203 research outputs found
The age of data-driven proteomics : how machine learning enables novel workflows
A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open modification searches. These workflows are all challenging because of ambiguity in the identification stage; they either expand the search space and thus increase the ambiguity of identifications, or, in the case of DIA, they generate data that is inherently more ambiguous. In this context, machine learning-based predictive models are now generating considerable excitement in the field of proteomics because these predictive models hold great potential to drastically reduce the ambiguity in the identification process of the above-mentioned workflows. Indeed, the field has already produced classical machine learning and deep learning models to predict almost every aspect of a liquid chromatography-mass spectrometry (LC-MS) experiment. Yet despite all the excitement, thorough integration of predictive models in these challenging LC-MS workflows is still limited, and further improvements to the modeling and validation procedures can still be made. In this viewpoint we therefore point out highly promising recent machine learning developments in proteomics, alongside some of the remaining challenges
The stability for the Cauchy problem for elliptic equations
We discuss the ill-posed Cauchy problem for elliptic equations, which is
pervasive in inverse boundary value problems modeled by elliptic equations. We
provide essentially optimal stability results, in wide generality and under
substantially minimal assumptions. As a general scheme in our arguments, we
show that all such stability results can be derived by the use of a single
building brick, the three-spheres inequality.Comment: 57 pages, review articl
MAGUKs, scaffolding proteins at cell junctions, are substrates of different proteases during apoptosis
A major feature of apoptotic cell death is gross structural changes, one of which is the loss of cell–cell contacts. The caspases, executioners of apoptosis, were shown to cleave several proteins involved in the formation of cell junctions. The membrane-associated guanylate kinases (MAGUKs), which are typically associated with cell junctions, have a major role in the organization of protein–protein complexes at plasma membranes and are therefore potentially important caspase targets during apoptosis. We report here that MAGUKs are cleaved and/or degraded by executioner caspases, granzyme B and several cysteine cathepsins in vitro. When apoptosis was induced by UV-irradiation and staurosporine in different epithelial cell lines, caspases were found to efficiently cleave MAGUKs in these cell models, as the cleavages could be prevented by a pan-caspase inhibitor N-benzyloxycarbonyl-Val-Ala-Asp(OMe)fluoromethylketone. Using a selective lysosomal disrupting agent -leucyl--leucine methyl ester, which induces apoptosis through the lysosomal pathway, it was further shown that MAGUKs are also cleaved by the cathepsins in HaCaT and CaCo-2 cells. Immunohistological data showed rapid loss of MAGUKs at the sites of cell–cell contacts, preceding actual cell detachment, suggesting that cleavage of MAGUKs is an important step in fast and efficient cell detachment
Identification of tetrahydrocarbazoles as novel multifactorial drug candidates for treatment of Alzheimer's disease
Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder and the most frequent cause of dementia. To date, there are only a few approved drugs for AD, which show little or no effect on disease progression. Impaired intracellular calcium homeostasis is believed to occur early in the cascade of events leading to AD. Here, we examined the possibility of normalizing the disrupted calcium homeostasis in the endoplasmic reticulum (ER) store as an innovative approach for AD drug discovery. High-throughput screening of a small-molecule compound library led to the identification of tetrahydrocarbazoles, a novel multifactorial class of compounds that can normalize the impaired ER calcium homeostasis. We found that the tetrahydrocarbazole lead structure, first, dampens the enhanced calcium release from ER in HEK293 cells expressing familial Alzheimer's disease (FAD)-linked presenilin 1 mutations. Second, the lead structure also improves mitochondrial function, measured by increased mitochondrial membrane potential. Third, the same lead structure also attenuates the production of amyloid-beta (A beta) peptides by decreasing the cleavage of amyloid precursor protein (APP) by beta-secretase, without notably affecting alpha- and gamma-secretase cleavage activities. Considering the beneficial effects of tetrahydrocarbazoles addressing three key pathological aspects of AD, these compounds hold promise for the development of potentially effective AD drug candidates
Retrieving the Elastodynamic Green's Function of an Arbitrary Inhomogeneous Medium by Cross Correlation
Effects of Transmitters and Amyloid-Beta Peptide on Calcium Signals in Rat Cortical Astrocytes: Fura-2AM Measurements and Stochastic Model Simulations
BACKGROUND: To better understand the complex molecular level interactions seen in the pathogenesis of Alzheimer's disease, the results of the wet-lab and clinical studies can be complemented by mathematical models. Astrocytes are known to become reactive in Alzheimer's disease and their ionic equilibrium can be disturbed by interaction of the released and accumulated transmitters, such as serotonin, and peptides, including amyloid- peptides (A). We have here studied the effects of small amounts of A25-35 fragments on the transmitter-induced calcium signals in astrocytes by Fura-2AM fluorescence measurements and running simulations of the detected calcium signals. METHODOLOGY/PRINCIPAL FINDINGS: Intracellular calcium signals were measured in cultured rat cortical astrocytes following additions of serotonin and glutamate, or either of these transmitters together with A25-35. A25-35 increased the number of astrocytes responding to glutamate and exceedingly increased the magnitude of the serotonin-induced calcium signals. In addition to A25-35-induced effects, the contribution of intracellular calcium stores to calcium signaling was tested. When using higher stimulus frequency, the subsequent calcium peaks after the initial peak were of lower amplitude. This may indicate inadequate filling of the intracellular calcium stores between the stimuli. In order to reproduce the experimental findings, a stochastic computational model was introduced. The model takes into account the major mechanisms known to be involved in calcium signaling in astrocytes. Model simulations confirm the principal experimental findings and show the variability typical for experimental measurements. CONCLUSIONS/SIGNIFICANCE: Nanomolar A25-35 alone does not cause persistent change in the basal level of calcium in astrocytes. However, even small amounts of A25-35, together with transmitters, can have substantial synergistic effects on intracellular calcium signals. Computational modeling further helps in understanding the mechanisms associated with intracellular calcium oscillations. Modeling the mechanisms is important, as astrocytes have an essential role in regulating the neuronal microenvironment of the central nervous system
Qubits made by advanced semiconductor manufacturing
AbstractFull-scale quantum computers require the integration of millions of qubits, and the potential of using industrial semiconductor manufacturing to meet this need has driven the development of quantum computing in silicon quantum dots. However, fabrication has so far relied on electron-beam lithography and, with a few exceptions, conventional lift-off processes that suffer from low yield and poor uniformity. Here we report quantum dots that are hosted at a 28Si/28SiO2 interface and fabricated in a 300 mm semiconductor manufacturing facility using all-optical lithography and fully industrial processing. With this approach, we achieve nanoscale gate patterns with excellent yield. In the multi-electron regime, the quantum dots allow good tunnel barrier control—a crucial feature for fault-tolerant two-qubit gates. Single-spin qubit operation using magnetic resonance in the few-electron regime reveals relaxation times of over 1 s at 1 T and coherence times of over 3 ms.</jats:p
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