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  1. Article ; Online: Spatial transcriptome data from coronal mouse brain sections after striatal injection of heme and heme-hemopexin

    Kevin Akeret / Michael Hugelshofer / Dominik J. Schaer / Raphael M. Buzzi

    Data in Brief, Vol 41, Iss , Pp 107866- (2022)

    2022  

    Abstract: Hemorrhagic stroke is a major cause of morbidity and mortality worldwide. Secondary mechanisms of brain injury adversely affect functional outcome in patients after intracranial hemorrhage. Potential drivers of intracranial hemorrhage-related secondary ... ...

    Abstract Hemorrhagic stroke is a major cause of morbidity and mortality worldwide. Secondary mechanisms of brain injury adversely affect functional outcome in patients after intracranial hemorrhage. Potential drivers of intracranial hemorrhage-related secondary brain injury are hemoglobin and its downstream degradation products released from lysed red blood cells, such as free heme. We established a mouse model with stereotactic striatal injection of heme-albumin to gain insights into the toxicity mechanisms of free heme in the brain and assess the therapeutic potential of heme binding and biochemical neutralization by hemopexin. We defined the dose-dependent transcriptional effect of heme or heme-hemopexin exposure 24 h after injection by spatial transcriptome analysis of lesion-centered coronal cryosections. The spatial transcriptome was interpreted in a multimodal approach along with histology, magnetic resonance imaging, and behavioral data and reported in the associated research article “Spatial transcriptome analysis defines heme as a hemopexin-targetable inflammatoxin in the brain” [1].The spatially resolved transcriptome dataset made available here is intended for continued analysis of free heme toxicity in the brain, which is of potential pathophysiological and therapeutic significance in the context of a wide range of neurovascular and neurodegenerative diseases.
    Keywords Spatial RNA sequencing ; Secondary brain injury ; Intracerebral hemorrhage ; Heme toxicity ; Visium ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Science (General) ; Q1-390
    Language English
    Publishing date 2022-04-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Multimodal anatomy of the human forniceal commissure

    Kevin Akeret / Stephanie J. Forkel / Raphael M. Buzzi / Flavio Vasella / Irmgard Amrein / Giovanni Colacicco / Carlo Serra / Niklaus Krayenbühl

    Communications Biology, Vol 5, Iss 1, Pp 1-

    2022  Volume 11

    Abstract: Anatomical dissection and tractography elucidate the delicate nature of the human forniceal commissure, an interhemispheric white matter circuit. ...

    Abstract Anatomical dissection and tractography elucidate the delicate nature of the human forniceal commissure, an interhemispheric white matter circuit.
    Keywords Biology (General) ; QH301-705.5
    Language English
    Publishing date 2022-07-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Topographic brain tumor anatomy drives seizure risk and enables machine learning based prediction

    Kevin Akeret / Vittorio Stumpo / Victor E. Staartjes / Flavio Vasella / Julia Velz / Federica Marinoni / Jean-Philippe Dufour / Lukas L. Imbach / Luca Regli / Carlo Serra / Niklaus Krayenbühl

    NeuroImage: Clinical, Vol 28, Iss , Pp 102506- (2020)

    2020  

    Abstract: Objective: The aim of this study was to identify relevant risk factors for epileptic seizures upon initial diagnosis of a brain tumor and to develop and validate a machine learning based prediction to allow for a tailored risk-based antiepileptic therapy. ...

    Abstract Objective: The aim of this study was to identify relevant risk factors for epileptic seizures upon initial diagnosis of a brain tumor and to develop and validate a machine learning based prediction to allow for a tailored risk-based antiepileptic therapy. Methods: Clinical, electrophysiological and high-resolution imaging data was obtained from a consecutive cohort of 1051 patients with newly diagnosed brain tumors. Factor-associated seizure risk difference allowed to determine the relevance of specific topographic, demographic and histopathologic variables available at the time of diagnosis for seizure risk. The data was divided in a 70/30 ratio into a training and test set. Different machine learning based predictive models were evaluated before a generalized additive model (GAM) was selected considering its traceability while maintaining high performance. Based on a clinical stratification of the risk factors, three different GAM were trained and internally validated. Results: A total of 923 patients had full data and were included. Specific topographic anatomical patterns that drive seizure risk could be identified. The involvement of allopallial, mesopallial or primary motor/somatosensory neopallial structures by brain tumors results in a significant and clinically relevant increase in seizure risk. While topographic input was most relevant for the GAM, the best prediction was achieved by a combination of topographic, demographic and histopathologic information (Validation: AUC: 0.79, Accuracy: 0.72, Sensitivity: 0.81, Specificity: 0.66). Conclusions: This study identifies specific phylogenetic anatomical patterns as epileptic drivers. A GAM allowed the prediction of seizure risk using topographic, demographic and histopathologic data achieving fair performance while maintaining transparency.
    Keywords Epilepsy ; Metastases ; Glioma ; Primary central nervous system lymphoma ; Generalized additive model ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurology. Diseases of the nervous system ; RC346-429
    Subject code 610
    Language English
    Publishing date 2020-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Anatomical features of primary brain tumors affect seizure risk and semiology

    Kevin Akeret / Carlo Serra / Omar Rafi / Victor E. Staartjes / Jorn Fierstra / David Bellut / Nicolai Maldaner / Lukas L. Imbach / Fabian Wolpert / Rositsa Poryazova / Luca Regli / Niklaus Krayenbühl

    NeuroImage: Clinical, Vol 22, Iss , Pp - (2019)

    2019  

    Abstract: Objective: An epileptic seizure is the most common clinical manifestation of a primary brain tumor. Due to modern neuroimaging, detailed anatomical information on a brain tumor is available early in the diagnostic process and therefore carries ... ...

    Abstract Objective: An epileptic seizure is the most common clinical manifestation of a primary brain tumor. Due to modern neuroimaging, detailed anatomical information on a brain tumor is available early in the diagnostic process and therefore carries considerable potential in clinical decision making. The goal of this study was to gain a better understanding of the relevance of anatomical tumor characteristics on seizure prevalence and semiology. Methods: We reviewed prospectively collected clinical and imaging data of all patients operated on a supratentorial intraparenchymal primary brain tumor at our department between January 2009 and December 2016. The effect of tumor histology, anatomical location and white matter infiltration on seizure prevalence and semiology were assessed using uni- and multivariate analyses. Results: Of 678 included patients, 311 (45.9%) presented with epileptic seizures. Tumor location within the central lobe was associated with higher seizure prevalence (OR 4.67, 95% CI: 1.90–13.3, p = .002), especially within the precentral gyrus or paracentral lobule (100%). Bilateral extension, location within subcortical structures and invasion of deeper white matter sectors were associated with a lower risk (OR 0.45, 95% CI: 0.25–0.78; OR 0.10, 95% CI: 0.04–0.21 and OR 0.39, 95% CI: 0.14–0.96, respectively). Multivariate analysis revealed the impact of a location within the central lobe on seizure risk to be highly significant and more relevant than histopathology (OR: 4.79, 95% CI: 1.82–14.52, p = .003). Seizures due to tumors within the central lobe differed from those of other locations by lower risk of secondary generalization (p < .001). Conclusions: Topographical lobar and gyral location, as well as extent of white matter infiltration impact seizure risk and semiology. This finding may have a high therapeutic potential, for example regarding the use of prophylactic antiepileptic therapy. Keywords: Anatomy, Brain tumor, Central lobe, Epilepsy, Glioma, Histology, Seizures, Topography, White ...
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurology. Diseases of the nervous system ; RC346-429
    Subject code 610
    Language English
    Publishing date 2019-01-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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