Impact of polycyclic aromatic hydrocarbon exposure on cognitive function and neurodegeneration in humans:A systematic review and meta-analysis

INTRODUCTION: This article documents an emerging body of evidence concerning the neurological effect of polycyclic aromatic hydrocarbon (PAH) exposure with regard to cognitive function and increased risk of neurodegeneration. METHODS: Two electronic databases, PubMed and Web of Science, were systematically searched. RESULTS: The 37/428 studies selected included outcomes measuring cognitive function, neurobehavioral symptoms of impaired cognition, and pathologies associated with neurodegeneration from pre-natal (21/37 studies), childhood (14/37 studies), and adult (8/37 studies) PAH exposure. Sufficient evidence was found surrounding pre-natal exposure negatively impacting child intelligence, mental development, average overall development, verbal IQ, and memory; externalizing, internalizing, anxious, and depressed behaviors; and behavioral development and child attentiveness. Evidence concerning exposure during childhood and as an adult was scarce and highly heterogeneous; however, the presence of neurodegenerative biomarkers and increased concentrations of cryptic “self” antigens in serum and cerebrospinal fluid samples suggest a higher risk of neurodegenerative disease. Associations with lowered cognitive ability and impaired attentiveness were found in children and memory disturbances, specifically auditory memory, verbal learning, and general memory in adults. DISCUSSION: Although evidence is not yet conclusive and further research is needed, the studies included supported the hypothesis that PAH exposure negatively impacts cognitive function and increases the risk of neurodegeneration in humans, and recommends considering the introduction of a variable “rural vs. urban” as covariate for adjusting analyses, where the neurological functions affected (as result of our review) are outcome variables

Reconstruction Schemes for MR Data. Discussion Session

The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is essential for simultaneously improving patient care, accuracy in diagnosis and quality in clinical research. Sponsored by the Royal Society through the Newton Mobility Grant Scheme, a half-day workshop on reconstruction schemes for MR data was held on the 17th of August 2016 to discuss new ideas from related research fields that could be useful to overcome the shortcomings of the conventional reconstruction methods that have been evaluated up to date. Participants were 21 university students, computer scientists, image analysts, engineers and physicists from institutions from 6 different countries. The discussion evolved around exploring new avenues to achieve high resolution, high quality and fast acquisition of MR imaging. This presentation introduces and reflects on these discussion topics

La biblioteca escolar y su contribución a la motivación por la lectura

The practice of routine and traditional readings during the educational process has become a problem, especially when the scholar needs to feel this activity as enjoyment and personal creation. In the article latent problems are identified and the theoretical bases are considered taking into account contributions from different sciences and disciplines related to the didactics of reading that are coherent with the educational ideas that identify the Cuban pedagogical tradition. Being the main objective to expose the tendencies and the main assumed assumptions that sustain the problem related to the motivation for reading. The activities project the process of training readers in a dynamic and creative way, from a perspective that integrates the use of reading animation techniques, a participatory and democratic style, causing emotional effects in school children. The study was carried out from September 2018 to March 2019. To evaluate the effectiveness of the study, the pedagogical experiment method was used, in its pre-experiment modality, with a pre-test and post-test design. The positive effects achieved in schoolchildren of the experimental group with respect to motivation levels have demonstrated the relevance and effectiveness of the proposed activities.La práctica de lecturas rutinarias y tradicionales durante el proceso educativo se ha convertido en una problemática, sobre todo, cuando el escolar necesita sentir esta actividad como disfrute y creación personal. En el artículo se identifican problemas latentes al respecto y se plantean las bases teóricas teniendo en cuenta aportes de diferentes ciencias y disciplinas afines a la didáctica de la lectura que son coherentes con las ideas educativas que identifican la tradición pedagógica cubana. Siendo el principal objetivo, exponer las tendencias y los principales presupuestos asumidos que sustentan el problema relacionado con la motivación por la lectura. Las actividades proyectan el proceso de formación de lectores de un modo dinámico y creativo, a partir de una perspectiva que integra el empleo de técnicas de animación de la lectura, un estilo participativo y democrático, provocando efectos emotivos en los escolares. El estudio se desarrolló en el período de septiembre de 2018 a marzo de 2019. Para evaluar la efectividad del estudio se empleó el método de experimento pedagógico, en su modalidad de pre - experimento, con un diseño de pre - test y pos - test. Los efectos positivos logrados en los escolares del grupo experimental con respecto a los niveles de motivación, han demostrado la pertinencia y efectividad de las actividades propuestas

GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks

One of the biggest issues facing the use of machine learning in medical imaging is the lack of availability of large, labelled datasets. The annotation of medical images is not only expensive and time consuming but also highly dependent on the availability of expert observers. The limited amount of training data can inhibit the performance of supervised machine learning algorithms which often need very large quantities of data on which to train to avoid overfitting. So far, much effort has been directed at extracting as much information as possible from what data is available. Generative Adversarial Networks (GANs) offer a novel way to unlock additional information from a dataset by generating synthetic samples with the appearance of real images. This paper demonstrates the feasibility of introducing GAN derived synthetic data to the training datasets in two brain segmentation tasks, leading to improvements in Dice Similarity Coefficient (DSC) of between 1 and 5 percentage points under different conditions, with the strongest effects seen fewer than ten training image stacks are available

Automatic Spatial Estimation of White Matter Hyperintensities Evolution in Brain MRI using Disease Evolution Predictor Deep Neural Networks

Funds from the Indonesia Endowment Fund for Education (LPDP), Ministry of Finance, Republic of Indonesia (MFR); Row Fogo Charitable Trust (Grant No. BRO-D.FID3668413)(MCVH); Wellcome Trust (patient recruitment, scanning, primary study Ref No. WT088134/Z/09/A); Fondation Leducq (Perivascular Spaces Transatlantic Network of Excellence); EU Horizon 2020 (SVDs@Target); and the MRC UK Dementia Research Institute at the University of Edinburgh (Wardlaw programme) are gratefully acknowledged. The Titan Xp used for this research was donated by the NVIDIA Corporation.Peer reviewedPublisher PD