Anisotropic Panglial Coupling Reflects Tonotopic Organization in the Inferior Colliculus

Astrocytes and oligodendrocytes in different brain regions form panglial networks and the topography of such networks can correlate with neuronal topography and function. Astrocyte-oligodendrocyte networks in the lateral superior olive (LSO)—an auditory brainstem nucleus—were found to be anisotropic with a preferred orientation orthogonally to the tonotopic axis. We hypothesized that such a specialization might be present in other tonotopically organized brainstem nuclei, too. Thus, we analyzed gap junctional coupling in the center of the inferior colliculus (IC)—another nucleus of the auditory brainstem that exhibits tonotopic organization. In acute brainstem slices obtained from mice, IC networks were traced employing whole-cell patch-clamp recordings of single sulforhodamine (SR) 101-identified astrocytes and concomitant intracellular loading of the gap junction-permeable tracer neurobiotin. The majority of dye-coupled networks exhibited an oval topography, which was preferentially oriented orthogonal to the tonotopic axis. Astrocyte processes showed preferentially the same orientation indicating a correlation between astrocyte and network topography. In addition to SR101-positive astrocytes, IC networks contained oligodendrocytes. Using Na+ imaging, we analyzed the capability of IC networks to redistribute small ions. Na+ bi-directionally diffused between SR101-positive astrocytes and SR101-negative cells—presumably oligodendrocytes—showing the functionality of IC networks. Taken together, our results demonstrate that IC astrocytes and IC oligodendrocytes form functional anisotropic panglial networks that are preferentially oriented orthogonal to the tonotopic axis. Thus, our data indicate that the topographic specialization of glial networks seen in IC and LSO might be a general feature of tonotopically organized auditory brainstem nuclei

Universal prediction of cell-cycle position using transfer learning.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBackground: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data. Results: Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays. Conclusions: Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data. Keywords: Cell cycle; Single-cell RNA-sequencing; Transfer learning.Chan Zuckerberg Initiative DAF Silicon Valley Community Foundation United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) Appeared in source as:National Institute of General Medical Sciences of the National Institutes of Health National Science Foundation (NSF) National Institute of Agin Maryland Stem Cell Research Foundation Kavli Neurodiscovery Institute Johns Hopkins Provost Award Program BRAIN Initiative United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Neurological Disorders & Stroke (NINDS) Appeared in source as:National Institute of Neurological Disorder

Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy

BACKGROUND: Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. OBJECTIVES: To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies. METHODS: The risk prediction model was developed using the British Association of Dermatologists Biologic Interventions Register (BADBIR), and the German Psoriasis Registry PsoBest was used as the validation dataset. Model discrimination and calibration were assessed internally and externally using the C-statistic, the calibration slope and the calibration in the large. RESULTS: Overall 175 (1·7%) out of 10 033 participants from BADBIR and 41 (1·7%) out of 2423 participants from PsoBest developed a serious infection within 1 year of therapy initiation. Selected predictors in a multiple logistic regression model included nine baseline covariates, and starting infliximab was the strongest predictor. Evaluation of model performance showed a bootstrap optimism-corrected C-statistic of 0·64 [95% confidence interval (CI) 0·60-0·69], calibration in the large of 0·02 (95% CI -0·14 to 0·17) and a calibration slope of 0·88 (95% CI 0·70-1·07), while external validation performance was poor, with C-statistic 0·52 (95% CI 0·42-0·62), calibration in the large 0·06 (95% CI -0·25 to 0·37) and calibration slope 0·36 (95% CI -0·24 to 0·97). CONCLUSIONS: We present the first results of the development of a multivariable prediction model. This model may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision-making process

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Державне регулювання системи факторів оцінки та мінімізації ризиків легалізації коштів, одержаних злочинним шляхом в процесі фінансового моніторингу комерційних банків України

Основною ціллю данної статті є формулювання важливості впливу чітко визначених факторів, які впливають на процеси фінансового моніторингу в комерційних банків України. Виходячи з поставлених цілей, завданнями даної статті є розроблення моделі оцінки ризиків банківської установи щодо протидії легалізації коштів одержаних злочинним шляхом в системі внутрішньобанківського фінансового моніторингу, та використання в подальшому запропонованих стратегій управління наслідками даних ризиків

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

A concept for integrated care pathways for atopic dermatitis-A GA2^{2} LEN ADCARE initiative

Introduction: The integrated care pathways for atopic dermatitis (AD‐ICPs) aim to bridge the gap between existing AD treatment evidence‐based guidelines and expert opinion based on daily practice by offering a structured multidisciplinary plan for patient management of AD. ICPs have the potential to enhance guideline recommendations by combining interventions and aspects from different guidelines, integrating quality assurance, and describing co‐ordination of care. Most importantly, patients can enter the ICPs at any level depending on AD severity, resources available in their country, and economic factors such as differences in insurance reimbursement systems. Methods: The GA$^{2}$LEN ADCARE network and partners as well as all stakeholders, abbreviated as the AD‐ICPs working group, were involved in the discussion and preparation of the AD ICPs during a series of subgroup workshops and meetings in years 2020 and 2021, after which the document was circulated within all GAL$^{2}$EN ADCARE centres. Results: The AD‐ICPs outline the diagnostic procedures, possible co‐morbidities, different available treatment options including differential approaches for the pediatric population, and the role of the pharmacists and other stakeholders, as well as remaining unmet needs in the management of AD. Conclusion: The AD‐ICPs provide a multidisciplinary plan for improved diagnosis, treatment, and patient feedback in AD management, as well as addressing critical unmet needs, including improved access to care, training specialists, implementation of educational programs, assessment on the impact of climate change, and fostering a personalised treatment approach. By focusing on these key areas, the initiative aims to pave the way for a brighter future in the management of AD