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Abstract This paper explores the Fourier decomposition method to approximate the decomposition of electrocardiogram (ECG) signals into their component waveforms, such as the QRS-complex and T-wave. We compute expansion coefficients using the $$\ell _1$$ ℓ 1 Fourier transform and the traditional $$\ell _2$$ ℓ 2 Fourier transform. Numerical examples are presented, and the analysis focuses on ECG signals as a real-world application, comparing the performance of the $$\ell _1$$ ℓ 1 and $$\ell _2$$ ℓ 2 Fourier transforms. Our results demonstrate that the $$\ell _1$$ ℓ 1 Fourier transform significantly enhances the separation of ECG signal components, such as the QRS-complex and T-wave. This improvement is attributed to a notable reduction in the Gibbs phenomenon introduced by the Fourier-series expansion when using the $$\ell _1$$ ℓ 1 Fourier transform, as opposed to the traditional $$\ell _2$$ ℓ 2 Fourier transform.

BackgroundElectrical remodeling has been linked to the progression and recurrence of atrial fibrillation (AF) after catheter ablation (CA). Substrate mapping based solely on a voltage amplitude electrogram (EGM) does not provide a comprehensive understanding of the left atrial (LA) disease. The aim of this study is to assess left atrial spatial entropy (LASE) from voltage maps routinely obtained during AF ablation to further characterize the LA substrate.Materials and MethodsHigh-density electroanatomic maps (EAMs) of 27 patients with paroxysmal or persistent AF undergoing routine CA were prospectively collected. Computational post-processing was performed on the voltage maps. Using the Shannon entropy model, the probability distribution of the amplitude range values associated with each point of the map was used to measure LASE. Finally, correlations between LASE and clinical and electrophysiological characteristics of AF were explored.ResultsLASE differentiated between patients with paroxysmal and persistent AF (6.45 ± 0.41 vs. 5.87 ± 0.53; p = 0.028) and patients with normal and abnormal LA substrate (6.42 ± 0.42 vs. 5.87 ± 0.56; p = 0.043), independent of the basal rhythm during EM acquisition (6.33 ± 0.41 vs. 6.11 ± 0.63; p = 0.619). Accordance between LASE and EAMs was assessed by ROC analysis (AUC: 0.81; C.I.: 0.62–0.99; Youden index: 6.06; sensitivity: 80%; and specificity: 80%). Patients with the lowest LASE reported AF recurrence at the follow-up.ConclusionLASE may play a role in the further characterization of the LA substrate and the type of AF, independent of basal rhythm.

Abstract Background Nutrition exerts a fundamental role in the prevention of obesity (OB). The aim of this study was to assess the extent to which well recognized risk factors for early OB can be associated to overweight (OW) or OB under a standardized nutritional approach and surveillance in toddlers. Methods The eligible population was represented by 676 toddlers aged 24–36 months, assigned to 18 primary care pediatricians trained on nutritional issues who shared a standardized nutritional approach. Six-hundred-twenty-nine children (333 boys), mean age 27.8 ± 4.2 months were effectively included in this observational study. Parents received nutritional advice with particular emphasis to proteins and sugar composition supported by leaflets and reinforced at each visit. Body mass index was assessed at the age of 24–36 months. The following individual and family risk factors were considered: gestational age, birth weight, eutocic/caesarean delivery, milk feeding history, household smoking or antibiotics exposure, parents’ weight, height and educational level. Prevalence of OW/OB was compared to a group of 742 toddlers (373 boys) under usual care. Results Under a standardized nutritional counselling, 28.1% toddlers were classified as OW/OB compared to 36.9% toddlers under usual care (p = 0.005). In unadjusted models, parental OW/OB was significantly associated to OW/OB in toddlers (p

Sample entropy embeds time series into m-dimensional spaces and estimates entropy based on the distances between points in these spaces. However, when samples can be considered as missing or invalid, defining distance in the embedding space becomes problematic. Preprocessing techniques, such as deletion or interpolation, can be employed as a solution, producing time series without missing or invalid values. While deletion ignores missing values, interpolation replaces them using approximations based on neighboring points. This paper proposes a novel approach for the computation of sample entropy when values are considered as missing or invalid. The proposed algorithm accommodates points in the m-dimensional space and handles them there. A theoretical and experimental comparison of the proposed algorithm with deletion and interpolation demonstrates several advantages over these other two approaches. Notably, the deviation of the expected sample entropy value for the proposed methodology consistently proves to be lowest one.

COVID-19 is an infectious disease that has greatly affected worldwide healthcare systems, due to the high number of cases and deaths. As COVID-19 patients may develop cardiac comorbidities that can be potentially fatal, electrocardiographic monitoring can be crucial. This work aims to identify electrocardiographic and vectorcardiographic patterns that may be related to mortality in COVID-19, with the application of the Advanced Repeated Structuring and Learning Procedure (AdvRS&LP). The procedure was applied to data from the “automatic computation of cardiovascular arrhythmic risk from electrocardiographic data of COVID-19 patients” (COVIDSQUARED) project to obtain neural networks (NNs) that, through 254 electrocardiographic and vectorcardiographic features, could discriminate between COVID-19 survivors and deaths. The NNs were validated by a five-fold cross-validation procedure and assessed in terms of the area under the curve (AUC) of the receiver operating characteristic. The features’ contribution to the classification was evaluated through the Local-Interpretable Model-Agnostic Explanations (LIME) algorithm. The obtained NNs properly discriminated between COVID-19 survivors and deaths (AUC = 84.31 ± 2.58% on hold-out testing datasets); the classification was mainly affected by the electrocardiographic-interval-related features, thus suggesting that changes in the duration of cardiac electrical activity might be related to mortality in COVID-19 cases.

BackgroundSecure attachment reflects caregiver-child relationship in which the caregiver is responsive when support and comforting are needed by the child. This pattern of bond has an important buffering role in the response to stress by the reduction of the negative experience and its associated physiological response. Disruption of the physiological stress system is thought to be a central mechanism by which early care impacts children. Early life stress causes cellular and molecular changes in brain regions associated with cognitive functions that are fundamental for early learning.MethodsThe association between attachment, cortisol response before and after the Strange Situation Experiment, and neurodevelopment was examined in a sample of 107 preschoolers at age three. Also, the predictive effect of cortisol reactivity and attachment on telomere length at age seven was investigated in a followed-up sample of 77 children.ResultsChildren with insecure attachment had higher cortisol secretion and poorer neurodevelopmental skills at age three. A significant cortisol change was observed across the experiment with non-significant interaction with attachment. The attachment and neurodevelopment association was not mediated by cortisol secretion. Preschoolers’ attachment and cortisol did not associate nor interacted to predict telomere length at age seven.ConclusionThese findings add evidence to the detrimental effects of insecure attachment as an aggravator of the physiological response to stress and poorer neurodevelopment during the preschool period. Although attachment and cortisol were not predictive of telomere length, intervention policies that promote secure attachment are more likely to positively echo on several health domains.

Background: Atrial fibrillation (AF) is the most common supraventricular arrhythmia, characterized by disorganized atrial electrical activity, maintained by localized arrhythmogenic atrial drivers. Pulmonary vein isolation (PVI) allows to exclude PV-related drivers. However, PVI is less effective in patients with additional extra-PV arrhythmogenic drivers. Objectives: To discriminate whether AF drivers are located near the PVs vs extra-PV regions using the noninvasive 12-lead electrocardiogram (ECG) in a computational and clinical framework, and to computationally predict the acute success of PVI in these cohorts of data. Methods: AF drivers were induced in 2 computerized atrial models and combined with 8 torso models, resulting in 1128 12-lead ECGs (80 ECGs with AF drivers located in the PVs and 1048 in extra-PV areas). A total of 103 features were extracted from the signals. Binary decision tree classifier was trained on the simulated data and evaluated using hold-out cross-validation. The PVs were subsequently isolated in the models to assess PVI success. Finally, the classifier was tested on a clinical dataset (46 patients: 23 PV-dependent AF and 23 with additional extra-PV sources). Results: The classifier yielded 82.6% specificity and 73.9% sensitivity for detecting PV drivers on the clinical data. Consistency analysis on the 46 patients resulted in 93.5% results match. Applying PVI on the simulated AF cases terminated AF in 100% of the cases in the PV class. Conclusion: Machine learning–based classification of 12-lead-ECG allows discrimination between patients with PV drivers vs those with extra-PV drivers of AF. The novel algorithm may aid to identify patients with high acute success rates to PVI.

Many popular entropy definitions for signals, including approximate and sample entropy, are based on the idea of embedding the time series into an m-dimensional space, aiming to detect complex, deeper and more informative relationships among samples. However, for both approximate and sample entropy, the high computational cost is a severe limitation. Especially when large amounts of data are processed, or when parameter tuning is employed premising a large number of executions, the necessity of fast computation algorithms becomes urgent. In the past, our research team proposed fast algorithms for sample, approximate and bubble entropy. In the general case, the bucket-assisted algorithm was the one presenting the lowest execution times. In this paper, we exploit the opportunities given by the multithreading technology to further reduce the computation time. Without special requirements in hardware, since today even our cost-effective home computers support multithreading, the computation of entropy definitions can be significantly accelerated. The aim of this paper is threefold: (a) to extend the bucket-assisted algorithm for multithreaded processors, (b) to present updated execution times for the bucket-assisted algorithm since the achievements in hardware and compiler technology affect both execution times and gain, and (c) to provide a Python library which wraps fast C implementations capable of running in parallel on multithreaded processors.

AI techniques have recently been put under the spotlight for analyzing electrocardiograms (ECGs). However, the performance of AI-based models relies on the accumulation of large-scale labeled datasets, which is challenging. To increase the performance of AI-based models, data augmentation (DA) strategies have been developed recently. The study presented a comprehensive systematic literature review of DA for ECG signals. We conducted a systematic search and categorized the selected documents by AI application, number of leads involved, DA method, classifier, performance improvements after DA, and datasets employed. With such information, this study provided a better understanding of the potential of ECG augmentation in enhancing the performance of AI-based ECG applications. This study adhered to the rigorous PRISMA guidelines for systematic reviews. To ensure comprehensive coverage, publications between 2013 and 2023 were searched across multiple databases, including IEEE Explore, PubMed, and Web of Science. The records were meticulously reviewed to determine their relevance to the study’s objective, and those that met the inclusion criteria were selected for further analysis. Consequently, 119 papers were deemed relevant for further review. Overall, this study shed light on the potential of DA to advance the field of ECG diagnosis and monitoring.

AimsAtrial fibrillation (AF) and heart failure often co-exist. Early identification of AF patients at risk for AF-induced heart failure (AF-HF) is desirable to reduce both morbidity and mortality as well as health care costs. We aimed to leverage the characteristics of beat-to-beat-patterns in AF to prospectively discriminate AF patients with and without AF-HF.MethodsA dataset of 10,234 5-min length RR-interval time series derived from 26 AF-HF patients and 26 control patients was extracted from single-lead Holter-ECGs. A total of 14 features were extracted, and the most informative features were selected. Then, a decision tree classifier with 5-fold cross-validation was trained, validated, and tested on the dataset randomly split. The derived algorithm was then tested on 2,261 5-min segments from six AF-HF and six control patients and validated for various time segments.ResultsThe algorithm based on the spectral entropy of the RR-intervals, the mean value of the relative RR-interval, and the root mean square of successive differences of the relative RR-interval yielded an accuracy of 73.5%, specificity of 91.4%, sensitivity of 64.7%, and PPV of 87.0% to correctly stratify segments to AF-HF. Considering the majority vote of the segments of each patient, 10/12 patients (83.33%) were correctly classified.ConclusionBeat-to-beat-analysis using a machine learning classifier identifies patients with AF-induced heart failure with clinically relevant diagnostic properties. Application of this algorithm in routine care may improve early identification of patients at risk for AF-induced cardiomyopathy and improve the yield of targeted clinical follow-up.

During labor, uterine contractions trigger the response of the autonomic nervous system (ANS) of the fetus, producing sawtooth-like decelerations in the fetal heart rate (FHR) series. Under chronic hypoxia, ANS is known to regulate FHR differently with respect to healthy fetuses. In this study, we hypothesized that such different ANS regulation might also lead to a change in the FHR deceleration morphology. The hypothesis was tested in an animal model comprising nine normoxic and five chronically hypoxic fetuses that underwent a protocol of umbilical cord occlusions (UCOs). Deceleration morphologies in the fetal inter-beat time interval (FRR) series were modeled using a trapezoid with four parameters, i.e., baseline b, deceleration depth a, UCO response time τu and recovery time τr. Comparing normoxic and hypoxic sheep, we found a clear difference for τu (24.8±9.4 vs. 39.8±9.7 s; p < 0.05), a (268.1±109.5 vs. 373.0±46.0 ms; p < 0.1) and Δτ = τu − τr (13.2±6.9 vs. 23.9±7.5 s; p < 0.05). Therefore, the animal model supported the hypothesis that hypoxic fetuses have a longer response time τu and larger asymmetry Δτ as a response to UCOs. Assessing these morphological parameters during labor is challenging due to non-stationarity, phase desynchronization and noise. For this reason, in the second part of the study, we quantified whether acceleration capacity (AC), deceleration capacity (DC), and deceleration reserve (DR), computed through Phase-Rectified Signal Averaging (PRSA, known to be robust to noise), were correlated with the morphological parameters. DC, AC and DR were correlated with τu, τr and Δτ for a wide range of the PRSA parameter T (Pearson's correlation ρ > 0.8, p < 0.05). In conclusion, deceleration morphologies have been found to differ between normoxic and hypoxic sheep fetuses during UCOs. The same difference can be assessed through PRSA based parameters, further motivating future investigations on the translational potential of this methodology on human data.

Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios.

ABSTRACT Histological analysis of bleached samples of Siderastrea stellata Verrill, 1868, with white plague disease and with alteration in the color pattern, revealed drastic tissue and cellular disturbances, such as lysis of the external epithelium, hyperplasia of gastrodermis, apoptosis of epithelial cells and zooxanthellae, and degradation of mesenteric filaments and reproductive cells. Fungal hyphae, diatoms, and cyanobacteria were present in diseased samples and colonies with alteration in the color pattern. Furthermore, bleached and diseased samples showed significant reductions in the number of zooxanthellae per 100 µm2 of gastrodermis and significant reductions in the diameters and volumes of stage V oocytes. We found that bleaching events, diseases, and colonies with alteration in the color pattern promoted degradation of reproductive cells, resulting in the consequent interruption of the reproduction of the coral S. stellata, which is one of the most common Brazilian coral species. The implications of these indirect effects of bleaching, disease, and changes in coral color patterns in the population dynamics of Brazilian reefs are discussed.

Introduction Best practice approaches for addressing COVID-19-related psychological distress among young people (

A highly aggressive necrotizing disease affecting the zooantharian Palythoa caribaeorum was studied on coastal reefs in northeastern Brazil during March and April of 2008. Approximately 87% of the colonies at each locality showed wounds ranging from 27 cm to 1200 cm long and from 12 to 320 cm wide. This disease initiates with the darkening of the polyps, followed by the appearance of a rapidly enlarging wound that decomposes colony tissues and eventually exposes the substrate. The exposed areas are subsequently colonized by macroalgae, Zoanthus sociatus, and other benthic organisms. The necrotized areas were dark-colored and expelled fetid odors. Although extremely aggressive, complete mortality of the colonies was not observed. Surviving fragments recomposed the colonies within 6 to 9 months. Recurrences of the disease were in the summer of 2008 and from February/2013 to March/2014. During the study period, we found various colonies having black-spots (early stage of necrotizing disease), suggesting stress conditions. Zooxanthellae densities in those black-spots were always lower than in apparently healthy colonies, with reductions of up to 74%. More than one environmental variable seems to influence the zooxanthellae densities significantly, but there is no evidence of any association with abnormally high water temperature, as thermal variations in the study area were within their normal range. Histological analysis showed losses of tissue organization in colonies with black-spots and necrotizing components with hypertrophy and cell apoptosis of the gastrodermal cells; apoptosis of zooxanthellae and damage in completes mesenteries. All these features showed an inflammatory response to necrosis disease.

Aims: Bubble entropy (bEn) is an entropy metric with a limited dependence on parameters. bEn does not directly quantify the conditional entropy of the series, but it assesses the change in entropy of the ordering of portions of its samples of length m, when adding an extra element. The analytical formulation of bEn for autoregressive (AR) processes shows that, for this class of processes, the relation between the first autocorrelation coefficient and bEn changes for odd and even values of m. While this is not an issue, per se, it triggered ideas for further investigation. Methods: Using theoretical considerations on the expected values for AR processes, we examined a two-steps-ahead estimator of bEn, which considered the cost of ordering two additional samples. We first compared it with the original bEn estimator on a simulated series. Then, we tested it on real heart rate variability (HRV) data. Results: The experiments showed that both examined alternatives showed comparable discriminating power. However, for values of 10

Elite performance in team sports attracts the attention of the general public. In particular, the best players became incredibly skilled and physically powerful, which is a fact that potentiates the delivery of a product that is considered attractive, exciting, and competitive. Not surprisingly, this is a very valuable product from an economic and social standpoint; thus, all sports professionals are extremely interested in developing new procedures to improve their sports performance. Furthermore, the great interests of the various stakeholders (owners, chief executive officers (CEOs), agents, fans, media, coaches, players, families, and friends) are one of the main reasons for this development under the sports science umbrella and the accompanying sports industry. All their personal performances should be coordinated and put into practice by the sports team. In this scientific and applied study, we primarily dealt with the individual treatment of players in order to improve their personal performance and, consequently, the team’s sporting performance.

Mixotrophic cultivation of microalgae provides a very promising alternative for producing carbohydrate-rich biomass to convert into bioethanol and value-added biocompounds, such as vitamins, pigments, proteins, lipids and antioxidant compounds. Spirulina platensis may present high yields of biomass and carbohydrates when it is grown under mixotrophic conditions using cheese whey. However, there are no previous studies evaluating the influence of this culture system on the profile of fatty acids or antioxidant compounds of this species, which are extremely important for food and pharmaceutical applications and would add value to the cultivation process. S. platensis presented higher specific growth rates, biomass productivity and carbohydrate content under mixotrophic conditions; however, the antioxidant capacity and the protein and lipid content were lower than that of the autotrophic culture. The maximum biomass yield was 2.98 ±0.07 g/L in growth medium with 5.0% whey. The phenolic compound concentration was the same for the biomass obtained under autotrophic and mixotrophic conditions with 2.5% and 5.0% whey. The phenolic compound concentrations showed no significant differences except for that in the growth medium with 10.0% whey, which presented an average value of 22.37±0.14 mg gallic acid/g. Mixotrophic cultivation of S. platensis using whey can be considered a viable alternative to reduce the costs of producing S. platensis biomass and carbohydrates, shorten cultivation time and produce carbohydrates, as it does not require adding expensive chemical nutrients to the growth medium and also takes advantage of cheese whey, an adverse dairy industry byproduct.

Wearable sensors play a significant role for monitoring the functional ability of the elderly and in general, promoting active ageing. One of the relevant variables to be tracked is the number of stair steps (single stair steps) performed daily, which is more challenging than counting flight of stairs and detecting stair climbing. In this study, we proposed a minimal complexity algorithm composed of a hierarchical classifier and a linear model to estimate the number of stair steps performed during everyday activities. The algorithm was calibrated on accelerometer and barometer recordings measured using a sensor platform worn at the wrist from 20 healthy subjects. It was then tested on 10 older people, specifically enrolled for the study. The algorithm was then compared with other three state-of-the-art methods, which used the accelerometer, the barometer or both. The experiments showed the good performance of our algorithm (stair step counting error: 13.8%), comparable with the best state-of-the-art (p > 0.05), but using a lower computational load and model complexity. Finally, the algorithm was successfully implemented in a low-power smartwatch prototype with a memory footprint of about 4 kB.

In December of 2019, there was an outbreak of a severe acute respiratory syndrome caused by the Coronavirus 2 (SARS-CoV-2 or COVID-19) in China. The virus rapidly spread into the whole World causing an unprecedented pandemic and forcing governments to impose a global quarantine, entering an extreme unknown situation. The organizational consequences of quarantine/isolation are: absence of organized training and competition, lack of communication among athletes and coaches, inability to move freely, lack of adequate sunlight exposure, inappropriate training conditions. Based on the current scientific, we strongly recommend encouraging the athlete to reset their mindset to understand quarantine as an opportunity for development, organizing appropriate guidance, educating and encourage athletes to apply appropriate preventive behavior and hygiene measures to promote immunity and ensuring good living isolation conditions. The athlete’s living space should be equipped with cardio and resistance training equipment (portable bicycle or rowing ergometer). Some forms of body mass resistance circuit-based training could promote aerobic adaptation. Sports skills training should be organized based on the athlete’s needs. Personalized conditioning training should be carried out with emphasis on neuromuscular performance. Athletes should also be educated about nutrition (Vitamin D and proteins) and hydration. Strategies should be developed to control body composition. Mental fatigue should be anticipated and mental controlled. Adequate methods of recovery should be provided. Daily monitoring should be established. This is an ideal situation in which to rethink personal life, understanding the situation, that can be promoted in these difficult times that affect practically the whole world.

RESUMO A zonação dos ambientes recifais permite avaliar possíveis impactos antropogênicos e subsidiar futuros planos de manejo. Este estudo teve por objetivo levantar as espécies bentônicas (com ênfase nos cnidários) no topo dos recifes emersos da Área de Proteção Ambiental (APA) Costa dos Corais, bem como calcular e comparar sua porcentagem de cobertura. Foram realizados transectos em linha contínuos, em seis praias da referida APA, em três regiões da plataforma recifal e com quatro réplicas para cada região. Os resultados mostraram maior cobertura de algas em todas as praias, com exceção de Tamandaré/PE. Entre os cnidários os zoantídeos predominaram, mas se registrou, também, a ocorrência dos corais escleractíneos Siderastrea stellata e Favia gravida. Outros organismos encontrados foram os poríferos, o molusco Brachidontes exustus e o equinodermo Echinometra lucunter. Foi observada ocorrência de branqueamento nas duas espécies de coral encontradas (em todas as praias visitadas) e no zoantídeo Palythoa caribaeorum. De forma geral, os organismos registrados se caracterizaram pela resistência às condições instáveis da plataforma recifal. Além disso, as análises de agrupamento mostraram que fatores como o aporte de rios e o impacto antrópico exercem substancial influência na caracterização da cobertura bentônica da plataforma recifal, sobrepondo-se até mesmo à proximidade geográfica de áreas.

We report here the occurrence of seasonal changes in the pigmentation of colonies of Siderastrea spp. during bleaching events on coastal reefs in northeastern Brazil. Bleached affected almost 50% of coral colonies analyzed in Cabo Branco reefs (Paraiba state) in the summer of 2005. The same phenomenon was detected along various coastal reefs in northeastern Brazil during the summer of 2007 and 2008. These events were seasonal, and began with the emergence of pale colonies that became pale-pink and then purple during the rainy months. The patterns and intensity of colonies pigmentation changes varied with the studied sites. The decrease in zooxanthellae density and chlorophyll-a content was quantified in the colonies with their pigmentation pattern altered (bleaching). Microbiological analyses revealed higher densities of bacteria in pink colonies (bleached) as compared to brown colonies (normal). Environmental disturbances may lead to the pigmentation changes in Siderastrea spp., but the immediate causes of this phenomenon are not clear and require further investigations.

Injuries caused by venomous animals reported by the agricultural workers from the municipality of Cuité, Curimataú region of Paraiba State, Northeast of Brazil, and the practices of folk medicine which they use to treat these cases were studied in this work from June to August 2010. The farmers studied aged from 11 to 90 years. The number of people who reported cases of injury by these animals in their families was high (89.3%). Scorpions, wasps, bees and snakes were the most cited and the extremities of the body (hands, feet, legs and head) were the most affected. The practice of folk medicine to treat these injuries includes various procedures ranging from ritualistic treatments, use of animals or parts of them, and some herbal preparations. The folk treatment was reported as effective by most of the workers injured (63.9%). Body parts of dead snakes are used in various zootherapic treatments. In the imaginary of the agricultural workers the venomous animals are considered hazardous (48.7%) or disgusting (11.3%), and several parts of such animals as the rattle, bee sting or snake leather are used as amulet. Several legends have also been reported about snakes, scorpions and bees. The need for educational activities that aim to clarify these workers about the dangers of such practices is urgent.

Background: Epidemiologic evidences suggest a strong association between low birth weight and some diseases in adult life ( hypertension, diabetes, cardiovascular diseases).Aim of this study was to evaluate the obesity/overweight prevalence in a population of children born small for gestation age, SGA children 400, 208 males and 192 females compared to a population of children born appropriate for gestational age 6818 AGA children, 3502 males and 3316 females, during childhood. Our intention was also to build the natural history of weight gain during prepubertal age in children born SGA and AGA. Design and Methods: Observational prospective longitudinal study. We followed our patients from January2001 up to December 2010; weight, height and body mass index (BMI) were evaluated in all the SGA and AGA children. BMI z -score range for defining overweight and obesity was, respectively, 1.13 to 1.7 and >1.7 according to CDC growth charts. Results: In transversal evaluation , we prove that 10-year-old SGA females are twice obese and more overweight compared to equal age AGA females. In longitudinal evaluation , we highlight different observations: SGA children obese at 2 years are still obese at 10 years; the number of obese SGA children increases gradually until the age of 10; AGA children, appear to be less obese than SGA children at 10 years. Conclusion: SGA males and females are more obese at 5 and 10 years compared to the AGA population. Primary care pediatricians, through early detection of the children at risk, can carry out an effective obesity prevention project in SGA children.

The aim of this study was to test, in delayed antibiotic strategy, if the usages of a point-of-care leukocyte count would significantly decrease the prescription rate of antibiotics for children with nonspecific upper respiratory tract infections. A prospective clinical trial was performed in 23 primary care pediatric doctors’ offices on children with nonspecific upper respiratory tract infection with fever for at least 48 hours. The children were randomized into 2 groups: one using a point-of-care white blood cell (WBC) count as guidance and the other prescribing antibiotics to all children, according to delayed antibiotics prescription strategy. A total of 792 patients participated. In the WBC group (n = 437), 56 patients had WBC >15 000/mm 3 and received antibiotics. At follow-up, an additional 44 children received antibiotics. In the control group (n = 355), antibiotics were prescribed to all children. The reduction of antibiotic usage was 77% between the groups. The decrease in antibiotic usage gave no influence on recovery, complications, or other medical outcome.

The seasonal dynamics of cell density and photosynthetic pigment contents of the zooxanthellae hosted by Montastrea cavernosa were investigated on coastal reefs off Picãozinho (06º42'05"/07º07'30"S and 34º48'37"/34º50'00" W), Northeast Brazil between September 1999 and 2000. A distinct pattern of these parameters was found: cell numbers were greater during the rainy season (autumn/winter) while photosynthetic pigments were greater during the dry season (summer). Both parameters showed drastic reductions during heavy rains (June and July 1999). We speculate that this pattern is largely influenced by the rain cycles which, owing to their magnitude and frequency, affect the water clarity and the seasonal physiological condition of the cells.A dinâmica sazonal na densidade de células e na concentração de pigmentos fotossintetizantes das zooxantelas de Montastrea cavernosa foram analisados no período setembro/1999 a setembro/2000 nos Recifes do Picãozinho (06º42'05"/07º07'30" S e 34º48'37"/34º50'00" W), Nordeste do Brasil. Verificou-se que existe um padrão distinto entre estes parâmetros, com maior quantidade de células no período chuvoso e maior concentração de pigmentos fotossintetizantes na época de estiagem. Ambos os parâmetros apresentaram, no entanto, uma nítida redução em seus valores nos meses de maiores índices pluviométricos (junho e julho /1999). Especulamos que tal fato deve estar relacionado com o regime de chuvas que pode variar em magnitude e freqüência, afetando a qualidade ótica da água e o estado fisiológico das células.

Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regularity/complexity of a time series. On the other hand, it is a computationally expensive method which may require a large amount of time when used in long series or with a large number of signals. The computationally intensive part is the similarity check between points in m dimensional space. In this paper, we propose new algorithms or extend already proposed ones, aiming to compute Sample Entropy quickly. All algorithms return exactly the same value for Sample Entropy, and no approximation techniques are used. We compare and evaluate them using cardiac inter-beat (RR) time series. We investigate three algorithms. The first one is an extension of the k d -trees algorithm, customized for Sample Entropy. The second one is an extension of an algorithm initially proposed for Approximate Entropy, again customized for Sample Entropy, but also improved to present even faster results. The last one is a completely new algorithm, presenting the fastest execution times for specific values of m, r, time series length, and signal characteristics. These algorithms are compared with the straightforward implementation, directly resulting from the definition of Sample Entropy, in order to give a clear image of the speedups achieved. All algorithms assume the classical approach to the metric, in which the maximum norm is used. The key idea of the two last suggested algorithms is to avoid unnecessary comparisons by detecting them early. We use the term unnecessary to refer to those comparisons for which we know a priori that they will fail at the similarity check. The number of avoided comparisons is proved to be very large, resulting in an analogous large reduction of execution time, making them the fastest algorithms available today for the computation of Sample Entropy.

The knee is the weight-bearing joint most commonly associated with sports injuries, and therefore is most at risk of developing degenerative changes, including osteoarthritis. Skyrunners can be considered to be at risk of developing symptoms of post-traumatic osteoarthritis due to downhill running.The aim of this study was to analyze the health of the knee joints of a large group of these athletes via a specific self-report questionnaire.This study was carried out by asking the participants of seven official Skyraces (22.4±3.1 km length; 1596±393 m elevation) to fill out a questionnaire. Information regarding age, sex, downhill elevation (m) during training and competitions over the last month, and history of previous knee injury was also collected before the participants filled out the Knee injury and Osteoarthritis Outcome Score (KOOS), which is a reliable and validated instrument designed to assess patients' opinions about their knees and associated problems that can result in post-traumatic osteoarthritis. Athletes were divided into six age groups (from 17 to 70 years) and 12 groups based on the downhill gradient they had covered over the last month (from 1,000 to 40,000 m).Six hundred twenty-one questionnaires were collected from 45% of the participants in the seven races. Multivariate analysis revealed that self-reported KOOS scores were unrelated to age, sex and monthly downhill gradient. Only 74 (12%) of the participants reported previous knee injuries. Significant differences in the five subscales of the KOOS were found between skyrunners with and without previous knee injuries (P

BACKGROUND: Fetal heart rate (FHR) variability is an indirect index of fetal autonomic nervous system (ANS) integrity. FHR variability analysis in labor fails to detect early hypoxia and acidemia. Phase-rectified signal averaging (PRSA) is a new method of complex biological signals analysis that is more resistant to non-stationarities, signal loss and artifacts. It quantifies the average cardiac acceleration and deceleration (AC/DC) capacity. OBJECTIVE: The aims of the study were: (1) to investigate AC/DC in ovine fetuses exposed to acute hypoxic-acidemic insult; (2) to explore the relation between AC/DC and acid-base balance; and (3) to evaluate the influence of FHR decelerations and specific PRSA parameters on AC/DC computation. METHODS: Repetitive umbilical cord occlusions (UCOs) were applied in 9 pregnant near-term sheep to obtain three phases of MILD, MODERATE, and SEVERE hypoxic-acidemic insult. Acid-base balance was sampled and fetal ECGs continuously recorded. AC/DC were calculated: (1) for a spectrum of T values (T = 1÷50 beats; the parameter limits the range of oscillations detected by PRSA); (2) on entire series of fetal RR intervals or on "stable" series that excluded FHR decelerations caused by UCOs. RESULTS: AC and DC progressively increased with UCOs phases (MILD vs. MODERATE and MODERATE vs. SEVERE, p

This paper reports the results obtained from studies on the estuarine phytoplankton of the Paraíba do Norte River in northeastern Brazil. Surface and near-bottom samples were taken at four stations numbered seawards, during high and low tides from September 1978 to September 1979. A total of 139 phytoplankters were encountered. Diatoms and dinoflagellates showed highest diversity in most saline areas. Typical freshwater organisms were restricted to stations I and II where salinity was more reduced. Maximum cell densities were: 11,256,000 cells/1, 4,380,000 cells/1, 1,276,000 cells/1 and 1,035,000 cells/1, for stations I, II, III and IV, respectively. Sewage enrichments were probably responsible for the greatest values of the first two stations. However, in these stations the turbidity reduces light penetration, limiting phytoplankton growth particularly during the rainy season. The phytoflagellates (maximum of up to 4,874,000 cells/1) and the diatoms Thalassiosira spp (maximum of up to 9,262,000 cells/1) were dominant during the annual cycle. Other important taxa were Navicula spp, Cylindrotheca closterium, Paralia sulcata, Thalassionema nitzschioides and the dinoflagellate Protoperidinium spp. Seasonal variations of phytoplankton densities, dissolved oxygen, phosphate, water transparency, temperature, salinity and suspended material are also presented.

Seven species of hyaline Tintinnina were obtained from plankton samples collected near the coastal reefs of Ponta do Seixas (Lat. 7º09'16"S, Long. 34º4735"W), Northeastern Brazil, from April 1981 to May 1982 and from April 1983 to May 1984: Amphorellopsis acuta (Schmidt, 1901), Dadayiella ganymedes (Entz Sr., 1884), Epiplocyloides reticulata (Ostenfeld & Schmidt, 1901), Eutintinnus tubulosus (Ostenfeld, 1899), Favella ehrenbergi (Claparède & Lachmann, 1858), Metacylis mereschkowskyi Kofoid & Campbell, 1929 and M. perspicax (Hada, 1938). The most frequent and abundant species were M. mereschkowskyi and F. ehrenbergi. Except/).ganymedes, E. reticulata and F. ehrenbergi all species are new records from Brazil. Metacylis perspicax is also the seventh world register. For all species we provide description, drawings, measurements, seasonal occurrence, world distribution and some systematic comments.