The spotted hyaena Crocuta crocuta is relatively understudied across its range despite evidence of widespread declines. It is therefore essential that robust baseline population density assessments are conducted to inform current management and future conservation policy. In Mozambique this is urgent as decades of armed conflict followed by unchecked poaching have resulted in large-scale wildlife declines and extirpations. We conducted the first robust population density estimate for a spotted hyaena population in Mozambique using spatially explicit capture–recapture methodologies. We recorded a relatively low population density of 0.8–2.1 hyaenas/100 km2 in the wildlife management area Coutada 11 in the Zambezi Delta of central Mozambique in 2021. These densities are well below the estimated carrying capacity for the landscape and are comparable to published densities in high human-impact, miombo woodland-dominated and arid environments. The combination of historical armed conflict, marginal trophy hunting and bushmeat poaching using wire snares and gin traps (with physical injuries evident in 9% of identified individuals) presents persistent anthropogenic pressure, limiting the post-war recovery of this resident hyaena population. We provide insights into the dynamics of hyaena population status and recovery in such post-war landscapes, adding to mounting evidence that the species is less resilient to severe anthropogenic disturbances than previously believed. We recommend long-term monitoring of this and other carnivore populations in post-war landscapes to ascertain demographic trends and implement effective conservation interventions for population recovery.

This manuscript addresses a critical topic: navigating complexities of conducting clinical trials during a pandemic. Central to this discussion is engaging communities to ensure diverse participation. The manuscript elucidates deliberate strategies employed to recruit minority communities with poor social drivers of health for participation in COVID-19 trials. The paper adopts a descriptive approach, eschewing analysis of data-driven efficacy of these efforts, and instead provides a comprehensive account of strategies utilized. The Accelerate COVID-19 Treatment Interventions and Vaccines (ACTIV) public–private partnership launched early in the COVID-19 pandemic to develop clinical trials to advance SARS-CoV-2 treatments. In this paper, ACTIV investigators share challenges in conducting research during an evolving pandemic and approaches selected to engage communities when traditional strategies were infeasible. Lessons from this experience include importance of community representatives’ involvement early in study design and implementation and integration of well-developed public outreach and communication strategies with trial launch. Centralization and coordination of outreach will allow for efficient use of resources and the sharing of best practices. Insights gleaned from the ACTIV program, as outlined in this paper, shed light on effective strategies for involving communities in treatment trials amidst rapidly evolving public health emergencies. This underscores critical importance of community engagement initiatives well in advance of the pandemic.

The objective of this study was to evaluate the effectiveness of the main anthelmintics used for the control of trematodes in cattle in an endemic area in the humid Mexican tropics. A diagnostic study was carried out in nine cattle farms to determine the prevalence of flukes through faecal examination. Only three farms with more than 20 cows positive to trematodes were chosen to determine the effectiveness of commercial anthelmintics (triclabendazole, TCBZ; ivermectin + closantel, (IVM + CLOS); IVM + clorsulon, (CLORS); nitroxynil, NITROX). The prevalence of Fasciola hepatica was 27.1% and 29.6% of paramphistomes. The faecal egg count of trematodes ranged from 0.0 to 12.2 eggs per gram of faeces. The highest effectiveness against F. hepatica was 96.7%, and 92.7% against paramphistomes. NITROX was the most effective in the control of trematodes, while other products, such as IVM + CLORS and TCBZ obtained values lower than 90%, which puts sustainable trematode control at risk. The presence of trematodes was observed on most farms, although the prevalence per herd was highly variable, which indicates that the trematodes F. hepatica and paramphistomes are endemic to the region and a suitable management programme is suggested to control infections caused by these parasites.

Abstract

The rapid spread of the current COVID-19 pandemic has affected societies worldwide, leading to excess mortality, long-lasting health consequences, strained healthcare systems, and additional strains and spillover effects on other sectors outside health (i.e., intersectoral costs and benefits). In this perspective piece, we demonstrate the broader societal impacts of COVID-19 on other sectors outside the health sector and the growing importance of capturing these in health economic analyses. These broader impacts include, for instance, the effects on the labor market and productivity, education, criminal justice, housing, consumption, and environment. The current pandemic highlights the importance of adopting a societal perspective to consider these broader impacts of public health issues and interventions and only omit these where it can be clearly justified as appropriate to do so. Furthermore, we explain how the COVID-19 pandemic exposed and exacerbated existing deep-rooted structural inequalities that contribute to the wider societal impacts of the pandemic.

The characteristic traits of maize (Zea mays L.) leaves affect light interception and photosynthesis. Measurement or estimation of individual leaf area has been described using discontinuous equations or bell-shaped functions. However, new maize hybrids show different canopy architecture, such as leaf angle in modern maize which is more upright and ear leaf and adjacent leaves which are longer than older hybrids. The original equations and their parameters, which have been used for older maize hybrids and grown at low plant densities, will not accurately represent modern hybrids. Therefore, the aim of this paper was to develop a new empirical equation that captures vertical leaf distribution. To characterize the vertical leaf profile, we conducted a field experiment in Jilin province, Northeast China from 2015 to 2018. Our new equation for the vertical distribution of leaf profile describes leaf length, width or leaf area as a function of leaf rank, using parameters for the maximum value for leaf length, width or area, the leaf rank at which the maximum value is obtained, and the width of the curve. It thus involves one parameter less than the previously used equations. By analysing the characteristics of this new equation, we identified four key leaf ranks (4, 8, 14 and 20) for which leaf parameter values need to be quantified in order to have a good estimation of leaf length, width and area. Together, the method of leaf area estimation proposed here adds versatility for use in modern maize hybrids and simplifies the field measurements by using the four key leaf ranks to estimate vertical leaf distribution in maize canopy instead of all leaf ranks.

Measurements in the infrared wavelength domain allow direct assessment of the physical state and energy balance of cool matter in space, enabling the detailed study of the processes that govern the formation and evolution of stars and planetary systems in galaxies over cosmic time. Previous infrared missions revealed a great deal about the obscured Universe, but were hampered by limited sensitivity.

SPICA takes the next step in infrared observational capability by combining a large 2.5-meter diameter telescope, cooled to below 8 K, with instruments employing ultra-sensitive detectors. A combination of passive cooling and mechanical coolers will be used to cool both the telescope and the instruments. With mechanical coolers the mission lifetime is not limited by the supply of cryogen. With the combination of low telescope background and instruments with state-of-the-art detectors SPICA provides a huge advance on the capabilities of previous missions.

SPICA instruments offer spectral resolving power ranging from R ~50 through 11 000 in the 17–230 μm domain and R ~28.000 spectroscopy between 12 and 18 μm. SPICA will provide efficient 30–37 μm broad band mapping, and small field spectroscopic and polarimetric imaging at 100, 200 and 350 μm. SPICA will provide infrared spectroscopy with an unprecedented sensitivity of ~5 × 10−20 W m−2 (5σ/1 h)—over two orders of magnitude improvement over what earlier missions. This exceptional performance leap, will open entirely new domains in infrared astronomy; galaxy evolution and metal production over cosmic time, dust formation and evolution from very early epochs onwards, the formation history of planetary systems.

The present study evaluated the behaviour of the AusBeef model for beef production as part of a 2 × 2 study simulating performance on forage-based and concentrate-based diets from Oceania and North America for four methane (CH4)-relevant outputs of interest. Three sensitivity analysis methods, one local and two global, were conducted. Different patterns of sensitivity were observed between forage-based and concentrate-based diets, but patterns were consistent within diet types. For the local analysis, 36, 196, 47 and 8 out of 305 model parameters had normalized sensitivities of 0, >0, >0·01 and >0·1 across all diets and outputs, respectively. No parameters had a normalized local sensitivity >1 across all diets and outputs. However, daily CH4 production had the greatest number of parameters with normalized local sensitivities >1 for each individual diet. Parameters that were highly sensitive for global and local analyses across the range of diets and outputs examined included terms involved in microbial growth, volatile fatty acid (VFA) yields, maximum absorption rates and their inhibition due to pH effects and particle exit rates. Global sensitivity analysis I showed the high sensitivity of forage-based diets to lipid entering the rumen, which may be a result of the use of a feedlot-optimized model to represent high-forage diets and warrants further investigation. Global sensitivity analysis II showed that when all parameter values were simultaneously varied within ±10% of initial value, >96% of output values were within ±20% of the baseline, which decreased to >50% when parameter value boundaries were expanded to ±25% of their original values, giving a range for robustness of model outputs with regards to potential different ‘true’ parameter values. There were output-specific differences in sensitivity, where outputs that had greater maximum local sensitivities displayed greater degrees of non-linear interaction in global sensitivity analysis I and less variance in output values for global sensitivity analysis II. For outputs with less interaction, such as the acetate : propionate ratio and microbial protein production, the single most sensitive term in global sensitivity analysis I contributed more to the overall total-order sensitivity than for outputs with more interaction, with an average of 49, 33, 15 and 14% of total-order sensitivity for microbial protein production, acetate : propionate ratio, CH4 production and energy from absorbed VFAs, respectively. Future studies should include data collection for highly sensitive parameters reported in the present study to improve overall model accuracy.

As demand for animal products, such as meat and milk, increases, and concern over environmental impact grows, mechanistic models can be useful tools to better represent and understand ruminant systems and evaluate mitigation options to reduce greenhouse gas emissions without compromising productivity. The objectives of the present study were to describe the representation of processes for growth and enteric methane (CH4) production in AusBeef, a whole-animal, dynamic, mechanistic model for beef production; evaluate AusBeef for its ability to predict daily methane production (DMP, g/day), gross energy intake (GEI, MJ/day) and methane yield (MJ CH4/MJ GEI) using an independent data set; and to compare AusBeef estimates to those from the empirical equations featured in the current National Academies of Sciences, Engineering and Medicine (NASEM, 2016) beef cattle requirements for growth and the Ruminant Nutrition System (RNS), a dynamic, mechanistic model of Tedeschi & Fox, 2016. AusBeef incorporates a unique fermentation stoichiometry that represents four microbial groups: protozoa, amylolytic bacteria, cellulolytic bacteria and lactate-utilizing bacteria. AusBeef also accounts for the effects of ruminal pH on microbial degradation of feed particles. Methane emissions are calculated from net ruminal hydrogen balance, which is defined as the difference between inputs from fermentation and outputs due to microbial use and biohydrogenation. AusBeef performed similarly to the NASEM empirical model in terms of prediction accuracy and error decomposition, and with less root mean square predicted error (RMSPE) than the RNS mechanistic model when expressed as a percentage of the observed mean (RMSPE, %), and the majority of error was non-systematic. For DMP, RMSPE for AusBeef, NASEM and RNS were 24·0, 19·8 and 50·0 g/day for the full data set (n = 35); 25·6, 18·2 and 56·2 g/day for forage diets (n = 19); and 21·8, 21·5 and 41·5 g/day for mixed diets (n = 16), respectively. Concordance correlation coefficients (CCC) were highest for GEI, with all models having CCC > 0·66, and higher CCC for forage diets than mixed, while CCC were lowest for MY, particularly forage diets. Systematic error increased for all models on forage diets, largely due to an increase in error due to mean bias, and while all models performed well for mixed diets, further refinements are required to improve the prediction of CH4 on forage diets.

Huntington's disease (HD) is an autosomal dominant disorder of the central nervous system, characterised by neurological, cognitive and psychiatric pathology. Recently the causative genetic defect was discovered. We present a retrospective study of 59 HD patients, investigating correlations between molecular and clinical data.

The correlation between CAG-repeatlength and age at onset is confirmed. No correlations between this biological marker and other clinical features are found (symptoms at onset, mode of progression of the disease).

The consequences of these findings for predictive testing are discussed. Furthermore, a short overview of the predictive testing procedure in the Center for Human Genetics in Leuven (Belgium) is given.

Perspectives from 22 countries on aspects of the legal environment for selection are presented in this article. Issues addressed include (a) whether there are racial/ethnic/religious subgroups viewed as “disadvantaged,” (b) whether research documents mean differences between groups on individual difference measures relevant to job performance, (c) whether there are laws prohibiting discrimination against specific groups, (d) the evidence required to make and refute a claim of discrimination, (e) the consequences of violation of the laws, (f) whether particular selection methods are limited or banned, (g) whether preferential treatment of members of disadvantaged groups is permitted, and (h) whether the practice of industrial and organizational psychology has been affected by the legal environment.

Introduction – The potential impact of electronic health records (EHR) in driving tobacco treatment behaviours within healthcare settings has been established. However, little is known about the administrative variables that may undermine effectiveness in real world settings.

Aims – Assist healthcare planners interested in implementing tobacco-EHR systems by identifying an EHR framework that is consistent with published treatment guidelines, and the important organisational variables that can undermine the effectiveness of tobacco-EHR.

Methods – This paper considers the established literature on EHR implementation and physician behaviour change, and integrates this understanding with the observations of an expert workgroup tasked with facilitating tobacco-EHR implementation in Southeastern Pennsylvania.

Results/ Findings – System change in this topic area will continue to be problematic unless attention is paid to several important lessons regarding: 1) the evolving healthcare regulatory environment, 2) the integration of tobacco use treatment into primary care, and 3) the existing social and organisational barriers to uptake of evidence-based recommendations.

Conclusion – Healthcare organisations seeking to reduce the impact of tobacco use on their patients are well served by tobacco-EHR systems that improve care. Managers can avoid sub-optimal implementation by considering several threats to effectiveness before proceeding to systems change.