Publications by authors named "A E Bittar"

Background: The misfolding and aggregation of the tau protein into neurofibrillary tangles constitute a central feature of tauopathies. Traumatic brain injury (TBI) has emerged as a potential risk factor, triggering the onset and progression of tauopathies. Our previous research revealed distinct polymorphisms in soluble tau oligomers originating from single versus repetitive mild TBIs.

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Objectives: This study aimed to compare the success of selective removal to soft dentine (SRSD) with or without calcium silicate (CS) and selective removal to firm dentine (SRFD) in permanent dentition.

Materials And Methods: Between November 2018 and March 2020, 165 posterior deep caries lesions in 134 patients were included in the study and randomly assigned into test (n = 101) and control (n = 64) groups. The control group (n = 46) received the treatment of SRFD with CS, while the test group was further randomized into two groups to receive SRSD with CS (n = 45) and SRSD without CS (n = 45).

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Article Synopsis
  • The study aimed to assess the effectiveness of a quantitative light-induced fluorescence device (QrayCam Pro) in detecting and determining the severity of caries in teeth.
  • It involved 120 teeth from 60 patients and utilized established scoring systems, along with bite-wing radiography to evaluate carious lesions.
  • Results showed high sensitivity (84-88.6%) and perfect specificity (100%) for the QrayCam Pro, indicating it could be a valuable tool for caries detection and assessment.
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Understanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning frameworks, and demonstrate that end-to-end gradient descent training leads to the emergence of neural oscillations in the central spiking neural network. Significant cross-frequency couplings, indicative of these oscillations, are measured within and across network layers during speech processing, whereas no such interactions are observed when handling background noise inputs.

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Background: The 'Fit to Dance?' survey has been used in a number of studies to understand the health and wellbeing of dancers. These data have not been collected in Brazil as there is no validated questionnaire available in Brazilian Portuguese, culturally validated in Brazil with a scope as broad and comprehensive as that of 'Fit to Dance?'.

Objective: Translate into Brazilian Portuguese and culturally validate the questionnaire 'Fit to Dance?' in Brazil.

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