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The prefrontal cortex (PFC) is considered the cognitive center of the mammalian brain. It is involved in a variety of cognitive functions such as decision making, working memory, goal-directed behavior, processing of emotions, flexible action selection, attention, and others (Fuster, 2015). In rodents, these functions are associated with the medial prefrontal cortex (mPFC). Experiments in mice and rats have shown that neurons in the mPFC are necessary for successful performance of many cognitive tasks. Moreover, measurements of neural activity in the mPFC show excitation or inhibition in different cells in relation to specific aspects of the tasks to be solved. To date, however, it is largely unknown whether prefrontal neurons are stably activated during the same behaviors within a task and whether similar aspects are represented by the same neurons in different tasks. In addition, it is unclear how specifically neurons are activated, for example, whether cells that are activated in response to reward are activated in a different task without reward in a different situation or remain inactive. To address these questions, we recorded the same neurons in the mPFC of mice over the course of several weeks while the animals performed various behaviors.
To do this, we expressed GCaMP6 in pyramidal neurons in the mPFC of mice. A small lens was implanted in the same location and a miniature microscope ("miniscope") was used to record neural activity. Later the extracted neurons got aligned based on their shape and position across multiple days and sessions. The mice performed five different behavioral tests while neural activity was measured: A spatial working memory test in a T-maze, exploration of the elevated plus maze (EPM), a novel object recognition (NO) test including free open field (OF) exploration, a social interaction (SI) test and discriminatory auditory fear conditioning (FC). Each task was repeated at least twice to check for stable task encoding across sessions. Behavioral performance and neural correlates to specific task events were similar to earlier studies across all tasks. We utilized generalized linear models (GLM) to determine which behavioral variables most strongly influence neural activity in the mPFC. The position of the mouse in the environment was found to explain most of the variance in neural activity, together with movement speed they were the strongest predictors of neural activity across all tasks. Reward time points in the working memory test, the conditioned stimulus after fear conditioning, or head direction in general were also strongly encoded in the mPFC.
Many of the recorded neurons showed a stable spatial activity profile across multiple sessions of the same task. Similarly, cells that coded for position in one task tended to code for position in other tasks. Not only did the same cells code for position across multiple tasks, but cells also coded for movement speed and head direction. This indicates that at least these general behavioral variables are each represented by the same neurons in the mPFC. Interestingly, the stability of position or speed coding did not depend on the time between two sessions, but only on whether it was within the same or across different tasks. Within the same task, stability was slightly higher than across different tasks.
To find out whether task-specific behavioral aspects were also stably encoded in the mPFC, difference scores as the difference in neural activity between two task aspects like left- and right-choice trials or exposed and enclosed locations were calculated. Many cells encoded these aspects stably across different sessions of each task. Both the left-right differences in the different phases of the working memory test, the open-closed-arm differences in the elevated plus maze, the different activity between center and corners in the open field, the social target-object differences in the social interaction test, and the differences between the two tones during fear conditioning were all stably encoded across the population of mPFC cells. Only the distinction between the novel and the familiar object during object recognition was not stably encoded, but also the preference for the novel object was not present in the second session of novel object exploration.
There was also an overlap in coding for different aspects within a task across multiple sessions. For example, cells stably encoded left-right differences in the T-maze between different sessions as a function of walking direction across different phases of working memory, an aspect that we could already show within one session (Vogel, Hahn et al., 2022). During fear conditioning, the same cells showed a discrimination between CS+ and CS- that also responded to the start of CS+.
Consistency in the neurons activity across different tasks was also found, but only between tasks with similar demands, the elevated plus-maze and free exploration of the open field. Cells that were more active in the open arms also showed more activity in the center of the open field and vice versa. This could be an indicator that the cells were coding for anxiety or exposure across those tasks, indicating that neurons in the mPFC also stably encode general task aspects independent of the specific environment. However, it remains unclear what exactly these neurons encode; in the case of a general fear signal, one would also expect activation during fear conditioning which could not be found.
Overall, we found that neurons in the mPFC of mice encoded multiple general behavioral variables across multiple tasks and task-specific variables were encoded stably within each of the tested tasks. However, we found little task-specific variables that were systematically encoded by the same neurons with the exception being the elevated plus-maze and open field exploration, two tasks with similar features.
Long non-coding RNAs are a very versatile class of molecules that can have important roles in regulating a cells function, including regulating other genes on the transcriptional level. One of these mechanisms is that RNA can directly interact with DNA thereby recruiting additional components such as proteins to these sites via an RNA:dsDNA triplex formation. We genetically deleted the triplex forming sequence (FendrrBox) from the lncRNA Fendrr in mice and found that this FendrrBox is partially required for Fendrr function in vivo. We found that the loss of the triplex forming site in developing lungs causes a dysregulation of gene programs associated with lung fibrosis. A set of these genes contain a triplex site directly at their promoter and are expressed in lung fibroblasts. We biophysically confirmed the formation of an RNA:dsDNA triplex with target promoters in vitro. We found that Fendrr with the Wnt signalling pathway regulates these genes, implicating that Fendrr synergizes with Wnt signalling in lung fibrosis.
Die Ergebnisse der Studie und die Diversität der Datenbanken ist groß.
Für 12 Datenbanken wurde ein Punktesystem mit elf Items entworfen, um die Qualität der einzelnen Datenbanken zu objektivieren. Keine Datenbank konnte alle Bewertungskriterien erfüllen. Der insgesamt schlechte Punktedurchschnitt ist ein Indikator für die Mängel der aktuell verfügbaren Datenbanken. Außerdem konnten wir einen Qualitätsunterschied zwischen kostenpflichtigen und kostenfreien Datenbanken beweisen und mussten im Zuge dieser Ergebnisse die Frage stellen, ob kostenfreie Datenbanken überhaupt nützlich sind. Zwischen den kostenpflichtigen Datenbanken fallen die Qualitätsunterschiede weniger gravierend aus, wenngleich Stärken und Schwächen sich deutlich unterscheiden. Die häufigsten Wechselwirkungen wurden in allen Datenbanken mit großem Abstand zwischen rein psychiatrischen Interaktionspaaren erfasst. Dieses zeigt, wie wechselwirkungsreich Psychopharmaka sind und dass psychiatrische Patienten besonders vulnerabel sind. Die Nutzung digitaler Hilfsmittel scheint bei Betrachtung der hohen Anzahl ausgegebener Warnmeldungen unabdingbar zu sein, dennoch existiert große Uneinheitlichkeit bei der Bewertung der einzelnen Interaktionen. Die Vorstellung, dass zwei Kliniker bei Nutzung zweier unterschiedlicher Datenbanken zu völlig unterschiedlichen Empfehlungen kommen, fällt nicht schwer. Gleichzeitig könnte die Kooperation von Heilberuflern, die unterschiedliche Datenbanken verwenden, die Chance auf zusätzlichen Informationsgewinn und Austausch erhöhen, was im Umkehrschluss in einer erhöhten Arzneimitteltherapiesicherheit resultiert. In Studien konnte der positive Effekt interdisziplinärer Zusammenarbeit bereits bewiesen werden.
Zusammenfassend konnten umfangreiche Differenzen zwischen allen untersuchten Datenbanken aufgezeigt werden. Um den Anforderungen des klinischen Alltags zu genügen, müssen digitale Unterstützungssysteme weiterentwickelt werden.
Die „ideale Datenbank“ gibt es bisher nicht – das lässt sich durch unser Punktesystem beweisen. Um im klinischen Alltag Patientensicherheit zu gewährleisten ist die Nutzung einer einzelnen Datenbank bisher nicht ausreichend.
Die Gewährung der Patientensicherheit sollte unser oberstes Ziel sein und um dieses zu erreichen, bedarf es vieler Komponenten. Neben der Nutzung und vor allem Weiterentwicklung digitaler Unterstützungssysteme sollte auch der zwischenmenschliche Austausch weiter gefördert werden. Interdisziplinäre Zusammenarbeit im Sinne pharmazeutischer Dienstleistungen zur Medikationsanalyse könnten ein zusätzliches Instrument zur Vermeidung arzneimittelbezogener Probleme werden.
Zukünftig werden unsere Patienten am meisten von optimaler Nutzung weiterentwickelter Technologien, sowie wachsendem zwischenmenschlichem Austausch profitieren.
Off-central heavy-ion collisions are known to feature magnetic fields with magnitudes and characteristic gradients corresponding to the scale of the strong interactions. In this work, we employ equilibrium lattice simulations of the underlying theory, QCD, involving similar inhomogeneous magnetic field profiles to achieve a better understanding of this system. We simulate three flavors of dynamical staggered quarks with physical masses at a range of magnetic fields and temperatures, and extrapolate the results to the continuum limit. Analyzing the impact of the field on the quark condensate and the Polyakov loop, we find non-trivial spatial features that render the QCD medium qualitatively different as in the homogeneous setup, especially at temperatures around the transition. In addition, we construct leading-order chiral perturbation theory for the inhomogeneous background and compare its prediction to our lattice results at low temperature. Our findings will be useful to benchmark effective theories and low-energy models of QCD for a better description of peripheral heavy-ion collisions.
Off-central heavy-ion collisions are known to feature magnetic fields with magnitudes and characteristic gradients corresponding to the scale of the strong interactions. In this work, we employ equilibrium lattice simulations of the underlying theory, QCD, involving similar inhomogeneous magnetic field profiles to achieve a better understanding of this system. We simulate three flavors of dynamical staggered quarks with physical masses at a range of magnetic fields and temperatures, and extrapolate the results to the continuum limit. Analyzing the impact of the field on the quark condensate and the Polyakov loop, we find non-trivial spatial features that render the QCD medium qualitatively different as in the homogeneous setup, especially at temperatures around the transition. In addition, we construct leading-order chiral perturbation theory for the inhomogeneous background and compare its prediction to our lattice results at low temperature. Our findings will be useful to benchmark effective theories and low-energy models of QCD for a better description of peripheral heavy-ion collisions.
Das Ziel in der vorliegenden systematischen Literaturrecherche ist es, den aktuellen Stand des Wissens über die Erfolgsfaktoren von Einzelzahnimplantaten, bei denen eine Sofortbelastung auf den provisorischen Implantatkronen zum Antagonisten erfolgt, wiederzugeben. In diesem Rahmen wurden Zusammenhänge zwischen der Implantatüberlebensrate, der Primärstabilität, der Implantatregion, des Implantatdesigns und des Implantationszeitpunktes getrennt nach okklusalem Belastungsprotokoll (mit versus ohne antagonistische Okklusionskontakte auf den provisorischen Implantatkronen) und der postoperativen Verhaltensweisen der Patienten analysiert. Der Prozess der systematischen Literaturrecherche wurde nach den PRISMA-Guidelines für den Suchzeitraum von 2012 bis 2022 durchgeführt.
Um die Forschungsfrage zu beantworten, wurde eine qualitative Analyse in deskriptiver Form durchgeführt.
In den analysierten Studien, wurde am häufigsten ein Eindrehmoment von ≥ 35 Ncm als Kriterium für eine Sofortbelastung gewählt. Die meisten Implantate wurden in der Oberkieferregion 15 bis 25 inseriert. Bei den Implantatkronen mit antagonistischen Okklusionskontakten fielen die Überlebensraten insgesamt niedriger aus als in den Studien, in denen die Implantatkronen ohne antagonistische Okklusionskontakte eingegliedert wurden. Die Überlebensraten waren weitestgehend vergleichbar mit den Ergebnissen konventioneller Belastungsprotokolle. Die Datenlage anhand dieser Recherche spricht zurzeit für die Realisierung der Sofortbelastung von provisorischen Implantatkronen ohne antagonistische Okklusionskontakte in Verbindung mit postoperativen Verhaltensmaßnahmen.
Life and biological resilience rely on the execution of precise gene expression profiles. A key mechanism to ensure cellular homeostasis is the regulation of protein synthesis. Recent studies have unveiled an intrinsic regulatory capacity of ribosomes, previously considered mere executors of mRNA translation. Neurons in particular finely regulate protein synthesis, at both global and local levels. This sustains their complex morphology and allows them to rapidly transmit, integrate, and respond to external stimuli. In this thesis, I investigated the neuronal ribosome and how subcellular environments and physiological perturbations shape it, by profiling its molecular composition, functional interconnections, and cellular distribution.
First, I used genetic engineering, biochemical purification, and mass spectrometry, to characterize in an unbiased manner the translation machinery specifically from excitatory and inhibitory neurons of the mouse cortex. I found that neuronal ribosomes commonly interact with RNA-binding proteins, components of the cytoskeleton, and proteins associated with the endoplasmic reticulum and vesicles. In line with the requirement for local protein synthesis in the distal parts of neurons, we observed that neuronal ribosomes preferentially interact with proteins involved in cellular transport. Remarkably, I observed a strong association between ribosomes and pre-synaptic vesicles, which suggests a potential regulatory interaction between local translation and neuronal activity.
Intriguingly, I and others have observed mRNAs encoding for core ribosomal proteins (RPs) among the genes most enriched in neuronal processes. This observation challenges two historical assumptions of ribosome biology: (1) new RPs are incorporated only into newly forming ribosomes, and (2) this incorporation occurs only in the nucleus and perinuclear region. In my PhD, I aimed to directly test these two assumptions and if proven wrong ask whether and why neurons would localize RP mRNAs far from their known assembly site.
Employing a combination of metabolic labeling and highly sensitive mass spectrometry techniques, I discovered that a subset of RPs rapidly and dynamically binds on and off mature ribosomes. Strikingly, this incorporation does not depend on the supply of new ribosomes from the nucleus. Therefore, my data refuted the assumption that ribosomes are built and degraded as a unit and revealed a more dynamic view of these machines, which can actively exchange core components. In particular, I found that the association of certain exchanging RPs is influenced by location (e.g., cell body versus neurites) and cellular state (e.g., post-oxidative stress). Neurons may use this mechanism to repair and/or specialize their protein synthesis machinery in a rapid and context-dependent manner.
Finally, I asked whether some steps of ribosome biogenesis could also take place in distal processes. Although most steps of ribosome assembly occur within the nucleus, the final stages of maturation are known to occur in the cytosol. By combining several imaging and biochemical approaches, I found that cytosolic (but not nuclear) pre-ribosomal particles are present in neuronal processes. Through the incorporation of new RPs into these immature particles, neurons may be able to locally “turn on” previously incompetent ribosomes. This may enable regions near synapses to enhance and customize their translational capacity, independently of the central pool of ribosomes from the cell body. Indeed, I observed that synaptic plasticity induces a maturation of cytosolic pre-ribosomes.
In summary, this thesis shows how neuronal ribosomes can sense cellular states, respond by adjusting their core composition, and in doing so influence the local capacity for protein synthesis. By overturning long-held assumptions in ribosome biology, this work highlights new molecular mechanisms of gene expression and enriches our understanding of the rapid and dynamic strategies cells employ to operate, thrive, and adaptively respond to environmental changes.
Precise regulation of gene expression networks is required to develop and maintain a healthy organism before and after birth and throughout adulthood. Such networks are mostly comprised of regulatory proteins, but meanwhile many long non-coding transcripts (lncRNAs) are shown to participate in these regulatory processes. The functions and mechanisms of these lncRNAs vary greatly, however they are often associated with transcriptional regulation. Three lncRNAs, namely Sweetheart RNA (Swhtr), Fetal-lethal noncoding developmental regulatory RNA / Foxf1 adjacent non-Coding developmental regulatory RNA (Fendrr) and lncFsd2, were studied in this work to demonstrate the variety of cellular and biological processes that require lncRNA-mediated fine-tuning, in regard to the cardiopulmonary system.
Swhtr was found to be expressed exclusively in cardiomyocytes and became critical for regeneration after myocardial injury. Mice lacking Swhtr did not show issues under normal conditions, but failed to undergo compensatory hypertrophic remodeling after injury, leading to increased mortality. This effect was rescued by re-expressing Swhtr, demonstrating importance of the RNA. Genes dependent on Swhtr during cardiac stress were found to likely be regulated by NKX2-5 through physical interaction with Swhtr. Fendrr was found to be expressed in lung and interacted with target promoters through its RNA:dsDNA binding domain, the FendrrBox, which was partially required for Fendrr function. Fendrr, together with activated WNT signaling, regulated fibrosis related target genes via the FendrrBox in fibroblasts. LncFsd2, an ubiquitously expressed lncRNA, showed possible interaction with the striated muscle specific Fsd2, but its exact function and regulatory role remain unclear in muscle physiology. Immunoprecipitation and subcellular fractionation experiments suggest that lncFsd2 might be involved in nuclear retention of Fsd2 mRNA, thus fine-tuning FSD2 protein expression. These investigations have shed light on the roles of these lncRNAs in stress responses, fibrosis-related gene regulation, and localization processes, advancing our understanding of cardiovascular and pulmonary maintenance, reaction to injury, and diseases. The diverse and intricate roles of these three lncRNAs highlight how they influence various cellular processes and disease states, offering avenues for exploring lncRNA functions in different biological contexts.
The free energy of TAP-solutions for the SK-model of mean field spin glasses can be expressed as a nonlinear functional of local terms: we exploit this feature in order to contrive abstract REM-like models which we then solve by a classical large deviations treatment. This allows to identify the origin of the physically unsettling quadratic (in the inverse of temperature) correction to the Parisi free energy for the SK-model, and formalizes the true cavity dynamics which acts on TAP-space, i.e. on the space of TAP-solutions. From a non-spin glass point of view, this work is the first in a series of refinements which addresses the stability of hierarchical structures in models of evolving populations.
The equation of state (EoS) of matter at extremely high temperatures and densities is currently not fully understood, and remains a major challenge in the field of nuclear physics. Neutron stars harbor such extreme conditions and therefore serve as celestial laboratories for constraining the dense matter EoS. In this thesis, we present a novel algorithm that utilizes the idea of Bayesian analysis and the computational efficiency of neural networks to reconstruct the dense matter equation of state from mass-radius observations of neutron stars. We show that the results are compatible with those from earlier works based on conventional methods, and are in agreement with the limits on tidal deformabilities obtained from the gravitational wave event, GW170817. We also observe that the resulting squared speed of sound from the reconstructed EoS features a peak, indicating a likely convergence to the conformal limit at asymptotic densities, as expected from quantum chromodynamics. The novel algorithm can also be applied across various fields faced with computational challenges in solving inverse problems. We further examine the efficiency of deep learning methods for analyzing gravitational waves from compact binary coalescences in this thesis. In particular, we develop a deep learning classifier to segregate simulated gravitational wave data into three classes: signals from binary black hole mergers, signals from binary neutron star mergers, or white noise without any signals. A second deep learning algorithm allows for the regression of chirp mass and combined tidal deformability from simulated binary neutron star mergers. An accurate estimation of these parameters is crucial to constrain the underlying EoS. Lastly, we explore the effects of finite temperatures on the binary neutron star merger remnant from GW170817. Isentropic EoSs are used to infer the frequencies of the rigidly rotating remnant and are noted to be significantly lower compared to previous estimates from zero temperature EoSs. Overall, this thesis presents novel deep learning methods to constrain the neutron star EoS, which will prove useful in future, as more observational data is expected in the upcoming years.