Machine learning algorithms development for sleep cycles detection and general physical activity based on biosignals

In this work, machine learning algorithms for automatic sleep cycles detection were developed. The features were selected based on the AASM manual, which is considered the gold standard for human technicians. These include features such as saturation of peripheral oxygen or others related to heart rate variation. As normally, the sleep phases naturally differ in frequency, to balance the classes within the dataset, we either oversampled the least common sleep stages or undersampled the most common, allowing for a less skewed performance favouring the most represented stages, while simultaneously improving worst-stage classification. For training the models we used MESA, a database containing 2056 full overnight unattended polysomnographies from a group of 2237 participants. With the goal of developing an algorithm that would only require a PPG device to be able to accurately predict sleep stages and quality, the main channels used from this dataset were SpO2 and PPG. Employing several popular Python libraries used for the development of machine learning and deep learning algorithms, we exhaustively explored the optimisation of the manifold parameters and hyperparameters conditioning both the training and architecture of these models in order for them to better fit our purposes. As a result of these strategies, we were able to develop a neural network model (Multilayer perceptron) with 80.50% accuracy, 0.7586 Cohen’s kappa, and 77.38% F1- score, for five sleep stages. The performance of our algorithm does not seem to be correlated with sleep quality or the number of transitional epochs in each recording, suggesting uniform performance regardless of the presence of sleep disorders. To test its performance in a different real-world scenario we compared the classifications attributed by a popular sleep stage classification android app, which collected information using a smartwatch, and our algorithm, using signals obtained from a device developed by PLUX. These algorithms displayed a strong level of agreement (90.96% agreement, 0.8663 Cohen’s kappa).Neste trabalho, foram desenvolvidos algoritmos de aprendizagem de máquinas para a detecção automática de ciclos de sono. Os sinais específicos captados durante a extração de características foram selecionados com base no manual AASM, que é considerado o padrão-ouro para técnicos. Estas incluem características como a saturação do oxigénio periférico ou outras relacionadas com a variação do ritmo cardíaco. A fim de equilibrar a frequência das classes dentro do conjunto de dados, ora se fez a sobreamostragem das fases menos comuns do sono, ora se fez a subamostragem das mais comuns, permitindo um desempenho menos enviesado em favor das fases mais representadas e, simultaneamente, melhorando a classificação das fases com pior desempenho. Para o treino dos modelos criados, utilizámos MESA, uma base de dados contendo 2056 polissonografias completas, feitas durante a noite e sem vigilância, de um grupo de 2237 participantes. Do conjunto de dados escolhido, os principais canais utilizados foram SpO2 e PPG, com o objetivo de desenvolver um algoritmo que apenas exigiria um dispositivo PPG para poder prever com precisão as fases e a qualidade do sono. Utilizando várias bibliotecas populares de Python para o desenvolvimento de algoritmos de aprendizagem de máquinas e de aprendizagem profunda, explorámos exaustivamente a optimização dos múltiplos parâmetros e hiperparâmetros que tanto condicionam a formação como a arquitetura destes modelos, de modo a que se ajustem melhor aos nossos propósitos. Como resultado disto, fomos capazes de desenvolver um modelo de rede neural (Multilayer perceptron) com 80.50% de precisão, 0.7586 kappa de Cohen e F1-score de 77.38%, para cinco fases de sono. O desempenho do nosso algoritmo não parece estar correlacionado com a qualidade do sono ou o número de épocas de transição em cada gravação, sugerindo um desempenho uniforme independentemente da presença de distúrbios do sono. Para testar o seu desempenho num cenário de mundo real diferente, comparámos as classificações atribuídas por uma aplicação Android de classificação de fases do sono popular, através da recolha de informação por um smartwatch, e o nosso algoritmo, utilizando sinais obtidos a partir de um dispositivo desenvolvido pela PLUX. Estes algoritmos demonstraram um forte nível de concordância (90.96% de concordância, 0.8663 kappa de Cohen)

As pequenas memórias de Saramago

As pequenas memórias é uma obra de agradável e fácil leitura, apesar das cenas e mensagens intensas nela presentes. Neste livro, José Saramago recria, de forma magistral, as impressionantes paisagens e aventuras da sua infância e juventude, vividas entre o ambiente rural do Ribatejo e o urbano de Lisboa. Nesta pequena autobiografia, Saramago constrói, a partir de reminiscências sobre a sua vida privada, um conjunto de sólidas reflexões poéticas, cheias de considerações históricas críticas sobre as mudanças vividas com a entrada de Portugal para a União Europeia. Este livro permite compreender o impacto das experiências juvenis sobre a sua alma de escritor. Adicionalmente, ao longo de toda a narrativa, são dadas a conhecer não só as origens do seu nome, como também de muitos títulos e enredos de romances que, posteriormente, viriam a ser escritos por ele.info:eu-repo/semantics/publishedVersio

Evaluation of the Cyclic and Torsional Fatigue Resistance of Thermally Treated Hyflex CM versus Aurum Blue Nickel-titanium Rotary Instruments

Introduction: We aim to evaluate the cyclic and torsional fatigue resistance of two rotary instruments, Hyflex CM 25/0.06 (HCM) (Coletene-Whaledent, Allstetten, Switzerland) and Aurum Blue (AB) 25/0.06 (Meta-Biomed, Republic of Korea). Methods and Materials: Forty rotary instruments, HCM 25/0.06 and AB 25/0.06 (n=20 each) were used. The instruments were rotated in an artificial stainless steel canal with a 60° angle and a 5-mm radius of curvature (n=10) at body temperature (35°±1°C). The torsional test evaluated the torque and angle of rotation at failure of new instruments (n=10) in the portion 3 mm from the tip according to ISO 3630-1. The fractured surface of each fragment was observed by scanning electron microscopy. The data were analyzed using unpaired student’s t- test, and the level of significance was set at 5%. Results: AB 25/0.06 had significantly greater number of cycles to failure than HCM 25/0.06 (P<0.05). The torsional test showed there were no significant differences in the torsional strength and angular rotation to fracture between the groups (P>0.05). Conclusion: Based on this in vitro study, AB 25/0.06 instrument was more resistant to cyclic fatigue than the HCM 25/0.06 instrument, suggested that these instruments are safer than HCM 25/0.06 for the preparation of severely curved canals. However; there was no significant difference in the torsional properties of the two instruments then appear to have similar performance during constricted canal preparation

VIVER COM HIV/AIDS EM SITUAÇÃO DE RUA: REPRESENTAÇÕES SOCIAIS DE PESSOAS HOSPITALIZADAS

Objetivo: apreender as representações sociais sobre o viver com HIV para pessoas hospitalizadas em situação de rua e identificar os conteúdos, elementos e estrutura dessas representações. Método: trata-se de estudo descritivo, embasado na Teoria das Representações Sociais, realizado com pessoas hospitalizadas, que vivem com HIV em situação de rua. Para coleta de dados utilizou-se um formulário e o Teste de Associação Livre de Palavras. A análise de dados ocorreu por meio da estatística descritiva e do software EVOC. Resultados: dos 65 participantes, 46 eram do sexo masculino, com idade média de 39 anos. Observou-se como núcleo central das representações sociais: medo, doente e preconceito, indicando as proporções funcionais e relacionadas à imagem do objeto investigado. O grupo investigado representou o viver com HIV/aids na rua por meio de palavras negativas, carregadas de mágoa, tristeza e medo. Conclusão: as representações têm um provável núcleo central na palavra “medo”. Descritores: Representação Social. Pessoas Mal Alojadas. HIV. Hospitalização. Enfermagem

Protocol Proposal For The Care Of The Person With Venous Ulcer

Objective: To propose a care protocol for the care of the person with a venous ulcer in highly complex services. Methods and results: This is a methodological study, in three stages: literature review, validation of content and validation in the clinical context. The literature review was carried out from June to August/2011, being the basis for the construction of the Protocol for Venous Ulcers. The content validation included 53 judges (44 nurses, 8 physicians and 1 physiotherapist) selected through the Lattes platform to evaluate the items of the protocol. Validation in the clinical context occurred at the University Hospital Onofre Lopes, in Natal/RN with four judges (nurses), who worked in pairs, evaluating 32 patients with venous ulcers. The protocol was validated with 15 categories: sociodemographic data; anamnesis; examinations; ulcer characteristics; care with the lesion and perilesional area; medicines used to treat the lesion; evaluation and treatment of pain; surgical treatment of chronic venous disease; recurrence prevention (clinical and educational strategies); reference; counter-reference; and quality of life. Conclusion: The validated protocol regarding content and clinical context was applicable. Its implementation is a viable measure that assists in the reorientation of the team in high complexity services, aiming at wound healing and restoration of the patient´s integral health. Keywords: Varicose ulcer; Tertiary Health Care; Protocols; Validation studies

Signal transduction-related responses to phytohormones and environmental challenges in sugarcane

BACKGROUND: Sugarcane is an increasingly economically and environmentally important C4 grass, used for the production of sugar and bioethanol, a low-carbon emission fuel. Sugarcane originated from crosses of Saccharum species and is noted for its unique capacity to accumulate high amounts of sucrose in its stems. Environmental stresses limit enormously sugarcane productivity worldwide. To investigate transcriptome changes in response to environmental inputs that alter yield we used cDNA microarrays to profile expression of 1,545 genes in plants submitted to drought, phosphate starvation, herbivory and N(2)-fixing endophytic bacteria. We also investigated the response to phytohormones (abscisic acid and methyl jasmonate). The arrayed elements correspond mostly to genes involved in signal transduction, hormone biosynthesis, transcription factors, novel genes and genes corresponding to unknown proteins. RESULTS: Adopting an outliers searching method 179 genes with strikingly different expression levels were identified as differentially expressed in at least one of the treatments analysed. Self Organizing Maps were used to cluster the expression profiles of 695 genes that showed a highly correlated expression pattern among replicates. The expression data for 22 genes was evaluated for 36 experimental data points by quantitative RT-PCR indicating a validation rate of 80.5% using three biological experimental replicates. The SUCAST Database was created that provides public access to the data described in this work, linked to tissue expression profiling and the SUCAST gene category and sequence analysis. The SUCAST database also includes a categorization of the sugarcane kinome based on a phylogenetic grouping that included 182 undefined kinases. CONCLUSION: An extensive study on the sugarcane transcriptome was performed. Sugarcane genes responsive to phytohormones and to challenges sugarcane commonly deals with in the field were identified. Additionally, the protein kinases were annotated based on a phylogenetic approach. The experimental design and statistical analysis applied proved robust to unravel genes associated with a diverse array of conditions attributing novel functions to previously unknown or undefined genes. The data consolidated in the SUCAST database resource can guide further studies and be useful for the development of improved sugarcane varieties

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

Postoperative outcomes in oesophagectomy with trainee involvement

BACKGROUND: The complexity of oesophageal surgery and the significant risk of morbidity necessitates that oesophagectomy is predominantly performed by a consultant surgeon, or a senior trainee under their supervision. The aim of this study was to determine the impact of trainee involvement in oesophagectomy on postoperative outcomes in an international multicentre setting. METHODS: Data from the multicentre Oesophago-Gastric Anastomosis Study Group (OGAA) cohort study were analysed, which comprised prospectively collected data from patients undergoing oesophagectomy for oesophageal cancer between April 2018 and December 2018. Procedures were grouped by the level of trainee involvement, and univariable and multivariable analyses were performed to compare patient outcomes across groups. RESULTS: Of 2232 oesophagectomies from 137 centres in 41 countries, trainees were involved in 29.1 per cent of them (n = 650), performing only the abdominal phase in 230, only the chest and/or neck phases in 130, and all phases in 315 procedures. For procedures with a chest anastomosis, those with trainee involvement had similar 90-day mortality, complication and reoperation rates to consultant-performed oesophagectomies (P = 0.451, P = 0.318, and P = 0.382, respectively), while anastomotic leak rates were significantly lower in the trainee groups (P = 0.030). Procedures with a neck anastomosis had equivalent complication, anastomotic leak, and reoperation rates (P = 0.150, P = 0.430, and P = 0.632, respectively) in trainee-involved versus consultant-performed oesophagectomies, with significantly lower 90-day mortality in the trainee groups (P = 0.005). CONCLUSION: Trainee involvement was not found to be associated with significantly inferior postoperative outcomes for selected patients undergoing oesophagectomy. The results support continued supervised trainee involvement in oesophageal cancer surgery