Classification of Continuous ECG Segments - Performance Analysis of a Deep Learning Model.

Classification of electrocardiogram (ECG) signals plays an important role in the diagnosis of heart diseases. It is a complex and non-linear signal, which is the first option to preliminary identify specific pathologies/conditions (e.g., arrhythmias). Currently, the scientific community has proposed a multitude of intelligent systems to automatically process the ECG signal, through deep learning techniques, as well as machine learning, where this present high performance, showing state-of-the-art results. However, most of these models are designed to analyze the ECG signal individually, i.e., segment by segment. The scientific community states that to diagnose a pathology in the ECG signal, it is not enough to analyze a signal segment corresponding to the cardiac cycle, but rather an analysis of successive segments of cardiac cycles, to identify a pathological pattern.In this paper, an intelligent method based on a Convolutional Neural Network 1D paired with a Multilayer Perceptron (CNN 1D+MLP) was evaluated to automatically diagnose a set of pathological conditions, from the analysis of the individual segment of the cardiac cycle. In particular, we intend to study the robustness of the referred method in the analysis of several simultaneous ECG signal segments. Two ECG signal databases were selected, namely: MIT-BIH Arrhythmia Database (D1) and European ST-T Database (D2). The data was processed to create datasets with two, three and five segments in a row, to train and test the performance of the method. The method was evaluated in terms of classification metrics, such as: precision, recall, f1-score, and accuracy, as well as through the calculation of confusion matrices.Overall, the method demonstrated high robustness in the analysis of successive ECG signal segments, which we can conclude that it has the potential to detect anomalous patterns in the ECG signal. In the future, we will use this method to analyze the ECG signal coming in real-time, acquired by a wearable device, through a cloud system.Clinical Relevance-This study evaluates the potential of a deep learning method to classify one or several segments of the cardiac cycle and diagnose pathologies in ECG signals.

A sensorized needle guide for ultrasound assisted breast biopsy.

One in every eight women will get breast cancer during their lifetime. Therefore, the early diagnosis of the lesions is fundamental to improve the chances of recovery. To find breast cancers, breast screening using techniques such as mammography and ultrasound (US) imaging scans are often used. When a lesion is found, a breast biopsy is performed to extract a tissue sample for analysis. The breast biopsy is usually assisted by an US to help find the lesion and guide the needle to its location. However, the identification of the needle tip in US image is challenging, possibly resulting in puncture failures. In this paper, we intend to study the potential of a sensorized needle guide system that provides information about the needle angle and displacement in respect to the US probe. Laboratory tests were initially conducted to evaluate the accuracy of each sensor in controlled conditions. After, a practical experiment with the US probe, working as a proof of concept, was performed. The angle sensor showed a root mean square error (RMSE) of 0.48 degrees and the displacement sensor showed a RMSE of 0.26mm after being calibrated. For the US probe tests, the displacement sensor shows high errors in the range of 1.19mm to 2.05mm due to mechanical reasons. Overall, the proposed system showed its potential to be used to accurately estimate needle tip localization throughout breast biopsies guided by US, corroborating its potential clinical application. Clinical relevance - Potential for clinical application where precise needle localization in ultrasound image is required.

Metabolome fingerprints, performance and carcass quality of beef calves supplemented with antibiotic free additive.

The aim of this study was to investigate the effects of probiotics on pre-weaning performance, muscle, and fat deposition and serum metabolite profiles in male and female Senepol calves. Thirty new-born Senepol calves, 15 males and 15 females, were randomly allocated to the following treatments: CON a control group that received the basal creep feeding diet and PRO animals that received the basal diet with addition of 2 g/100 kg of body weight (BW) of probiotic. PRO supplementation did not change the DMI but increased average BW, final BW, ADG relative to animals fed CON. Additionally, PRO improved LMA and marbling. Regardless of the serum metabolite profile, the important metabolites for discriminating PRO and CON were glutamine, leucine, creatine, acetate, creatinine, arginine, glutamate, hippurate, glycerol, carnitine, lactate, carnosine, myo-inositol and histidine. According to gender, males had an overabundance of glutamine, glycerol, isoleucine, creatinine and glucose, whereas females had an overabundance of acetyl carnitine, glutamate and carnitine. In conclusion, the addition of PRO in the pre-weaning diet of calves increases performance, weight at weaning and muscle and fat deposition on the carcass, improving proteins and fatty acid metabolism, the immune system response and rumen development.

Metabolomic signature of genetic potential for muscularity in beef cattle.

The aim of this study was to investigate the serum and meat metabolomic changes according to the genetic potential for muscularity of non-castrated Nellore males and its association with phenotypic traits. Forty-eight non-castrated Nellore males were separated into two groups based on their genetic potential for post-weaning muscularity: high (HM) and low (LM). Selection for muscularity did not cause noticeable differences in the traits evaluated during the finishing phase and after slaughter. However, several metabolites in meat and serum, have changed according to the muscularity group. HM animals presented an over-abundance of glycerol, glutamine, choline, methylhistidine, betaine, creatinine and methionine in serum, compared with their LM counterparts. Similarly, the meat samples of HM animals were rich in glucose-6-phosphate, lactate, pyruvate, creatinine, betaine, choline, glycerol and arginine relative to LM bulls. Inosine monophosphate was the only metabolite over-abundant in LM animals. In conclusion, the genetic potential for post-weaning muscularity did not affect performance during the finishing phase, carcass traits and meat quality. However, multivariate analysis shows that the genetic potential of muscularity can be correlated with serum lipid and protein metabolites, and with energy metabolism in meat, providing a footprint of cattle muscularity metabolism.

Using TD-NMR relaxometry and 1D 1H NMR spectroscopy to evaluate aging of Nellore beef.

The aim of this study was to explore the use of TD-NMR relaxometry and 1H NMR spectroscopy-based for detecting differences in meat quality attributes. There was limited association between various TD-NMR signals and any physicochemical parameters of fresh and aged meat differing in tenderness ratings. Samples were then divided into three groups based on statistical changes in metabolite concentration. Group A samples possessed near linear increases in metabolite concentration over aging time; whereas samples assigned to Groups B and C were characterized by increases in metabolites that peaked between 7 and 14 days, and up to 14 days aging, respectively. 1H NMR spectroscopy discriminated meat quality using changes in metabolites reflective of glycolysis, the citric acid cycle, protein degradation, amino acid generation and purine metabolisms. These data suggest segregation of meat quality is possible using both NMR technologies but additional work is necessary to understand fully their utility in a commercial industry setting.

Characterization of chicken muscle disorders through metabolomics, pathway analysis, and water relaxometry: a pilot study.

Metabolite profiles of chicken breast extracts and water mobility in breasts were studied using proton nuclear magnetic resonance (1H-NMR) spectroscopy and time-domain NMR (TD-NMR) relaxometry, respectively, using normal breast (NB), and wooden breast (WB) and white striping (WS) myopathies in broilers. One thousand eight hundred sixty broilers were raised to commercial standards, receiving the same diets that were formulated as per the different growth stages. At 49 D of age, 200 animals were slaughtered following routine commercial procedures, and at 4 h postmortem, the whole breast (pectoralis major muscle) was removed and visually inspected by an experienced meat inspector who selected NB (without myopathies) and samples with the presence of WS and WB myopathies. Fifteen breasts (5 each of NB, WS, and WB) were analyzed through TD-NMR relaxometry, and samples of approximately 20 g were taken from each breast and frozen at -80°C for metabolite profiling through 1H-NMR spectroscopy. Multivariate statistical analysis was used to evaluate the effect on water relaxometry and metabolite profile in accordance with the presence and type of myopathy in the breast. 1H-NMR data showed that the metabolite profiles in WS and WB breasts were different from each other and from NB. This pilot study shows that myopathies appear to be related to hypoxia, connective tissue deposition, lower mitochondrial function, and greater oxidative stress compared with NB. The longitudinal and transverse relaxation time of the breasts determined by TD-NMR relaxometry was shorter for NB than that for WS and WB, indicating greater water mobility in breasts affected by myopathies. 1H-NMR spectroscopy can be used to differentiate the metabolism of WS, WB, and NB, and TD-NMR has the potential to be a fast, simple, and noninvasive method to distinguish NB from WB and WS. As a practical application, the metabolomic profile as per the occurrence of breast myopathies may be used for a better understanding of these issues, which opens a gap to mitigate the incidence and severity of WS and WB. In addition, the present study brings an opportunity for the development of a new and objective tool to classify the incidence of breast myopathies through TD-NMR relaxometry.

A climate-change vulnerability and adaptation assessment for Brazil's protected areas.

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km2 ) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km2 ), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.

Evaluación de la Vulnerabilidad y Adaptación al Cambio Climático de Áreas Protegidas en Brasil Resumen Brasil alberga la mayor extensión de ecosistemas tropicales dentro de áreas protegidas (AP), que protegen la biodiversidad y sustentan a poblaciones humanas tradicionales. Evaluamos la vulnerabilidad al cambio climático de 993 AP brasileñas terrestres y costeras-marinas mediante la combinación de indicadores de riesgo de cambio climático con indicadores de la resiliencia de AP (tamaño, cobertura de vegetación nativa y la probabilidad de transición en la vegetación como consecuencia del cambio climático). Esta combinación de indicadores permite la identificación de amplias rutas de adaptación al cambio climático. Diecisiete AP (20,611 km2 ) fueron altamente vulnerables y se localizaron principalmente en el Bosque Atlántico (7 AP), El Cerrado (6) y la Amazonía (4). Doscientos cincuenta y ocho AP (756,569 km2 ), localizadas principalmente en la Amazonía, tuvieron vulnerabilidad media. En la Amazonía y el oeste de El Cerrado, el severo cambio climático proyectado y la probabilidad de transición de vegetación dirigida por el clima incrementó la vulnerabilidad, a pesar del estado de conservación generalmente bueno de las AP. Más de 80% de las AP con vulnerabilidad alta o media son manejadas por poblaciones indígenas. Por lo tanto, además de los riesgos potenciales para la biodiversidad, también hay amenazas para el conocimiento tradicional y las formas de vida de la gente que habita en esas AP. En por lo menos 870 AP, principalmente en el Bosque Atlántico y la Amazonía, la adaptación podría suceder con poca o ninguna intervención debido al bajo riesgo de cambio climático, estatus de resiliencia alta, o ambos. Por lo menos 20 AP en el Bosque Atlántico, El Cerrado y la Amazonía deberían ser objetivo de intervenciones mayores (e.g., mejoramiento de la conectividad ecológica), dada su estatus de resiliencia baja. A pesar de que es un primer intento para vincular vulnerabilidad y adaptación en AP brasileñas, sugerimos que algunas de las AP identificadas como alta o moderadamente vulnerables se deben priorizar para probar posibles estrategias de adaptación en un futuro próximo.