Dynamic causal communication channels between neocortical areas

Processing of sensory information depends on the interactions between hierarchically connected neocortical regions, but it remains unclear how the activity in one area causally influences the activity dynamics in another and how rapidly such interactions change with time. Here, we show that the communication between the primary visual cortex (V1) and high-order visual area LM is context-dependent and surprisingly dynamic over time. By momentarily silencing one area while recording activity in the other, we find that both areas reliably affected changing subpopulations of target neurons within one hundred milliseconds while mice observed a visual stimulus. The influence of LM feedback on V1 responses became even more dynamic when the visual stimuli predicted a reward, causing fast changes in the geometry of V1 population activity and affecting stimulus coding in a context-dependent manner. Therefore, the functional interactions between cortical areas are not static but unfold through rapidly shifting communication subspaces whose dynamics depend on context when processing sensory information

Imaging development and plasticity in the mouse visual system

Neuronal activity, both intrinsically generated and sensory-evoked, is known to play an important role in the development of the brain. Sensory experiences continue to exert a strong influence on the functional connectivity of neuronal circuits, especially in the cerebral cortex, allowing for learning and adaptation to an ever changing environment. The visual system provides a convenient and well established model to study both development and experience-dependent plasticity of neuronal circuits. The aim of this thesis is to employ the mouse visual system to explore how neuronal activity influences the formation of brain circuits and mediates their experience-dependent modification later in life. In the first part of this thesis (Chapter 2), I examined the role of retinal activity in the formation of topographic maps in a target region of retinal ganglion cells. It is generally assumed that in order to obtain such highly precise and ordered maps during development, spontaneous patterns of neuronal activity are crucial for the refinement of connections. Applying intrinsic signal imaging to mouse superior colliculus (SC), I confirmed this assumption by showing that functional connectivity is less precise in transgenic mice with disrupted patterns of retinal ganglion cell activity. In comparison to normal mice, visual stimuli activated larger, less defined regions in the SC in mice lacking early retinal waves. Surprisingly, I also found that the overall topographic organization was affected by the lack of correlated spiking in the retina. Although the rough retinotopic organization was maintained, the map showed substantial distortion, indicating that patterned retinal activity before eye-opening plays a more important role in topographic map formation than previously thought. Later in development, sensory-evoked activity is equally influential in shaping functional connectivity, since altered sensory input induces strong changes in cortical circuitry. Closure of one eye for a few days (monocular deprivation, MD), for instance, substantially changes cortical responsiveness to the two eyes, shifting ocular dominance (OD) towards the non-deprived eye. This paradigm therefore provides a powerful model system for experience-dependent plasticity. In Chapter 3, I used intrinsic signal imaging to assess the magnitude of cortical responses evoked by stimulation of the two eyes in order to explore OD plasticity in mouse visual cortex. I confirmed recent, debated findings in demonstrating strong MD-induced plasticity in adult animals, which was mediated by partly different mechanisms than in juvenile mice. I also found that restoring binocular vision after MD led to full recovery of eye-specific responses at all ages. Interestingly, the prior experience of altered sensory input seemed to be somehow preserved in cortical circuits, such that subsequent cortical adaptation to the same experience was improved. A second MD resulted in much faster and more persistent OD shifts. This enhancement of plasticity was highly specific, as it was only observed for repeated deprivation of the same eye, indicating that a lasting trace was established in cortical connections by the initial experience. In Chapter 4, I explored OD plasticity in greater detail by monitoring network activity at the level of individual neurons with in vivo two-photon imaging of calcium signals. Monitoring calcium transients associated with neuronal activity in up to hundred cells simultaneously, enabled me to examine MD-induced changes in the functional properties of each neuron independently. I found that, in general, deprived eye responses were weakened and non-deprived eye responses strengthened after MD in juvenile mice, as was expected from previous population response measurements. Neurons still dominated by deprived-eye inputs, however, did not lose their responsiveness, but rather exhibited enhanced responses following MD. This strongly suggests that homeostatic plasticity acted on these cells during deprivation and caused an up-scaling of their responsiveness, while neurons also receiving substantial input from the non-deprived eye shifted their responsiveness towards that eye. Both competitive and homeostatic processes therefore seem to operate during OD plasticity, depending on the distribution of functional inputs in individual cells. In conclusion, the work presented in this thesis provides further insight into the role of activity-dependent mechanisms in determining and shaping functional connectivity in the brain

In vitro assessment of the pharmacodynamic properties of DB75, piperaquine, OZ277 and OZ401 in cultures of Plasmodium falciparum

Objectives Using synchronized cultures of Plasmodium falciparum, the time- and concentration-dependent growth changes of erythrocytic parasite stages to DB75, piperaquine, OZ277 and OZ401 were investigated in vitro over a concentration range of ∼1-100× the IC50 of piperaquine, OZ277 and OZ401 and ∼10-1000× the IC50 of DB75. Methods The effects of timed in vitro exposure (1, 6, 12 or 24 h) were monitored by the incorporation of [3H]hypoxanthine into the parasite nucleic acids. Results After 1 h of exposure to the highest concentration of the compound followed by removal of the compound, the growth of all stages of P. falciparum was reduced to <34% for DB75 and 15% for piperaquine, OZ277 and OZ401 compared with untreated control parasites. At this time point, no stage-specific effects were observed at any of the concentrations. Strong inhibition (≤10% growth) of all parasite stages was observed when the parasites were exposed to 10× or 100× the IC50 of OZ277 and OZ401 for ≥6 h. At the 6 h incubation time point, DB75 was more active against mature parasite stages, with the IC50s of young ring forms elevated up to 7-fold. This trend was observed up to 12 h, but was only statistically significant at the lowest concentration. Interestingly, the stage-specific effect of DB75 on ring forms was not detectable when washing procedures were omitted. This indicates a cytostatic action of DB75 on P. falciparum ring forms. Conclusions The current study suggests that P. falciparum ring stages are less susceptible to DB75. A milder and often statistically insignificant stage-specific trend was observed for piperaquine, whereas OZ277 and OZ401 were equally active against the erythrocytic parasite stage

Peptide Bbeta(15-42) preserves endothelial barrier function in shock

Loss of vascular barrier function causes leak of fluid and proteins into tissues, extensive leak leads to shock and death. Barriers are largely formed by endothelial cell-cell contacts built up by VE-cadherin and are under the control of RhoGTPases. Here we show that a natural plasmin digest product of fibrin, peptide Bß15-42 (also called FX06), significantly reduces vascular leak and mortality in animal models for Dengue shock syndrome. The ability of Bß15-42 to preserve endothelial barriers is confirmed in rats i.v.-injected with LPS. In endothelial cells, Bß15-42 prevents thrombin-induced stress fiber formation, myosin light chain phosphorylation and RhoA activation. The molecular key for the protective effect of Bß15-42 is the src kinase Fyn, which associates with VE-cadherin-containing junctions. Following exposure to Bß15-42 Fyn dissociates from VE-cadherin and associates with p190RhoGAP, a known antagonists of RhoA activation. The role of Fyn in transducing effects of Bß15-42 is confirmed in Fyn -/- mice, where the peptide is unable to reduce LPS-induced lung edema, whereas in wild type littermates the peptide significantly reduces leak. Our results demonstrate a novel function for Bß15-42. Formerly mainly considered as a degradation product occurring after fibrin inactivation, it has now to be considered as a signaling molecule. It stabilizes endothelial barriers and thus could be an attractive adjuvant in the treatment of shock

Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction

Recent advancements in natural language processing (NLP) methods have significantly improved their performance. However, more complex NLP models are more difficult to interpret and computationally expensive. Therefore, we propose an approach to dictionary creation that carefully balances the trade-off between complexity and interpretability. This approach combines a deep neural network architecture with techniques to improve model explainability to automatically build a domain-specific dictionary. As an illustrative use case of our approach, we create an objective dictionary that can infer conflict intensity from text data. We train the neural networks on a corpus of conflict reports and match them with conflict event data. This corpus consists of over 14,000 expert-written International Crisis Group (ICG) CrisisWatch reports between 2003 and 2021. Sensitivity analysis is used to extract the weighted words from the neural network to build the dictionary. In order to evaluate our approach, we compare our results to state-of-the-art deep learning language models, text-scaling methods, as well as standard, nonspecialized, and conflict event dictionary approaches. We are able to show that our approach outperforms other approaches while retaining interpretability

Auswirkungen von Sport und Bewegung während der Arbeitszeit auf die Gesundheit und die Produktivität am Arbeitsplatz : Recherche Schweiz und International

Radiobeitrag zum Thema: https://www.srf.ch/audio/ratgeber/bewegte-mitarbeiter-sind-gesunde-mitarbeiter?id=1183613

A gene expression profile associated with relapse of cytogenetically normal acute myeloid leukemia is enriched for leukemia stem cell genes

Some 50 – 80% of patients with acute myeloid leukemia (AML) achieve a complete remission with contemporary chemotherapy protocols, yet the majority of them eventually relapse with resistant disease: some patients no longer respond to chemotherapy at disease recurrence; others accomplish second and even third remissions whose decreasing duration nevertheless indicates that the pool of residual leukemic cells, i.e. of cells that persisted during treatment with cytotoxic drugs, increases with every round of therapy [1]. Either of these clinical courses therefore refl ects an enhanced chemotherapy resistance of leukemic cells at relapse as compared to the cell population at diagnosis. Molecular changes enabling malignant cells to survive exposure to cytotoxic drugs may already have been present in a subset of the leukemic cell population at presentation, or may emerge during treatment [2,3], but in any case are thought to be selected as a consequence of drug therapy, and to play a major role in therapy resistance at relapse. Remarkably, however, even though various types of molecular alterations may be acquired at relapse, neither specifi c cytogenetic alterations nor functionally relevant point mutations as identifi ed by whole genome sequencing were associated with relapse in a recurrent manner [2,3]. Certain copy number variations and known AML associated point mutations were newly present at relapse in small proportions of patients (usually 10%), but the latter were lost in other patients, indicating that they are unlikely to represent drivers of therapy resistance at disease recurrence [4]. Th ese fi ndings could either indicate that chemotherapy resistance at relapse is acquired through a large variety of different mechanisms, or that molecular changes of other types than those mentioned above are of more general relevance in this context. Indeed, an earlier study has suggested that the expression of specifi c genes may change in a consistent manner between diagnosis and relapse of AML [5]. However, only a limited number of genes and mostly unpaired samples were probed in this investigation. Th erefore, in the present study, genes whose expression changed in a relapse-specifi c manner were sought in a set of paired AML samples and on a genome-wide scale. To limit the genetic heterogeneity of the study population, only samples from patients with cytogenetically normal (CN) AML were used.Letter to the Edito

Learning shapes cortical dynamics to enhance integration of relevant sensory input

Adaptive sensory behavior is thought to depend on processing in recurrent cortical circuits, but how dynamics in these circuits shapes the integration and transmission of sensory information is not well understood. Here, we study neural coding in recurrently connected networks of neurons driven by sensory input. We show analytically how information available in the network output varies with the alignment between feedforward input and the integrating modes of the circuit dynamics. In light of this theory, we analyzed neural population activity in the visual cortex of mice that learned to discriminate visual features. We found that over learning, slow patterns of network dynamics realigned to better integrate input relevant to the discrimination task. This realignment of network dynamics could be explained by changes in excitatory-inhibitory connectivity among neurons tuned to relevant features. These results suggest that learning tunes the temporal dynamics of cortical circuits to optimally integrate relevant sensory input

Microarrayed human bone marrow organoids for modeling blood stem cell dynamics

In many leukemia patients, a poor prognosis is attributed either to the development of chemotherapy resistance by leukemic stem cells (LSCs) or to the inefficient engraftment of transplanted hematopoietic stem/progenitor cells (HSPCs) into the bone marrow (BM). Here, we build a 3D in vitro model system of bone marrow organoids (BMOs) that recapitulate several structural and cellular components of native BM. These organoids are formed in a high-throughput manner from the aggregation of endothelial and mesenchymal cells within hydrogel microwells. Accordingly, the mesenchymal compartment shows partial maintenance of its self-renewal and multilineage potential, while endothelial cells self-organize into an interconnected vessel-like network. Intriguingly, such an endothelial compartment enhances the recruitment of HSPCs in a chemokine ligand/receptor-dependent manner, reminiscent of HSPC homing behavior in vivo. Additionally, we also model LSC migration and nesting in BMOs, thus highlighting the potential of this system as a well accessible and scalable preclinical model for candidate drug screening and patient-specific assays

A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging

Inference of action potentials (‘spikes’) from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals (‘ground truth’). In this study, we compiled a large, diverse ground truth database from publicly available and newly performed recordings in zebrafish and mice covering a broad range of calcium indicators, cell types and signal-to-noise ratios, comprising a total of more than 35 recording hours from 298 neurons. We developed an algorithm for spike inference (termed CASCADE) that is based on supervised deep networks, takes advantage of the ground truth database, infers absolute spike rates and outperforms existing model-based algorithms. To optimize performance for unseen imaging data, CASCADE retrains itself by resampling ground truth data to match the respective sampling rate and noise level; therefore, no parameters need to be adjusted by the user. In addition, we developed systematic performance assessments for unseen data, openly released a resource toolbox and provide a user-friendly cloud-based implementation