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Decoding astrocytic identity shifts post-injury: implications for neuronal reprogramming
Get PDFThe regenerative capacity of the central nervous system (CNS) in the adult mammalian brain is severely limited, often leading to irreversible neuronal loss and functional decline following injury or disease. Astrocytes, the predominant glial cells in the CNS, play crucial roles in maintaining neural homeostasis, supporting the blood-brain barrier, and facilitating neuronal and synaptic functions. Upon injury or disease, these cells undergo reactive astrogliosis, significantly altering their function and phenotype. Notably, following invasive injuries, a subset of astrocytes has been observed to acquire proliferative capacity, express markers characteristic of neural stem cells (NSCs), and demonstrate the ability to self-renew and form multipotent neurospheres in vitro. This discovery adds a new dimension to our understanding of the neurogenic potential in the adult brain, which was previously thought to be limited and confined to specialized neurogenic niches such as the subventricular zone (SVZ) and the hippocampal dentate gyrus. However, the scarcity of these plastic astrocytes (occurring in low frequency) and the lack of distinct molecular markers have hindered their study and subsequent application in CNS repair strategies. Therefore, the thesis aims to 1) identify specific marker genes of this plastic astrocytic subset following stab wound injuries in the mouse cortex and 2) explore their potential in regenerative strategies, such as direct neuronal reprogramming.
To identify putative markers for plastic astrocytes post-injury, a trans-species approach was adopted, leveraging regenerative insights from zebrafish ependymoglia, and integrating them with astrocyte populations in a mouse stab wound model through single-cell transcriptomic integration analysis. This method enabled the identification of key marker genes, such as Hmgb2 (High Mobility Group Box 2) and others, characterizing this distinct plastic astrocytic subset. These markers are expressed in a small subset of astrocytes emerging post-injury, demonstrating proliferation and capability of forming neurospheres in vitro. Subsequent investigation revealed that these plastic astrocytic subsets exhibit transcriptional similarities to transient amplifying progenitors (TAPs) in the SVZ. They display a partial trajectory towards neurogenic lineages while retaining gliogenic potentials due to distinct signalling pathways, compared to bonafide TAPs.
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The identification of Hmgb2, a chromatin-associated protein, through this comparative analysis, underscores its potential role in the reprogramming process, likely due to its involvement in chromatin remodelling—a critical step in activating neurogenic programs. Overexpressing Hmgb2 alongside the pioneer transcription factor Neurog2 in vitro, under culture conditions mimicking the in vivo injury microenvironment, significantly enhances the efficiency of neuronal conversion of astrocytes to induced neurons (iNs). This improvement is attributed to the chromatin remodelling effects of Hmgb2, which facilitate accessibility and expression of neurogenic or reprogramming relevant genes, as evidenced by analysis of chromatin (ATAC-Seq) and transcriptome (RNA-Seq) data, along with the promoting maturation of iNs.
In summary, this study illuminates astrocyte plasticity following CNS injury, identifies crucial marker genes, and lays the groundwork for exploring their stem cell potential. Additionally, it underscores their significance in strategies for neuronal replacement, such as direct neuronal reprogramming. Together, these findings pave the way for advancing astrocyte research in regenerative medicine and repair approaches
Behavior and effect of nanoparticles in the pulmonary microcirculation
Get PDFThe lung, with its large surface area and thin air-blood barrier, presents an ideal site for drug delivery and serves as the main entry portal for inhaled particles. Additionally, the abundant pulmonary capillary bed provides an important surface for interactions with particles suspended in the bloodstream. Therefore, engi- neered nanoparticles (NPs) offer promising prospects for precision drug delivery to the lung. However, despite the potential benefits of NPs, their interactions and possible adverse effects in the pulmonary microcirculation under both healthy and pathophysiological conditions remain largely unknown. Understanding these in- teractions is crucial for harnessing the full potential of NPs in lung-specific drug delivery and ensuring their safety and efficacy for clinical applications.
To visualize and quantify the real-time dynamics of intravenously delivered or injected NPs and their interactions with the pulmonary vascular innate immune system, we utilized intra-vital microscopy of the alveolar region in mice. The NPs used in the study were divided into two distinct subsets: one usually considered of a low potential for interacting with biomolecules and cells (PEG-amine-QDs, referred to as aQDs), and the other with a high potential for such interactions (carboxyl-QDs, referred to as cQDs).
In vitro experiments demonstrated that cQDs were taken up more efficiently by Human Umbilical Vein Endothelial Cells compared to aQDs. In vivo experiments revealed that intravenously applied cQDs interacted with endothelial cells and might be taken up by them. In contrast, aQDs tended to form clusters in pulmo- nary vessels over time and induced stronger inflammation compared to cQDs, indicating that the PEG modification of QDs did not fully protect against their po- tential effects in the pulmonary microcirculation.
Under healthy conditions, i.v. injection of aQDs induced neutrophil recruitment, but did not significantly alter the immune responses under pathological conditions, such as LPS-induced acute inflammation and Bleomycin-induced fibrosis. The initiation of neutrophil recruitment induced by aQDs was found to require cellular degranulation and release of TNF-α. Furthermore, neutrophil response to aQDs appeared to involve the release of damage-associated molecular patterns (DAMPs), particularly extracellular ATP (eATP). This process also involved the upregulation of relevant selectins (such as E-selectin) and the involvement of in- tegrins (such as LFA-1 and MAC-1) on endothelial cells and neutrophils. These, in turn, resulted in a slowdown of the crawling velocity of neutrophils on the vas- cular surface. The blockage of selectins and integrins or the use of an eATP an- tagonist prevented recruitment of neutrophils and partially restored their reduced crawling velocity. Furthermore, the accumulation and retention of neutrophils in the pulmonary microcirculation led to a decrease in local blood flow velocity. Ac- cordingly, when factors involved in neutrophil recruitment, such as cellular degranulation, DAMPs, and TNF-α release, as well as the upregulation of se- lectins and integrins, were diminished, blood perfusion could be restored to base- line levels.
Overall, this study unveils a detailed mechanism underlying the neutrophil re- sponse to aQDs, involving cellular degranulation, DAMPs and TNF-α release, as well as the upregulation of selectins and integrins. This intricate cascade ulti- mately leads to a reduced velocity of crawling neutrophils and a slowdown in blood perfusion. These insights pave the way for further exploration and optimi- zation of NP-based drug delivery strategies, aiming to enhance efficacy and safety in medical applications
Blood coagulation factors as possible risk factors for cardiovascular diseases in a population-based cross-sectional study
Get PDFBackground and purpose: Even though many risk factors for cardiovascular diseases (CVD), especially for myocardial infarction (MI) and ischemic stroke (IS), are already well known and researched, there are still not enough representative population-based studies in the field of primary prevention, which investigated deep vein thrombosis (DVT) and pulmonary embolism (PE). Particularly, there is little research on blood coagulation factors and their impact as possible risk factors on venous thrombosis (VT) in the adult population.
Methods: The prevalence of common risk factors of CVD were described in the population-based KORA-Fit study (n = 3,059). In a subsample (KORA-Fit (S4), n = 805) also the blood concentrations of hemostatic factors were determined and their association with the CVD risk was analyzed. For statistical analysis multivariable logistic regression models were used.
Results: In KORA-Fit study overall 9.7% of the participants had been diagnosed with MI, IS or VT. 4.6% of all participants suffered from VT (3.7% men and 5.3% women). Participants with a VT diagnosis were older, had higher Body Mass Index, suffered from diabetes mellitus more often (14.5% versus 7.8% in participants without VT) and took more anticoagulants (17.9%) and other medication (30.7%). Regarding clinical laboratory parameters lower glomerular filtration rate, higher liver enzymes (GGT, AST, ALT) and higher levels of inflammatory markers (hsCRP) in participants with VT were observed.
The regression analysis indicated, that higher levels of fibrinogen are associated with higher risk of VT and MI. Factor VIII showed positive correlation only to VT. Plasma protein C had, however, an inverse association with VT. There was no correlation between analyzed blood coagulation factors and the prevalence of ischemic stroke.
Conclusions: In this population-based study a significant correlation between blood coagulation factors and cardiovascular diseases was observed. The evaluation of hemostatic factors in the adult population, such as fibrinogen, factor VIII, or protein C may help to develop the field of primary prevention of CVD and should be a subject of further research
Klinisches Outcome prämorbid funktionell abhängiger Schlaganfallpatienten nach Verlegung zur endovaskulären Thrombektomie in einem telemedizinischen Netzwerk
Get PDFAttention-based neural sequence-to-sequence methods for information extraction and text summarization
Get PDFNatural language processing (NLP) is an essential technology in the information age. There is a large variety of machine learning models powering NLP applications. Recently, deep learning approaches have obtained exciting performance across a broad range of NLP tasks. Such models are often trained end-to-end and are more efficient and cost-effective than traditional task-specific feature engineering. In this dissertation, we focus on several NLP tasks using a specific deep learning technique -- sequence-to-sequence (seq2seq).
We first explore the fine-grained entity mention classification problem, an instance of naturally occurring hierarchical learning, where an entity mention in a given context or a sentence can have one or more fine-grained types, e.g., Obama is both a politician and an author in a context in which his election is related to his prior success as a best-selling author. We model the structure of the hierarchy more directly than standard approaches of flat and local classification. This reorganization of problem and utilization of seq2seq model has the advantage (compared to prior work of hierarchical entity classification) that our architecture can be trained end-to-end. Experiments show that our model performs better than prior work on the FIGER dataset.
Second, we investigate a key problem in information extraction: entity-driven relation extraction. Given a large text corpus, a query entity Q (e.g., Q = "Steve Jackson") and a predefined relational schema, a system has to extract a set of facts from the corpus that are oriented to this schema, e.g., "Q authored notable work with title X" linked to schema class \verb=per:notable_work=. We define the task of Open-Type Relation Argument Extraction (ORAE), where the model has to extract relation arguments without being able to rely on an entity extractor to find the argument candidates. In ORAE, we circumvent the use of additional entity taggers and let the relation extraction module perform this task implicitly. We propose a set of relation extraction models such as traditional CRF-based sequence taggers and seq2seq-based pointer networks.
Third, we define the task of teaser generation and provide an evaluation benchmark and baseline systems for the process of generating teasers. A teaser is a short reading suggestion for an article that is illustrative and includes curiosity-arousing elements to entice potential readers to read particular news items. We compile a novel dataset of teasers by systematically accumulating tweets and selecting those that conform to the teaser definition. We compare several seq2seq-based abstractive summarization systems on the task of teaser generation.
Fourth, we address summarization of interleaved text in a low-resource setting. Interleaved text refers to the phenomenon of posts belonging to different threads occurring in a sequence. This commonly occurs in online chat posts. It can be time-consuming to quickly obtain an overview of such a discussion. An end-to-end trainable summarization system obviates the need of explicit disentanglement; however, such a system requires a large amount of labeled data. To address this, we propose to pretrain an end-to-end trainable hierarchical seq2seq system using synthetic interleaved texts. We show that by fine-tuning on a real-world meeting dataset (AMI), such a system outperforms a traditional two-step system by 22%.
Fifth, we investigate the radiology report summarization task. The Impressions section of a radiology report about an imaging study is a summary of the radiologist’s reasoning and conclusions, and it also aids the referring physician in confirming or excluding certain diagnoses. To automatically generate an abstractive summary of the typical information-rich radiology report requires the acquisition of salient content from the report and the generation of a concise, easily consumable Impressions section. To achieve that, we design a two-step approach:
extractive summarization followed by abstractive summarization. We additionally break down the extractive part into two independent tasks: extraction of salient (1) sentences and (2) keywords. We show our novel approach leads to a more precise summary compared to single-step and to two-step-with-single-extractive-process baselines with an overall improvement in F1 score of 3-4%
Diagnostik episodischer Schwindelsyndrome
Get PDFBislang werden verschiedene neurootologische Diagnosen, wie z.B. der Morbus Menière oder die sog. Vestibuläre Migräne, allein auf der Basis einer Definition klinischer Symptome gestellt. Da sich diese bei beiden Krankheiten deutlich überlappen, ist eine eindeutige Zuordnung nicht immer möglich. Die Therapie beider Erkrankungen unterscheidet sich grundlegend, weshalb nach zusätzlichen Parametern gesucht wird, die eine genauere Diagnosestellung ermöglichen. So wird vermehrt z.B. die Bildgebung des Innenohrs mit der Magnetresonanztomographie (MRT) eingesetzt, um Pathologien im Innenohr aufzudecken wie u.a. eine Störung der Endolymph-Flüssigkeit. Ein Ungleichgewicht zwischen Endolymphbildung und Resorption kann zu einer Flüssigkeitsansammlung, dem sog. Endolymphhydrops (ELH), führen, welcher lange Zeit als pathognomonisch für den Morbus Menière gesehen wurde. Allerdings konnte inzwischen auch bei anderen neurootologischen Erkrankungen ein ELH nachgewiesen werden, weshalb exakte Auswertemethoden notwendig sind, um dessen pathologische Relevanz und krankheitstypische Muster besser zu verstehen.
Diese Dissertation befasst sich mit der Entwicklung, Testung und Anwendung einer quantifizierenden Methode der Innenohrbildgebung mit Hilfe kontrastmittelverstärkter, verzögerter MRT. Hiermit kann kontrastmittelangereicherte Perilymphflüssigkeit mit speziellen MRT-Sequenzen nachgewiesen werden. Basis der Quantifikation ist dabei ein dreidimensional und automatisch ablaufender Algorithmus, der die kontrastmittelverstärkte Perilymphe von der Endolymphe (welche kein KM aufnimmt) differenzieren kann. Ziel war es, in der Auswahl der verwendeten Software auf proprietäre, kommerziell vertriebene Software so weit wie möglich zu verzichten. Die entwickelten Lösungsansätze sollten für den klinischen Alltag praktikable Ansprüche bezüglich Rechenleistung und Bearbeitungszeit stellen.
Die Arbeit „VOLT: a novel open-source pipeline for automatic segmentation of endolymphatic space in inner ear MRI“ befasst sich mit der semiautomatischen Auswertung von Innenohr-MRT-Aufnahmen. Auf Basis von local-thresholding-Algorithmen wurde eine valide Methode entwickelt, die bereits in Folgestudien Anwendung fand. Zur Segmentation wurde eine Deep-Learning-Anwendung eingesetzt. Mit einem artifiziellen dreidimensionalen Testvolumen wurde die Leistung der Methode auf Rohdaten mit Bewegungs- oder Rauschartefakten geprüft. Es zeigte sich ein der manuellen Segmentation ebenbürtiges Ergebnis und eine Überlegenheit insbesondere bei artefaktreicheren Daten. Die berechneten Volumina korrelierten hochsignifikant mit den klinischen Graduierungen.
Ziel der Arbeit „Intravenous delayed gadolinium-enhanced MR imaging of the endolymphatic space: A methodological comparative study“ war die klinische Anwendung der neuen semiquantitativen Methodik bei einem größeren Datensatz, um mögliche Fallstricke im alltäglichen Gebrauch zu testen und um die Leistungen im Vergleich zu etablierten schnittbasierten Quantifizierungs-methoden zu überprüfen. Dazu wurde VOLT bei insgesamt 216 Innenohren von 75 Menière-Patient:innen (55.2 ± 14.9 Jahre) sowie 33 gesunden Proband:innen (46.4 ± 15.6 Jahre) angewendet. Hier zeigte sich ein nur geringer Einfluss von Signal-Rausch-Verhältnis auf die Graduierungen und eine insgesamt gute Korrelation aus klinischer Graduierung und VOLT-Volumina. Für die klinische Einordnung der verschiedenen Krankheitsentitäten waren die ELH-Asymmetrie und die normalisierten ELH-Volumina am aussagekräftigsten.
Zusammengefasst behandelt diese Dissertation somit eine neuartige Quantifizierungsmethode zur Innenohrbildgebung, die schnell, einfach und günstig anwendbar ist und zur besseren Vergleichbarkeit von Innenohr-MRTs und damit zur besseren Abgrenzung verschiedener Erkrankungen beitragen kann.To date, various neuro-otological diagnoses, such as Meniere's disease or vestibular migraine, have been made solely on the basis of clinical symptoms. As these often overlap in both diseases, a clear classification is not always possible. The treatment of both diseases differs fundamentally, which is why additional parameters are being sought to enable a more precise diagnosis. For example, magnetic resonance imaging (MRI) is increasingly being used to detect pathologies in the inner ear, such as disorders of the endolymphatic fluid. An imbalance between endolymph formation and resorption can lead to an accumulation of fluid, the so-called endolymphatic hydrops (ELH), which for a long time was seen as pathognomonic for Meniere's disease. However, ELH has now also been demonstrated in other neuro-otologic diseases, which is why precise evaluation methods are necessary to better understand its pathological relevance and disease-typical patterns.
This dissertation deals with the development, testing and application of a quantifying method of inner ear imaging using contrast-enhanced delayed MRI. This allows contrast-enhanced perilymph fluid to be detected using special MRI sequences. The quantification is based on a three-dimensional and automatic algorithm that can differentiate the contrast-enhanced perilymph from the endolymph (which does not absorb contrast agent). The aim was to avoid proprietary, commercially marketed software as far as possible. The solutions developed were to meet practical requirements in terms of computing power and processing time for everyday clinical practice.
The study "VOLT: a novel open-source pipeline for automatic segmentation of endolymphatic space in inner ear MRI" deals with the semi-automatic evaluation of inner ear MRI images. Based on local-thresholding algorithms, a valid method was developed, which has already been used in follow-up studies. A deep learning application was used for segmentation. An artificial three-dimensional test volume was used to test the performance of the method on raw data with motion or noise artifacts. The results were on a par with manual segmentation and showed superior scores especially for data with more artifacts. The calculated volumes correlated highly significantly with the clinical graduations.
The aim of the study "Intravenous delayed gadolinium-enhanced MR imaging of the endolymphatic space: A methodological comparative study" was the clinical application of the new semi-quantitative methodology on a larger data set to test potential pitfalls in everyday use and to verify the performance in comparison to established slice-based quantification methods. For this purpose, VOLT was applied to a total of 216 inner ears of 75 Meniere's patients (55.2 ± 14.9 years) and 33 healthy subjects (46.4 ± 15.6 years). Here, there was only a slight influence of signal-to-noise ratio on the graduations and an overall good correlation between clinical graduation and VOLT volumes. The ELH asymmetry and the normalized ELH volumes were the most meaningful for the clinical classification of the different disease entities.
In summary, this dissertation deals with a novel quantification method for inner ear imaging that is quick, easy and inexpensive to use and can contribute to better comparability of inner ear MRIs and thus to better differentiation of different diseases
Reciprocal regulation of mTORC1 and ribosomal biosynthesis determines cell cycle progression in activated T cells
Get PDFIn-vivo-Quantifizierung neuronaler Netzwerk-Veränderungen mittels metabolischer Konnektivität in Mausmodellen neurodegenerativer Erkrankungen
Get PDFAmong functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (β-amyloid and tau) by use of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging. We compared the results of FDG-µPET MC with conventional VOI-based analysis and behavioral assessment in the Morris water maze (MWM). The impact of awake versus anesthesia conditions on MC read-outs was studied and the robustness of MC data deriving from different scanners was tested. MC proved to be an accurate and robust indicator of functional connectivity loss when sample sizes ≥12 were considered. MC readouts were robust across scanners and in awake/ anesthesia conditions. MC loss was observed throughout all brain regions in tauopathy mice, whereas β-amyloid indicated MC loss mainly in spatial learning areas and subcortical networks. This study established a methodological basis for the utilization of MC in different β-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.
Background: In vivo assessment of neuroinflammation by 18-kDa translocator protein positron-emission-tomography(TSPO-PET) ligands receives growing interest in preclinical and clinical research of neurodegenerative disorders. Higher TSPOPET binding as a surrogate for microglial activation in females has been reported for cognitively normal humans, but such effects have not yet been evaluated in rodent models of neurodegeneration and their controls. Thus, we aimed to investigate the impact of sex on microglial activation in amyloid and tau mouse models and wild-type controls.
Methods: TSPO-PET (18F-GE-180) data of C57Bl/6 (wild-type), AppNL-G-F (β-amyloid model), and P301S (tau model) mice was assessed longitudinally between 2 and 12 months of age. The AppNL-G-F group also underwent longitudinal β-amyloid-PET imaging (Aβ-PET; 18F-florbetaben). PET results were confirmed and validated by immunohistochemical investigation of microglial (Iba-1, CD68), astrocytic (GFAP), and tau (AT8) markers. Findings in cerebral cortex were compared by sex using linear mixed models for PET data and analysis of variance for immunohistochemistry.
Results: Wild-type mice showed an increased TSPO-PET signal over time (female +23%, male +4%), with a significant
sex × age interaction (T = − 4.171, p < 0.001). The Aβ model AppNL-G-F mice also showed a significant sex × age
interaction (T = − 2.953, p = 0.0048), where cortical TSPO-PET values increased by 31% in female AppNL-G-F mice, versus only 6% in the male mice group from 2.5 to 10months of age. Immunohistochemistry for the microglial markers Iba-1
and CD68 confirmed the TSPO-PET findings in male and female mice aged 10 months. Aβ-PET in the same AppNL-G-F
mice indicated no significant sex × age interaction (T = 0.425, p = 0.673). The P301S tau model showed strong cortical
increases of TSPO-PET from 2 to 8.5 months of age (female + 32%, male + 36%), without any significant sex × age
interaction (T = − 0.671, p = 0.504), and no sex differences in Iba-1, CD68, or AT8 immunohistochemistry