maintenance of divergence between populations. Here, we study two sunflower ecotypes in distinct, adjacent habitats by combining demographic models with genome-wide sequence data to estimate fitness and allele frequency change at multiple life stages. This framework allows us to estimate that only local ecotypes are likely to experience positive population growth (λ > 1) and that the maintenance of divergent adaptation appears to be mediated via habitat- and life stage-specific selection. We identify genetic variation, significantly driven by loci in chromosomal inversions, associated with different life history strategies in neighbouring ecotypes that optimize different fitness components and may contribute to the maintenance of distinct ecotypes.

Pharmacodynamic modelling and exposure-response assessment of inebilizumab in subjects with neuromyelitis optica spectrum disorders.

AIMS: Neuromyelitis optica spectrum disorders (NMOSD) is an autoantibody-mediated, B cell-driven disease. Inebilizumab is a humanized, affinity-optimized, afucosylated IgG1 κ monoclonal antibody that binds to the B-cell specific surface antigen CD19, resulting in rapid, profound and sustained depletion of circulating peripheral B cells in NMOSD subjects (pivotal study). The objective of this study was to conduct population modelling of B-cell response following inebilizumab treatment in adult subjects with NMOSD, and to assess the impact of drug exposure to outcome. METHODS: A haematopoietic transit model was developed to describe the joint effects of reducing influx from pro-B cells and accelerating CD20+ B-cell depletion in the blood by inebilizumab. Furthermore, the relationships between inebilizumab pharmacokinetic (PK) exposure and the primary efficacy endpoint and key secondary efficacy endpoints were evaluated. RESULTS: At the 300-mg dose, there was no apparent relationship between efficacy (reduction in disease attack risk, risk of worsening from baseline in Expanded Disability Status Scale, cumulative total active MRI lesions, and the number of NMOSD-related in-patient hospitalizations) and PK exposure. Subjects with low, medium and high PK exposure had a similar hazard ratio of NMOSD attack vs. placebo group. CONCLUSION: The pharmacodynamic modelling confirmed effective depletion of B cells is achieved with a 300 mg intravenous dose of inebilizumab administered on Day 1 and Day 15 and every 6 months thereafter. The PK variability between patients had no apparent effect on clinical efficacy.

Towards an ecological modelling approach for assessing ionizing radiation impact on wildlife populations.

The emphasis of the international system of radiological protection of the environment is to protect populations of flora and fauna. Throughout the MODARIA programmes, the United Nations' International Atomic Energy Agency (IAEA) has facilitated knowledge sharing, data gathering and model development on the effect of radiation on wildlife. We present a summary of the achievements of MODARIA I and II on wildlife dose effect modelling, extending to a new sensitivity analysis and model development to incorporate other stressors. We reviewed evidence on historical doses and transgenerational effects on wildlife from radioactively contaminated areas. We also evaluated chemical population modelling approaches, discussing similarities and differences between chemical and radiological impact assessment in wildlife. We developed population modelling methodologies by sourcing life history and radiosensitivity data and evaluating the available models, leading to the formulation of an ecosystem-based mathematical approach. This resulted in an ecologically relevant conceptual population model, which we used to produce advice on the evaluation of risk criteria used in the radiological protection of the environment and a proposed modelling extension for chemicals. This work seeks to inform stakeholder dialogue on factors influencing wildlife population responses to radiation, including discussions on the ecological relevance of current environmental protection criteria. The area of assessment of radiation effects in wildlife is still developing with underlying data and models continuing to be improved. IAEA's ongoing support to facilitate the sharing of new knowledge, models and approaches to Member States is highlighted, and we give suggestions for future developments in this regard.

Range dynamics mediated by compensatory life stage responses to experimental climate manipulations.

The expectations of polar or upslope distributional shifts of species ranges in response to warming climate conditions have been recently questioned. Diverse responses of different life stages to changing temperature and moisture regimes may alter these predicted range dynamics. Furthermore, the climate driver(s) influencing demographic rates, and the contribution of each demographic rate to population growth rate (λ), may shift across a species range. We investigated these demographic effects by experimentally manipulating climate and measuring responses of λ in nine populations spanning the elevation range of an alpine plant (Ivesia lycopodioides). Populations exhibited stable growth rates (λ ~ 1) under naturally wet conditions and declining rates (λ < 1) under naturally dry conditions. However, opposing vital rate responses to experimental heating and watering lead to negligible or negative effects on population stability. These findings indicate that life stage-specific responses to changing climate can disrupt the current relationships between population stability and climate across species ranges.

Plasma and cerebrospinal fluid pharmacokinetics of ondansetron in humans.

AIMS: Changes in serotonergic sensory modulation associated with overexpression of 5-HT3 receptors in the central nervous system (CNS) have been implicated in the pathophysiology of neuropathic pain after peripheral nerve damage. 5-HT3 receptor antagonists such as ondansetron can potentially alleviate neuropathic pain, but have limited effectiveness, due potentially to limited CNS access. However, there is currently limited information on CNS disposition of systemically-administered 5-HT3 receptor antagonists. This study evaluated the cerebrospinal fluid (CSF) disposition of ondansetron, as a surrogate of CNS penetration. METHODS: Fifteen patients were given a single 16 mg intravenous 15 minute infusion of ondansetron, followed by serial blood and a single CSF sampling. Population pharmacokinetic (PK) modelling was implemented to describe the average and individual plasma and CSF profiles of ondansetron. A two-compartmental model was used to capture ondansetron plasma PK with a single CSF compartment to describe distribution to the CNS. RESULTS: The individual model-estimated CSF to plasma partition coefficients of ondansetron were between 0.09 and 0.20. These values were mirrored in the calculated CSF penetration ratios, ranging from 0.08 to 0.26. CONCLUSIONS: After intravenous administration, CSF concentrations of ondansetron were approximately 7-fold lower than those observed in the plasma. A model could be developed to describe individual CSF concentration-time profiles of ondansetron based on a single CSF data point. The low CSF penetration of ondansetron may explain its limited analgesic effectiveness, and affords an opportunity to explore enhancing its CNS penetration for targeting conditions such as neuropathic pain.

Capturing the dynamics of small populations: A retrospective assessment using long-term data for an island reintroduction.

The art of population modelling is to incorporate factors essential for capturing a population's dynamics while otherwise keeping the model as simple as possible. However, it is unclear how optimal model complexity should be assessed, and whether this optimal complexity has been affected by recent advances in modelling methodology. This issue is particularly relevant to small populations because they are subject to complex dynamics but inferences about those dynamics are often constrained by small sample sizes. We fitted Bayesian hierarchical models to long-term data on vital rates (survival and reproduction) for the toutouwai Petroica longipes population reintroduced to Tiritiri Matangi, a 220-ha New Zealand island, and quantified the performance of those models in terms of their likelihood of replicating the observed population dynamics. These dynamics consisted of overall growth from 33 (±0.3) to 160 (±6) birds from 1992-2018, including recoveries following five harvest events for further reintroductions to other sites. We initially included all factors found to affect vital rates, which included inbreeding, post-release effects (PRE), density-dependence, sex, age and random annual variation, then progressively removed these factors. We also compared performance of models where data analysis and simulations were done simultaneously to those produced with the traditional two-step approach, where vital rates are estimated first then fed into a separate simulation model. Parametric uncertainty and demographic stochasticity were incorporated in all projections. The essential factors for replicating the population's dynamics were density-dependence in juvenile survival and PRE, i.e. initial depression of survival and reproduction in translocated birds. Inclusion of other factors reduced the precision of projections, and therefore the likelihood of matching observed dynamics. However, this reduction was modest when the modelling was done in an integrated framework. In contrast, projections were much less precise when done with a two-step modelling approach, and the cost of additional parameters was much higher under the two-step approach. These results suggest that minimization of complexity may be less important than accounting for covariances in parameter estimates, which is facilitated by integrating data analysis and population projections using Bayesian methods.

How disease constrains the evolution of social systems.

Animal populations are occasionally shocked by epidemics of contagious diseases. The ability of social systems to withstand epidemic shocks and mitigate disruptions could shape the evolution of complex animal societies. We present a mathematical model to explore the potential impact of disease on the evolutionary fitness of different organizational strategies for populations of social species whose survival depends on collaborative efficiency. We show that infectious diseases select for a specific feature in the organization of collaborative roles-cohort stability-and that this feature is costly, and therefore unlikely to be maintained in environments where infection risks are absent. Our study provides evidence for an often-stated (but rarely supported) claim that pathogens have been the dominant force shaping the complexity of division of labour in eusocial societies of honeybees and termites and establishes a general theoretical approach for assessing evolutionary constraints on social organization from disease risk in other collaborative taxa.

Modelling of neutrophil dynamics in children receiving busulfan or treosulfan for haematopoietic stem cell transplant conditioning.

AIMS: Busulfan and treosulfan are cytotoxic agents used in the conditioning regime prior to paediatric haematopoietic stem cell transplantation (HSCT). These agents cause suppression of myeloid cells leaving patients severely immunocompromised in the early post-HSCT period. The main objectives were: (i) to establish a mechanistic pharmacokinetic-pharmacodynamic (PKPD) model for the treatment and engraftment effects on neutrophil counts comparing busulfan and treosulfan-based conditioning, and (ii) to explore current dosing schedules with respect to time to HSCT. METHODS: Data on 126 patients, 72 receiving busulfan (7 months-18 years, 5.1-47.0 kg) and 54 treosulfan (4 months-17 years, 3.8-35.8 kg), were collected. In total, 8935 neutrophil count observations were recorded during the study period in addition to drug concentrations to develop a mechanistic PKPD model. Absolute neutrophil count profiles were modelled semimechanistically, accounting for transplant effects and differing set points pre- and post-transplant. RESULTS: PK were best described by 2-compartment models for both drugs. The Friberg semimechanistic neutropenia model was applied with a linear model for busulfan and a maximum efficacy model for treosulfan describing drug effects at various stages of neutrophil maturation. System parameters were consistent across both drugs. The HSCT was represented by an amount of progenitor cells enhancing the neutrophils' proliferation and maturation compartments. Alemtuzumab was found to enhance the proliferative rate under which the absolute neutrophil count begin to grow after HSCT. CONCLUSION: A semimechanistic PKPD model linking exposure to either busulfan or treosulfan to the neutrophil reconstitution dynamics was successfully built. Alemtuzumab coadministration enhanced the neutrophil proliferative rate after HSCT. Treosulfan administration was suggested to be delayed with respect to time to HSCT, leaving less time between the end of the administration and stem cell infusion.

Ontogenetic niche shifts as a driver of seasonal migration.

Ontogenetic niche shifts have helped to understand population dynamics. Here we show that ontogenetic niche shifts also offer an explanation, complementary to traditional concepts, as to why certain species show seasonal migration. We describe how demographic processes (survival, reproduction and migration) and associated ecological requirements of species may change with ontogenetic stage (juvenile, adult) and across the migratory range (breeding, non-breeding). We apply this concept to widely different species (dark-bellied brent geese (Branta b. bernicla), humpback whales (Megaptera novaeangliae) and migratory Pacific salmon (Oncorhynchus gorbuscha) to check the generality of this hypothesis. Consistent with the idea that ontogenetic niche shifts are an important driver of seasonal migration, we find that growth and survival of juvenile life stages profit most from ecological conditions that are specific to breeding areas. We suggest that matrix population modelling techniques are promising to detect the importance of the ontogenetic niche shifts in maintaining migratory strategies. As a proof of concept, we applied a first analysis to resident, partial migratory and fully migratory populations of barnacle geese (Branta leucopsis). We argue that recognition of the costs and benefits of migration, and how these vary with life stages, is important to understand and conserve migration under global environmental change.

Pharmacokinetics and Pharmacodynamics of Drugs in Obese Pediatric Patients: How to Map Uncharted Clinical Territories.

Clinicians are increasingly faced with challenges regarding the pharmacological treatment of obese pediatric patients. To provide guidance for these treatments, a better understanding of the impact of obesity on pharmacological processes in children is needed. Results on pharmacological studies in adults show however ambiguous patterns regarding the impact of obesity on ADME processes or on drug pharmacodynamics. Additionally, based on the limited research performed in obese pediatric patients, it becomes clear that findings from obese adults cannot be expected to always translate directly to similar findings in obese children. To improve knowledge on drug pharmacology in obese pediatric patients, studies should focus on quantifying the impact of maturation, obesity, and other relevant variables on primary pharmacological parameters and on disentangling systemic (renal and/or hepatic) and presystemic (gut and/or first-pass hepatic) clearance. For this, data is required from well-designed clinical trials that include patients with not only a wide range in age but also a range in excess body weight, upon oral and intravenous dosing. Population modelling approaches are ideally suitable for this purpose and can also be used to link the pharmacokinetics to pharmacodynamics and to derive drug dosing regimens. Generalizability of research findings can be achieved by including mechanistic aspects in the data analysis, for instance, using either extrapolation approaches in population modelling or by applying physiologically based modelling principles. It is imperative that more and smarter studies are performed in obese pediatric patients to provide safe and effective treatment for this special patient population.

Mountain pine beetle outbreak duration and pine mortality depend on direct control effort.

The efficacy of direct control methods in bark beetle outbreaks is a disputed topic. While some studies report that control reduces tree mortality, others see little effect. Existing models, linking control rate to beetle population dynamics and tree infestations, give insights, but there is a need to take into account the environment spatial variability and its impact on beetle life cycle. Here, we use natural variability found in a carefully monitored and controlled infestation to simulate outbreak dynamics under different control effort and to explore the impact of control on outbreaks suppression and tree mortality. Our semi-empirical predictive model of the number of infested trees as a function of ecological and environmental variables is coupled to a simulation model for infestation dynamics. We show that even a little control can have a major impact on the number of infested trees after several years of sustained effort. However, a moderate control of 60% is required to reduce the beetle population on the long term. Furthermore, a control rate of 69%-83% is needed to achieve outbreak suppression in under 13 years depending on the abundance of incoming flights from outside sources.

Framework for quantifying population responses to disturbance reveals that coastal birds are highly resilient to hurricanes.

Changes in the frequency and severity of extreme weather may introduce new threats to species that are already under stress from gradual habitat loss and climate change. We provide a probabilistic framework that quantifies potential threats by applying concepts from ecological resilience to single populations. Our approach uses computation to compare disturbance-impacted projections to a population's normal range of variation, quantifying the full range of potential impacts. We illustrate this framework with projection models for coastal birds, which are commonly depicted as vulnerable to disturbances, especially hurricanes and oil spills. We found that populations of coastal specialists are resilient to extreme disturbances, with high resistance to the effects of short-term reductions in vital rates and recovery within 20 years. Applying the general framework presented here across disturbance-prone species and ecosystems would improve understanding of population resilience and generate specific projections of resilience that are needed for effective conservation planning.

How many and when? Optimising targeted gene flow for a step change in the environment.

Targeted gene flow is an emerging conservation strategy that involves introducing individuals with particular traits to places where these traits are of benefit. One obvious application is to adapt a recipient population to a known threat, but questions remain as to how best to achieve this. Here, we vary timing and size of the introduction to maximise our objective - survival of the recipient population's genome. We explore a generic population model as well as a specific example - the northern quoll, an Australian marsupial predator threatened by the toxic cane toad. We reveal a trade-off between preserving the recipient genome and reducing population extinction risk, but key management levers can often optimise this so that nearly 100% of the recipient population's genome is preserved. Any action was better than none but the size of the benefit was sensitive to outbreeding depression, recombination rate, and the timing and size of the introduction.

Predicting population change from models based on habitat availability and utilization.

The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations.

Management and population dynamics of diamondback moth (Plutella xylostella): planting regimes, crop hygiene, biological control and timing of interventions.

Using an age-structured process-based simulation model for diamondback moth (DBM), we model the population dynamics of this major Brassica pest using the cropping practices and climate of Guangdong, China. The model simulates two interacting sub-populations (demes), each representing a short season crop. The simulated DBM abundance, and hence pest problems, depend on planting regime, crop hygiene and biological control. A continuous supply of hosts, a low proportion of crop harvested and long residue times between harvest and replanting each exacerbate pest levels. Biological control provided by a larval parasitoid can reduce pest problems, but not eliminate them when climate is suitable for DBM and under certain planting practices. The classic Integrated Pest Management (IPM) method of insecticide application, when pest threshold is reached, proved effective and halved the number of insecticide sprays when compared with the typical practice of weekly insecticide application.

Can Population Modelling Principles be Used to Identify Key PBPK Parameters for Paediatric Clearance Predictions? An Innovative Application of Optimal Design Theory.

PURPOSE: Physiologically-based pharmacokinetic (PBPK) models are essential in drug development, but require parameters that are not always obtainable. We developed a methodology to investigate the feasibility and requirements for precise and accurate estimation of PBPK parameters using population modelling of clinical data and illustrate this for two key PBPK parameters for hepatic metabolic clearance, namely whole liver unbound intrinsic clearance (CLint,u,WL) and hepatic blood flow (Qh) in children. METHODS: First, structural identifiability was enabled through re-parametrization and the definition of essential trial design components. Subsequently, requirements for the trial components to yield precise estimation of the PBPK parameters and their inter-individual variability were established using a novel application of population optimal design theory. Finally, the performance of the proposed trial design was assessed using stochastic simulation and estimation. RESULTS: Precise estimation of CLint,u,WL and Qh and their inter-individual variability was found to require a trial with two drugs, of which one has an extraction ratio (ER) ≤ 0.27 and the other has an ER ≥ 0.93. The proposed clinical trial design was found to lead to precise and accurate parameter estimates and was robust to parameter uncertainty. CONCLUSION: The proposed framework can be applied to other PBPK parameters and facilitate the development of PBPK models.

A dosing algorithm for metformin based on the relationships between exposure and renal clearance of metformin in patients with varying degrees of kidney function.

PURPOSE: The aims of this study were to investigate the relationship between metformin exposure, renal clearance (CLR), and apparent non-renal clearance of metformin (CLNR/F) in patients with varying degrees of kidney function and to develop dosing recommendations. METHODS: Plasma and urine samples were collected from three studies consisting of patients with varying degrees of kidney function (creatinine clearance, CLCR; range, 14-112 mL/min). A population pharmacokinetic model was built (NONMEM) in which the oral availability (F) was fixed to 0.55 with an estimated inter-individual variability (IIV). Simulations were performed to estimate AUC0-τ, CLR, and CLNR/F. RESULTS: The data (66 patients, 327 observations) were best described by a two-compartment model, and CLCR was a covariate for CLR. Mean CLR was 17 L/h (CV 22%) and mean CLNR/F was 1.6 L/h (69%).The median recovery of metformin in urine was 49% (range 19-75%) over a dosage interval. When CLR increased due to improved renal function, AUC0-τ decreased proportionally, while CLNR/F did not change with kidney function. Target doses (mg/day) of metformin can be reached using CLCR/3 × 100 to obtain median AUC0-12 of 18-26 mg/L/h for metformin IR and AUC0-24 of 38-51 mg/L/h for metformin XR, with Cmax < 5 mg/L. CONCLUSIONS: The proposed dosing algorithm can be used to dose metformin in patients with various degrees of kidney function to maintain consistent drug exposure. However, there is still marked IIV and therapeutic drug monitoring of metformin plasma concentrations is recommended.