Insulin Resistance in HIV-Patients: Causes and Consequences

Here we review how immune activation and insulin resistance contribute to the metabolic alterations observed in HIV-infected patients, and how these alterations increase the risk of developing CVD. The introduction and evolution of antiretroviral drugs over the past 25 years has completely changed the clinical prognosis of HIV-infected patients. The deaths of these individuals are now related to atherosclerotic CVDs, rather than from the viral infection itself. However, HIV infection, cART, and intestinal microbiota are associated with immune activation and insulin resistance, which can lead to the development of a variety of diseases and disorders, especially with regards to CVDs. The increase in LPS and proinflammatory cytokines circulating levels and intracellular mechanisms activate serine kinases, resulting in insulin receptor substrate-1 (IRS-1) serine phosphorylation and consequently a down regulation in insulin signaling. While lifestyle modifications and pharmaceutical interventions can be employed to treat these altered metabolic functions, the mechanisms involved in the development of these chronic complications remain largely unresolved. The elucidation and understanding of these mechanisms will give rise to new classes of drugs that will further improve the quality of life of HIV-infected patients, over the age of 50

Abordagem terapêutica da lesão renal aguda (LRA): avanços e atualizações

A lesão renal aguda (LRA) apresenta-se como um diagnóstico comum, com incidência que varia entre 5 a 7,5% em pacientes hospitalizados, e que atinge taxas de 60% em pacientes críticos. Dado o impacto do prognóstico da LRA, é importante melhorar o reconhecimento dos pacientes de risco e as estratégias preventivas, diagnósticas e terapêuticas. O presente estudo de revisão buscou avaliar novos avanços e atualizações na abordagem terapêutica da lesão renal aguda, documentados por meio de estudos clínicos e randomizados. Trata-se de uma pesquisa de revisão integrativa realizada por meio da base de dados PubMed, que levou em consideração os seguintes critérios de inclusão: ensaios clínicos e testes controlados e aleatórios; artigos publicados no último ano; que possuíam texto completo disponível e que abordassem acerca da terapêutica da lesão renal aguda. Ficou constatado que a administração profilática de curcuminóides reduziu a incidência de LRA pós-contraste em pacientes com DRC. Além disso, o L-FABP se mostrou viável como marcador clínico para avaliar o risco em potencial de LRA pós-contraste, o que lhe confere utilidade clínica nesse contexto. Por fim, a proencefalina A 119-159 pode ser um biomarcador útil para liberação bem-sucedida de TRS e, ainda, permitir uma abordagem individualizada para guiar estratégias de liberação de TRS em pacientes criticamente enfermos com LRA

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

Transtorno bipolar em crianças: análise de relato de caso 2018-2023

O transtorno bipolar em crianças é uma realidade clínica que demanda atenção especializada. A compreensão dos sintomas, fatores de risco, prevalência e desafios diagnósticos é fundamental para proporcionar intervenções precoces e adequadas, visando melhorar a qualidade de vida desses jovens e reduzir o impacto a longo prazo dessa condição psiquiátrica. Trata-se de um estudo cujo objetivo foi objetivo revisar relatos de caso publicados entre 2018 e 2023 sobre transtorno bipolar em crianças, identificando o estado da arte desses estudos. Para isso, se realizou uma revisão sistemática de literatura utilizando as bases de dados Medical Literature Analysis and Retrieval System Online (MEDLINE), Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS) e Scientific Electronic Library Online (SCIELO). Com a análise e interpretação qualitativa dos resultados, a principal conclusão deste estudo é que o transtorno bipolar na infância é uma condição complexa, manifestando-se com comportamentos consistentes com o Transtorno de Conduta e sendo influenciado por fatores ambientais, familiares e genéticos. O tratamento eficaz requer uma abordagem multidisciplinar, integrando intervenções farmacológicas e não farmacológicas, personalizadas conforme as necessidades individuais. A supervisão familiar é crucial para a adesão ao tratamento, mas reconhece-se a necessidade contínua de pesquisa para aprimorar as estratégias terapêuticas diante da diversidade de casos

[Covid-19 in the Northeast of Brazil: from lockdown to the relaxation of social distancing measures].

Even in the period when the Covid-19 pandemic was on the rise in the Northeast of Brazil, the relaxation of social distancing measures was introduced. The scope of the study is to assess, in the light of the epidemiological-sanitary situation in the region, the suitability of relaxation of social distancing measures. Based on the WHO guidelines for relaxation of social distancing, operational indicators were created and analyzed for each guideline in the context of the Northeast. To analyze the behavior of the epidemic, according to selected indicators, Joinpoint trend analysis techniques, heat maps, rate ratios and time trends between capitals and the state interior were compared. The weekly growth peak of the epidemic occurred in May-July 2020 (epidemiological weeks 19 to 31). In most capitals, there was no simultaneous downward trend in the number of cases and deaths in the 14 days prior to flexibilization. In all states the number of tests performed was insufficient. In epidemiological week 24, the state percentages of ICU/Covid-19 bed occupancy were close to or above 70%. The epidemiological situation of the nine Northeastern state capitals analyzed here did not meet criteria and parameters recommended by the World Health Organization for the relaxation of social distancing measures

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

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good