Expressão dos genes nodC, nodW e nopP em Bradyrhizobium japonicum estirpe CPAC 15 avaliada por RT-qPCR.

Resumo O objetivo deste trabalho foi avaliar a expressão, por RT-qPCR, dos genes de nodulação nodC e nodW e do gene nopP da estirpe CPAC 15, que provavelmente atuam na infecção das raízes da soja. Foram realizados dois experimentos. No primeiro, a expressão dos genes foi avaliada nas células após a incubação com genisteína por 15 min, 1, 4 e 8 horas. Os resultados revelaram que os três genes apresentaram maior expressão imediatamente após o contato com o indutor (15 min). No segundo experimento, a bactéria foi cultivada na presença de indutores (genisteína ou exsudatos de sementes de soja) por 48 horas. A expressão dos três genes foi maior na presença de genisteína, com valores de expressão para nodC, nodW e nopP superiores ao controle. Os resultados obtidos confirmam a funcionalidade dos três genes na estirpe CPAC 15, com ênfase para o nopP, cuja funcionalidade em Bradyrhizobium japonicum foi descrita pela primeira vez. Termos para indexação: Glycine max, flavonoides, genes de nodulação, sistema de secreção tipo III

Principal component analysis for the detection and assessment of T-wave alternans

Abstract T wave alternans (TWA) is an electrophisiologic Introduction T-wave alternans is a prognostic indicator of preceding episodes of Torsade de Pointes life-threatening arrhythmia TWA appears in the electrocardiogram as a consistent fluctuation in the repolarization morphology on everyother beat basis. The computerized ECG analysis led to the discovery, and routine clinical assessment, of invisible to the naked eye microvolt TWA Heart rate alone appears to be the main factor of determining the onset of TWA during submaximal exercise stress tests A variety of algorithms for detecting and quantifying TWA have been proposed, employing techniques as spectral analysis, complex demodulation, zero-crossings counting in a series of correlation coefficients, KarhunenLoève transform, low-pass Capon filtering, Poincaré mapping, periodicity transforms, statistical tests, modified moving average, Laplacian likelihood ratio, etc. A review by Martínez and Olmos [8] highlights the need for methodological systematization effort in characterization and comparison of the different methods. A multilead approach to T-wave alternans detection combining PCA and the Laplacian likelihood ratio method is proposed by Monasterio and Martínez The aim of this study is to assess the detection and quantification of TWA, by the performance of two combined methods: Twave amplitude statistical analysis and PCA in the framework of PhysioNet/Computers in Cardiology 2008 Challenge [10]. Methods A set of 100 ECG recordings were selected and collected in the framework of the Challenge [10] in order to test different algorithms for the detection and the quantification of TWA. These recordings consisted of 16 with 2 leads, 12 with 3 leads and the remaining 72 recordings with 12 leads

Injury and Illness Rates During Ultratrail Running

This study aimed to describe injury/illness rates in ultratrail runners competing in a 65-km race to build a foundation for injury prevention and help race organizers to plan medical provision for these events. Prospectively transcribed medical records were analysed for 77 athletes at the end of the race. Number of injuries/illnesses per 1\u2009000 runners and per 1\u2009000-h run, overall injury/illness rate and 90% confidence intervals and rates for major and minor illnesses, musculoskeletal injuries, and skin disorders were analysed. A total of 132 injuries/illnesses were encountered during the race. The overall injuries/illnesses were 1.9 per runner and 13.1 per 1\u2009000-h run. Medical illnesses were the most prominent medical diagnoses encountered (50.3%), followed by musculoskeletal injuries (32.8%), and skin-related disorders (16.9%). Despite the ultra-long nature of the race, the majority of injuries/illnesses were minor in nature. Medical staff and runners should prepare to treat all types of injuries and illnesses, especially the fatigue arising throughout the course of an ultratrail run and injuries to the lower limbs. Future studies should attempt to systematically identify injury locations and mechanisms in order to better direct injury prevention strategies and plan more accurate medical care

Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project

During the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas. Methods: Data were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified. Results: We estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits. Conclusion: Implementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future

ECG Wavelet Analysis for the Detection of Gene Mutations in Patients with Brugada Syndrome

Abstract We applied wavelet transform (WT) Introduction The Brugada syndrome (BrS) is an inherited ion chanelopathy characterised by a typical electrocardiographic (ECG) pattern of J point and ST segment elevation in the right precordial leads and predisposition towards malignant ventricular arrhythmias Both depolarisation and repolarisation abnormalities contribute to the arrhythmia substrate and arrhythmia genesis in the BrS Wavelet analysis is a form of time-frequency transformation that has long been used in non-invasive electrocardiology for detection of characteristic ECG components, heart rate variability, analysis of ischaemic ST changes, ventricular repolarisation and others In this study, we hypothesised that continuous wavelet transform (WT) applied to the QRS and ST-T wave can help to identify carriers of SCN5A mutations among patients with the BrS. We analysed digital 15-lead ECGs previously recorded during positive diagnostic ajmaline test for BrS with simultaneous acquisition of the right precordial leads in both standard, as well as "high" electrode positions. Methods Study population and data acquisition The study population consisted of 26 patients (age 42.0±17.8 years, 13 men, 13 women, age 41.6±19.1 and 42.4±17.2, respectively, p=0.92 for men vs women) with suspected BrS who underwent diagnostic ajmaline test as part of their standard clinical management. All patients had either normal or non-diagnostic (i.e. not displaying type 1 Brugada ECG pattern) resting ECGs before the test. Details about this patient population have been partially described in previous publication

Dataset of manually measured QT intervals in the electrocardiogram

BACKGROUND: The QT interval and the QT dispersion are currently a subject of considerable interest. Cardiac repolarization delay is known to favor the development of arrhythmias. The QT dispersion, defined as the difference between the longest and the shortest QT intervals or as the standard deviation of the QT duration in the 12-lead ECG is assumed to be reliable predictor of cardiovascular mortality. The seventh annual PhysioNet/Computers in Cardiology Challenge, 2006 addresses a question of high clinical interest: Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations? METHOD: The PTB Diagnostic ECG Database was given to 4 cardiologists and 1 biomedical engineer for manual marking of QRS onsets and T-wave ends in 458 recordings. Each recording consisted of one selected beat in lead II, chosen visually to have minimum baseline shift, noise, and artifact. In cases where no T wave could be observed or its amplitude was very small, the referees were instructed to mark a 'group-T-wave end' taking into consideration leads with better manifested T wave. A modified Delphi approach was used, which included up to three rounds of measurements to obtain results closer to the median. RESULTS: A total amount of 2*5*548 Q-onsets and T-wave ends were manually marked during round 1. To obtain closer to the median results, 8.58 % of Q-onsets and 3.21 % of the T-wave ends had to be reviewed during round 2, and 1.50 % Q-onsets and 1.17 % T-wave ends in round 3. The mean and standard deviation of the differences between the values of the referees and the median after round 3 were 2.43 ± 0.96 ms for the Q-onset, and 7.43 ± 3.44 ms for the T-wave end. CONCLUSION: A fully accessible, on the Internet, dataset of manually measured Q-onsets and T-wave ends was created and presented in additional file: 1 (Table 4) with this article. Thus, an available standard can be used for the development of automated methods for the detection of Q-onsets, T-wave ends and for QT interval measurements

Solving Fuzzy Job-Shop Scheduling Problems with a Multiobjective Optimizer

International audienceIn real-world manufacturing environments, it is common to face a job-shop scheduling problem (JSP) with uncertainty. Among different sources of uncertainty, processing times uncertainty is the most common. In this paper, we investigate the use of a multiobjective genetic algorithm to address JSPs with uncertain durations. Uncertain durations in a JSP are expressed by means of triangular fuzzy numbers (TFNs). Instead of using expected values as in other work, we consider all vertices of the TFN representing the overall completion time. As a consequence, the proposed approach tries to obtain a schedule that optimizes the three component scheduling problems (corresponding to the lowest, most probable, and largest durations) all at the same time. In order to verify the quality of solutions found by the proposed approach, an experimental study was carried out across different benchmark instances. In all experiments, comparisons with previous approaches that are based on a single-objective genetic algorithm were also performed

A General Framework for Ordering Fuzzy Sets

Abstract. Orderings and rankings of fuzzy sets have turned out to play a funda-mental role in various disciplines. Throughout the previous 25 years, a lot a different approaches to this issue have been introduced, ranging from rather simple ones to quite exotic ones. The aim of this paper is to present a new framework for com-paring fuzzy sets with respect to a general class of fuzzy orderings. This approach includes several known techniques based on generalizing the crisp linear ordering of real numbers by means of the extension principle, however, in its general form, it is applicable to any fuzzy subsets of any kind of universe for which a fuzzy ordering is known – no matter whether linear or partial.