Energy depletion and opportunistic microbial colonisation in white syndrome lesions from corals across the Indo-Pacific

Corals are dependent upon lipids as energy reserves to mount a metabolic response to biotic and abiotic challenges. This study profiled lipids, fatty acids, and microbial communities of healthy and white syndrome (WS) diseased colonies of Acropora hyacinthus sampled from reefs in Western Australia, the Great Barrier Reef, and Palmyra Atoll. Total lipid levels varied significantly among locations, though a consistent stepwise decrease from healthy tissues from healthy colonies (HH) to healthy tissue on WS-diseased colonies (HD; i.e. preceding the lesion boundary) to diseased tissue on diseased colonies (DD; i.e. lesion front) was observed, demonstrating a reduction in energy reserves. Lipids in HH tissues were comprised of high energy lipid classes, while HD and DD tissues contained greater proportions of structural lipids. Bacterial profiling through 16S rRNA gene sequencing and histology showed no bacterial taxa linked to WS causation. However, the relative abundance of Rhodobacteraceae-affiliated sequences increased in DD tissues, suggesting opportunistic proliferation of these taxa. While the cause of WS remains inconclusive, this study demonstrates that the lipid profiles of HD tissues was more similar to DD tissues than to HH tissues, reflecting a colony-wide systemic effect and provides insight into the metabolic immune response of WS-infected Indo-Pacific corals

Social protection as a strategy for HIV prevention, education promotion and child marriage reduction among adolescents: a cross-sectional population-based study in Lesotho

Background: Lesotho’s government has shown consistent efforts to implement social protection programmes. However, while recent evidence established a positive causal relationship between some of these programmes and food security there is little evidence on the extent to which these initiatives are associated with better educational and sexual and reproductive health outcomes among vulnerable adolescents in Lesotho. Methods and Findings: The study uses cross-sectional, nationally representative data from the 2018 Lesotho Violence Against Children and Youth Survey. Our research examined the association between social protection receipt and educational and sexual and reproductive health outcomes among adolescents and young people (13–24 years) living in poverty. We employed multivariate logistic regression controlling for age, orphanhood, HIV status and sex. Social protection receipt was defined as household receipt of financial support from a governmental, non-governmental, or community-based program that provides income. Additionally, we fitted a marginal effects model by sex. Among the 3,506 adolescent females and males living in the two lowest poverty quintiles, receipt of social protection was associated with improvements in multiple adolescent outcomes: higher odds of consistent condom use (aOR 1.64, 95% CI 1.17–2.29), educational attainment (aOR 1.79, 95% CI 1.36–2.36), and school enrolment (aOR 2.19, 95% CI 1.44–3.34). Stratified analyses by sex showed that social protection receipt was also associated with reduced likelihood of child marriage among females (aOR 0.59, 95% CI 0.42–0.83) and higher odds of educational attainment and school enrolment among males (aOR 2.53, 95% CI 1.59–4.03 and aOR 3.11, 95% CI 1.56–6.19, respectively). Conclusions: Our study provides evidence that social protection programs are associated with improved educational, sexual and reproductive health and child marriage prevention outcomes among adolescents living in poverty. Implementing and expanding such social protection initiatives could prove instrumental in improving the well-being of vulnerable adolescents. Contributions: Social protection programs have been increasing in sub-Saharan African countries, playing a pivotal role in poverty reduction, with Lesotho being no exception. Despite the optimistic outlook brought about by the implementation of the National Social Protection Strategy Lesotho I (2014-19) and II (2021–2031), the impact of these programs on some specific outcomes that concern the lives of the most vulnerable adolescents in Lesotho remains to some extent unexplored. Additionally, Lesotho grapples with high rates of HIV, adolescent pregnancy, child marriage and early school dropout, which can further contribute to poor long-term health and social outcomes among adolescents. In this study, we used data from the 2018 Lesotho Violence Against Children and Youth Survey (VACS) to examine the association between receiving social protection and multiple adolescent outcomes: educational, sexual and reproductive. The findings revealed that social protection programs, particularly the existing government-provided cash transfers, are significantly associated with multiple better outcomes among adolescents living in the poorest households in Lesotho. Such cash transfer schemes in Lesotho are associated with improved sexual and reproductive health outcomes for adolescent females, including reduced child marriage rates, and improved educational outcomes for males. These findings indicate that government-led social protection programmes are positively associated with favourable outcomes that can improve the quality of life for adolescents in resource-limited settings

Social Vulnerability, Frailty, and Their Association With Mortality in Older Adults Living in Rural Tanzania.

BackgroundSocial vulnerability correlates with frailty and is associated with mortality and disability. However, few studies have investigated this relationship outside of high-income country settings. This study aimed to produce and analyze a culturally adapted social vulnerability index (SVI) to investigate the relationship between social vulnerability, frailty, and mortality in older adults in Tanzania.MethodsAn SVI was produced using data from a cohort study investigating frailty in older adults in Tanzania. Variables were selected based on previous SVI studies using the categories established by Andrew et al. from the Canadian Study of Health and Aging, and National Population Health Survey. The SVI distribution was examined and compared with a frailty index (FI) produced from the same sample, using mutually exclusive variables. Cox regression survival analysis was used to investigate the association between social vulnerability, frailty, and mortality.ResultsA stratified cohort of 235 individuals were included in the study at baseline, with a mean age of 75.2 (SD 11.5). Twenty-six participants died within the follow-up period, with a mean of 503 days (range: 405-568) following the initial assessment. The SVI had a median score of 0.47 (interquartile range: 0.23, range: 0.14-0.86). Social vulnerability significantly predicted mortality when adjusting for age and gender, but not when also adjusting for frailty.ConclusionsSocial vulnerability can be successfully operationalized and culturally adapted in Tanzania. Social vulnerability is associated with mortality in Tanzania, but not independently of frailty

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Artificial intelligence (AI) applications in drug discovery and drug delivery : revolutionizing personalized medicine

Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug development and discovery to personalized medicine, including target identification and validation, selection of excipients, prediction of the synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While the integration of AI promises to enhance efficiency, reduce costs, and improve both medicines and patient health, it also raises important questions from a regulatory point of view. In this review article, we will present a comprehensive overview of AI’s applications in the pharmaceutical industry, covering areas such as drug discovery, target optimization, personalized medicine, drug safety, and more. By analyzing current research trends and case studies, we aim to shed light on AI’s transformative impact on the pharmaceutical industry and its broader implications for healthcare

Marine Strategy Framework Directive - Descriptor 2, Non-Indigenous Species, Delivering solid recommendations for setting threshold values for non-indigenous species pressure on European seas

Marine Non-Indigenous Species (NIS) are animals and plants introduced accidently or deliberately into the European seas, originating from other seas of the globe. About 800 marine non-indigenous species (NIS) currently occur in the European Union national marine waters, several of which have negative impacts on marine ecosystem services and biodiversity. Under the Marine Strategy Framework Directive (MSFD) Descriptor 2 (D2), EU Member States (MSs) need to consider NIS in their marine management strategies. The Descriptor D2 includes one primary criterion (D2C1: new NIS introductions), and two secondary criteria (D2C2 and D2C3). The D2 implementation is characterized by a number of issues and uncertainties which can be applicable to the Descriptor level (e.g. geographical unit of assessment, assessment period, phytoplanktonic, parasitic, oligohaline NIS, etc.), to the primary criterion D2C1 level (e.g. threshold values, cryptogenic, questionable species, etc), and to the secondary criteria D2C2 and D2C3. The current report tackles these issues and provides practical recommendations aiming at a smoother and more efficient implementation of D2 and its criteria at EU level. They constitute a solid operational output which can result in more comparable D2 assessments among MSs and MSFD regions/subregions. When it comes to the policy-side, the current report calls for a number of different categories of NIS to be reported in D2 assessments, pointing the need for the species to be labelled/categorised appropriately in the MSFD reporting by the MSs. These suggestions are proposed to be communicated to the MSFD Working Group of Good Environmental Status (GES) and subsequently to the Marine Strategy Coordination Group (MSCG) of MSFD. Moreover, they can serve as an input for revising the Art. 8 Guidelines

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

Aim: Comprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW). Location: Global. Taxon: All extant mammal species. Methods: Range maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species). Results: Range maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use. Main conclusion: Expert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control.Fil: Marsh, Charles J.. Yale University; Estados UnidosFil: Sica, Yanina. Yale University; Estados UnidosFil: Burguin, Connor. University of New Mexico; Estados UnidosFil: Dorman, Wendy A.. University of Yale; Estados UnidosFil: Anderson, Robert C.. University of Yale; Estados UnidosFil: del Toro Mijares, Isabel. University of Yale; Estados UnidosFil: Vigneron, Jessica G.. University of Yale; Estados UnidosFil: Barve, Vijay. University Of Florida. Florida Museum Of History; Estados UnidosFil: Dombrowik, Victoria L.. University of Yale; Estados UnidosFil: Duong, Michelle. University of Yale; Estados UnidosFil: Guralnick, Robert. University Of Florida. Florida Museum Of History; Estados UnidosFil: Hart, Julie A.. University of Yale; Estados UnidosFil: Maypole, J. Krish. University of Yale; Estados UnidosFil: McCall, Kira. University of Yale; Estados UnidosFil: Ranipeta, Ajay. University of Yale; Estados UnidosFil: Schuerkmann, Anna. University of Yale; Estados UnidosFil: Torselli, Michael A.. University of Yale; Estados UnidosFil: Lacher, Thomas. Texas A&M University; Estados UnidosFil: Wilson, Don E.. National Museum of Natural History; Estados UnidosFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Aguirre, Luis F.. Universidad Mayor de San Simón; BoliviaFil: Arroyo Cabrales, Joaquín. Instituto Nacional de Antropología E Historia, Mexico; MéxicoFil: Astúa, Diego. Universidade Federal de Pernambuco; BrasilFil: Baker, Andrew M.. Queensland University of Technology; Australia. Queensland Museum; AustraliaFil: Braulik, Gill. University of St. Andrews; Reino UnidoFil: Braun, Janet K.. Oklahoma State University; Estados UnidosFil: Brito, Jorge. Instituto Nacional de Biodiversidad; EcuadorFil: Busher, Peter E.. Boston University; Estados UnidosFil: Burneo, Santiago F.. Pontificia Universidad Católica del Ecuador; EcuadorFil: Camacho, M. Alejandra. Pontificia Universidad Católica del Ecuador; EcuadorFil: de Almeida Chiquito, Elisandra. Universidade Federal do Espírito Santo; BrasilFil: Cook, Joseph A.. University of New Mexico; Estados UnidosFil: Cuéllar Soto, Erika. Sultan Qaboos University; OmánFil: Davenport, Tim R. B.. Wildlife Conservation Society; TanzaniaFil: Denys, Christiane. Muséum National d'Histoire Naturelle; FranciaFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Eldridge, Mark D. B.. Australian Museum; AustraliaFil: Fernandez Duque, Eduardo. University of Yale; Estados UnidosFil: Francis, Charles M.. Environment And Climate Change Canada; CanadáFil: Frankham, Greta. Australian Museum; AustraliaFil: Freitas, Thales. Universidade Federal do Rio Grande do Sul; BrasilFil: Friend, J. Anthony. Conservation And Attractions; AustraliaFil: Giannini, Norberto Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; ArgentinaFil: Gursky-Doyen, Sharon. Texas A&M University; Estados UnidosFil: Hackländer, Klaus. Universitat Fur Bodenkultur Wien; AustriaFil: Hawkins, Melissa. National Museum of Natural History; Estados UnidosFil: Helgen, Kristofer M.. Australian Museum; AustraliaFil: Heritage, Steven. University of Duke; Estados UnidosFil: Hinckley, Arlo. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Holden, Mary. American Museum of Natural History; Estados UnidosFil: Holekamp, Kay E.. Michigan State University; Estados UnidosFil: Humle, Tatyana. University Of Kent; Reino UnidoFil: Ibáñez Ulargui, Carlos. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Jackson, Stephen M.. Australian Museum; AustraliaFil: Janecka, Mary. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Jenkins, Paula. Natural History Museum; Reino UnidoFil: Juste, Javier. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; EspañaFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Novaes, Roberto Leonan M.. Universidade Federal do Rio de Janeiro; BrasilFil: Lim, Burton K.. Royal Ontario Museum; CanadáFil: Maisels, Fiona G.. Wildlife Conservation Society; Estados UnidosFil: Mares, Michael A.. Oklahoma State University; Estados UnidosFil: Marsh, Helene. James Cook University; AustraliaFil: Mattioli, Stefano. Università degli Studi di Siena; ItaliaFil: Morton, F. Blake. University of Hull; Reino UnidoFil: Ojeda, Agustina Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Ordóñez Garza, Nicté. Instituto Nacional de Biodiversidad; EcuadorFil: Pardiñas, Ulises Francisco J.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto de Diversidad y Evolución Austral; ArgentinaFil: Pavan, Mariana. Universidade de Sao Paulo; BrasilFil: Riley, Erin P.. San Diego State University; Estados UnidosFil: Rubenstein, Daniel I.. University of Princeton; Estados UnidosFil: Ruelas, Dennisse. Museo de Historia Natural, Lima; PerúFil: Schai-Braun, Stéphanie. Universitat Fur Bodenkultur Wien; AustriaFil: Schank, Cody J.. University of Texas at Austin; Estados UnidosFil: Shenbrot, Georgy. Ben Gurion University of the Negev; IsraelFil: Solari, Sergio. Universidad de Antioquia; ColombiaFil: Superina, Mariella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Tsang, Susan. American Museum of Natural History; Estados UnidosFil: Van Cakenberghe, Victor. Universiteit Antwerp; BélgicaFil: Veron, Geraldine. Université Pierre et Marie Curie; FranciaFil: Wallis, Janette. Kasokwa-kityedo Forest Project; UgandaFil: Whittaker, Danielle. Michigan State University; Estados UnidosFil: Wells, Rod. Flinders University.; AustraliaFil: Wittemyer, George. State University of Colorado - Fort Collins; Estados UnidosFil: Woinarski, John. Charles Darwin University; AustraliaFil: Upham, Nathan S.. University of Yale; Estados UnidosFil: Jetz, Walter. University of Yale; Estados Unido

Expert range maps of global mammal distributions harmonised to three taxonomic authorities

AimComprehensive, global information on species' occurrences is an essential biodiversity variable and central to a range of applications in ecology, evolution, biogeography and conservation. Expert range maps often represent a species' only available distributional information and play an increasing role in conservation assessments and macroecology. We provide global range maps for the native ranges of all extant mammal species harmonised to the taxonomy of the Mammal Diversity Database (MDD) mobilised from two sources, the Handbook of the Mammals of the World (HMW) and the Illustrated Checklist of the Mammals of the World (CMW).LocationGlobal.TaxonAll extant mammal species.MethodsRange maps were digitally interpreted, georeferenced, error-checked and subsequently taxonomically aligned between the HMW (6253 species), the CMW (6431 species) and the MDD taxonomies (6362 species).ResultsRange maps can be evaluated and visualised in an online map browser at Map of Life (mol.org) and accessed for individual or batch download for non-commercial use.Main conclusionExpert maps of species' global distributions are limited in their spatial detail and temporal specificity, but form a useful basis for broad-scale characterizations and model-based integration with other data. We provide georeferenced range maps for the native ranges of all extant mammal species as shapefiles, with species-level metadata and source information packaged together in geodatabase format. Across the three taxonomic sources our maps entail, there are 1784 taxonomic name differences compared to the maps currently available on the IUCN Red List website. The expert maps provided here are harmonised to the MDD taxonomic authority and linked to a community of online tools that will enable transparent future updates and version control

Long-term thermal sensitivity of Earth’s tropical forests

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate