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In recent history, normalized digital surface models (nDSMs) have been constantly gaining importance as a means to solve large-scale geographic problems. High-resolution surface models are precious, as they can provide detailed information for a specific area. However, measurements with a high resolution are time consuming and costly. Only a few approaches exist to create high-resolution nDSMs for extensive areas. This article explores approaches to extract high-resolution nDSMs from low-resolution Sentinel-2 data, allowing us to derive large-scale models. We thereby utilize the advantages of Sentinel 2 being open access, having global coverage, and providing steady updates through a high repetition rate. Several deep learning models are trained to overcome the gap in producing high-resolution surface maps from low-resolution input data. With U-Net as a base architecture, we extend the capabilities of our model by integrating tailored multiscale encoders with differently sized kernels in the convolution as well as conformed self-attention inside the skip connection gates. Using pixelwise regression, our U-Net base models can achieve a mean height error of approximately 2 m. Moreover, through our enhancements to the model architecture, we reduce the model error by more than 7%.
Background: Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals.
Objective: This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI).
Methods: Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics.
Results: The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations.
Conclusions: A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing.
Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.
ABSTRACT
The highly conserved heterotrimeric protein kinase SNF1 is important for metabolic adaptations in the pathogenic yeast Candida albicans. A key function of SNF1 is to inactivate the repressor protein Mig1 and thereby allow the expression of genes that are required for the utilization of alternative carbon sources when the preferred carbon source, glucose, is absent or becomes limiting. However, how SNF1 controls Mig1 activity in C. albicans has remained elusive. Using a phosphoproteomics approach, we found that Mig1 is phosphorylated at multiple serine residues. Replacement of these serine residues by nonphosphorylatable alanine residues strongly increased the repressor activity of Mig1 in cells lacking a functional SNF1 complex, indicating that additional protein kinases are involved in the regulation of Mig1. Unlike wild-type Mig1, whose levels strongly decreased when the cells were grown on sucrose or glycerol instead of glucose, the levels of a mutant Mig1 protein lacking nine phosphorylation sites remained high under these conditions. Despite the increased protein levels and the absence of multiple phosphorylation sites, cells with a functional SNF1 complex could still sufficiently inhibit the hyperactive Mig1 to enable wild-type growth on alternative carbon sources. In line with this, phosphorylated forms of the mutant Mig1 were still detected in the presence and absence of a functional SNF1, demonstrating that Mig1 contains additional, unidentified phosphorylation sites and that downstream protein kinases are involved in the control of Mig1 activity by SNF1.
IMPORTANCE
The SNF1 protein kinase signaling pathway, which is highly conserved in eukaryotic cells, is important for metabolic adaptations in the pathogenic yeast Candida albicans. However, so far, it has remained elusive how SNF1 controls the activity of one of its main effectors, the repressor protein Mig1 that inhibits the expression of genes required for the utilization of alternative carbon sources when glucose is available. In this study, we have identified multiple phosphorylation sites in Mig1 that contribute to its inactivation. Mutation of these sites strongly increased Mig1 repressor activity in the absence of SNF1, but SNF1 could still sufficiently inhibit the hyperactive Mig1 to enable growth on alternative carbon sources. These findings reveal features of Mig1 that are important for controlling its repressor activity. Furthermore, they demonstrate that both SNF1 and additional protein kinases regulate Mig1 in this pathogenic yeast.
Abstract
Protein kinases are central components of almost all signaling pathways that control cellular activities. In the model organism Saccharomyces cerevisiae, the paralogous protein kinases Ypk1 and Ypk2, which control membrane lipid homeostasis, are essential for viability, and previous studies strongly indicated that this is also the case for their single ortholog Ypk1 in the pathogenic yeast Candida albicans. Here, using FLP-mediated inducible gene deletion, we reveal that C. albicans ypk1Δ mutants are viable but slow-growing, explaining prior failures to obtain null mutants. Phenotypic analyses of the mutants showed that the functions of Ypk1 in regulating sphingolipid biosynthesis and cell membrane lipid asymmetry are conserved, but the consequences of YPK1 deletion are milder than in S. cerevisiae. Mutational studies demonstrated that the highly conserved PDK1 phosphorylation site T548 in its activation loop is essential for Ypk1 function, whereas the TORC2 phosphorylation sites S687 and T705 at the C-terminus are important for Ypk1-dependent resistance to membrane stress. Unexpectedly, Pkh1, the single C. albicans orthologue of Pkh1/Pkh2, which mediate Ypk1 phosphorylation at the PDK1 site in S. cerevisiae, was not required for normal growth of C. albicans under nonstressed conditions, and Ypk1 phosphorylation at T548 was only slightly reduced in pkh1Δ mutants. We found that another protein kinase, Pkh3, whose ortholog in S. cerevisiae cannot substitute Pkh1/2, acts redundantly with Pkh1 to activate Ypk1 in C. albicans. No phenotypic effects were observed in cells lacking Pkh3 alone, but pkh1Δ pkh3Δ double mutants had a severe growth defect and Ypk1 phosphorylation at T548 was completely abolished. These results establish that Ypk1 is not essential for viability in C. albicans and that, despite its generally conserved function, the Ypk1 signaling pathway is rewired in this pathogenic yeast and includes a novel upstream kinase to activate Ypk1 by phosphorylation at the PDK1 site.
Author summary
Protein kinases are key components of cellular signaling pathways, and elucidating the specific roles of individual kinases is important to understand how organisms adapt to changes in their environment. The protein kinase Ypk1 is highly conserved in eukaryotic organisms and crucial for the maintenance of cell membrane homeostasis. It was previously thought that Ypk1 is essential for viability in the pathogenic yeast Candida albicans, as in the model organism Saccharomyces cerevisiae. Here, by using forced, inducible gene deletion, we reveal that C. albicans mutants lacking Ypk1 are viable but have a strong growth defect. The phenotypes of the mutants indicate that the known functions of Ypk1 are conserved in C. albicans, but loss of this kinase has less severe consequences than in S. cerevisiae. We also unravel the puzzling previous observation that C. albicans mutants lacking the Ypk1-activating kinase Pkh1, which is essential in S. cerevisiae, have no obvious growth defects. We show that the protein kinase Pkh3, which has not previously been implicated in the Ypk1 signaling pathway, can substitute Pkh1 and activate Ypk1 in C. albicans. These findings provide novel insights into this conserved signaling pathway and how it is rewired in a human-pathogenic fungus.
Bulk RNA sequencing technologies have provided invaluable insights into host and bacterial gene expression and associated regulatory networks. Nevertheless, the majority of these approaches report average expression across cell populations, hiding the true underlying expression patterns that are often heterogeneous in nature. Due to technical advances, single-cell transcriptomics in bacteria has recently become reality, allowing exploration of these heterogeneous populations, which are often the result of environmental changes and stressors. In this work, we have improved our previously published bacterial single-cell RNA sequencing (scRNA-seq) protocol that is based on multiple annealing and deoxycytidine (dC) tailing-based quantitative scRNA-seq (MATQ-seq), achieving a higher throughput through the integration of automation. We also selected a more efficient reverse transcriptase, which led to reduced cell loss and higher workflow robustness. Moreover, we successfully implemented a Cas9-based rRNA depletion protocol into the MATQ-seq workflow. Applying our improved protocol on a large set of single Salmonella cells sampled over different growth conditions revealed improved gene coverage and a higher gene detection limit compared to our original protocol and allowed us to detect the expression of small regulatory RNAs, such as GcvB or CsrB at a single-cell level. In addition, we confirmed previously described phenotypic heterogeneity in Salmonella in regard to expression of pathogenicity-associated genes. Overall, the low percentage of cell loss and high gene detection limit makes the improved MATQ-seq protocol particularly well suited for studies with limited input material, such as analysis of small bacterial populations in host niches or intracellular bacteria.
IMPORTANCE: Gene expression heterogeneity among isogenic bacteria is linked to clinically relevant scenarios, like biofilm formation and antibiotic tolerance. The recent development of bacterial single-cell RNA sequencing (scRNA-seq) enables the study of cell-to-cell variability in bacterial populations and the mechanisms underlying these phenomena. Here, we report a scRNA-seq workflow based on MATQ-seq with increased robustness, reduced cell loss, and improved transcript capture rate and gene coverage. Use of a more efficient reverse transcriptase and the integration of an rRNA depletion step, which can be adapted to other bacterial single-cell workflows, was instrumental for these improvements. Applying the protocol to the foodborne pathogen Salmonella, we confirmed transcriptional heterogeneity across and within different growth phases and demonstrated that our workflow captures small regulatory RNAs at a single-cell level. Due to low cell loss and high transcript capture rates, this protocol is uniquely suited for experimental settings in which the starting material is limited, such as infected tissues.
Die Dissertation beschäftigt sich mit der Analyse von oxidischen Nanostrukturen. Die Grundlage der Bauelemente stellt dabei die LaAlO3/SrTiO3-Heterostruktur dar. Hierbei entsteht an der Grenzfläche beider Übergangsmetalloxide ein quasi zweidimensionales Elektronengas, welches wiederum eine Fülle von beachtlichen Eigenschaften und Charakteristika zeigt. Mithilfe lithographischer Verfahren wurden zwei unterschiedliche Bauelemente verwirklicht. Dabei handelt es sich einerseits um einen planaren Nanodraht mit lateralen Gates, welcher auf der Probenoberfläche prozessiert wurde und eine bemerkenswerte Trialität aufweist. Dieses Bauelement kann unter anderem als ein herkömmlicher Feldeffekttransistor agieren, wobei der Ladungstransport durch die lateral angelegte Spannung manipuliert wird. Zusätzlich konnten auch Speichereigenschaften beobachtet werden, sodass das gesamte Bauelement als ein sogenannter Memristor fungieren kann. In diesem Fall hängt der Ladungstransport von der Elektronenakkumulation auf den lateralen potentialfreien Gates ab. Die Memristanz des Nanodrahts lässt sich unter anderem durch Lichtleistungen im Nanowattbereich und mithilfe von kurzen Spannungspulsen verändern. Darüber hinaus kann die Elektronenakkumulation auch in Form einer memkapazitiven Charakteristik beobachtet werden. Neben dem Nanodraht wurde auch eine Kreuzstruktur, die eine ergänzende ferromagnetischen Elektrode beinhaltet, realisiert. Mit diesem neuartigen Bauteil wird die Umwandlung zwischen Spin- und Ladungsströmen innerhalb der nanoskaligen Struktur untersucht. Hierbei wird die starke Spin-Bahn-Kopplung im quasi zweidimensionalen Elektronengas ausgenutzt.
The development of retrogressive thaw slumps (RTS) is known to be strongly influenced by relief-related parameters, permafrost characteristics, and climatic triggers. To deepen the understanding of RTS, this study examines the subsurface characteristics in the vicinity of an active thaw slump, located in the Richardson Mountains (Western Canadian Arctic). The investigations aim to identify relationships between the spatiotemporal slump development and the influence of subsurface structures. Information on these were gained by means of electrical resistivity tomography (ERT) and ground-penetrating radar (GPR). The spatiotemporal development of the slump was revealed by high-resolution satellite imagery and unmanned aerial vehicle–based digital elevation models (DEMs). The analysis indicated an acceleration of slump expansion, especially since 2018. The comparison of the DEMs enabled the detailed balancing of erosion and accumulation within the slump area between August 2018 and August 2019. In addition, manual frost probing and GPR revealed a strong relationship between the active layer thickness, surface morphology, and hydrology. Detected furrows in permafrost table topography seem to affect the active layer hydrology and cause a canalization of runoff toward the slump. The three-dimensional ERT data revealed a partly unfrozen layer underlying a heterogeneous permafrost body. This may influence the local hydrology and affect the development of the RTS. The results highlight the complex relationships between slump development, subsurface structure, and hydrology and indicate a distinct research need for other RTSs.
Early-onset torsion dystonia (DYT-TOR1A, DYT1) is an inherited hyperkinetic movement disorder caused by a mutation of the TOR1A gene encoding the torsinA protein. DYT-TOR1A is characterized as a network disorder of the central nervous system (CNS), including predominantly the cortico-basal ganglia-thalamo-cortical loop resulting in a severe generalized dystonic phenotype. The pathophysiology of DYTTOR1A is not fully understood. Molecular levels up to large-scale network levels of the CNS are suggested to be affected in the pathophysiology of DYT-TOR1A. The reduced penetrance of 30% - 40% indicates a gene-environmental interaction, hypothesized as “second hit”. The lack of appropriate and phenotypic DYT-TOR1A animal models encouraged us to verify the “second hit” hypothesis through a unilateral peripheral nerve trauma of the sciatic nerve in a transgenic asymptomatic DYT-TOR1A rat model (∆ETorA), overexpressing the human mutated torsinA protein. In a multiscale approach, this animal model was characterized phenotypically and pathophysiologically.
Nerve-injured ∆ETorA rats revealed dystonia-like movements (DLM) with a partially generalized phenotype. A physiomarker of human dystonia, describing increased theta oscillation in the globus pallidus internus (GPi), was found in the entopeduncular nucleus (EP), the rodent equivalent to the human GPi, of nerve-injured ∆ETorA rats. Altered oscillation patterns were also observed in the primary motor cortex. Highfrequency stimulation (HFS) of the EP reduced DLM and modulated altered oscillatory activity in the EP and primary motor cortex in nerve-injured ∆ETorA rats. Moreover, the dopaminergic system in ∆ETorA rats demonstrated a significant increased striatal dopamine release and dopamine turnover. Whole transcriptome analysis revealed differentially expressed genes of the circadian clock and the energy metabolism, thereby pointing towards novel, putative pathways in the pathophysiology of DYTTOR1A dystonia.
In summary, peripheral nerve trauma can trigger DLM in genetically predisposed asymptomatic ΔETorA rats leading to neurobiological alteration in the central motor network on multiple levels and thereby supporting the “second hit” hypothesis. This novel symptomatic DYT-TOR1A rat model, based on a DYT-TOR1A genetic background, may prove as a valuable chance for DYT-TOR1A dystonia, to further investigate the pathomechanism in more detail and to establish new treatment strategies.
Young grapevines (Vitis vinifera) suffer and eventually can die from the crown gall disease caused by the plant pathogen Allorhizobium vitis (Rhizobiaceae). Virulent members of A. vitis harbor a tumor-inducing plasmid and induce formation of crown galls due to the oncogenes encoded on the transfer DNA. The expression of oncogenes in transformed host cells induces unregulated cell proliferation and metabolic and physiological changes. The crown gall produces opines uncommon to plants, which provide an important nutrient source for A. vitis harboring opine catabolism enzymes. Crown galls host a distinct bacterial community, and the mechanisms establishing a crown gall–specific bacterial community are currently unknown. Thus, we were interested in whether genes homologous to those of the tumor-inducing plasmid coexist in the genomes of the microbial species coexisting in crown galls. We isolated 8 bacterial strains from grapevine crown galls, sequenced their genomes, and tested their virulence and opine utilization ability in bioassays. In addition, the 8 genome sequences were compared with 34 published bacterial genomes, including closely related plant-associated bacteria not from crown galls. Homologous genes for virulence and opine anabolism were only present in the virulent Rhizobiaceae. In contrast, homologs of the opine catabolism genes were present in all strains including the nonvirulent members of the Rhizobiaceae and non-Rhizobiaceae. Gene neighborhood and sequence identity of the opine degradation cluster of virulent and nonvirulent strains together with the results of the opine utilization assay support the important role of opine utilization for cocolonization in crown galls, thereby shaping the crown gall community.
Abstract
Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboard and engulfing patterns. In this model, the cell-cell communication has been implemented as a signal that disperses throughout the tissue. On the other hand, machine learning models have been developed for pattern recognition and pattern reconstruction tasks. We combined synthetic data generated by the mathematical model with spatial summary statistics and deep learning algorithms to recognize and reconstruct cell fate patterns in organoids of mouse embryonic stem cells. Application of Moran’s index and pair correlation functions for in vitro and synthetic data from the model showed local clustering and radial segregation. To assess the patterns as a whole, a graph neural network was developed and trained on synthetic data from the model. Application to in vitro data predicted a low signal dispersion value. To test this result, we implemented a multilayer perceptron for the prediction of a given cell fate based on the fates of the neighboring cells. The results show a 70% accuracy of cell fate imputation based on the nine nearest neighbors of a cell. Overall, our approach combines deep learning with mathematical modeling to link cell fate patterns with potential underlying mechanisms.
Author summary
Mammalian embryo development relies on organized differentiation of stem cells into different lineages. Particularly at the early stages of embryogenesis, cells of different fates form three-dimensional spatial patterns that are difficult to identify by eye. Pattern quantification and mathematical modeling have produced first insights into potential mechanisms for the cell fate arrangements. However, these approaches have relied on classifications of the patterns such as inside-out or random, or used summary statistics such as pair correlation functions or cluster radii. Deep neural networks allow characterizing patterns directly. Since the tissue context can be readily reproduced by a graph, we implemented a graph neural network to characterize the patterns of embryonic stem cell organoids as a whole. In addition, we implemented a multilayer perceptron model to reconstruct the fate of a given cell based on its neighbors. To train and test the models, we used synthetic data generated by our mathematical model for cell-cell communication. This interplay of deep learning and mathematical modeling in combination with summary statistics allowed us to identify a potential mechanism for cell fate determination in mouse embryonic stem cells. Our results agree with a mechanism with a dispersion of the intercellular signal that links a cell’s fate to those of the local neighborhood.
The ANTARES neutrino telescope has an energy threshold of a few tens of GeV. This allows to study the phenomenon of atmospheric muon neutrino disappearance due to neutrino oscillations. In a similar way, constraints on the 3+1 neutrino model, which foresees the existence of one sterile neutrino, can be inferred. Using data collected by the ANTARES neutrino telescope from 2007 to 2016, a new measurement of m 2 and (23) has been performed which is consistent with world best-fit values and constraints on the 3+1 neutrino model have been derived.
Background
Neoadjuvant chemotherapy (NACT) for early breast cancer can make breast-conserving surgery more feasible and might be more likely to eradicate micrometastatic disease than might the same chemotherapy given after surgery. We investigated the long-term benefits and risks of NACT and the influence of tumour characteristics on outcome with a collaborative meta-analysis of individual patient data from relevant randomised trials.
Methods
We obtained information about prerandomisation tumour characteristics, clinical tumour response, surgery, recurrence, and mortality for 4756 women in ten randomised trials in early breast cancer that began before 2005 and compared NACT with the same chemotherapy given postoperatively. Primary outcomes were tumour response, extent of local therapy, local and distant recurrence, breast cancer death, and overall mortality. Analyses by intention-to-treat used standard regression (for response and frequency of breast-conserving therapy) and log-rank methods (for recurrence and mortality).
Findings
Patients entered the trials from 1983 to 2002 and median follow-up was 9 years (IQR 5-14), with the last follow-up in 2013. Most chemotherapy was anthracycline based (3838 [81%] of 4756 women). More than two thirds (1349 [69%] of 1947) of women allocated NACT had a complete or partial clinical response. Patients allocated NACT had an increased frequency of breast-conserving therapy (1504 [65%] of 2320 treated with NACT vs 1135 [49%] of 2318 treated with adjuvant chemotherapy). NACT was associated with more frequent local recurrence than was adjuvant chemotherapy: the 15 year local recurrence was 21.4% for NACT versus 15.9% for adjuvant chemotherapy (5.5% increase [95% CI 2.4-8.6]; rate ratio 1.37 [95% CI 1.17-1.61]; p = 0.0001). No significant difference between NACT and adjuvant chemotherapy was noted for distant recurrence (15 year risk 38.2% for NACT vs 38.0% for adjuvant chemotherapy; rate ratio 1.02 [95% CI 0.92-1.14]; p = 0.66), breast cancer mortality (34.4% vs 33.7%; 1.06 [0.95-1.18]; p = 0.31), or death from any cause (40.9% vs 41.2%; 1.04 [0.94-1.15]; p = 0.45).
Interpretation
Tumours downsized by NACT might have higher local recurrence after breast-conserving therapy than might tumours of the same dimensions in women who have not received NACT. Strategies to mitigate the increased local recurrence after breast-conserving therapy in tumours downsized by NACT should be considered-eg, careful tumour localisation, detailed pathological assessment, and appropriate radiotherapy. Copyright (c) The Author(s). Published by Elsevier Ltd.
We consider the process of muon-electron elastic scattering, which has been proposed as an ideal framework to measure the running of the electromagnetic coupling constant at space-like momenta and determine the leading-order hadronic contribution to the muon g-2 (MUonE experiment). We compute the next-to-leading (NLO) contributions due to QED and purely weak corrections and implement them into a fully differential Monte Carlo event generator, which is available for first experimental studies. We show representative phenomenological results of interest for the MUonE experiment and examine in detail the impact of the various sources of radiative corrections under different selection criteria, in order to study the dependence of the NLO contributions on the applied cuts. The study represents the first step towards the realisation of a high-precision Monte Carlo code necessary for data analysis.
The Best for the Most Important: Maintaining a Pristine Proteome in Stem and Progenitor Cells
(2019)
Pluripotent stem cells give rise to reproductively enabled offsprings by generating progressively lineage-restricted multipotent stem cells that would differentiate into lineage-committed stem and progenitor cells. These lineage-committed stem and progenitor cells give rise to all adult tissues and organs. Adult stem and progenitor cells are generated as part of the developmental program and play critical roles in tissue and organ maintenance and/or regeneration. The ability of pluripotent stem cells to self-renew, maintain pluripotency, and differentiate into a multicellular organism is highly dependent on sensing and integrating extracellular and extraorganismal cues. Proteins perform and integrate almost all cellular functions including signal transduction, regulation of gene expression, metabolism, and cell division and death. Therefore, maintenance of an appropriate mix of correctly folded proteins, a pristine proteome, is essential for proper stem cell function. The stem cells' proteome must be pristine because unfolded, misfolded, or otherwise damaged proteins would interfere with unlimited self-renewal, maintenance of pluripotency, differentiation into downstream lineages, and consequently with the development of properly functioning tissue and organs. Understanding how various stem cells generate and maintain a pristine proteome is therefore essential for exploiting their potential in regenerative medicine and possibly for the discovery of novel approaches for maintaining, propagating, and differentiating pluripotent, multipotent, and adult stem cells as well as induced pluripotent stem cells. In this review, we will summarize cellular networks used by various stem cells for generation and maintenance of a pristine proteome. We will also explore the coordination of these networks with one another and their integration with the gene regulatory and signaling networks.
Summary
Embryos develop in a concerted sequence of spatiotemporal arrangements of cells. In the preimplantation mouse embryo, the distribution of the cells in the inner cell mass evolves from a salt-and-pepper pattern to spatial segregation of two distinct cell types. The exact properties of the salt-and-pepper pattern have not been analyzed so far. We investigate the spatiotemporal distribution of NANOG- and GATA6-expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single-cell-based neighborhood analyses. A combination of spatial statistics and agent-based modeling reveals that the cell fate distribution follows a local clustering pattern. Using ordinary differential equations modeling, we show that this pattern can be established by a distance-based signaling mechanism enabling cells to integrate information from the whole inner cell mass into their cell fate decision. Our work highlights the importance of longer-range signaling to ensure coordinated decisions in groups of cells to successfully build embryos.
Highlights
• The local cell neighborhood and global ICM population composition correlate
• ICM cells show characteristics of local clustering in early and mid mouse blastocysts
• ICM patterning requires integration of signals from cells beyond the first neighbors
Background:
Cancer patients often suffer from psychological symptoms and need psychological support. Especially during the COVID-19 pandemic, eHealth interventions might be helpful to overcome the obstacles of the pandemic. This study evaluates the effectiveness of a video sequence-based eHealth intervention on anxiety, fatigue, and depression in cancer patients.
Methods:
Patients (N = 157) with different tumor entities were randomly assigned to the video intervention group (IG) and the waiting control group (CG). Patients in the IG received a video intervention comprising 8 video sequences over 4 weeks. The videos included psychoeducation on distress and psychological symptoms, Acceptance and Commitment Therapy elements, and Yoga and Qigong exercises. Patients’ anxiety and fear of progression (primary outcomes) and secondary outcomes were assessed before randomization (T1) and after the end of the intervention for IG or the waiting period for CG (T2) using self-reported questionnaires (GAD-7, PA-F-KF, EORTC QLQ-FA12, PHQ-8).
Results:
Patients of the IG showed no significant improvement in anxiety (GAD-7; P = .75), fear of progression (FoP-Q-SF; P = .29), fatigue (EORTC QLQ-FA12; P = .72), and depression (PHQ-8; P = .95) compared to patients in the waiting CG. However, symptoms of anxiety, fatigue, and depression decreased in both groups. Exploratory subgroup analysis regarding sex, therapy status, therapy goal, and tumor entity showed no effects. Overall, the intervention had a high level of acceptance.
Conclusions:
The video intervention was ineffective in reducing the psychological burden compared to a waiting CG. The findings support prior observations of the value of therapeutic guidance and promoting self-management for improving patients’ psychological burdens. Further studies are required to evaluate the effectiveness of psycho-oncological eHealth delivered through video sequences.
RNA-binding proteins emerge as effectors of the DNA damage response (DDR). The multifunctional non-POU domain-containing octamer-binding protein NONO/p54\(^{nrb}\) marks nuclear paraspeckles in unperturbed cells, but also undergoes re-localization to the nucleolus upon induction of DNA double-strand breaks (DSBs). However, NONO nucleolar re-localization is poorly understood. Here we show that the topoisomerase II inhibitor etoposide stimulates the production of RNA polymerase II-dependent, DNA damage-inducible antisense intergenic non-coding RNA (asincRNA) in human cancer cells. Such transcripts originate from distinct nucleolar intergenic spacer regions and form DNA–RNA hybrids to tether NONO to the nucleolus in an RNA recognition motif 1 domain-dependent manner. NONO occupancy at protein-coding gene promoters is reduced by etoposide, which attenuates pre-mRNA synthesis, enhances NONO binding to pre-mRNA transcripts and is accompanied by nucleolar detention of a subset of such transcripts. The depletion or mutation of NONO interferes with detention and prolongs DSB signalling. Together, we describe a nucleolar DDR pathway that shields NONO and aberrant transcripts from DSBs to promote DNA repair.
The transcription factor SPT5 physically interacts with MYC oncoproteins and is essential for efficient transcriptional activation of MYC targets in cultured cells. Here, we use Drosophila to address the relevance of this interaction in a living organism. Spt5 displays moderate synergy with Myc in fast proliferating young imaginal disc cells. During later development, Spt5-knockdown has no detectable consequences on its own, but strongly enhances eye defects caused by Myc overexpression. Similarly, Spt5-knockdown in larval type 2 neuroblasts has only mild effects on brain development and survival of control flies, but dramatically shrinks the volumes of experimentally induced neuroblast tumors and significantly extends the lifespan of tumor-bearing animals. This beneficial effect is still observed when Spt5 is knocked down systemically and after tumor initiation, highlighting SPT5 as a potential drug target in human oncology.