MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Uma revisão integrativa sobre a Colangite Biliar Primária

A colangite biliar primária, um novo nome para a cirrose biliar primária, é uma doença colestática de etiologia autoimune e representa a primeira causa de colestase intra-hepática. Caracteriza-se pela destruição de pequenos dutos biliares ligados à infiltração de linfócitos, com prevalência de 10 a 40 por 100.000 habitantes no mundo. Este estudo teve como objetivo refletir sobre novas informações a respeito da colangite biliar primária. Para isso, foi realizada uma revisão integrativa de literatura, selecionando artigos publicados nas bases de dados Medical Literature Analysis and Retrieval System Online e Literatura Latino-americana e do Caribe em Ciências da Saúde. A partir da análise qualitativa dos dados, obteve-se como conclusão as seguintes descobertas: A PBC é um problema de saúde raro e mal diagnosticado; não há conhecimento ainda sobre as razões da predominância dessa da CBP em mulheres, resposta à terapêutica, distribuição geográfica e mortalidade entre sexos; os casos dessa doença são assintomáticos; a qualidade de vida dos pacientes é comprometida com o agravamento dos casos, onde apresentam inicialmente sinais de prurido (20 a 70% dos casos) e fadiga (entre 50% a 78% dos pacientes); exames de biópsica hepática podem ser tranquilamente substituídos por testes não-invasivos, em análises de rotina de bioquímica hepática; a possiblidade de diagnosticar a PBC pode ser diagnosticada partindo de fatores biológicos exclusivos que indicam a presença de anticorpos anti-mitocondriais e uma elevação da fosfatase alcalina. No entanto é quase possível que o PBC seja soronegativo; a etiologia da CBP não sendo encontra clara, sendo o tratamento difícil; em caso de tratamento, utiliza-se mais ursodesoxicólico, ácido biliar hidrofílico natural que bloqueia a síntese hepática do colesterol, estimulando a síntese de ácidos biliares e restaurando o equilíbrio entre esses

Conhecendo a síndrome de autofermentação: etiopatogenia, apresentação e abordagem

Revisar os dados sobre síndrome da autofermentação disponíveis na literatura e reforçar a possibilidade dessa condição como hipótese durante as avaliações diagnósticas. Revisão de literatura de caráter exploratório com estudos selecionados nas plataformas PubMED e Google Scholar, no período de 2015 a 2024. Foram elegidos, após a aplicação dos critérios de seleção e exclusão, 20 artigos para a leitura completa e adicionados 4 materiais extras de valor para o estudo.  A síndrome da autofermentação é uma intoxicação alcoólica de origem endógena, causada, principalmente, por fungos fermentadores após um processo de disbiose intestinal. Suas principais manifestações incluem desorientação, descoordenação motora, marcha atáxica e desinibição social. O diagnóstico é realizado por anamnese detalhada, detecção de altos níveis séricos de álcool e teste do desafio dos carboidratos positivo. O manejo da condição consiste em evitar fatores que prejudiquem o microbioma intestinal e tratar os agentes causadores com uso de antifúngicos principalmente. A síndrome da autofermentação pode ter impacto nos contextos médico, legal e social. É necessário que ela seja mais disseminada entre a comunidade médica e leiga com intuito de permitir que o paciente possa ter um diagnóstico e tratamento adequados

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

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

Agreement between mechanical and digital skinfold callipers

Background: Skinfold callipers are often used in clinical practice to estimate subcutaneous adipose tissue thickness. Recently, LipoTool emerged as a potential digital system to measure skinfolds, however comparisons with competing equipment are lacking. Aim: The aim of this study was to test the agreement between two competing skinfold callipers (digital and mechanical). Methods: The sample included 22 healthy male adult participants. A certified observer measured eight skinfolds twice using different skinfold callipers (digital and mechanical). Differences between equipment were tested using Wilcoxon signed rank test The distribution of error was examined using the normality test Results: Differences between skinfold callipers were significantly in five skinfolds: triceps (Z = -3.546; P < 0.001), subscapular (Z = -3.984; P < 0.001), suprailiac (Z = 3.024; P = 0.002), supraspinale (Z = 3.885; P < 0.001), abdominal (Z z=−2.937; P = 0.003), thigh (Z = -2.224; P = 0.026) and calf (Z = -2.052; P = 0.040). Differences between callipers were constant. Conclusions: Mechanical and digital callipers tended to record different values of skinfold thickness. Clinical examination should consider equipment-related variation in fat mass estimation