Amyloid-β oligomerization monitored by single-molecule stepwise photobleaching

A major hallmark of Alzheimer’s disease is the misfolding and aggregation of the amyloid- β peptide (Aβ). While early research pointed towards large fibrillar- and plaque-like aggregates as being the most toxic species, recent evidence now implicates small soluble Aβ oligomers as being orders of magnitude more harmful. Techniques capable of characterizing oligomer stoichiometry and assembly are thus critical for a deeper understanding of the earliest stages of neurodegeneration and for rationally testing next-generation oligomer inhibitors. While the fluorescence response of extrinsic fluorescent probes such as Thioflavin-T have become workhorse tools for characterizing large Aβ aggregates in solution, it is widely accepted that these methods suffer from many important drawbacks, including an insensitivity to oligomeric species. Here, we integrate several biophysics techniques to gain new insight into oligomer formation at the single-molecule level. We showcase single-molecule stepwise photobleaching of fluorescent dye molecules as a powerful method to bypass many of the traditional limitations, and provide a step-by-step guide to implementing the technique in vitro. By collecting fluorescence emission from single Aβ(1–42) peptides labelled at the N-terminal position with HiLyte Fluor 555 via wide-field total internal reflection fluorescence (TIRF) imaging, we demonstrate how to characterize the number of peptides per single immobile oligomer and reveal heterogeneity within sample populations. Importantly, fluorescence emerging from Aβ oligomers cannot be easily investigated using diffraction-limited optical microscopy tools. To assay oligomer activity, we also demonstrate the implementation of another biophysical method involving the ratiometric imaging of Fura-2-AM loaded cells which quantifies the rate of oligomer-induced dysregulation of intracellular Ca2+ homeostasis. We anticipate that the integrated single-molecule biophysics approaches highlighted here will develop further and in principle may be extended to the investigation of other protein aggregation systems under controlled experimental conditions

The Effect of Memory Contention on the Scalability of Page-based Software Distributed Shared Memory Systems

In this paper, we examine the causes and effects of contentionfor shared data access in parallel programs running on a software distributed shared memory (DSM) system. Specifically, we experiment on two widely-used, pagebased protocols, Princeton’s home-based lazy release consistency (HLRC) and TreadMarks. For most of our programs, these protocols were equally affected by latency increases caused by contention and achieved similar performance. Where they differ significantly, HLRC’s ability to manually eliminate load imbalance was the largest factor accounting for the difference. Finally, to quantify the effects of contention we either modified the application to eliminate the cause of the contention or modified the underlying protocol to efficiently handle it. Overall, we find that contention has profound effects on performance: eliminating contention reduced execution time by 64% in the most extreme case, even at the relatively modest scale of 32 nodes that we consider in this paper

Proyecto “Turmicultura”: Cultivo de trufas del desierto contra el cambio climático y para el desarrollo rural

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Using social cognitive career theory to understand why students choose to study computer science

The aim of this research is to use Social Cognitive Career Theory (SCCT) to identify and understand reasons why students choose to study Computer Science (CS) at university. SCCT focuses on students’ prior experience, social support, self-efficacy and outcome expectation. The research is part motivated by the desire to increase female participation rates in CS, particularly in the UK. Policymakers can use the factors that both females and males identify as influencing their choice of studying CS to enhance the experiences of all students prior to coming to university, but female students in particular. The study uses a semi-structured interview with 17 mixed gender subjects currently studying CS at three Scottish universities. The findings are that social support from family, teachers, friends and mentors is a particularly important factor in choosing to study CS, especially for female subjects. The career paths offered by a CS degree is another major factor, not just the potential jobs, but also the general value of a CS education and the potential to make useful contributions to society. School education appeared to have limited influence, though exposure to problem solving, programming, online self-learning and internships are positive influences. The stereotypical view of CS students as ‘geeks’ is outdated and unhelpful – it is more appropriate to see them as ‘analytical’ or ‘over-achievers’. Subjects make many suggestions for improving the CS education provided at school, especially to make it more attractive to females, including: make it compulsory, teach it earlier, include more programming and problem solving, and increase the visibility of female exemplars and role models