Activated Bone Marrow-Derived Macrophages Eradicate Alzheimer's-Related Aβ42 Oligomers and Protect Synapses.

Impaired synaptic integrity and function due to accumulation of amyloid β-protein (Aβ42) oligomers is thought to be a major contributor to cognitive decline in Alzheimer's disease (AD). However, the exact role of Aβ42 oligomers in synaptotoxicity and the ability of peripheral innate immune cells to rescue synapses remain poorly understood due to the metastable nature of oligomers. Here, we utilized photo-induced cross-linking to stabilize pure oligomers and study their effects vs. fibrils on synapses and protection by Aβ-phagocytic macrophages. We found that cortical neurons were more susceptible to Aβ42 oligomers than fibrils, triggering additional neuritic arborization retraction, functional alterations (hyperactivity and spike waveform), and loss of VGluT1- and PSD95-excitatory synapses. Co-culturing neurons with bone marrow-derived macrophages protected synapses against Aβ42 fibrils; moreover, immune activation with glatiramer acetate (GA) conferred further protection against oligomers. Mechanisms involved increased Aβ42 removal by macrophages, amplified by GA stimulation: fibrils were largely cleared through intracellular CD36/EEA1+-early endosomal proteolysis, while oligomers were primarily removed via extracellular/MMP-9 enzymatic degradation. In vivo studies in GA-immunized or CD115+-monocyte-grafted APPSWE/PS1ΔE9-transgenic mice followed by pre- and postsynaptic analyses of entorhinal cortex and hippocampal substructures corroborated our in vitro findings of macrophage-mediated synaptic preservation. Together, our data demonstrate that activated macrophages effectively clear Aβ42 oligomers and rescue VGluT1/PSD95 synapses, providing rationale for harnessing macrophages to treat AD

Analyzing the Impact of Concurrency on Scaling Machine Learning Programs Using TensorFlow

In recent times, computer scientists and technology companies have quickly begun to realize that machine learning and creating computer software that is capable of reasoning for itself (at least in theory). What was once only considered science fiction lore is now becoming a reality in front of our very eyes. With this type of computational capability at our disposal, we are left with the question of how best to use it and where to start in creating models that can help us best utilize it. TensorFlow is an open source software library used in machine learning developed and released by Google. It was created by the company in order to help them meet their expanding needs to train systems that can build and detect neural networks for pattern recognition that could be used in their services. It was first released by the Google Brain Team in November 2015 and, at the time of the preparation of this research, the project is still being heavily developed by programmers and researchers both inside of Google and around the world. Thus, it is very possible that some future releases of the software package could remove and/or replace some current capabilities. The point of this thesis is to examine how machine learning programs written with TensorFlow that do not scale well (such as large-scale neural networks) can be made more scalable by using concurrency and distribution of computation among threads. To do this, we will be using lock elision using conditional variables and locking mechanisms (such as semaphores) to allow for smooth distribution of resources to be used by the architecture. We present the trial runs and results of the added implementations and where the results fell short of optimistic expectation. Although TensorFlow is still a work in progress, we will also address where this framework was insufficient in addressing the needs of programmers attempting to write scalable code and whether this type of implementation is sustainable

A Foothold for Real Democracy in Eastern Europe

Ukraine has never had a criminal or civil jury trial despite the fact that the right to a criminal jury trial is guaranteed by Ukraine\u27s Constitution. The lack of jury trials is one of the factors likely contributing to the corruption and deficiencies inherent in Ukraine\u27s judicial system. This Article argues that Ukraine can and should make room for juries in its judicial system and proposes a framework for both criminal and civil jury trials. Although the use of juries will not remedy all of the problems plaguing Ukraine, it could bring the country closer to achieving a truly democratic form of government. Specifically, the introduction of a jury trial framework in Ukraine will aid in the legitimization of the Ukrainian government and court system, harmonizing the presently tumultuous relationship between Ukrainian citizens and their government. Once Ukraine puts jury trials into practice, other former Soviet republics could learn and benefit from Ukraine\u27s example

Occurrence of chlorophyll allomers during virus-induced mortality and population decline in the ubiquitous picoeukaryote Ostreococcus tauri

During viral infection and growth limitation of the picoeukaryote Ostreococcus tauri, we examined the relationship between membrane permeability, oxidative stress and chlorophyll allomers (oxidation products). Chlorophyll allomers were measured in batch-cultures of O. tauri in parallel with maximum quantum efficiency of photosystem II photochemistry (Fv/Fm), carotenoids, and reactive oxygen species and membrane permeability using fluorescent probes (CM-H2DCFDA and SYTOX-Green). Viral infection led to mass cell lysis of the O. tauri cells within 48 h. The concentration of the allomer hydroxychlorophyll a peaked with a 16-fold increase (relative to chlorophyll-a) just after the major lysis event. In contrast, cell death due to growth limitation resulted in a 2-fold increase in allomer production, relative to chl-a. Two allomers were detected solely in association with O. tauri debris after viral lysis, and unlike other allomers were not observed before viral lysis, or during cell death due to growth limitation. Conversely, the component chl-aP276 was found in the highest concentrations relative to chl-a, in exponentially growing O. tauri. The components described have potential as indicators of mode of phytoplankton mortality, and of population growth

Evaluation of Outcomes Between the Top-down Versus the Bottom-up Approach for Retropubic Midurethral Sling

Introduction and hypothesis: Retropubic midurethral sling (MUS) placement is the gold standard for the treatment of stress urinary incontinence in the USA. The procedure can be approached from either a top-down or a bottom-up direction, but there is a paucity of contemporary data regarding outcomes between these approaches. The aim of this study was to provide updated clinical outcomes data. Methods: This was a retrospective cohort study of women undergoing the retropubic MUS procedure alone or at the time of pelvic organ prolapse repair between 2010 and 2020 at a single academic medical center. The electronic medical record was used to extract demographic data, operative approach, and perioperative complications. The primary outcome was a composite incidence of any perioperative complication. Results: Of the 309 patients analyzed, 140 (45.3%) underwent top-down and 169 (54.7%) underwent bottom-up retropubic MUS placement. Patients undergoing top-down MUS placement were more likely to be older (mean age 58 vs 54, p=0.02), have a history of diabetes mellitus (20% vs 8.9%, p=0.004), and have had a prior hysterectomy (27% vs 16%, p=0.02). They were less likely to have a concurrent anterior (p\u3c0.001) or posterior repair (p\u3c0.001). Patients undergoing the top-down procedure were less likely to experience sling exposure (p=0.02); complications in the two groups were otherwise similar. Conclusions: The top-down approach to retropubic MUS placement was associated with lower rates of mesh erosion in this population of patients. Neither approach is associated with an increased overall risk of complications or de novo overactive bladder symptoms