Short communication: Genetic analysis of lactation curves in buffaloes, using Wood’s model

Aim of study: To estimate the heritability and genetic correlations for lactation curve traits in buffaloes.Area of study: The buffalo cows were raised on properties located in the states of São Paulo, Ceará and Rio Grande do Norte, Brazil.Material and methods: The individual parameters of Wood’s model ( , , and ) were obtained using a non-linear mixed model. Peak yield (PY), peak time (PT) and lactation persistency (LP) were also calculated. These individual parameters were employed in multi-trait analysis with the milk yield (MY) using Bayesian inference.Main results: The heritability estimates were of low to moderate magnitudes, with values ranging from 0.156 ( ) to 0.299 (PY). The estimates for genetic correlation between the Wood’s parameters and MY were of low to high magnitude and ranged from -0.533 (  and MY) to 0.983 (PY and MY).Research highlights: The heritability estimates obtained indicate that the traits studied can be used in animal breeding programs

A novel case of human visceral leishmaniasis from the urban area of the city of Rio de Janeiro: autochthonous or imported from Spain ?

Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle, 10ª Enfermaria. Rio de Janeiro, RJ, Brasil.Universidade Federal do Estado do Rio de Janeiro. Centro de Ciências Biológicas e da Saúde. Hospital Universitário Gaffrée e Guinle. Serviço de Anatomia Patológica. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Pesquisa Clínica e Vigilância em Leishmanioses. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Pesquisa Clínica e Vigilância em Leishmanioses. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Pesquisa Clínica e Vigilância em Leishmanioses. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Pesquisa Clínica e Vigilância em Leishmanioses. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Pesquisa Clínica e Vigilância em Leishmanioses. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Laboratório de Pesquisa Clínica e Vigilância em Leishmanioses. Rio de Janeiro, RJ, Brasil

The Functional Consequences of Mutualistic Network Architecture

The architecture and properties of many complex networks play a significant role in the functioning of the systems they describe. Recently, complex network theory has been applied to ecological entities, like food webs or mutualistic plant-animal interactions. Unfortunately, we still lack an accurate view of the relationship between the architecture and functioning of ecological networks. In this study we explore this link by building individual-based pollination networks from eight Erysimum mediohispanicum (Brassicaceae) populations. In these individual-based networks, each individual plant in a population was considered a node, and was connected by means of undirected links to conspecifics sharing pollinators. The architecture of these unipartite networks was described by means of nestedness, connectivity and transitivity. Network functioning was estimated by quantifying the performance of the population described by each network as the number of per-capita juvenile plants produced per population. We found a consistent relationship between the topology of the networks and their functioning, since variation across populations in the average per-capita production of juvenile plants was positively and significantly related with network nestedness, connectivity and clustering. Subtle changes in the composition of diverse pollinator assemblages can drive major consequences for plant population performance and local persistence through modifications in the structure of the inter-plant pollination networks

Incorporating biodiversity responses to land use change scenarios for preventing emerging zoonotic diseases in areas of unknown host-pathogen interactions

The need to reconcile food production, the safeguarding of nature, and the protection of public health is imperative in a world of continuing global change, particularly in the context of risks of emerging zoonotic disease (EZD). In this paper, we explored potential land use strategies to reduce EZD risks using a landscape approach. We focused on strategies for cases where the dynamics of pathogen transmission among species were poorly known and the ideas of “land-use induced spillover” and “landscape immunity” could be used very broadly. We first modeled three different land-use change scenarios in a region of transition between the Cerrado and the Atlantic Forest biodiversity hotspots. The land-use strategies used to build our scenarios reflected different proportions of native vegetation cover, as a proxy of habitat availability. We then evaluated the effects of the proportion of native vegetation cover on the occupancy probability of a group of mammal species and analyzed how the different land-use scenarios might affect the distribution of species in the landscape and thus the risk of EZD. We demonstrate that these approaches can help identify potential future EZD risks, and can thus be used as decision-making tools by stakeholders, with direct implications for improving both environmental and socio-economic outcomes

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): study protocol for a randomized controlled trial

BACKGROUND: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). METHODS/DESIGN: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH2O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure 6430 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. DISCUSSION: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration metho

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

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