Manejo Terapêutico do Paciente Queimado: Revisão de Literatura

Burns are traumatic wounds resulting from thermal, chemical, electrical or radioactive agents that compromise vital skin functions. In Brazil, they constitute one of the main external causes of death, alongside transport accidents and homicides. An integrative review was carried out, using the Google Scholar database with the following descriptors “Burn”, “Pain Management”, “Therapeutic Indication”. In which 8 articles were selected from 1,710, published in English and Portuguese from 2019 to 2024. The main author conducted the analysis, with disagreements resolved between the authors. WHO estimates indicate 300,000 annual deaths from burns globally. In Brazil, one million people suffer burns annually, with young adults being the most vulnerable, mainly in domestic or work environments. The classification of burns, extent of the affected area and treatment are fundamental for the best therapeutic management, given that pain is a prevalent complaint that is difficult to control in these patients. Protocols vary, and wound care, hydration, and pain management are challenges. Different therapies, including agents such as silver sulfadiazine and essential fatty acids, show promising results. Surgical treatment aims to remove compromised tissues, contributing to effective healing. The study reinforces the importance of medical knowledge in the management of burns and its relevance to public health.As queimaduras são feridas traumáticas resultantes de agentes térmicos, químicos, elétricos ou radioativos que comprometem funções vitais tanto da pele, como dos demais órgãos internos. No Brasil, constituem uma das principais causas externas de morte, disputando com acidentes de transporte e homicídios. Realizou-se uma revisão integrativa, utilizando a base de dados Google Acadêmico com os seguintes descritores “Queimadura”, “Manejo da Dor”, “Indicação Terapêutica”. Nos quais foram selecionados 8 artigos entre 1.710, publicados em inglês e português de 2019 a 2024. O autor principal conduziu a análise, com discordâncias resolvidas entre os autores. Estimativas da OMS indicam 300 mil mortes anuais por queimaduras globalmente. No Brasil, um milhão de pessoas anualmente sofrem queimaduras, sendo adultos jovens mais vulneráveis, principalmente em ambientes domésticos ou laborais. A classificação das queimaduras, extensão da área afetada e o tratamento são fundamentais para o melhor manejo terapêutico, haja vista que a dor é uma queixa prevalente e de difícil controle nesses pacientes. Protocolos variam, e o cuidado da ferida, hidratação e manejo da dor são desafios. Diferentes terapias, incluindo agentes como sulfadiazina de prata e ácidos graxos essenciais, apresentam resultados promissores. O tratamento cirúrgico visa a remoção de tecidos comprometidos, contribuindo para a cicatrização eficaz. O estudo reforça a importância do conhecimento médico na abordagem de queimaduras e sua relevância para a saúde pública

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

A Machine Learning Application Based in Random Forest for Integrating Mass Spectrometry-Based Metabolomic Data: A Simple Screening Method for Patients With Zika Virus

Recent Zika outbreaks in South America, accompanied by unexpectedly severe clinical complications have brought much interest in fast and reliable screening methods for ZIKV (Zika virus) identification. Reverse-transcriptase polymerase chain reaction (RT-PCR) is currently the method of choice to detect ZIKV in biological samples. This approach, nonetheless, demands a considerable amount of time and resources such as kits and reagents that, in endemic areas, may result in a substantial financial burden over affected individuals and health services veering away from RT-PCR analysis. This study presents a powerful combination of high-resolution mass spectrometry and a machine-learning prediction model for data analysis to assess the existence of ZIKV infection across a series of patients that bear similar symptomatic conditions, but not necessarily are infected with the disease. By using mass spectrometric data that are inputted with the developed decision-making algorithm, we were able to provide a set of features that work as a “fingerprint” for this specific pathophysiological condition, even after the acute phase of infection. Since both mass spectrometry and machine learning approaches are well-established and have largely utilized tools within their respective fields, this combination of methods emerges as a distinct alternative for clinical applications, providing a diagnostic screening—faster and more accurate—with improved cost-effectiveness when compared to existing technologies