Incomplete annotation has a disproportionate impact on our understanding of Mendelian and complex neurogenetic disorders

Growing evidence suggests that human gene annotation remains incomplete; however, it is unclear how this affects different tissues and our understanding of different disorders. Here, we detect previously unannotated transcription from Genotype-Tissue Expression RNA sequencing data across 41 human tissues. We connect this unannotated transcription to known genes, confirming that human gene annotation remains incomplete, even among well-studied genes including 63% of the Online Mendelian Inheritance in Man–morbid catalog and 317 neurodegeneration-associated genes. We find the greatest abundance of unannotated transcription in brain and genes highly expressed in brain are more likely to be reannotated. We explore examples of reannotated disease genes, such as SNCA, for which we experimentally validate a previously unidentified, brain-specific, potentially protein-coding exon. We release all tissue-specific transcriptomes through vizER: http://rytenlab.com/browser/app/vizER. We anticipate that this resource will facilitate more accurate genetic analysis, with the greatest impact on our understanding of Mendelian and complex neurogenetic disorders

Prediction of mechanistic subtypes of Parkinson’s using patient-derived stem cell models

Parkinson’s disease is a common, incurable neurodegenerative disorder that is clinically heterogeneous: it is likely that different cellular mechanisms drive the pathology in different individuals. So far it has not been possible to define the cellular mechanism underlying the neurodegenerative disease in life. We generated a machine learning-based model that can simultaneously predict the presence of disease and its primary mechanistic subtype in human neurons. We used stem cell technology to derive control or patient-derived neurons, and generated different disease subtypes through chemical induction or the presence of mutation. Multidimensional fluorescent labelling of organelles was performed in healthy control neurons and in four different disease subtypes, and both the quantitative single-cell fluorescence features and the images were used to independently train a series of classifiers to build deep neural networks. Quantitative cellular profile-based classifiers achieve an accuracy of 82%, whereas image-based deep neural networks predict control and four distinct disease subtypes with an accuracy of 95%. The machine learning-trained classifiers achieve their accuracy across all subtypes, using the organellar features of the mitochondria with the additional contribution of the lysosomes, confirming the biological importance of these pathways in Parkinson’s. Altogether, we show that machine learning approaches applied to patient-derived cells are highly accurate at predicting disease subtypes, providing proof of concept that this approach may enable mechanistic stratification and precision medicine approaches in the future

Hinduismo e cristianesimo in dialogo

Il volume presenta in modo sintetico non solo la ricchezza che la tradizione religiosa hindú racchiude in sé, ma anche le principali prospettive su cui si sta sviluppando il dialogo hindū-cristiano.- Indice #9-Introduzione, Andrea Pacini #13- Hinduismo: elementi fondamentali caratterizzanti la tradizione hindū, Stefano Piano #19- Dio nelle tradizioni religiose hindū, Francis X. D’Sa #39- L’uomo e la salvezza nella tradizione hindū, Mario Piantelli #59- Le pratiche religiose nello hinduismo, Kala Acharya #81- Hinduismo, modernità e politica nell’India contemporanea, Urvashi Butalia #109- Hinduismo e religioni universali. Relazioni storiche e prospettive attuali di dialogo, Anantanand Rambachan #121- Le visioni hindū di Cristo, Anand Amaladass S. J. #139- Un volto indiano per Gesù Cristo, Jacques Dupuis #165- Possibilità molteplici di dialogo fra cristiani e hindū, Thomas Matus #193- Bibliografia generale #20

Mitochondrial dysfunction is a key pathological driver of early stage Parkinson’s

Background:The molecular drivers of early sporadic Parkinson’s disease (PD) remain unclear, and the presence of widespread end stage pathology in late disease masks the distinction between primary or causal disease-specific events and late secondary consequences in stressed or dying cells. However, early and mid-stage Parkinson’s brains (Braak stages 3 and 4) exhibit alpha-synuclein inclusions and neuronal loss along a regional gradient of severity, from unaffected-mild-moderate-severe. Here, we exploited this spatial pathological gradient to investigate the molecular drivers of sporadic PD. Methods: We combined high precision tissue sampling with unbiased large-scale profiling of protein expression across 9 brain regions in Braak stage 3 and 4 PD brains, and controls, and verified these results using targeted proteomic and functional analyses. Results: We demonstrate that the spatio-temporal pathology gradient in early-mid PD brains is mirrored by a biochemical gradient of a changing proteome. Importantly, we identify two key events that occur early in the disease, prior to the occurrence of alpha-synuclein inclusions and neuronal loss: (i) a metabolic switch in the utilisation of energy substrates and energy production in the brain, and (ii) perturbation of the mitochondrial redox state. These changes may contribute to the regional vulnerability of developing alpha-synuclein pathology. Later in the disease, mitochondrial function is affected more severely, whilst mitochondrial metabolism, fatty acid oxidation, and mitochondrial respiration are affected across all brain regions. Conclusions: Our study provides an in-depth regional profile of the proteome at different stages of PD, and highlights that mitochondrial dysfunction is detectable prior to neuronal loss, and alpha-synuclein fibril deposition, suggesting that mitochondrial dysfunction is one of the key drivers of early disease

A review on substances and processes relevant for optical remote sensing of extremely turbid marine areas, with a focus on the Wadden Sea

The interpretation of optical remote sensing data of estuaries and tidal flat areas is hampered by optical complexity and often extreme turbidity. Extremely high concentrations of suspended matter, chlorophyll and dissolved organic matter, local differences, seasonal and tidal variations and resuspension are important factors influencing the optical properties in such areas. This review gives an overview of the processes in estuaries and tidal flat areas and the implications of these for remote sensing in such areas, using the Wadden Sea as a case study area. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible. However, this requires sensors with a large ground resolution, algorithms tuned for high concentrations of various substances and the local specific optical properties of these substances, a simultaneous detection of water colour and land-water boundaries, a very short time lag between acquisition of remote sensing and in situ data used for validation and sufficient geophysical and ecological knowledge of the area. © 2010 The Author(s)

Molecular Chemistry to the Fore: New Insights into the Fascinating World of Photoactive Colloidal Semiconductor Nanocrystals

Colloidal semiconductor nanocrystals possess unique properties that are unmatched by other chromophores such as organic dyes or transition-metal complexes. These versatile building blocks have generated much scientific interest and found applications in bioimaging, tracking, lighting, lasing, photovoltaics, photocatalysis, thermoelectrics, and spintronics. Despite these advances, important challenges remain, notably how to produce semiconductor nanostructures with predetermined architecture, how to produce metastable semiconductor nanostructures that are hard to isolate by conventional syntheses, and how to control the degree of surface loading or valence per nanocrystal. Molecular chemists are very familiar with these issues and can use their expertise to help solve these challenges. In this Perspective, we present our group\u27s recent work on bottom-up molecular control of nanoscale composition and morphology, low-temperature photochemical routes to semiconductor heterostructures and metastable phases, solar-to-chemical energy conversion with semiconductor-based photocatalysts, and controlled surface modification of colloidal semiconductors that bypasses ligand exchange

Selective phosphodiesterase inhibitors: a promising target for cognition enhancement

# The Author(s) 2008. This article is published with open access at Springerlink.com Rationale One of the major complaints most people face during aging is an impairment in cognitive functioning. This has a negative impact on the quality of daily life and is even more prominent in patients suffering from neurodegenerative and psychiatric disorders including Alzheimer’s disease, schizophrenia, and depression. So far, the majority of cognition enhancers are generally targeting one particular neurotransmitter system. However, recently phosphodiesterases (PDEs) have gained increased attention as a potential new target for cognition enhancement. Inhibition of PDEs increases the intracellular availability of the second messengers cGMP and/or cAMP. Objective The aim of this review was to provide an overvie