5-Lipoxygenase-Dependent Recruitment of Neutrophils and Macrophages by Eotaxin-Stimulated Murine Eosinophils

The roles of eosinophils in antimicrobial defense remain incompletely understood. In ovalbumin-sensitized mice, eosinophils are selectively recruited to the peritoneal cavity by antigen, eotaxin, or leukotriene(LT)B4, a 5-lipoxygenase (5-LO) metabolite. 5-LO blockade prevents responses to both antigen and eotaxin. We examined responses to eotaxin in the absence of sensitization and their dependence on 5-LO. BALB/c or PAS mice and their mutants (5-LO-deficient ALOX; eosinophil-deficient GATA-1) were injected i.p. with eotaxin, eosinophils, or both, and leukocyte accumulation was quantified up to 24 h. Significant recruitment of eosinophils by eotaxin in BALB/c, up to 24 h, was accompanied by much larger numbers of recruited neutrophils and monocytes/macrophages. These effects were abolished by eotaxin neutralization and 5-LO-activating protein inhibitor MK886. In ALOX (but not PAS) mice, eotaxin recruitment was abolished for eosinophils and halved for neutrophils. In GATA-1 mutants, eotaxin recruited neither neutrophils nor macrophages. Transfer of eosinophils cultured from bone-marrow of BALB/c donors, or from ALOX donors, into GATA-1 mutant recipients, i.p., restored eotaxin recruitment of neutrophils and showed that the critical step dependent on 5-LO is the initial recruitment of eosinophils by eotaxin, not the secondary neutrophil accumulation. Eosinophil-dependent recruitment of neutrophils in naive BALB/c mice was associated with increased binding of bacteria

Single channel approach for filtering electroencephalographic signals strongly contaminated with facial electromyography

Eliminating facial electromyographic (EMG) signal from the electroencephalogram (EEG) is crucial for the accuracy of applications such as brain computer interfaces (BCIs) and brain functionality measurement. Facial electromyography typically corrupts the electroencephalogram. Although it is possible to find in the literature a number of multi-channel approaches for filtering corrupted EEG, studies employing single-channel approaches are scarce. In this context, this study proposed a single-channel method for attenuating facial EMG noise from contaminated EEG. The architecture of the method allows for the evaluation and incorporation of multiple decomposition and adaptive filtering techniques. The decomposition method was responsible for generating EEG or EMG reference signals for the adaptive filtering stage. In this study, the decomposition techniques CiSSA, EMD, EEMD, EMD-PCA, SSA, and Wavelet were evaluated. The adaptive filtering methods RLS, Wiener, LMS, and NLMS were investigated. A time and frequency domain set of features were estimated from experimental signals to evaluate the performance of the single channel method. This set of characteristics permitted the characterization of the contamination of distinct facial muscles, namely Masseter, Frontalis, Zygomatic, Orbicularis Oris, and Orbicularis Oculi. Data were collected from ten healthy subjects executing an experimental protocol that introduced the necessary variability to evaluate the filtering performance. The largest level of contamination was produced by the Masseter muscle, as determined by statistical analysis of the set of features and visualization of topological maps. Regarding the decomposition method, the SSA method allowed for the generation of more suitable reference signals, whereas the RLS and NLMS methods were more suitable when the reference signal was derived from the EEG. In addition, the LMS and RLS methods were more appropriate when the reference signal was the EMG. This study has a number of practical implications, including the use of filtering techniques to reduce EEG contamination caused by the activation of facial muscles required by distinct types of studies. All the developed code, including examples, is available to facilitate a more accurate reproduction and improvement of the results of this study

Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data

Tropical savanna ecosystems play a major role in the seasonality of the global carbon cycle. However, their ability to store and sequester carbon is uncertain due to combined and intermingling effects of anthropogenic activities and climate change, which impact wildfire regimes and vegetation dynamics. Accurate measurements of tropical savanna vegetation aboveground biomass (AGB) over broad spatial scales are crucial to achieve effective carbon emission mitigation strategies. UAV-lidar is a new remote sensing technology that can enable rapid 3-D mapping of structure and related AGB in tropical savanna ecosystems. This study aimed to assess the capability of high-density UAV-lidar to estimate and map total (tree, shrubs, and surface layers) aboveground biomass density (AGBt) in the Brazilian Savanna (Cerrado). Five ordinary least square regression models esti-mating AGBt were adjusted using 50 field sample plots (30 m × 30 m). The best model was selected under Akaike Information Criterion, adjusted coefficient of determination (adj.R2), absolute and relative root mean square error (RMSE), and used to map AGBt from UAV-lidar data collected over 1,854 ha spanning the three major vegetation formations (forest, savanna, and grassland) in Cerrado. The model using vegetation height and cover was the most effective, with an overall model adj-R2 of 0.79 and a leave-one-out cross-validated RMSE of 19.11 Mg/ha (33.40%). The uncertainty and errors of our estimations were assessed for each vegetation formation separately, resulting in RMSEs of 27.08 Mg/ha (25.99%) for forests, 17.76 Mg/ha (43.96%) for savannas, and 7.72 Mg/ha (44.92%) for grasslands. These results prove the feasibility and potential of the UAV-lidar technology in Cerrado but also emphasize the need for further developing the estimation of biomass in grasslands, of high importance in the characterization of the global carbon balance and for supporting integrated fire management activities in tropical savanna ecosystems. Our results serve as a benchmark for future studies aiming to generate accurate biomass maps and provide baseline data for efficient management of fire and predicted climate change impacts on tropical savanna ecosystems

Health-related quality of life in patients with type 1 diabetes mellitus in the different geographical regions of Brazil : data from the Brazilian Type 1 Diabetes Study Group

Background: In type 1 diabetes mellitus (T1DM) management, enhancing health-related quality of life (HRQoL) is as important as good metabolic control and prevention of secondary complications. This study aims to evaluate possible regional differences in HRQoL, demographic features and clinical characteristics of patients with T1DM in Brazil, a country of continental proportions, as well as investigate which variables could influence the HRQoL of these individuals and contribute to these regional disparities. Methods: This was a retrospective, cross-sectional, multicenter study performed by the Brazilian Type 1 Diabetes Study Group (BrazDiab1SG), by analyzing EuroQol scores from 3005 participants with T1DM, in 28 public clinics, among all geographical regions of Brazil. Data on demography, economic status, chronic complications, glycemic control and lipid profile were also collected. Results: We have found that the North-Northeast region presents a higher index in the assessment of the overall health status (EQ-VAS) compared to the Southeast (74.6 ± 30 and 70.4 ± 19, respectively; p < 0.05). In addition, North- Northeast presented a lower frequency of self-reported anxiety-depression compared to all regions of the country (North-Northeast: 1.53 ± 0.6; Southeast: 1.65 ± 0.7; South: 1.72 ± 0.7; Midwest: 1.67 ± 0.7; p < 0.05). These findings could not be entirely explained by the HbA1c levels or the other variables examined. Conclusions: Our study points to the existence of additional factors not yet evaluated that could be determinant in the HRQoL of people with T1DM and contribute to these regional disparities

Enxaqueca em 746 pacientes com esclerose múltipla

Enxaqueca piora o sofrimento do paciente que tem esclerose múltipla (EM). ID-migraine é uma ferramenta útil para seleção de pacientes com enxaqueca e Migraine Disability Assessment (MIDAS) é um questionário que avalia o impacto da doença. O objetivo do presente estudo foi avaliar a presença e impacto de enxaqueca em pacientes com EM. Métodos: Pacientes diagnosticados com EM e tratados em clínicas especializadas foram convidados a responder um questionário online se também apresentassem cefaleia. Resultados: O estudo incluiu 746 participantes com cefaleia e EM que preencheram completamente as respostas. Foram 625 mulheres e 121 homens, sendo 69% dos pacientes com idade entre 20 e 40 anos. Enxaqueca foi identificada em 404 pacientes (54,1%) e moderado a grave impacto da doença foi observado em 68,3% dos casos. Conclusão: Enxaqueca é uma cefaleia primária frequente e incapacitante relatada por pacientes com EM.Migraine adds to the burden of patients suffering from multiple sclerosis (MS). The ID-migraine is a useful tool for screening migraine, and the Migraine Disability Assessment questionnaire can evaluate disease burden. The aim of the present study was to assess the presence and burden of migraine in patients with MS. Methods: Patients diagnosed with MS attending specialized MS units were invited to answer an online survey if they also experienced headache. Results: The study included 746 complete responses from patients with MS and headache. There were 625 women and 121 men, and 69% of all the patients were aged between 20 and 40 years. Migraine was identified in 404 patients (54.1%) and a moderate-to-high burden of disease was observed in 68.3% of the patients. Conclusion: Migraine is a frequent and disabling type of primary headache reported by patients with MS

Avanços da cirurgia robotica no tratamento do Câncer

A cirurgia robótica tem sido almejada por profissionais cirurgiões, visto que, é um procedimento considerado de alta eficácia, assim como, apresenta reduzidos níveis de riscos ao paciente, o que configura significativamente a qualidade elevada do procedimento médico. Logo, tem sido utilizada no tratamento cirúrgico de diversos tipos de câncer, o qual tem demonstrado melhores resultados quando comparados com procedimentos mais invasivas ou tradicionais O principal objetivo do é discutir por meio de uma revisão sistematizada da literatura acerca dos avanços da cirurgia robótica no tratamento dos demais tipos de cânceres. O presente estudo trata-se de uma revisão sistemática da literatura, de modo que, realizou-se buscas de na Scielo, Periódico Capes e na Biblioteca Virtual em Saúde (BVS), através de termos específicos do Decs, o qual resultou-se em: “Neoplasias” AND “Procedimentos Cirúrgicos Robóticos” AND “Terapêutica”. Foram elegíveis um total de 8 estudos na presente revisão sistemática. Este procedimento é devidamente realizado com menores danos de incisão possível no paciente, de modo que, possibilitou a diminuição de dores pós-operatórios, além da redução de sangramentos, traumas, respostas inflamatórias, tempo de internação e até mesmo melhores resultados estéticos nos pacientes, quando comparados com os métodos mais tradicionais e invasivos

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