Intracellular deposition of fibrillar aggregates of alpha synuclein (αSyn) characterizes neurodegenerative diseases such as Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). However, recent evidence indicates that small αSyn oligomeric aggregates that precede fibril formation may be the most neurotoxic species and can be found extracellularly. This new evidence has changed the view of pathological αSyn aggregation from a self-contained cellular phenomenon to an extracellular event and prompted investigation of the putative effects of extracellular αSyn oligomers. Here, we report that extracellular application of αSyn oligomers detrimentally impacts neuronal welfare and memory function. We found that oligomeric αSyn increased intracellular Ca2+ levels, induced calcineurin (CaN) activity, decreased cAMP response element binding protein (CREB) transcriptional activity and resulted in calcineurin-dependent death of human neuroblastoma cells. Similarily, CaN induction and CREB inhibition were observed when αSyn oligomers were applied to organotypic brain slices, which opposed hippocampal long-term potentiation (LTP). Furthermore, αSyn oligomers induced CaN, inhibited CREB and evoked memory impairments in mice that received acute intracerebroventricular injections. Notably, all these events were reversed by pharmacological inhibition of CaN. Moreover, we found decreased active calcineurin (CaN) and reduced levels of phosphorylated CREB in autopsy brain tissue from patients affected by DLB, which is characterized by deposition of αSyn aggregates and progressive cognitive decline. These results indicate that exogenously-applied αSyn oligomers impact neuronal function and produce memory deficits through mechanisms that involve CaN activation.

Alzheimer’s Disease (AD) is characterized by the cerebral accumulation of misfolded and aggregated amyloid-β protein (Aβ). Disease symptoms can be alleviated, in vitro and in vivo, by “β-sheet breaker” pentapeptides that reduce plaque volume. However the peptide nature of these compounds, made them biologically unstable and unable to penetrate membranes with high efficiency. The main goal of this study was to use computational methods to identify small molecule mimetics with better drug-like properties. For this purpose, the docked conformations of the active peptides were used to identify compounds with similar activities. A series of related β-sheet breaker peptides were docked to solid state NMR structures of a fibrillar form of Aβ. The lowest energy conformations of the active peptides were used to design three dimensional (3D)-pharmacophores, suitable for screening the NCI database with Unity. Small molecular weight compounds with physicochemical features in a conformation similar to the active peptides were selected, ranked by docking solubility parameters. Of 16 diverse compounds selected for experimental screening, 2 prevented and reversed Aβ aggregation at 2–3 μM concentration, as measured by Thioflavin T (ThT) fluorescence and ELISA assays. They also prevented the toxic effects of aggregated Aβ on neuroblastoma cells. Their low molecular weight and aqueous solubility makes them promising lead compounds for treating AD.

In spite of the substantial progress on understanding the critical role of protein misfolding and aggregation, drugs effective against this process are still years away from approval.

Background AlzPED is a publicly available database created by the National Institute on Aging to address key factors contributing to poor translation of preclinical efficacy from animal models to the clinic in Alzheimer’s disease (AD) therapy development. Specifically, AlzPED is missioned to identify critical experimental design elements and methodology missing from studies that make them susceptible to misinterpretation and reduce their reproducibility and translational value, as well as serve as a platform for reporting unpublished negative findings. AlzPED provides funding agencies with a tool for enforcement of the requirements for transparent reporting and rigorous study design. Through these capabilities, AlzPED is intended to guide the development and implementation of strategies and recommendations for standardized best practices for the rigorous preclinical testing of AD candidate therapeutics and mitigate the publication bias that favors the reporting of positive findings. Method Using key word‐driven literature searches published studies are acquired and curated by two experts for data on authors, funding source, AD animal models, therapeutic targets and therapeutic agents, study design, and outcome measures, prior to publication in the database. Rigor in study design is evaluated with an experimental design scorecard that summarizes the elements of experimental design reported in each study in the database. Result AlzPED currently houses curated summaries from 917 published studies. Summaries are searchable by author, funding source, animal model, therapeutic target and therapeutic agent. At present, the database contains data on 185 animal models, 175 therapeutic targets, 804 therapeutic agents and, more than 1500 AD‐related outcome measures. Evaluation of experimental design scorecards from each study demonstrates significant under‐reporting of critical elements of methodology even in high impact factor journals and highly cited published preclinical research. Conclusion Analysis of curated studies demonstrates serious deficiencies in reporting critical elements of methodology such as power/sample size calculation, blinding for treatment/outcomes, randomization, balancing for sex, animal genetic background and others, irrespective of journal impact factor and number of citations. These deficiencies diminish the scientific rigor, reproducibility and translational value of the preclinical studies. Thus, it is evident that a standardized set of best practices is required for successful translation of therapeutic efficacy in AD research.

If a rigorous quality control is established for MLC and optimisation criteria (number of gantry angles, minimum segment size, levels of intensity for fluency map) are used. Then, QC for IMRT standard treatment plans would be only based on the verification of monitor units and dose distributions using e-IMRT II.This work has been funded by the Xunta de Galicia, Project R&D Grant 09SIN007CT. We would like to thank Centro de Supercomputacià n de Galicia for the computational resources and support.