Continuous positive airway pressure and body position alter lung clearance of the radiopharmaceutical 99mtechnetium-diethylenetriaminepentaacetic acid (99mTc-DTPA)

The purpose of this investigation was to evaluate the pulmonary clearance rate of 99mtechnetium-diethylenetriaminepentaacetic acid (99mTc-DTPA) through the use of continuous positive airway pressure (CPAP) in different postures. It was a quasi-experimental study involving 36 healthy individuals with normal spirometry. 99mTc-DTPA, as aerosol, was nebulized for 3 min with the individual in a sitting position. The pulmonary clearance rate was assessed through pulmonary scintigraphy under spontaneous breathing and under 20 and 10 cmH2O CPAP in the sitting and supine positions. The clearance rate was expressed as the half-time (T1/2), that is, the time for the activity to decrease to 50% of the peak value. 20 cmH2O CPAP produced significant reduction of the T1/2 of 99mTc-DTPA in the supine position (P = 0.009) and in the sitting position (P = 0.005). However, 10 cmH2O CPAP did not alter the T1/2 of DTPA in both positions. The postural variation from supine to the sitting position with 10 cmH2O CPAP (P = 0.01) and 20 cmH2O (P = 0.02) also reduced the T1/2 of 99mTc-DTPA. High levels of positive pressure in normal lungs resulted in faster 99mTc-DTPA clearance. Moreover, the sitting position further increased the clearance rate of the 99mTc radioaerosol imaging in the two pressure levels studied.Key words: Continuous positive airway pressure, 99mTc-DTPA, scintigraphy, posture

Fyn Mediates Leptin Actions in the Thymus of Rodents

BACKGROUND:Several effects of leptin in the immune system rely on its capacity to modulate cytokine expression and apoptosis in the thymus. Surprisingly, some of these effects are dependent on signal transduction through the IRS1/PI3-kinase, but not on the activation of JAK2. Since all the well known effects of leptin in different cell types and tissues seem to be dependent on JAK2 activation, we hypothesized that, at least for the control of thymic function, another, unknown kinase could mediate the transduction of the leptin signal from the ObR towards the IRS1/PI3-kinase signaling cascade. METHODOLOGY/PRINCIPAL FINDINGS:Here, by employing immunoblot, real-time PCR and flow citometry we show that the tyrosine kinase, Fyn, is constitutively associated with the ObR in thymic cells. Following a leptin stimulus, Fyn undergoes an activating tyrosine phosphorylation and a transient association with IRS1. All these effects are independent of JAK2 activation and, upon Fyn inhibition, the signal transduction towards IRS1/PI3-kinase is abolished. In addition, the inhibition of Fyn significantly modifies the effects of leptin on thymic cytokine expression. CONCLUSION/SIGNIFICANCE:Therefore, in the thymus, Fyn acts as a tyrosine kinase that transduces the leptin signal independently of JAK2 activation, and mediates some of the immunomodulatory effects of leptin in this tissue

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

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