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Synaptic vesicle recycling has long served as a model for the general mechanisms of cellular trafficking. We used an integrative approach, combining quantitative immunoblotting and mass spectrometry to determine protein numbers; electron microscopy to measure organelle numbers, sizes, and positions; and super-resolution fluorescence microscopy to localize the proteins. Using these data, we generated a three-dimensional model of an \"average\" synapse, displaying 300,000 proteins in atomic detail. The copy numbers of proteins involved in the same step of synaptic vesicle recycling correlated closely. In contrast, copy numbers varied over more than three orders of magnitude between steps, from about 150 copies for the endosomal fusion proteins to more than 20,000 for the exocytotic ones.

Quantum information carriers, just like most physical systems, naturally occupy high-dimensional Hilbert spaces. Instead of restricting them to a two-level subspace, these high-dimensional (qudit) quantum systems are emerging as a powerful resource for the next generation of quantum processors. Yet harnessing the potential of these systems requires efficient ways of generating the desired interaction between them. Here, we experimentally demonstrate an implementation of a native two-qudit entangling gate up to dimension 5 in a trapped-ion system. This is achieved by generalizing a recently proposed light-shift gate mechanism to generate genuine qudit entanglement in a single application of the gate. The gate seamlessly adapts to the local dimension of the system with a calibration overhead that is independent of the dimension. Encoding quantum information in qudits instead of qubits allows for several advantages, but scalable native entangling techniques would be needed. Here, the authors show how to use light-shift gates to perform entangling operations on trapped ion systems, with a calibration overhead which is independent on the qudit dimension.

Fluorescence microscopy is a key driver of discoveries in the life sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how content-aware image restoration based on deep learning extends the range of biological phenomena observable by microscopy. We demonstrate on eight concrete examples how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to tenfold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times-higher frame rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FIJI, and KNIME.

A large body of evidence has implicated amyloid precursor protein (APP) and its proteolytic derivatives as key players in the physiological context of neuronal synaptogenesis and synapse maintenance, as well as in the pathology of Alzheimer's Disease (AD). Although APP processing and release are known to occur in response to neuronal stimulation, the exact mechanism by which APP reaches the neuronal surface is unclear. We now demonstrate that a small but relevant number of synaptic vesicles contain APP, which can be released during neuronal activity, and most likely represent the major exocytic pathway of APP. This novel finding leads us to propose a revised model of presynaptic APP trafficking that reconciles existing knowledge on APP with our present understanding of vesicular release and recycling.

Synaptic vesicles release neurotransmitters both at rest and when stimulated. Wilhelm et al . use a variety of assays to show that the same vesicles participate in both active and spontaneous release. Synaptic vesicles release neurotransmitter both actively (on stimulation) and spontaneously (at rest). It has been assumed that identical vesicles use both modes of release; however, recent evidence has challenged this view. Using several assays (FM dye imaging, pHluorin imaging and antibody-labeling of synaptotagmin) in neuromuscular preparations from Drosophila , frog and mouse, as well as rat cultured neurons, we found that the same vesicles participate in active and spontaneous release.

Chemical synapses contain substantial numbers of neurotransmitter-filled synaptic vesicles, ranging from approximately 100 to many thousands. The vesicles fuse with the plasma membrane to release neurotransmitter and are subsequently reformed and recycled. Stimulation of synapses in vitro generally causes the majority of the synaptic vesicles to release neurotransmitter, leading to the assumption that synapses contain numerous vesicles to sustain transmission during high activity. We tested this assumption by an approach we termed cellular ethology, monitoring vesicle function in behaving animals (10 animal models, nematodes to mammals). Using FM dye photooxidation, pHluorin imaging, and HRP uptake we found that only approximately 1–5% of the vesicles recycled over several hours, in both CNS synapses and neuromuscular junctions. These vesicles recycle repeatedly, intermixing slowly (over hours) with the reserve vesicles. The latter can eventually release when recycling is inhibited in vivo but do not seem to participate under normal activity. Vesicle recycling increased only to ≈5% in animals subjected to an extreme stress situation (frog predation on locusts). Synapsin, a molecule binding both vesicles and the cytoskeleton, may be a marker for the reserve vesicles: the proportion of vesicles recycling in vivo increased to 30% in synapsin-null DROSOPHILA: We conclude that synapses do not require numerous reserve vesicles to sustain neurotransmitter release and thus may use them for other purposes, examined in the accompanying paper.

Purpose The purpose of this paper is to: determine the relative importance that Generation Y consumers indicate for 13 wine attributes in their selection of wine; determine if these wine attributes are significantly distinct in importance in the mind of the consumer; and compare the wine attribute importance findings with the US findings of Chrysochou et al. (2012). Design/methodology/approach Quantitative data were gathered from a convenience student sample (n=429) to which the Best-Worst Scaling method was applied for 13 pre-determined wine attributes in a Balanced Incomplete Block Design. Data analysis included descriptive statistics, reliability analysis, t-tests and mixed model repeated measure ANOVA. Findings Respondents were able to differentiate between the importance of wine attributes. Taste was the most important wine attribute followed by someone recommended it. Alcohol level below 13 per cent was least important. Firm controlled information such as information on back label was of little importance. South African Generation Y consumers seem to select wine similarly to those in the USA. Originality/value Findings contribute to generation-based research in wine marketing and increase the understanding of the wine selection behaviour of Generation Y consumers in South Africa. More effective marketing strategies to Generation Y consumers can result to grow wine consumption in this significant segment.

The study examined the relationship between expenditures and student achievement in Ohio school districts for the years 2015 through 2019. Data were analyzed for categorical district expenditures correlated to student achievement. Operating and instructional expenditure categories, along with typology demographics, comprised the independent variable group. The performance index measure served as the dependent variable of student achievement in the study. The research analyzed the relationship between expenditure categories and performance index among both Ohio schools at-large and those sharing similar demographic characteristics, per ODE's Typology of Ohio's School Districts (ODE, 2019). Data for the study were collected from the Ohio Department of Education database and is available to the public. Descriptive statistics and regression analyses were applied to examine the relationship between expenditures and achievement among sample groups.The quantitative findings indicate that while regressions among both Ohio districts at-large and Category 1 schools demonstrate significance, the connections between independent spending categories and achievement are mixed. Furthermore, the predictive model strength in both sample groups was significantly reduced when demographic inputs were removed from the regressions. However, research findings indicate a stronger observable relationship between specific expenditure categories and achievement when demographic variables are streamlined, as demonstrated in the Category 1 sample results. Recommendations and analysis were given based on the findings from the research. Overall, the study was significant in that it seeks to provide valuable data to district leaders, along with local and state governing bodies, in the allocation of educational funds for student achievement.

High-dimensional quantum systems are a valuable resource for quantum information processing. They can be used to encode error-correctable logical qubits, which has been demonstrated using continuous-variable states in microwave cavities or the motional modes of trapped ions. For example, high-dimensional systems can be used to realize ‘Schrödinger cat’ states, which are superpositions of widely displaced coherent states that can be used to illustrate quantum effects at large scales. Recent proposals have suggested encoding qubits in high-spin atomic nuclei, which are finite-dimensional systems that can host hardware-efficient versions of continuous-variable codes. Here we demonstrate the creation and manipulation of Schrödinger cat states using the spin-7/2 nucleus of an antimony atom embedded in a silicon nanoelectronic device. We use a multi-frequency control scheme to produce spin rotations that preserve the symmetry of the qudit, and we constitute logical Pauli operations for qubits encoded in the Schrödinger cat states. Our work demonstrates the ability to prepare and control non-classical resource states, which is a prerequisite for applications in quantum information processing and quantum error correction, using our scalable, manufacturable semiconductor platform. A large nuclear spin has been successfully placed in a Schrödinger cat state, a superposition of its two most widely separated spin coherent states. This can be used as an error-correctable qubit.