Filter Results
2366836 results
  • The COVID-19 pandemic is a worldwide public health crisis. A vaccine with efficacy against SARS-CoV-2, the pathogen that causes COVID-19, is needed. While most vaccines under investigation are optimized to generate an antibody response, we hypothesize that peptide vaccines containing optimized epitope regions with concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation would drive both humoral and cellular immunity with high specificity, potentially avoiding undesired effects such as antibody-dependent enhancement (ADE), all the while providing a platform with fast manufacturing potential and with high shelf-life stability. Here we combine computational prediction of T cell epitopes with recently published B cell epitope mapping studies to propose optimized peptide vaccines for SARS-CoV-2. We begin with an exploration of the predicted T cell epitope space in SARS-CoV-2, with interrogation of HLA-I and -II epitope overlap, protein source, concurrent human/murine coverage, and allelic space. The T cell vaccine candidates were selected by further considering their predicted affinities for MHC-I and MHC-II alleles across the human population (as well as H2-b/H2-d murine coverage to support preclinical studies), predicted immunogenicity, viral protein abundance, sequence conservation, and co-localization of MHC-I and -II epitopes. The predicted B cell epitope regions were selected by starting from responses identified in linear epitope mapping studies of patient serum and filtering to select those with high molecular dynamics-derived surface accessibility, high sequence conservation, spatial localization within functional domains of the spike glycoprotein (RBD, FP, and HR regions), and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified using these criteria. By combining these B cell and T cell analyses, we propose a set of human and murine-compatible SARS-CoV-2 vaccine peptide candidates.
    Data Types:
    • Other
    • Sequencing Data
    • Tabular Data
    • Dataset
    • Text
  • MD simulations were performed using Desmond on supercomputer TSUBAME 3.0. SARS-CoV-2 RdRp (also named nsp12) with/without template RNA and Remdesivir triphosphate complex models were placed in the orthorhombic box with a buffer distance of 10 Å in order to create a hydration model. TIP3P water model was used for creation of the hydration model. We performed MD simulations under the NPT ensemble for 1 μs on three complex structures using OPLS3e force field.
    Data Types:
    • Other
    • Dataset
  • The purpose of this experiment was to compare between-strain differences regarding avoidance behavior. Active avoidance data were collected from 40 Wistar-Kyoto (WKY) and 40 Sprague Dawley (SD) rats during a foot-shock experiment. The experiment consisted of 12 sessions each composed of 25 trials. Each trial consisted of a warning period, a possible shock period (if avoidance did not occur), and an intertrial interval (ITI) representing a safety period. During warning periods, rats had an option to press a lever in order to avoid future shock. However, if a lever press did not occur, then a shock period began during which the rats could press the lever to escape the foot-shock. After an escape or an avoidance, a 180-second safe period began (ITI). The maximum time of a warning period and a shock were both 72-seconds each if the rat failed to lever press during both periods. Every session also began with a 60-second habituation period during which the rat could familiarize itself with the experimental cage. Lever presses during ITI periods were classified as inter-trial responses (ITRs) whereas lever presses during the habituation periods were classified as anticipatory responses (ARs). Lever presses during shock periods were labeled as escapes “E” whereas lever presses during warning periods were labeled as avoidances “A”. Lever press data were discretized to 12-second periods. Frequency counts for lever presses during each 12-second timestep can be found in the raw data files (located in the “ratRL_datafiles_Model_InputOutput” folder). An example name of this file is “S09.csv” representing an SD rat or “W09.csv” representing a WKY rat. A reinforcement learning, actor-critic model was applied to this raw data to determine different learning parameters for each rat. The code for this model fitting can be found in the folder titled “ratRL_ModelFitting_Code”. Based on learning parameters determined from the reinforcement learning model code, a simulation of theoretical rats running through the experimental protocol was created. This simulation can be found in the “ratRL_Simulation_Code” folder. Inputs to this simulation are found in the “ratRL_codedTrials_Sim_InputOutput” folder. The summaries for each experimental rat’s performance during the foot-shock avoidance experiment are labeled “Sum” files (ie S09sum.csv) and the learning parameters for each rat are stored in the file called “parm_listfile.csv”. Output files are labeled “out” (ie S09out.csv) and represent the performance of a theoretical simulated rat. The differences in learning parameters between the two rat strains can provide insight into anxiety-disorders as the WKY rats have been used as an animal model for anxiety. Learning parameters can also be mapped to certain brain regions in order to explore possible neurological differences in the two strains in future experiments.
    Data Types:
    • Other
    • Software/Code
    • Tabular Data
    • Dataset
    • Text
  • Oncogenic events of cutaneous T-cell lymphomas (CTCLs) progression remain elusive. Telomere remodeling, a manifestation of genetic instability, is associated with progression of some malignancies. We aim to characterize the three-dimensional (3D) telomeric organization in CTCLs. We performed 3D telomeric quantitative FISH (3D Telo-q-FISH) of skin tissue of 9 patients with CTCL and control lymphocytes. Reported parameters included telomeres of low intensity (TLI), number and intensity of telomeric signals, telomere aggregates and nuclear volume. Stratification was based on CD30 expression and clinical stage. CTCLs had more TLIs than controls (27% vs 16%, p<0.0001). TLI proportion was higher in CD30-high cells than CD30-low cells (34% vs 22%, p<0.0001) and in the advanced group compared to the early group (30% vs 24%, p<0.0001). CD30 expression and advanced stage were associated with larger nuclei and more telomeres and advanced stage cells had significantly more aggregates. We show that 3D Telo-QFISH is feasible in small skin biopsies with limited tissue, and we report evidence that advanced CTCLs are associated with an increased proportion of TLIs, a hallmark feature in many tumor cells. Our analysis suggests that CTCL cells undergo in a first step telomere shortening and loss compared to healthy controls. In a second step further telomeric shortening associated with chromosomal rearrangements and Breakage-fusion-Bridge cycles may be involved in the progression of CTCL.
    Data Types:
    • Other
    • Tabular Data
    • Dataset
  • This dataset consists of 2702 audio files (Mono, 16 kHz, 32-bit float in *.wav format) classified as Vietnamese questions. The dataset is useful for various Vietnamese question / intention detection research and development activities. Copyright 2018 FPT Corporation Permission is hereby granted, free of charge, non-exclusive, worldwide, irrevocable, to any person obtaining a copy of this data or software and associated documentation files (the “Data or Software”), to deal in the Data or Software without restriction, including without limitation the rights to use, copy, modify, remix, transform, merge, build upon, publish, distribute and redistribute, sublicense, and/or sell copies of the Data or Software, for any purpose, even commercially, and to permit persons to whom the Data or Software is furnished to do so, subject to the following conditions: The above copyright notice, and this permission notice, and indication of any modification to the Data or Software, shall be included in all copies or substantial portions of the Data or Software. THE DATA OR SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATA OR SOFTWARE OR THE USE OR OTHER DEALINGS IN THE DATA OR SOFTWARE. Patent and trademark rights are not licensed under this FPT Public License.
    Data Types:
    • Dataset
    • Audio
  • iVR is a progress monitoring tool in near real-time using Digital Twin. it integrate extended reality with 3D laser scanners to exchange data between construction jobsite and construction office. the gap between office and site is reduced by utilizing the power of visual programming in tranferring and visualizing data in high quality and fast rate. the Virtual reality, Augmented reality and BIM technologies are used to make the virtual reality as close as possible to construction job site for Quality Assurance.
    Data Types:
    • Other
    • Dataset
    • Text
    • File Set
  • Raw data used in the article "Physical and chemical properties of natural latex biomembranes associated with phototherapy designed for healing diabetic foot ulcers". We performed physical and chemical tests to evaluate the membranes: Tensile Strength Test, Thermogravimetric Analysis, Wettability Assay and Fourier-transform infrared spectroscopy.
    Data Types:
    • Other
    • Software/Code
    • Image
    • Tabular Data
    • Dataset
    • Text
  • Threat assessments continue to conclude that terrorist groups and individuals as well as those wanting to cause harm to society have the ambition and increasing means to acquire unconventional weapons such as improvised nuclear explosive devices and radiological disposal devices. Such assessments are given credence by public statements of intent by such groups/persons, by reports of attempts to acquire radioactive material, and by law enforcement actions which have interdicted, apprehended or prevented attempts to acquire such material. As a mechanism through which to identify radioactive materials being transported on an individual’s person, this work sought to develop a detection system than is of lower-cost, reduced form-factor and more covert than existing infrastructure, while maintaining adequate sensitivity and being retrofittable into an industry standard and widely utilised Gunnebo Speed Gate system. The system developed comprised an array of six off-set Geiger-Muller detectors positioned around the gate, alongside a single scintillator detector for spectroscopy – triggered by the systems inbuilt existing IR proximity sensor. This configuration served to not only reduce the cost for such a system but also allowed for source localisation and identification to be performed. Utilising the current setup, it was possible to detect a 1 µSv/hr source carried into the Speed Gate on all of instances, alongside locating and spectrally analyzing the material.
    Data Types:
    • Other
    • Image
    • Dataset
  • These are companion data to the paper "Unblending of transcriptional condensates in human repeat expansion disease" at CELL 2020, May 7, doi: https://doi.org/10.1016/j.cell.2020.04.018 Shaon Basu, Sebastian D. Mackowiak, Henri Niskanen, Dora Knezevic , Vahid Asimi, Stefanie Grosswendt, Hylkje Geertsema, Salaheddine Ali, Ivana Jerković, Helge Ewers, Stefan Mundlos, Alexander Meissner, Daniel M. Ibrahim, Denes Hnisz It includes raw data, microscopy images, computational datasets to generate the figures in the study. Programming code is available at https://github.com/hniszlab/hoxd13 GEO data is available GSE128818
    Data Types:
    • Other
    • Software/Code
    • Image
    • Sequencing Data
    • Tabular Data
    • Document
    • Text
    • File Set
  • These files have been uploaded as a reference for the following submission to the Elsevier Journal of Reliability Engineering and System Safety: 'Consistent and Coherent Treatment of Uncertainties and Dependencies in Fatigue Crack Growth Calculations Using Multi-Level Bayesian Models' by D.Di Francesco, M.H.Faber, M.Chryssanthopoulos and U.Bharadwaj.
    Data Types:
    • Other
    • Dataset