Association of the fibronectin type III domain–containing protein 5 rs1746661 single nucleotide polymorphism with reduced brain glucose metabolism in elderly humans

Fibronectin type III domain–containing protein 5 (FNDC5) and its derived hormone, irisin, have been associated with metabolic control in humans, with described FNDC5 single nucleotide polymorphisms being linked to obesity and metabolic syndrome. Decreased brain FNDC5/irisin has been reported in subjects with dementia due to Alzheimer’s disease. Since impaired brain glucose metabolism develops in ageing and is prominent in Alzheimer’s disease, here, we examined associations of a single nucleotide polymorphism in the FNDC5 gene (rs1746661) with brain glucose metabolism and amyloid-β deposition in a cohort of 240 cognitively unimpaired and 485 cognitively impaired elderly individuals from the Alzheimer’s Disease Neuroimaging Initiative. In cognitively unimpaired elderly individuals harbouring the FNDC5 rs1746661(T) allele, we observed a regional reduction in low glucose metabolism in memory-linked brain regions and increased brain amyloid-β PET load. No differences in cognition or levels of cerebrospinal fluid amyloid-β42, phosphorylated tau and total tau were observed between FNDC5 rs1746661(T) allele carriers and non-carriers. Our results indicate that a genetic variant of FNDC5 is associated with low brain glucose metabolism in elderly individuals and suggest that FNDC5 may participate in the regulation of brain metabolism in brain regions vulnerable to Alzheimer’s disease pathophysiology. Understanding the associations between genetic variants in metabolism-linked genes and metabolic brain signatures may contribute to elucidating genetic modulators of brain metabolism in humans

Exposure computational models with voxel phantoms coupled to EGSnrc Monte Carlo code

In computational dosimetry of ionizing radiation, the energy deposited in radiosensitive organs and tissues is evaluated when an anthropomorphic simulator (phantom) is irradiated using Exposure Computational Models (ECMs). An ECM is a virtual scene with a phantom positioned mathematically relative to a radioactive source. The initial state includes information like the type of primary particle, its energy, starting point coordinates, and direction. Subsequently, robust Monte Carlo (MC) codes are used to simulate the particle's mean free path, interaction with the medium's atoms, and energy deposition. These are common steps for simulations involving photons and/or primary electrons. The GDN (Research Group on Numerical Dosimetry and the Research Group on Computational Dosimetry and Embedded Systems) has published ECMs with voxel phantoms irradiated by photons using the MC code EGSnrc. This work has led to specific computational tools development for various numerical dosimetry stages, including input file preparation, ECM execution, and result analysis. Since 2004, the GDN developed in-house applications like FANTOMAS, CALDose_X, DIP, and MonteCarlo. Certain previously used phantoms are reintroduced to provide historical context in the ECMs' production timeline, emphasizing additive modifications inherent in systematic theme studies. The dosimetric evaluations used the binary version of the MASH (Male Adult mesh) phantom, converted to the SID (Dosimetric Information System) text file type. This format has been used by the group since 2021 to couple a voxel phantom to the EGSnrc user code. The ECM included an environmental dosimetry problem simulation. Most of these tools are accessible on the GDN page (http://dosimetrianumerica.org)

Tonometria Gastrointestinal no Perioperatório do Transplante Hepático: Uma Revisão Integrativa

Introdução: A tonometria gástrica é uma ferramenta útil para examinar a perfusão esplâncnica regional por permitir o fornecimento de uma avaliação indireta do estado do enxerto hepático. Isso ocorre devido à hipoperfusão esplâncnica ser um parâmetro crítico no contexto do transplante de fígado, estando associada ao desenvolvimento de problemas como insuficiência hepática aguda e falência de múltiplos órgãos. Objetivo: Analisar os efeitos da tonometria gastrointestinal no perioperatório dos pacientes submetidos ao transplante hepático. Metodologia: Trata-se de uma Revisão Integrativa realizada nas bases de dados PubMed e BVS. Foram utilizados os descritores: “Tonometry”, “Splanchnic circulation” e “Liver transplantation”, incluindo o operador booleano “AND”, e selecionados artigos de relevância para o tema. Foram selecionados inicialmente 24 artigos, todos publicados nos últimos 20 anos, em português e/ou inglês. Após análise, seis artigos corresponderam ao objetivo proposto. Resultado: Observou-se que a diferença entre a PraCO2 no final da cirurgia e na fase anepática foi maior em pacientes sem disfunção do enxerto hepático. Foi identificada uma correlação positiva entre ΔpraCO2 e o pico de ALT após o transplante de fígado. Em outro estudo, verificou-se que a presença de enzimas hepáticas elevadas e a piora da função hepática sintética, coagulopatia e encefalopatia estava relacionada à má função do enxerto. Também foi comprovado que o pH gástrico intramucoso pode predizer a funcionalidade precoce do enxerto. Em um grupo com disfunção hepática, os pacientes apresentaram pH gástrico intramucoso abaixo de 7,3 no período perioperatório, mantendo-se baixo até a 24ª hora pós-operatória, enquanto o grupo sem disfunção apresentou pH gástrico intramucoso acima de 7,3, exceto na fase anepática, quando ficou abaixo desse valor. Conclusão: Descreve-se a utilidade da tonometria gastrointestinal para monitorar a circulação esplâncnica e a função do enxerto hepático durante o transplante hepático. Embora alguns estudos ofereçam suporte a essa afirmação, esta revisão apresenta limitações devido à quantidade restrita de artigos disponíveis, o que a impede de abranger uma ampla gama de evidências científicas

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

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 cmH(2)O 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 <= 30 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 method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt