Adipose Tissue-Derived Mesenchymal Stem Cells Increase Skin Allograft Survival and Inhibit Th-17 Immune Response

Adipose tissue-derived mesenchymal stem cells (ADSC) exhibit immunosuppressive capabilities both in vitro and in vivo. Their use for therapy in the transplant field is attractive as they could render the use of immunosuppressive drugs unnecessary. The aim of this study was to investigate the effect of ADSC therapy on prolonging skin allograft survival. Animals that were treated with a single injection of donor allogeneic ADSC one day after transplantation showed an increase in donor skin graft survival by approximately one week. This improvement was associated with preserved histological morphology, an expansion of CD4+ regulatory T cells (Treg) in draining lymph nodes, as well as heightened IL-10 expression and down-regulated IL-17 expression. In vitro, ADSC inhibit naïve CD4+ T cell proliferation and constrain Th-1 and Th-17 polarization. In summary, infusion of ADSC one day post-transplantation dramatically increases skin allograft survival by inhibiting the Th-17 pathogenic immune response and enhancing the protective Treg immune response. Finally, these data suggest that ADSC therapy will open new opportunities for promoting drug-free allograft survival in clinical transplantation

Dectin-1 Activation Exacerbates Obesity and Insulin Resistance in the Absence of MyD88

This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, grant numbers 11/15682-4, 12/02270-2, 15/18121-4), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Regenera INCT Process Grant 465656/2014-5). JL is funded by the NIH/NIDDK R01DK106210. GDB is funded by the Wellcome Trust and the MRC Centre for Medical Mycology. Open access journalPeer reviewedPublisher PD

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

First Latin American clinical practice guidelines for the treatment of systemic lupus erythematosus: Latin American Group for the Study of Lupus (GLADEL, Grupo Latino Americano de Estudio del Lupus)-Pan-American League of Associations of Rheumatology (PANLAR)

Systemic lupus erythematosus (SLE), a complex and heterogeneous autoimmune disease, represents a significant challenge for both diagnosis and treatment. Patients with SLE in Latin America face special problems that should be considered when therapeutic guidelines are developed. The objective of the study is to develop clinical practice guidelines for Latin American patients with lupus. Two independent teams (rheumatologists with experience in lupus management and methodologists) had an initial meeting in Panama City, Panama, in April 2016. They selected a list of questions for the clinical problems most commonly seen in Latin American patients with SLE. These were addressed with the best available evidence and summarised in a standardised format following the Grading of Recommendations Assessment, Development and Evaluation approach. All preliminary findings were discussed in a second face-to-face meeting in Washington, DC, in November 2016. As a result, nine organ/system sections are presented with the main findings; an 'overarching' treatment approach was added. Special emphasis was made on regional implementation issues. Best pharmacologic options were examined for musculoskeletal, mucocutaneous, kidney, cardiac, pulmonary, neuropsychiatric, haematological manifestations and the antiphospholipid syndrome. The roles of main therapeutic options (ie, glucocorticoids, antimalarials, immunosuppressant agents, therapeutic plasma exchange, belimumab, rituximab, abatacept, low-dose aspirin and anticoagulants) were summarised in each section. In all cases, benefits and harms, certainty of the evidence, values and preferences, feasibility, acceptability and equity issues were considered to produce a recommendation with special focus on ethnic and socioeconomic aspects. Guidelines for Latin American patients with lupus have been developed and could be used in similar settings.Fil: Pons Estel, Bernardo A.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Bonfa, Eloisa. Universidade de Sao Paulo; BrasilFil: Soriano, Enrique R.. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cardiel, Mario H.. Centro de Investigación Clínica de Morelia; MéxicoFil: Izcovich, Ariel. Hospital Alemán; ArgentinaFil: Popoff, Federico. Hospital Aleman; ArgentinaFil: Criniti, Juan M.. Hospital Alemán; ArgentinaFil: Vásquez, Gloria. Universidad de Antioquia; ColombiaFil: Massardo, Loreto. Universidad San Sebastián; ChileFil: Duarte, Margarita. Hospital de Clínicas; ParaguayFil: Barile Fabris, Leonor A.. Hospital Angeles del Pedregal; MéxicoFil: García, Mercedes A.. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Amigo, Mary Carmen. Centro Médico Abc; MéxicoFil: Espada, Graciela. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutiérrez"; ArgentinaFil: Catoggio, Luis J.. Hospital Italiano. Instituto Universitario. Escuela de Medicina; ArgentinaFil: Sato, Emilia Inoue. Universidade Federal de Sao Paulo; BrasilFil: Levy, Roger A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Acevedo Vásquez, Eduardo M.. Universidad Nacional Mayor de San Marcos; PerúFil: Chacón Díaz, Rosa. Policlínica Méndez Gimón; VenezuelaFil: Galarza Maldonado, Claudio M.. Corporación Médica Monte Sinaí; EcuadorFil: Iglesias Gamarra, Antonio J.. Universidad Nacional de Colombia; ColombiaFil: Molina, José Fernando. Centro Integral de Reumatología; ColombiaFil: Neira, Oscar. Universidad de Chile; ChileFil: Silva, Clóvis A.. Universidade de Sao Paulo; BrasilFil: Vargas Peña, Andrea. Hospital Pasteur Montevideo; UruguayFil: Gómez Puerta, José A.. Hospital Clinic Barcelona; EspañaFil: Scolnik, Marina. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Pons Estel, Guillermo J.. Centro Regional de Enfermedades Autoinmunes y Reumáticas; Argentina. Hospital Provincial de Rosario; ArgentinaFil: Ugolini Lopes, Michelle R.. Universidade de Sao Paulo; BrasilFil: Savio, Verónica. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Drenkard, Cristina. University of Emory; Estados UnidosFil: Alvarellos, Alejandro J.. Hospital Privado Universitario de Córdoba; ArgentinaFil: Ugarte Gil, Manuel F.. Universidad Cientifica del Sur; Perú. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Babini, Alejandra. Instituto Universitario Hospital Italiano de Buenos Aires. Rectorado.; ArgentinaFil: Cavalcanti, André. Universidade Federal de Pernambuco; BrasilFil: Cardoso Linhares, Fernanda Athayde. Hospital Pasteur Montevideo; UruguayFil: Haye Salinas, Maria Jezabel. Hospital Privado Universitario de Córdoba; ArgentinaFil: Fuentes Silva, Yurilis J.. Universidad de Oriente - Núcleo Bolívar; VenezuelaFil: Montandon De Oliveira E Silva, Ana Carolina. Universidade Federal de Goiás; BrasilFil: Eraso Garnica, Ruth M.. Universidad de Antioquia; ColombiaFil: Herrera Uribe, Sebastián. Hospital General de Medellin Luz Castro de Gutiérrez; ColombiaFil: Gómez Martín, DIana. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Robaina Sevrini, Ricardo. Universidad de la República; UruguayFil: Quintana, Rosana M.. Hospital Provincial de Rosario; Argentina. Centro Regional de Enfermedades Autoinmunes y Reumáticas; ArgentinaFil: Gordon, Sergio. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Fragoso Loyo, Hilda. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Rosario, Violeta. Hospital Docente Padre Billini; República DominicanaFil: Saurit, Verónica. Hospital Privado Universitario de Córdoba; ArgentinaFil: Appenzeller, Simone. Universidade Estadual de Campinas; BrasilFil: Dos Reis Neto, Edgard Torres. Universidade Federal de Sao Paulo; BrasilFil: Cieza, Jorge. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: González Naranjo, Luis A.. Universidad de Antioquia; ColombiaFil: González Bello, Yelitza C.. Ceibac; MéxicoFil: Collado, María Victoria. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Sarano, Judith. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Retamozo, Maria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Sattler, María E.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gamboa Cárdenas, Rocio V.. Hospital Nacional Guillermo Almenara Irigoyen; PerúFil: Cairoli, Ernesto. Universidad de la República; UruguayFil: Conti, Silvana M.. Hospital Provincial de Rosario; ArgentinaFil: Amezcua Guerra, Luis M.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Silveira, Luis H.. Instituto Nacional de Cardiologia Ignacio Chavez; MéxicoFil: Borba, Eduardo F.. Universidade de Sao Paulo; BrasilFil: Pera, Mariana A.. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Alba Moreyra, Paula B.. Universidad Nacional de Córdoba. Facultad de Medicina; ArgentinaFil: Arturi, Valeria. Hospital Interzonal General de Agudos General San Martín; ArgentinaFil: Berbotto, Guillermo A.. Provincia de Buenos Aires. Ministerio de Salud. Hospital Interzonal de Agudos "Eva Perón"; ArgentinaFil: Gerling, Cristian. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Gobbi, Carla Andrea. Universidad Nacional de Córdoba. Facultad de Medicina; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gervasoni, Viviana L.. Hospital Provincial de Rosario; ArgentinaFil: Scherbarth, Hugo R.. Hospital Interzonal General de Agudos Dr Oscar Alende. Unidad de Reumatología y Enfermedades Autoinmunes Sistémicas; ArgentinaFil: Brenol, João C. Tavares. Hospital de Clinicas de Porto Alegre; BrasilFil: Cavalcanti, Fernando. Universidade Federal de Pernambuco; BrasilFil: Costallat, Lilian T. Lavras. Universidade Estadual de Campinas; BrasilFil: Da Silva, Nilzio A.. Universidade Federal de Goiás; BrasilFil: Monticielo, Odirlei A.. Hospital de Clinicas de Porto Alegre; BrasilFil: Seguro, Luciana Parente Costa. Universidade de Sao Paulo; BrasilFil: Xavier, Ricardo M.. Hospital de Clinicas de Porto Alegre; BrasilFil: Llanos, Carolina. Universidad Católica de Chile; ChileFil: Montúfar Guardado, Rubén A.. Instituto Salvadoreño de la Seguridad Social; El SalvadorFil: Garcia De La Torre, Ignacio. Hospital General de Occidente; MéxicoFil: Pineda, Carlos. Instituto Nacional de Rehabilitación; MéxicoFil: Portela Hernández, Margarita. Umae Hospital de Especialidades Centro Medico Nacional Siglo Xxi; MéxicoFil: Danza, Alvaro. Hospital Pasteur Montevideo; UruguayFil: Guibert Toledano, Marlene. Medical-surgical Research Center; CubaFil: Reyes, Gil Llerena. Medical-surgical Research Center; CubaFil: Acosta Colman, Maria Isabel. Hospital de Clínicas; ParaguayFil: Aquino, Alicia M.. Hospital de Clínicas; ParaguayFil: Mora Trujillo, Claudia S.. Hospital Nacional Edgardo Rebagliati Martins; PerúFil: Muñoz Louis, Roberto. Hospital Docente Padre Billini; República DominicanaFil: García Valladares, Ignacio. Centro de Estudios de Investigación Básica y Clínica; MéxicoFil: Orozco, María Celeste. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Burgos, Paula I.. Pontificia Universidad Católica de Chile; ChileFil: Betancur, Graciela V.. Instituto de Rehabilitación Psicofísica; ArgentinaFil: Alarcón, Graciela S.. Universidad Peruana Cayetano Heredia; Perú. University of Alabama at Birmingahm; Estados Unido

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Maternal outcomes and risk factors for COVID-19 severity among pregnant women.

Pregnant women may be at higher risk of severe complications associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which may lead to obstetrical complications. We performed a case control study comparing pregnant women with severe coronavirus disease 19 (cases) to pregnant women with a milder form (controls) enrolled in the COVI-Preg international registry cohort between March 24 and July 26, 2020. Risk factors for severity, obstetrical and immediate neonatal outcomes were assessed. A total of 926 pregnant women with a positive test for SARS-CoV-2 were included, among which 92 (9.9%) presented with severe COVID-19 disease. Risk factors for severe maternal outcomes were pulmonary comorbidities [aOR 4.3, 95% CI 1.9-9.5], hypertensive disorders [aOR 2.7, 95% CI 1.0-7.0] and diabetes [aOR2.2, 95% CI 1.1-4.5]. Pregnant women with severe maternal outcomes were at higher risk of caesarean section [70.7% (n = 53/75)], preterm delivery [62.7% (n = 32/51)] and newborns requiring admission to the neonatal intensive care unit [41.3% (n = 31/75)]. In this study, several risk factors for developing severe complications of SARS-CoV-2 infection among pregnant women were identified including pulmonary comorbidities, hypertensive disorders and diabetes. Obstetrical and neonatal outcomes appear to be influenced by the severity of maternal disease

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC