Weaned piglets fed diets with milk protein and supplemental zinc

Avaliaram-se os efeitos da utilização de proteína láctea ou zinco suplementar na dieta sobre o desempenho, os pesos relativos do intestino delgado e fígado, a morfologia intestinal e as concentrações séricas de IGF-I (fator de crescimento semelhante à insulina), hormônio do crescimento e zinco em leitões. O experimento teve duração de 14 dias e foi realizado com 60 leitões desmamados aos 21 dias de idade (5,43 ± 0,46 kg), em delineamento de blocos casualizados, em fatorial 2 x 2, composto de dois níveis de proteína láctea (com e sem, 4%) e dois de zinco (com e sem, 2.250 ppm) na dieta. No período de 1 a 7 dias de experimento, o zinco proporcionou melhor conversão alimentar e, no período de 1 a 14 dias, promoveu maior pesos aos 14 dias e maior ganho de peso. O fornecimento de proteína láctea na dieta piorou a conversão alimentar nas duas fases (de 1 a 7 dias e de 1 a 14 dias de experimento) e resultou em menor profundidade de cripta no jejuno aos 7 dias e maior altura de vilosidade aos 14 dias de experimento. Aos 7 dias de experimento, Houve interação proteína láctea e zinco para a relação altura de vilosidades:profundidade de criptas do jejuno, a qual foi também maior nos animais recebendo proteína láctea. A adição de zinco na dieta reduziu a concentração de IGF-I e o peso relativo do fígado aos 14 dias de experimento, enquanto o uso de proteína láctea aumentou a concentração de IGF-I. A inclusão de proteína láctea melhorou a conversão alimentar, influenciou a morfologia intestinal e aumentou a concentração de IGF-I, mas a suplementação de zinco não foi eficiente para alterar os níveis de hormônio do crescimento no organismo.It was evaluated the effects of using milk protein or supplemental zinc in the diet on performance, relative weights of small intestine and liver, intestine morphology and IGF-I (insulin-like growth factor) serum concentrations, growth hormone and zinc in piglets. The experiment lasted 14 days and it was carried out using 60 piglets weaned at 21 days of age (5.43 ± 0.46 kg) in a complete random design, in a 2 x 2 factorial composed of two levels of milk protein (with and without, 4%) and two levels of zinc (with or without, 2,250 ppm) in the diet. In the 1-7 day experiment period, zinc provided better feed conversion and the in the 1-14 day experiment period, it promoted higher body weight at 14 days and higher weight gain. Supply of milk protein in the diet worsened feed conversion in the two phases (from 1 to 7 days and from 1 to 14 days of the experiment) and it resulted in a lower crypts depth in the jejunum and a higher villous height on day 14 of the experiment. On the 7th day of the experiment, there was an interaction among milk protein and supplemental zinc for villous height:crypts depth relationship, which was also higher for animals fed milk protein. The addition of zinc in the diet reduced insuline-like growth factor concentration and the average weight of the liver on day 14 of the experiment while the use of milk protein increased IGF-I concentrations. The inclusion of milk protein improves feed conversion, affects intestine morphology and increases IGF-I concentration, but supplementation of zinc is not efficient to affect levels of growth hormone in the organism.Zinpro Performance Mineral

Adequação de protocolos de classificação de risco para COVID-19 às orientações da OMS: uma proposta de instrumento

Objective: This article proposes to create an instrument to analyze the adequacy of risk classification protocols for COVID-19 to the guidelines of the World Health Organization (WHO) and analyzes the protocol used by Santa Catarina. Method: The descriptive research was composed of three parts: 1) extraction of information regarding risk analysis and COVID-19 from WHO documents; 2) elaboration of an instrument to analyze the adequacy of risk classification protocols for COVID-19 to the WHO guidelines; 3) application of the instrument to the protocol used in the state of Santa Catarina. Results: Five WHO documents were reviewed. The built instrument included five dimensions: risk assessment itself, exposure assessment, context assessment, risk characterization and reliability. Partial information regarding the risk assessment itself and reliability was found in the Santa Catarina government protocol. No information was found regarding the other dimensions. Discussion: The mismatch between the matrix used by the state of Santa Catarina and the WHO risk analysis guidelines is huge. Thus, without an adequate analysis of these factors, the entire strategy for implementing actions can be compromised, exposing the population of the state to risk.Objetivo: Este artigo propõe criar um instrumento para analisar a adequação de protocolos de classificação de risco para COVID-19 às orientações da Organização Mundial de Saúde (OMS) e analisa o protocolo utilizado por Santa Catarina. Método: A pesquisa descritiva foi composta de três partes: 1) extração de informações concernentes à análise de risco e à COVID-19 dos documentos da OMS; 2) elaboração de instrumento para análise da adequação de protocolos de classificação de risco para COVID-19 às orientações da OMS; 3) aplicação do instrumento ao protocolo utilizado no estado de Santa Catarina. Resultados: Cinco documentos da OMS foram revistos. O instrumento construído contemplou cinco dimensões: avaliação do risco em si, avaliação da exposição, avaliação do contexto, caracterização do risco e confiabilidade. Informações parciais com relação à avaliação do risco em si e à confiabilidade foram encontradas no protocolo do governo catarinense. Não foram encontradas informações com relação às demais dimensões. Discussão: O desencontro entre a matriz utilizada pelo estado de Santa Catarina e as orientações para análise de risco da OMS são grandes. Assim, sem uma análise adequada desses fatores toda a estratégia de implementação de ações pode ser comprometida, expondo a população do estado a risco

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

Histone H3.3 beyond cancer: Germline mutations in Histone 3 Family 3A and 3B cause a previously unidentified neurodegenerative disorder in 46 patients

Although somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferation

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

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Histone H3.3 beyond cancer: Germline mutations in Histone 3 Family 3A and 3B cause a previously unidentified neurodegenerative disorder in 46 patients

International audienceAlthough somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferation

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data