Around 1000 years ago, Madagascar experienced the collapse of populations of large vertebrates that ultimately resulted in many species going extinct. The factors that led to this collapse appear to have differed regionally, but in some ways, key processes were similar across the island. This review evaluates four hypotheses that have been proposed to explain the loss of large vertebrates on Madagascar: Overkill, aridification, synergy, and subsistence shift. We explore regional differences in the paths to extinction and the significance of a prolonged extinction window across the island. The data suggest that people who arrived early and depended on hunting, fishing, and foraging had little effect on Madagascar’s large endemic vertebrates. Megafaunal decline was triggered initially by aridification in the driest bioclimatic zone, and by the arrival of farmers and herders in the wetter bioclimatic zones. Ultimately, it was the expansion of agropastoralism across both wet and dry regions that drove large endemic vertebrates to extinction everywhere.

A growing number of Australians are experiencing challenges accessing and affording healthy food due to climate-related disasters, global supply chain disruptions, and rapid inflation that is affecting the cost of healthy food(1). There is limited understanding of how participation community-based food cooperatives can address these challenges and improve food security and dietary intake. This study investigated the motivations for joining and impact of participation in a community-based food cooperative called Box Divvy on self-reported food security status and intake of fruits and vegetables among a sample of Australian adults. A cross-sectional online survey was conducted among Box Divvy members, that measured sociodemographic characteristics, motivations for joining, self-reported fruit and vegetable intake (serves/week), and food insecurity status (USDA 6-item short form(2)) before and while using Box Divvy. Participants were classified as being food secure, or experiencing marginal, moderate, or severe food insecurity. Logistic regression assessed demographic predictors and self-reported change in food security status, and ANOVA examined changes in dietary intake before joining and while using Box Divvy. Of participants (n = 2764, 37% aged 35–44 years, 83% European ethnicity, 92% New South Wales residents), most joined Box Divvy to support local farmers (87.3%), and save money on healthy foods (70.6%). Around half of respondents (50.8%) reported experiencing food insecurity before joining Box Divvy (24.5% marginal, 18.4% moderate, 7.9% severe food insecurity). Univariate logistic regression identified age, household structure, and income as significant predictors of food insecurity (p < 0.001). Participants experiencing food insecurity reported significantly lower consumption of fruits and vegetables prior to joining Box Divvy compared to those who were food secure (p < 0.001). While using Box Divvy, 28.2% of participants reported experiencing food insecurity (16.6% marginal, 9.6% moderate, 2.1% severe food insecurity). The odds of food insecurity while using Box Divvy were 62% lower than before joining (OR: 0.38; 95% CI 0.34–0.43; p < 0.001). On average, participants reported their fruit intake increased by 2.5 ± 5.6 serves/week (p < 0.001), and vegetable intake increased by 3.3 ± 5.7 serves/week (p < 0.001). The mean increase was significantly greater among moderately food insecure (fruit mean difference 3.2 ± 6.5 serves/week; vegetable mean difference 3.9 ± 6.9 serves/week) and severely food insecure groups (fruit mean difference 4.4 ± 6.9 serves/week; vegetable mean difference 5.5 ± 7.7 serves/week; p < 0.001). Participation in Box Divvy significantly improved self-reported food security status and fruit and vegetable intake among a large sample of Australian adults. Notably, fruit and vegetable intake significantly increased among those experiencing moderate and severe food insecurity. This underscores the potential of community-based food cooperatives to improve food security and promote healthier eating habits among Australian adults, especially households experiencing food insecurity.

Lewy body dementias (LBD) are the second most common dementia. Several genes have been associated with LBD, but little is known about their contributions to LBD pathophysiology. Each gene may transcribe multiple RNA, and LBD brains have extensive RNA splicing dysregulation. Hence, we completed the first transcriptome-wide transcript-level differential expression analysis of post-mortem LBD brains for gaining more insights into LBD molecular pathology that are essential for facilitating discovery of novel therapeutic targets and biomarkers for LBD. We completed transcript-level quantification of next-generation RNA-sequencing data from post-mortem anterior cingulate (ACC) and dorsolateral prefrontal cortices (DLPFC) of people with pathology-verified LBD (LBD = 14; Controls = 7) using Salmon. We identified differentially expressed transcripts (DET) using edgeR and investigated their functional implications using DAVID. We performed transcriptome-wide alternative splicing analysis using DRIMseq. We identified 74 DET in ACC and 96 DET in DLPFC after Benjamini-Hochberg false discovery rate (FDR) correction (5%). There were 135 and 98 FDR-corrected alternatively spliced genes in ACC and DLPFC of LBD brains, respectively. Identified DET may contribute to LBD pathology by altering DNA repair, apoptosis, neuroplasticity, protein phosphorylation, and regulation of RNA transcription. We confirm widespread alternative splicing and absence of chronic neuroinflammation in LBD brains. Transcript-level differential expression analysis can reveal specific DET that cannot be detected by gene-level expression analyses. Therapeutic and diagnostic biomarker potential of identified DET, especially those from TMEM18, MICB, MPO, and GABRB3, warrant further investigation. Future LBD blood-based biomarker studies should prioritise measuring the identified DET in small extracellular vesicles.

Most of the Ross Sea has been designated a marine protected area (MPA), proposed ‘to protect ecosystem structure and function’. To assess effectiveness, the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) selected Adélie (Pygoscelis adeliae) and emperor (Aptenodytes forsteri) penguins, Weddell seals (Leptonychotes weddellii) and Antarctic toothfish (Dissostichus mawsoni) as ecosystem change ‘indicator species’. Stable for decades, penguin and seal populations increased during 1998–2018 to surpass historical levels, indicating that change in ecosystem structure and function is underway. We review historical impacts to population trends, decadal datasets of ocean climate and fishing pressure on toothfish. Statistical modelling for Adélie penguins and Weddell seals indicates that variability in climate factors and cumulative extraction of adult toothfish may explain these trends. These mesopredators, and adult toothfish, all prey heavily on Antarctic silverfish (Pleuragramma antarcticum). Toothfish removal may be altering intraguild predation dynamics, leading to competitive release of silverfish and contributing to penguin and seal population changes. Despite decades of ocean/weather change, increases in indicator species numbers around Ross Island only began once the toothfish fishery commenced. The rational-use, ecosystem-based viewpoint promoted by CCAMLR regarding toothfish management needs re-evaluation, including in the context of the Ross Sea Region MPA.

Medical researchers are increasingly prioritizing the inclusion of underserved communities in clinical studies. However, mere inclusion is not enough. People from underserved communities frequently experience chronic stress that may lead to accelerated biological aging and early morbidity and mortality. It is our hope and intent that the medical community come together to engineer improved health outcomes for vulnerable populations. Here, we introduce Health Equity Engineering (HEE), a comprehensive scientific framework to guide research on the development of tools to identify individuals at risk of poor health outcomes due to chronic stress, the integration of these tools within existing healthcare system infrastructures, and a robust assessment of their effectiveness and sustainability. HEE is anchored in the premise that strategic intervention at the individual level, tailored to the needs of the most at-risk people, can pave the way for achieving equitable health standards at a broader population level. HEE provides a scientific framework guiding health equity research to equip the medical community with a robust set of tools to enhance health equity for current and future generations.

The current small study utilised prospective data collection of patterns of prenatal alcohol and tobacco exposure (PAE and PTE) to examine associations with structural brain outcomes in 6-year-olds and served as a pilot to determine the value of prospective data describing community-level patterns of PAE and PTE in a non-clinical sample of children. Participants from the Safe Passage Study in pregnancy were approached when their child was ∼6 years old and completed structural brain magnetic resonance imaging to examine with archived PAE and PTE data (n = 51 children–mother dyads). Linear regression was used to conduct whole-brain structural analyses, with false-discovery rate (FDR) correction, to examine: (a) main effects of PAE, PTE and their interaction; and (b) predictive potential of data that reflect patterns of PAE and PTE (e.g. quantity, frequency and timing (QFT)). Associations between PAE, PTE and their interaction with brain structural measures demonstrated unique profiles of cortical and subcortical alterations that were distinct between PAE only, PTE only and their interactive effects. Analyses examining associations between patterns of PAE and PTE (e.g. QFT) were able to significantly detect brain alterations (that survived FDR correction) in this small non-clinical sample of children. These findings support the hypothesis that considering QFT and co-exposures is important for identifying brain alterations following PAE and/or PTE in a small group of young children. Current results demonstrate that teratogenic outcomes on brain structure differ as a function PAE, PTE or their co-exposures, as well as the pattern (QFT) or exposure.

Cyclosporiasis is an illness characterised by watery diarrhoea caused by the food-borne parasite Cyclospora cayetanensis. The increase in annual US cyclosporiasis cases led public health agencies to develop genotyping tools that aid outbreak investigations. A team at the Centers for Disease Control and Prevention (CDC) developed a system based on deep amplicon sequencing and machine learning, for detecting genetically-related clusters of cyclosporiasis to aid epidemiologic investigations. An evaluation of this system during 2018 supported its robustness, indicating that it possessed sufficient utility to warrant further evaluation. However, the earliest version of CDC's system had some limitations from a bioinformatics standpoint. Namely, reliance on proprietary software, the inability to detect novel haplotypes and absence of a strategy to select an appropriate number of discrete genetic clusters would limit the system's future deployment potential. We recently introduced several improvements that address these limitations and the aim of this study was to reassess the system's performance to ensure that the changes introduced had no observable negative impacts. Comparison of epidemiologically-defined cyclosporiasis clusters from 2019 to analogous genetic clusters detected using CDC's improved system reaffirmed its excellent sensitivity (90%) and specificity (99%), and confirmed its high discriminatory power. This C. cayetanensis genotyping system is robust and with ongoing improvement will form the basis of a US-wide C. cayetanensis genotyping network for clinical specimens.

A new fossil site in a previously unexplored part of western Madagascar (the Beanka Protected Area) has yielded remains of many recently extinct vertebrates, including giant lemurs (Babakotia radofilai, Palaeopropithecus kelyus, Pachylemur sp., and Archaeolemur edwardsi), carnivores (Cryptoprocta spelea), the aardvark-like Plesiorycteropus sp., and giant ground cuckoos (Coua). Many of these represent considerable range extensions. Extant species that were extirpated from the region (e.g., Prolemur simus) are also present. Calibrated radiocarbon ages for 10 bones from extinct primates span the last three millennia. The largely undisturbed taphonomy of bone deposits supports the interpretation that many specimens fell in from a rock ledge above the entrance. Some primates and other mammals may have been prey items of avian predators, but human predation is also evident. Strontium isotope ratios (87Sr/86Sr) suggest that fossils were local to the area. Pottery sherds and bones of extinct and extant vertebrates with cut and chop marks indicate human activity in previous centuries. Scarcity of charcoal and human artifacts suggests only occasional visitation to the site by humans. The fossil assemblage from this site is unusual in that, while it contains many sloth lemurs, it lacks ratites, hippopotami, and crocodiles typical of nearly all other Holocene subfossil sites on Madagascar.

In this paper, we revisit our previous work in which we derive an effective macroscale description suitable to describe the growth of biological tissue within a porous tissue-engineering scaffold. The underlying tissue dynamics is described as a multiphase mixture, thereby naturally accommodating features such as interstitial growth and active cell motion. Via a linearization of the underlying multiphase model (whose nonlinearity poses a significant challenge for such analyses), we obtain, by means of multiple-scale homogenization, a simplified macroscale model that nevertheless retains explicit dependence on both the microscale scaffold structure and the tissue dynamics, via so-called unit-cell problems that provide permeability tensors to parameterize the macroscale description. In our previous work, the cell problems retain macroscale dependence, posing significant challenges for computational implementation of the eventual macroscopic model; here, we obtain a decoupled system whereby the quasi-steady cell problems may be solved separately from the macroscale description. Moreover, we indicate how the formulation is influenced by a set of alternative microscale boundary conditions.

Legionnaires’ disease (LD) incidence in the USA has quadrupled since 2000. Health departments must detect LD outbreaks quickly to identify and remediate sources. We tested the performance of a system to prospectively detect simulated LD outbreaks in Allegheny County, Pennsylvania, USA. We generated three simulated LD outbreaks based on published outbreaks. After verifying no significant clusters existed in surveillance data during 2014–2016, we embedded simulated outbreak-associated cases into 2016, assigning simulated residences and report dates. We mimicked daily analyses in 2016 using the prospective space-time permutation scan statistic to detect clusters of ⩽30 and ⩽180 days using 365-day and 730-day baseline periods, respectively. We used recurrence interval (RI) thresholds of ⩾20, ⩾100 and ⩾365 days to define significant signals. We calculated sensitivity, specificity and positive and negative predictive values for daily analyses, separately for each embedded outbreak. Two large, simulated cooling tower-associated outbreaks were detected. As the RI threshold was increased, sensitivity and negative predictive value decreased, while positive predictive value and specificity increased. A small, simulated potable water-associated outbreak was not detected. Use of a RI threshold of ⩾100 days minimised time-to-detection while maximizing positive predictive value. Health departments should consider using this system to detect community-acquired LD outbreaks.

The Pueblo population of Chaco Canyon during the Bonito Phase (AD 800–1130) employed agricultural strategies and water-management systems to enhance food cultivation in this unpredictable environment. Scepticism concerning the timing and effectiveness of this system, however, remains common. Using optically stimulated luminescence dating of sediments and LiDAR imaging, the authors located Bonito Phase canal features at the far west end of the canyon. Additional ED-XRF and strontium isotope (87Sr/86Sr) analyses confirm the diversion of waters from multiple sources during Chaco’s occupation. The extent of this water-management system raises new questions about social organisation and the role of ritual in facilitating responses to environmental unpredictability.

We derive an effective macroscale description for the growth of tissue on a porous scaffold. A multiphase model is employed to describe the tissue dynamics; linearisation to facilitate a multiple-scale homogenisation provides an effective macroscale description, which incorporates dependence on the microscale structure and dynamics. In particular, the resulting description admits both interstitial growth and active cell motion. This model comprises Darcy flow, and differential equations for the volume fraction of cells within the scaffold and the concentration of nutrient, required for growth. These are coupled with Stokes-type cell problems on the microscale, incorporating dependence on active cell motion and pore scale structure. The cell problems provide the permeability tensors with which the macroscale flow is parameterised. A subset of solutions is illustrated by numerical simulations.