Prevalência de síndrome metabólica (SM) em usuários de antipsicóticos

-OBJETIVOS: São descritos diversos transtornos metabólicos, associados ao uso de antipsicóticos, sugerindo interface com o quadro de síndrome metabólica (SM). O objetivo do presente estudo é determinar a freqüência dos componentes da SM, em indivíduos com diagnóstico prévio de esquizofrenia, usuários de medicação antipsicótica, verificando possível relação entre uso o dessas drogas e a SM. MATERIAL E MÉTODOS: Foram estudados 64 indivíduos sendo 28 usuários de antipsicóticos típicos (grupo 1), 17 usuários de antipsicóticos atípicos (grupo 2) e 19 como grupo controle (grupo 3). Cada indivíduo foi submetido à avaliação clínica, avaliação do nível de atividade física e às dosagens de glicose, colesterol total e HDL, triglicérides, insulina e leptina. RESULTADOS: As médias dos parâmetros clínicos foram: idade, 37±10 anos, 35±7 anos e 37±10 anos; circunferência abdominal, 97±15cm, 93±12cm e 86±14cm (p<0,05); IMC 26,3±3,7kg/m2 , 25,1±4,0kg/m2, 24,5±4,9kg/m2; PAS 119±21mmHg; 112±15mmHg e 120±19mmHg e PAD 79±14mmHg; 70±9mmHg e 77±14mmHg, nos grupos 1, 2 e 3, respectivamente. Foram considerados sedentários 90,6% dos indivíduos do grupo 1, 59,2% do grupo 2 e 49,7%, do grupo 3. As médias dos exames laboratoriais foram colesterol total: 185± 31mg/dl, 170±42mg/dl e 169±25mg/dl; colesterol HDL:42±12mg/dl, 43±15mg/dl, 51±13mg/dl (p<0,05), triglicérides: 161±105mg/dl, 119±60mg/dl e 114±84mg/dl, glicose: 90±15mg/dl, 86±10mg/dl e 89±16mg/dl, HOMA-index: 1,5± 1,1, 1,5±1,0, 1,2 ±0,8 e leptina 2,5±1,7mg/dl, 2,3± 1,5mg/dl, 3,3± 2,1mg/dl (NS), nos grupos 1, 2 e 3, respectivamente. A prevalência de SM foi 33%, 20% e 25%, nos grupos 1, 2 e 3, respectivamente. DISCUSSÃO: Na maioria dos parâmetros, não se encontrou diferença significativa entre os grupos, todavia observou-se perfil metabólico mais desfavorável, no grupo 1. Diferença significativa nos níveis de HDL colesterol e na circunferência abdominal bem como maior prevalência de SM em usuários de antipsicóticos típicos sugerem possível relação desses transtornos metabólicos e o uso desse tipo de droga. Todavia, existe a possibilidade de que o sedentarismo e o ganho de peso que estão ligados à doença psiquiátrica de base e não o tipo de tratamento em si possam ser a causa do transtorno metabólico. CONCLUSÃO: Os achados sugerem que usuários de antipsicóticos apresentam maior prevalência de SM. A ampliação do número de indivíduos avaliados poderá esclarecer a possível relação entre o tipo de medicação anti-psicótica e a SM

Risk of SARS-CoV-2 infection among front-line healthcare workers in Northeast Brazil : a respondent-driven sampling approach

Objectives We assessed the prevalence of SARS-CoV-2 infection, personal protective equipment (PPE) shortages and occurrence of biological accidents among front-line healthcare workers (HCW). Design, setting and participants Using respondent-driven sampling, the study recruited distinct categories of HCW attending suspected or confirmed patients with COVID-19 from May 2020 to February 2021, in the Recife metropolitan area, Northeast Brazil. Outcome measures The criterion to assess SARS-CoV-2 infection among HCW was a positive self-reported PCR test. Results We analysed 1525 HCW: 527 physicians, 471 registered nurses, 263 nursing assistants and 264 physical therapists. Women predominated in all categories (81.1%; 95% CI: 77.8% to 84.1%). Nurses were older with more comorbidities (hypertension and overweight/obesity) than the other staff. The overall prevalence of SARS-CoV-2 infection was 61.8% (95% CI: 55.7% to 67.5%) after adjustment for the cluster random effect, weighted by network, and the reference population size. Risk factors for a positive RT-PCR test were being a nursing assistant (OR adjusted: 2.56; 95% CI: 1.42 to 4.61), not always using all recommended PPE while assisting patients with COVID-19 (OR adj: 2.15; 95% CI: 1.02 to 4.53) and reporting a splash of biological fluid/respiratory secretion in the eyes (OR adj: 3.37; 95% CI: 1.10 to 10.34). Conclusions This study shows the high frequency of SARS-CoV2 infection among HCW presumably due to workplace exposures. In our setting, nursing assistant comprised the most vulnerable category. Our findings highlight the need for improving healthcare facility environments, specific training and supervision to cope with public health emergencies

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

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

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

Timed artificial insemination and early pregnancy diagnosis in crossbred dairy cows

This study aimed to evaluate the reproductive performance of 94 Bos taurus x Bos indicus crossbred dairy cows for one year, undergoing a program of assisted reproduction. One protocol for timed artificial insemination (TAI) was performed through intravaginal progesterone inserts, injections of prostaglandin F2 (PGF2) and estradiol cypionate (EC). Ovulation s detections were performed by ultrasonography between the seventh and fourteenth day and executions of pregnancy diagnosis (PD) to the twenty eighth day after the inseminations. It was honored a voluntary waiting period (VWP) of 45 days after calving, before the first service. There was no influence of the body condition score (BCS) and corpus luteum (CL) presence before the start of the protocol, neither of reuse of the intravaginal insert and controlled mount (CM) or artificial insemination (AI) on rates of ovulation (OR), conception (CR) and conception of ovulated cows (COCR). Significant effect (P<0.05) was detected in the number of days in milk (DIM) and time of the year on the CR and COCR.Fundação de Amparo a Pesquisa do Estado de Minas GeraisMestre em Ciências VeterináriasAvaliou-se o desempenho reprodutivo de 94 vacas leiteiras mestiças Bos taurus x Bos indicus durante um ano, submetidas a um programa de reprodução assistida. Um protocolo de inseminação artificial em tempo fixo (IATF) foi executado por meio de dispositivos intravaginais contendo progesterona, injeções de prostaglandina F2 (PGF2) e de cipionato de estradiol (CE). Realizaram-se, por meio de ultrassonografia, detecções da ovulação entre o sétimo e o décimo quarto dia e diagnósticos de gestação (DG) ao vigésimo oitavo dia após as inseminações ou montas controladas (MC). Respeitou-se um período mínimo de 45 dias após o parto, antes do primeiro serviço. Não houve influência do escore de condição corporal (ECC) e da presença de corpo lúteo (CL) no início do protocolo, nem da reutilização do dispositivo intravaginal e da monta controlada ou inseminação artificial (IA), sobre as taxas de ovulação (TO), concepção (TC) e concepção das vacas ovuladas (TCVO). Detectaram-se diferenças (P<0,05) no efeito do número de dias pós-parto (DPP) e da época do ano sobre a TC e TCVO