Structural and functional changes in the retina in Parkinson's disease.

Parkinson's disease is caused by degeneration of dopaminergic neurons, originating in the substantia nigra pars compacta and characterised by bradykinesia, rest tremor and rigidity. In addition, visual disorders and retinal abnormalities are often present and can be identified by decreased visual acuity, abnormal spatial contrast sensitivity or even difficulty in complex visual task completion. Because of their early onset in patients with de novo Parkinson's disease, the anatomical retinal changes and electrophysiological modification could be valuable markers even at early stages of the disease. However, due to the concomitant occurrence of normal ageing, the relevance and specificity of these predictive values can be difficult to interpret. This review examines retinal dysfunction arising in Parkinson's disease. We highlight the electrophysiological delays and decreased amplitude in the electroretinography recorded in patients and animal models. We relate this to coexisting anatomical changes such as retinal nerve fibre layer and macular thinning, measured using optical coherence tomography, and show that functional measures are more consistent overall than optical coherence-measured structural changes. We review the underlying chemical changes seen with loss of retinal dopaminergic neurons and the effect of levodopa treatment on the retina in Parkinson's disease. Finally, we consider whether retinal abnormalities in Parkinson's disease could have a role as potential markers of poorer outcomes and help stratify patients at early stages of the disease. We emphasise that retinal measures can be valuable, accessible and cost-effective methods in the early evaluation of Parkinson's disease pathogenesis with potential for patient stratification.

NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines.

Recent years have witnessed a massive push towards reproducible research in neuroscience. Unfortunately, this endeavor is often challenged by the large diversity of tools used, project-specific custom code and the difficulty to track all user-defined parameters. NeuroPycon is an open-source multi-modal brain data analysis toolkit which provides Python-based template pipelines for advanced multi-processing of MEG, EEG, functional and anatomical MRI data, with a focus on connectivity and graph theoretical analyses. Importantly, it provides shareable parameter files to facilitate replication of all analysis steps. NeuroPycon is based on the NiPype framework which facilitates data analyses by wrapping many commonly-used neuroimaging software tools into a common Python environment. In other words, rather than being a brain imaging software with is own implementation of standard algorithms for brain signal processing, NeuroPycon seamlessly integrates existing packages (coded in python, Matlab or other languages) into a unified python framework. Importantly, thanks to the multi-threaded processing and computational efficiency afforded by NiPype, NeuroPycon provides an easy option for fast parallel processing, which critical when handling large sets of multi-dimensional brain data. Moreover, its flexible design allows users to easily configure analysis pipelines by connecting distinct nodes to each other. Each node can be a Python-wrapped module, a user-defined function or a well-established tool (e.g. MNE-Python for MEG analysis, Radatools for graph theoretical metrics, etc.). Last but not least, the ability to use NeuroPycon parameter files to fully describe any pipeline is an important feature for reproducibility, as they can be shared and used for easy replication by others. The current implementation of NeuroPycon contains two complementary packages: The first, called ephypype, includes pipelines for electrophysiology analysis and a command-line interface for on the fly pipeline creation. Current implementations allow for MEG/EEG data import, pre-processing and cleaning by automatic removal of ocular and cardiac artefacts, in addition to sensor or source-level connectivity analyses. The second package, called graphpype, is designed to investigate functional connectivity via a wide range of graph-theoretical metrics, including modular partitions. The present article describes the philosophy, architecture, and functionalities of the toolkit and provides illustrative examples through interactive notebooks. NeuroPycon is available for download via github (https://github.com/neuropycon) and the two principal packages are documented online (https://neuropycon.github.io/ephypype/index.html, and https://neuropycon.github.io/graphpype/index.html). Future developments include fusion of multi-modal data (eg. MEG and fMRI or intracranial EEG and fMRI). We hope that the release of NeuroPycon will attract many users and new contributors, and facilitate the efforts of our community towards open source tool sharing and development, as well as scientific reproducibility.

Avaliação histológica dos testículos de ovinos da raça Santa Inês nascidos em diferentes estações do ano / Histological evaluation of Santa Ines sheep testicles born in different seasons

Foram analisados quatro grupos de ovinos machos da raça Santa Inês nascidos em quatro estações do ano, no Distrito Federal, a fim de observar as idades e o peso corporal em que estes atingiram a puberdade. A partir dos cortes histológicos dos testículos, foram analisados parâmetros celulares e mensurações dos túbulos seminíferos. O efeito da data de nascimento sobre os parâmetros avaliados foi significativo (P<0,01), indicando que a estação do ano influenciou as características histológicas dos testículos dos cordeiros Santa Inês. Os animais nascidos no período da seca apresentaram maior precocidade à puberdade, porém pior perfil histológico dos testículos. O final da época de águas apresentou-se como a melhor estação para nascimentos de ovinos na região Central do Brasil, com características histológicas testiculares mais desejáveis na puberdade desses animais.

Four groups of Santa Inês male sheep born in four seasons in the Distrito Federal were analyzed to evaluate the age and body weight at puberty, at which point were castrated. Histological measurements were carried out on the testicles to evaluate cellular parameters and size measurements of the seminiferous tubules. The effect of the group on cellular parameters was significant (P<0.01). Animals born in the dry season were more precocious than the others, but showed the worst histological profile of the testis. The histological traits of the testis of the Santa Inês rams were influenced by the season. The end of the rainy season was shown to the best season for births of sheep in the Central region of Brazil, with histological testicular traits at puberty being superior to the other groups.