Medizinische Fakultät
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Item Finger kinematics of natural hand movements recorded by an exoskeleton data glove in younger and elderly persons(2022) Christoph Reichert, Lisa Klemm, Avinash Kalyani, Stefanie Schreiber, Esther Kühn, Elena AzañónThe data set provides measurements using a SenseGlove DK1.3 exoskeleton data glove while healthy younger and elderly participants performed natural hand movements. Specifically, participants were asked to perform six types of hand-movements where each finger (D2-D5) was used once per trial to perform a grip movement together with the thumb resulting in a sequence of four finger movements per trial.Item Behavioral and optogenetic analyses of reinforcement processing in larval Drosophila – Raw data(Medizinische Fakultät, Otto-von-Guericke Universität Magdeburg, 2020) Weiglein, AliceUnderstanding the complexity of reward processing in the brain is one of the major challenges in the contemporary neurosciences. Using Drosophila as a model organism and state-of-the-art genetic tools as well as behavioral paradigms, the study connected to the raw data files gives novel insights in reward processing and suggests timing-dependent valence reversal as an across-species principle.Item Spatial attention shifts to colored items - an EEG-based brain-computer interface(Medizinische Fakultät, Otto-von-Guericke Universität Magdeburg, 2020) Reichert, Christoph; Tellez Ceja, Igor F.; Dürschmid, StefanThis dataset has been released as a contribution to the Frontiers Research Topic "Datasets for Brain-Computer Interface Applications" https://www.frontiersin.org/research-topics/9784/datasets-for-brain-computer-interface-applications. Here we provide EEG (electroencephalogram) data recorded during BCI (brain-computer interface) control. The BCI was intended for the decoding of binary decisions from a series of visual stimuli. The decoding task is to determine to which of the simultaneously presented items the participant shifted his/her attention. By determining the visual field in which the target was presented, the subjectively selected target color, which was associated with a “yes”/”no” response, can be determined. 18 Participants were presented with a sequence of ten visual stimuli in which a red "x"-cross and a green "+"-cross were presented simultaneously in the opposite visual hemifields. Participants associated the green cross with the word "yes" and the red cross with the word "no" while responding to questions, which were shown on the screen beforehand. They communicated their response only by directing their attention to the respective cross, while fixating their visual gaze on a cross in the center of the screen. The size and eccentricity of the symbols varied between trials. The online decoded response was presented as feedback on the screen, showing the word "yes" or "no". Before the experiment started, eye movements were recorded to determine the relationship between EOG signal strength and shift of gaze angle. For this purpose, participants were asked to track a cross jumping to peripheral positions and back to the center.Item Entwurf Notaufnahmeprotokoll V2020 - Datenelemente für Notaufnahmedokumentationssysteme Stand 27.11.2019(Medizinische Fakultät, Otto-von-Guericke Universität Magdeburg, 2019) Brammen, Dominik; Kulla, MartinDie Datenelemente für Notaufnahmedokumentationssysteme sind die Weiterentwicklung des Notaufnahmeprotokoll Datensatzes V2015.1. Diese Datendefinition definiert die Datenelemente, die während der innerklinischen Versorgung eines notfallmedizinischen Patienten in einer Notaufnahme / Notfallambulanz / Notfallzentrum erfolgt. Dabei werden externe Datenquellen wie präklinisches (prähospitales) Notfallprotokoll (z.B. Notarztprotokoll) oder Voranmeldungsdaten aus IVENA integriert. Primäres Ziel ist die medizinische Dokumentation zur Informationsweitergabe im Behandlungsverlauf. Sekundäres Ziel ist die Datenerhebung und Datenweiterleitung für Sekundärnutzer wie medizinische Register (TraumaRegister DGU, Reanimationsregister, Schlaganfallregister, Herzinfarktregister; AKTIN-NotaufnahmeRegister). Auf Basis der Datenelemente für Notalldokumentationssysteme sollen technische Artefakte wie Leitfäden für HL7 CDA oder HL7 FHIR entwickelt werden. Die Datenelemente sollen ebenfalls die Basis für Minimaldokumentationsdefinitionen (Minimaldatensätze) für spezifisch klinische Situationen in der innerklinischen Notfallmedizin darstellen, die noch entwickelt werden müssen.Item PDCD4-bound mRNA profile in T lymphocytes(Universitätskinderklinik (HL, MB-W) und Institut für Genetik (DS, MZ), Medizinische Fakultät, OVGU Magdeburg, 2017) Lingel, Holger; Schanze, Denny; Zenker, Martin; Brunner-Weinzierl, MonikaThe blockade of inhibitory receptors such as CTLA-4 (CD152) is being used as immune-checkpoint therapy, offering a powerful strategy to restore effective immune responses against tumors. To determine signal components that are induced under the control of CTLA-4 we analyzed activated murine CD8+ T cells by quantitative proteomics. Accurate mass spectrometry revealed that CTLA-4 engagement led to central changes in the phosphorylation of proteins involved in T-cell differentiation. Beside other targets, we discovered a CTLA-4-mediated induction of the translational inhibitor programmed cell death-4 (PDCD4) as a result of FoxO1 nuclear re-localization. PDCD4 further bound a distinct set of mRNAs including Glutaminase, which points out a critical role for CTLA-4 in CD8+ T-cell metabolism. Consequently, PDCD4-deficient cytotoxic T-lymphocytes (CTLs) expressed increased amounts of otherwise repressed effector molecules and ultimately led to superior control of tumor growth in vivo. These findings reveal a novel CTLA-4-mediated pathway to attenuate CTLs and indicate the importance of post-transcriptional mechanisms in the regulation of anti-tumor immune responses.Item Raw data from: T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μ m(Medizinische Fakultät, Otto-von-Guericke Universität Magdeburg, 2017) Lüsebrink, Falk; Sciarra, Alessandro; Mattern, Hendrik; Yakupov, Renat; Speck, OliverWe present an ultrahigh resolution in vivo human brain magnetic resonance imaging (MRI) dataset. It consists of T1-weighted whole brain anatomical data acquired at 7 Tesla with a nominal isotropic resolution of 250 μm of a single young healthy Caucasian subject and was recorded using prospective motion correction. The raw data amounts to approximately 1.2 TB and was acquired in eight hours total scan time. The resolution of this dataset is far beyond any previously published in vivo structural whole brain dataset. Its potential use is to build an in vivo MR brain atlas. Methods for image reconstruction and image restoration can be improved as the raw data is made available. Pre-processing and segmentation procedures can possibly be enhanced for high magnetic field strength and ultrahigh resolution data. Furthermore, potential resolution induced changes in quantitative data analysis can be assessed, e.g., cortical thickness or volumetric measures, as high quality images with an isotropic resolution of 1 and 0.5 mm of the same subject are included in the repository as well.