Adaptation of sea turtles to climate warming: Will phenological responses be sufficient to counteract changes in reproductive output?

Sea turtles are vulnerable to climate change since their reproductive output is influenced by incubating temperatures, with warmer temperatures causing lower hatching success and increased feminization of embryos. Their ability to cope with projected increases in ambient temperatures will depend on their capacity to adapt to shifts in climatic regimes. Here, we assessed the extent to which phenological shifts could mitigate impacts from increases in ambient temperatures (from 1.5 to 3°C in air temperatures and from 1.4 to 2.3°C in sea surface temperatures by 2100 at our sites) on four species of sea turtles, under a "middle of the road" scenario (SSP2-4.5). Sand temperatures at sea turtle nesting sites are projected to increase from 0.58 to 4.17°C by 2100 and expected shifts in nesting of 26-43 days earlier will not be sufficient to maintain current incubation temperatures at 7 (29%) of our sites, hatching success rates at 10 (42%) of our sites, with current trends in hatchling sex ratio being able to be maintained at half of the sites. We also calculated the phenological shifts that would be required (both backward for an earlier shift in nesting and forward for a later shift) to keep up with present-day incubation temperatures, hatching success rates, and sex ratios. The required shifts backward in nesting for incubation temperatures ranged from -20 to -191 days, whereas the required shifts forward ranged from +54 to +180 days. However, for half of the sites, no matter the shift the median incubation temperature will always be warmer than the 75th percentile of current ranges. Given that phenological shifts will not be able to ameliorate predicted changes in temperature, hatching success and sex ratio at most sites, turtles may need to use other adaptive responses and/or there is the need to enhance sea turtle resilience to climate warming.

Medicines and Healthcare products Regulatory Agency's "Consultation on proposals for legislative changes for clinical trials": a response from the Trials Methodology Research Partnership Adaptive Designs Working Group, with a focus on data sharing.

In the UK, the Medicines and Healthcare products Regulatory Agency consulted on proposals "to improve and strengthen the UK clinical trials legislation to help us make the UK the best place to research and develop safe and innovative medicines". The purpose of the consultation was to help finalise the proposals and contribute to the drafting of secondary legislation. We discussed these proposals as members of the Trials Methodology Research Partnership Adaptive Designs Working Group, which is jointly funded by the Medical Research Council and the National Institute for Health and Care Research. Two topics arose frequently in the discussion: the emphasis on legislation, and the absence of questions on data sharing. It is our opinion that the proposals rely heavily on legislation to change practice. However, clinical trials are heterogeneous, and as a result some trials will struggle to comply with all of the proposed legislation. Furthermore, adaptive design clinical trials are even more heterogeneous than their non-adaptive counterparts, and face more challenges. Consequently, it is possible that increased legislation could have a greater negative impact on adaptive designs than non-adaptive designs. Overall, we are sceptical that the introduction of legislation will achieve the desired outcomes, with some exceptions. Meanwhile the topic of data sharing - making anonymised individual-level clinical trial data available to other investigators for further use - is entirely absent from the proposals and the consultation in general. However, as an aspect of the wider concept of open science and reproducible research, data sharing is an increasingly important aspect of clinical trials. The benefits of data sharing include faster innovation, improved surveillance of drug safety and effectiveness and decreasing participant exposure to unnecessary risk. There are already a number of UK-focused documents that discuss and encourage data sharing, for example, the Concordat on Open Research Data and the Medical Research Council's Data Sharing Policy. We strongly suggest that data sharing should be the norm rather than the exception, and hope that the forthcoming proposals on clinical trials invite discussion on this important topic.

Sample size determination for point-of-care COVID-19 diagnostic tests: a Bayesian approach.

BACKGROUND: In a pandemic setting, it is critical to evaluate and deploy accurate diagnostic tests rapidly. This relies heavily on the sample size chosen to assess the test accuracy (e.g. sensitivity and specificity) during the diagnostic accuracy study. Too small a sample size will lead to imprecise estimates of the accuracy measures, whereas too large a sample size may delay the development process unnecessarily. This study considers use of a Bayesian method to guide sample size determination for diagnostic accuracy studies, with application to COVID-19 rapid viral detection tests. Specifically, we investigate whether utilising existing information (e.g. from preceding laboratory studies) within a Bayesian framework can reduce the required sample size, whilst maintaining test accuracy to the desired precision. METHODS: The method presented is based on the Bayesian concept of assurance which, in this context, represents the unconditional probability that a diagnostic accuracy study yields sensitivity and/or specificity intervals with the desired precision. We conduct a simulation study to evaluate the performance of this approach in a variety of COVID-19 settings, and compare it to commonly used power-based methods. An accompanying interactive web application is available, which can be used by researchers to perform the sample size calculations. RESULTS: Results show that the Bayesian assurance method can reduce the required sample size for COVID-19 diagnostic accuracy studies, compared to standard methods, by making better use of laboratory data, without loss of performance. Increasing the size of the laboratory study can further reduce the required sample size in the diagnostic accuracy study. CONCLUSIONS: The method considered in this paper is an important advancement for increasing the efficiency of the evidence development pathway. It has highlighted that the trade-off between lab study sample size and diagnostic accuracy study sample size should be carefully considered, since establishing an adequate lab sample size can bring longer-term gains. Although emphasis is on its use in the COVID-19 pandemic setting, where we envisage it will have the most impact, it can be usefully applied in other clinical areas.

Subgroup analyses in randomized controlled trials frequently categorized continuous subgroup information.

BACKGROUND AND OBJECTIVES: To investigate how subgroup analyses of published Randomized Controlled Trials (RCTs) are performed when subgroups are created from continuous variables. METHODS: We carried out a review of RCTs published in 2016-2021 that included subgroup analyses. Information was extracted on whether any of the subgroups were based on continuous variables and, if so, how they were analyzed. RESULTS: Out of 428 reviewed papers, 258 (60.4%) reported RCTs with a subgroup analysis. Of these, 178/258 (69%) had at least one subgroup formed from a continuous variable and 14/258 (5.4%) were unclear. The vast majority (169/178, 94.9%) dichotomized the continuous variable and treated the subgroup as categorical. The most common way of dichotomizing was using a pre-specified cutpoint (129/169, 76.3%), followed by a data-driven cutpoint (26/169, 15.4%), such as the median. CONCLUSION: It is common for subgroup analyses to use continuous variables to define subgroups. The vast majority dichotomize the continuous variable and, consequently, may lose substantial amounts of statistical information (equivalent to reducing the sample size by at least a third). More advanced methods that can improve efficiency, through optimally choosing cutpoints or directly using the continuous information, are rarely used.

Generalisations of a Bayesian decision-theoretic randomisation procedure and the impact of delayed responses.

The design of sequential experiments and, in particular, randomised controlled trials involves a trade-off between operational characteristics such as statistical power, estimation bias and patient benefit. The family of randomisation procedures referred to as Constrained Randomised Dynamic Programming (CRDP), which is set in the Bayesian decision-theoretic framework, can be used to balance these competing objectives. A generalisation and novel interpretation of CRDP is proposed to highlight its inherent flexibility to adapt to a variety of practicalities and align with individual trial objectives. CRDP, as with most response-adaptive randomisation procedures, hinges on the limiting assumption of patient responses being available before allocation of the next patient. This forms one of the greatest barriers to their implementation in practice which, despite being an important research question, has not received a thorough treatment. Therefore, motivated by the existing gap between the theory of response-adaptive randomisation (which is abundant with proposed methods in the immediate response setting) and clinical practice (in which responses are typically delayed), the performance of CRDP in the presence of fixed and random delays is evaluated. Simulation results show that CRDP continues to offer patient benefit gains over alternative procedures and is relatively robust to delayed responses. To compensate for a fixed delay, a method which adjusts the time horizon used in the optimisation objective is proposed and its performance illustrated.

Bendamustine is safe and effective for lymphodepletion before tisagenlecleucel in patients with refractory or relapsed large B-cell lymphomas.

BACKGROUND: Anti-CD19 chimeric antigen receptor T-cell immunotherapy (CAR-T) is now a standard treatment of relapsed or refractory B-cell non-Hodgkin lymphomas; however, a significant portion of patients do not respond to CAR-T and/or experience toxicities. Lymphodepleting chemotherapy is a critical component of CAR-T that enhances CAR-T-cell engraftment, expansion, cytotoxicity, and persistence. We hypothesized that the lymphodepletion regimen might affect the safety and efficacy of CAR-T. PATIENTS AND METHODS: We compared the safety and efficacy of lymphodepletion using either fludarabine/cyclophosphamide (n = 42) or bendamustine (n = 90) before tisagenlecleucel in two cohorts of patients with relapsed or refractory large B-cell lymphomas treated consecutively at three academic institutions in the United States (University of Pennsylvania, n = 90; Oregon Health & Science University, n = 35) and Europe (University of Vienna, n = 7). Response was assessed using the Lugano 2014 criteria and toxicities were assessed by the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 and, when possible, the American Society for Transplantation and Cellular Therapy (ASTCT) consensus grading. RESULTS: Fludarabine/cyclophosphamide led to more profound lymphocytopenia after tisagenlecleucel infusion compared with bendamustine, although the efficacy of tisagenlecleucel was similar between the two groups. We observed significant differences, however, in the frequency and severity of adverse events. In particular, patients treated with bendamustine had lower rates of cytokine release syndrome and neurotoxicity. In addition, higher rates of hematological toxicities were observed in patients receiving fludarabine/cyclophosphamide. Bendamustine-treated patients had higher nadir neutrophil counts, hemoglobin levels, and platelet counts, as well as a shorter time to blood count recovery, and received fewer platelet and red cell transfusions. Fewer episodes of infection, neutropenic fever, and post-infusion hospitalization were observed in the bendamustine cohort compared with patients receiving fludarabine/cyclophosphamide. CONCLUSIONS: Bendamustine for lymphodepletion before tisagenlecleucel has efficacy similar to fludarabine/cyclophosphamide with reduced toxicities, including cytokine release syndrome, neurotoxicity, infectious and hematological toxicities, as well as reduced hospital utilization.

Bayesian sample size determination for diagnostic accuracy studies.

The development of a new diagnostic test ideally follows a sequence of stages which, among other aims, evaluate technical performance. This includes an analytical validity study, a diagnostic accuracy study, and an interventional clinical utility study. In this article, we propose a novel Bayesian approach to sample size determination for the diagnostic accuracy study, which takes advantage of information available from the analytical validity stage. We utilize assurance to calculate the required sample size based on the target width of a posterior probability interval and can choose to use or disregard the data from the analytical validity study when subsequently inferring measures of test accuracy. Sensitivity analyses are performed to assess the robustness of the proposed sample size to the choice of prior, and prior-data conflict is evaluated by comparing the data to the prior predictive distributions. We illustrate the proposed approach using a motivating real-life application involving a diagnostic test for ventilator associated pneumonia. Finally, we compare the properties of the approach against commonly used alternatives. The results show that, when suitable prior information is available, the assurance-based approach can reduce the required sample size when compared to alternative approaches.

Selective Ion Acceleration by Intense Radiation Pressure.

We report on the selective acceleration of carbon ions during the interaction of ultrashort, circularly polarized and contrast-enhanced laser pulses, at a peak intensity of 5.5×10^{20} W/cm^{2}, with ultrathin carbon foils. Under optimized conditions, energies per nucleon of the bulk carbon ions reached significantly higher values than the energies of contaminant protons (33 MeV/nucleon vs 18 MeV), unlike what is typically observed in laser-foil acceleration experiments. Experimental data, and supporting simulations, emphasize different dominant acceleration mechanisms for the two ion species and highlight an (intensity dependent) optimum thickness for radiation pressure acceleration; it is suggested that the preceding laser energy reaching the target before the main pulse arrives plays a key role in a preferential acceleration of the heavier ion species.

Modelling the links between farm characteristics, respiratory health and pig production traits.

Sustainable livestock production requires links between farm characteristics, animal performance and animal health to be recognised and understood. In the pig industry, respiratory disease is prevalent, and has negative health, welfare and economic consequences. We used national-level carcass inspection data from the Food Standards Agency to identify associations between pig respiratory disease, farm characteristics (housing type and number of source farms), and pig performance (mortality, average daily weight gain, back fat and carcass weight) from 49 all in/all out grow-to-finish farms. We took a confirmatory approach by pre-registering our hypotheses and used Bayesian multi-level modelling to quantify the uncertainty in our estimates. The study findings showed that acquiring growing pigs from multiple sources was associated with higher respiratory condition prevalence. Higher prevalence of respiratory conditions was linked with higher mortality, and lower average daily weight gain, back fat and pig carcass weight. Our results support previous literature using a range of data sources. In conclusion, we find that meat inspection data are more valuable at a finer resolution than has been previously indicated and could be a useful tool in monitoring batch-level pig health in the future.

Determining pig holding type from British movement data using analytical and machine learning approaches.

Determining the size, location and structure of a livestock population is an essential aspect of surveillance and research as it provides understanding of the representativeness and coverage of any project or scheme. It is an important input for a variety of epidemiological analyses, for example, allowing generation of more accurate sample size calculations for estimating prevalence or freedom from disease, cost-benefit analyses for control measures to reduce or eradicate livestock disease, or development of between-herd network models to estimate the impact of movement of animals between farms on the spread of livestock diseases. The work described here provides information on how British pig movement data was compared against other datasets related to the British pig population to define its appropriateness for defining pig holding demographics. The data were then used to identify the location of pig holdings and the estimated herd size (split into five categories). Two methods are described that were used to classify the holding type of the identified pig holdings. The first method was an epidemiological method that used expert opinion to determine a set of rules based on movement characteristics to classify each holding. The second method was a machine learning approach that used k means cluster analysis to automatically estimate the holding type based on a set of proxy indicators. Each method had a good accuracy rate, when compared to matched holdings present in data provided by the Annual June Agricultural Survey, but all misclassified some holdings. While both of the methods on their own provided a reasonable estimate, it was concluded that a consensus model, considering the results of both models and the Survey, provided the most accurate result. However, the machine learning approach was beneficial, as although some technical expertise was needed to set up the model, it was considerably faster to implement than the other method, as well as being quicker and easier to adapt and re-run with updated information.

Influence of temperature on prevalence of health and welfare conditions in pigs: time-series analysis of pig abattoir inspection data in England and Wales.

The prevalence of many diseases in pigs displays seasonal distributions. Despite growing concerns about the impacts of climate change, we do not yet have a good understanding of the role that weather factors play in explaining such seasonal patterns. In this study, national and county-level aggregated abattoir inspection data were assessed for England and Wales during 2010-2015. Seasonally-adjusted relationships were characterised between weekly ambient maximum temperature and the prevalence of both respiratory conditions and tail biting detected at slaughter. The prevalence of respiratory conditions showed cyclical annual patterns with peaks in the summer months and troughs in the winter months each year. However, there were no obvious associations with either high or low temperatures. The prevalence of tail biting generally increased as temperatures decreased, but associations were not supported by statistical evidence: across all counties there was a relative risk of 1.028 (95% CI 0.776-1.363) for every 1 °C fall in temperature. Whilst the seasonal patterns observed in this study are similar to those reported in previous studies, the lack of statistical evidence for an explicit association with ambient temperature may possibly be explained by the lack of information on date of disease onset. There is also the possibility that other time-varying factors not investigated here may be driving some of the seasonal patterns.

High order mode structure of intense light fields generated via a laser-driven relativistic plasma aperture.

The spatio-temporal and polarisation properties of intense light is important in wide-ranging topics at the forefront of extreme light-matter interactions, including ultrafast laser-driven particle acceleration, attosecond pulse generation, plasma photonics, high-field physics and laboratory astrophysics. Here, we experimentally demonstrate modifications to the polarisation and temporal properties of intense light measured at the rear of an ultrathin target foil irradiated by a relativistically intense laser pulse. The changes are shown to result from a superposition of coherent radiation, generated by a directly accelerated bipolar electron distribution, and the light transmitted due to the onset of relativistic self-induced transparency. Simulations show that the generated light has a high-order transverse electromagnetic mode structure in both the first and second laser harmonics that can evolve on intra-pulse time-scales. The mode structure and polarisation state vary with the interaction parameters, opening up the possibility of developing this approach to achieve dynamic control of structured light fields at ultrahigh intensities.

Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19.

The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial's scientific validity or integrity. In this article, we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive designs.

Atopic dermatitis in the elderly: a review of clinical and pathophysiological hallmarks.

BACKGROUND: Atopic dermatitis (AD) is a multifactorial and complex disease, characterized by an impaired skin barrier function and abnormal immune response. Many elderly patients present with pruritus and xerosis to dermatology, allergy and primary care clinics, and there is a lack of information available to clinicians regarding the proper diagnosis and management of these patients. Although the elderly are described as having a distinct presentation of AD and important comorbidities, most investigations and clinical care guidelines pertaining to AD do not include patients aged 60 years and older as a separate group from younger adults. OBJECTIVES: To summarize current information on pathophysiology, diagnosis and management of AD in the elderly population and identify areas of insufficient information to be explored in future investigations. METHODS: We carried out a systematic review of published literature, which assessed changes in the skin barrier and immune function with ageing and current information available for physicians to use in the diagnosis and treatment of AD in elderly patients. RESULTS: Many age-related changes overlap with key hallmarks observed in AD, most notably a decline in skin barrier function, dysregulation of the innate immune system, and skewing of adaptive immunity to a type-2 T helper cell response, in addition to increased Staphylococcus aureus infection. CONCLUSIONS: While general physiological alterations with ageing overlap with key features of AD, a research gap exists regarding specific ageing-related changes in AD disease development. More knowledge about AD in the elderly is needed to establish firm diagnostic and treatment methodologies. What's already known about this topic? Atopic dermatitis (AD) is a common inflammatory skin disease that causes significant burden worldwide. Recently, elderly patients have been considered a subgroup of patients with distinct AD manifestation. Limited studies have characterized the clinical presentation and role of IgE-mediated allergy in elderly patients with AD. What does this study add? This review offers a summary of age-related skin and immune alterations that correspond to pathogenic changes noted in patients with AD. The role of itch, environmental factors and skin microbiota in AD disease presentation in ageing patients is explored.

A response-adaptive randomization procedure for multi-armed clinical trials with normally distributed outcomes.

We propose a novel response-adaptive randomization procedure for multi-armed trials with continuous outcomes that are assumed to be normally distributed. Our proposed rule is non-myopic, and oriented toward a patient benefit objective, yet maintains computational feasibility. We derive our response-adaptive algorithm based on the Gittins index for the multi-armed bandit problem, as a modification of the method first introduced in Villar et al. (Biometrics, 71, pp. 969-978). The resulting procedure can be implemented under the assumption of both known or unknown variance. We illustrate the proposed procedure by simulations in the context of phase II cancer trials. Our results show that, in a multi-armed setting, there are efficiency and patient benefit gains of using a response-adaptive allocation procedure with a continuous endpoint instead of a binary one. These gains persist even if an anticipated low rate of missing data due to deaths, dropouts, or complete responses is imputed online through a procedure first introduced in this paper. Additionally, we discuss how there are response-adaptive designs that outperform the traditional equal randomized design both in terms of efficiency and patient benefit measures in the multi-armed trial context.

Efficient adaptive designs for clinical trials of interventions for COVID-19

The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial's scientific validity or integrity. In this paper we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive design

Innovative playgrounds: use, physical activity, and implications for health.

OBJECTIVES: The aim of the study is to assess the use and levels of moderate-to-vigorous physical activity (MVPA) occurring in innovative playgrounds in London vs. traditional playgrounds in the US in neighborhoods with a similar population density. STUDY DESIGN: This is a cross-sectional observational study. METHODS: We selected a sample of London playgrounds based on their innovative design. One group of eight playgrounds was matched to the US playgrounds by size and population density; a second group of very large London playgrounds was matched only by population density. Playground use and person-hours of MVPA were measured using direct observation at similar times of the day and days of the week in all locations. RESULTS: The number of playground visit hours was 58% higher in London than in the US (394 vs 249). The matched London playgrounds had 37.8% more children and 129% more adults who were, respectively, engaging in 90% and 116% more MVPA. While the London playgrounds were nearly 8.5 times larger than the US ones, they attracted a total of 5.8 times more visitors (1399 vs 243, P < .0001), and this included 10 times as many adults (679 vs. 66, P < .0001) and 7.5 times more seniors (23 vs. 3). The London playgrounds included more amenities targeting adults. CONCLUSIONS: The design of an innovative playground was associated with the amount of MVPA in similar-sized playgrounds, but the size of the playground was more strongly associated with the number of visitors. It is as important to design playgrounds for adults as it is for children to increase visit hours.

The effect of sertraline, haloperidol and apomorphine on the behavioural manipulation of slugs (Deroceras invadens) by the nematode Phasmarhabditis hermaphrodita.

The nematode Phasmarhabditis hermaphrodita can infect and kill many species of slugs and has been formulated into a biological control agent for farmers and gardeners. P. hermaphrodita can manipulate the behaviour of slugs, making those infected move to areas where the nematode is present. Research suggests P. hermaphrodita uses manipulation of biogenic amines to achieve this, however the exact role of serotonin and dopamine needs further elucidation. Here we fed slugs Deroceras invadens (uninfected and infected with P. hermaphrodita) apomorphine, sertraline and haloperidol and observed their behaviour when given a choice between a P. hermaphrodita infested habitat, or a parasite free area of soil. In contrast to their usual P. hermaphrodita avoidance behaviour, uninfected D. invadens fed sertraline were attracted to the nematodes and conversely those fed haloperidol avoided the nematodes. D. invadens fed apomorphine were recorded equally on the control and nematode side. D. invadens pre-infected with P. hermaphrodita fed sertraline and apomorphine were found significantly more on the side with the nematodes. However, suppressing dopaminergic signalling through feeding with haloperidol abrogated this attraction and slugs were found on both sides. These results demonstrate that serotonin and dopamine are potential regulators of behavioural manipulation by P. hermaphrodita.

An optically multiplexed single-shot time-resolved probe of laser-plasma dynamics.

We introduce a new approach to temporally resolve ultrafast micron-scale processes via the use of a multi-channel optical probe. We demonstrate that this technique enables highly precise time-resolved, two-dimensional spatial imaging of intense laser pulse propagation dynamics, plasma formation and laser beam filamentation within a single pulse over four distinct time frames. The design, development and optimization of the optical probe system is presented, as are representative experimental results from the first implementation of the multi-channel probe with a high-power laser pulse interaction with a helium gas jet target.