The apparent detection of an exoplanet orbiting Fomalhaut was announced in 2008. However, subsequent observations of Fomalhaut b raised questions about its status: Unlike other exoplanets, it is bright in the optical and nondetected in the infrared, and its orbit appears to cross the debris ring around the star without...

In the Central Western Carpathians (CWC), most published paleomagnetic results from Permo-Mesozoic rocks document extensive remagnetizations and come from thin-skinned thrust units that have undergone multistage deformation. We present results from lower Triassic redbeds from the autochthonous cover overlying the basement that carry a primary magnetization. Petromagnetic results indicate that the dominant ferromagnetic carrier is hematite, while magnetic susceptibility and its anisotropy are controlled by both ferromagnetic and paramagnetic minerals. Magnetic fabrics document weak deformation related to Late Cretaceous shortening. The directions of the high unblocking temperature remanence components pass both reversal and fold tests, attesting to their primary nature. Paleomagnetic inclinations are flatter than expected from reference datasets, suggesting small latitudinal separation between the CWC and stable Europe. Paleomagnetic declinations are mostly clustered within individual mountain massifs, implying their tectonic coherence. They show only minor differences between the massifs, indicating a lack of significant vertical-axis tectonic rotations within the studied central parts of the CWC. The paleomagnetic declinations are therefore representative of the whole of the CWC in terms of regional paleogeographic interpretations, and imply moderate counterclockwise rotations (c. 26°) of the region with respect to stable Europe since the Early Triassic.

A time course experiment is a widely used design in the study of cellular processes such as differentiation or response to stimuli. In this paper, we propose time course regulatory analysis (TimeReg) as a method for the analysis of gene regulatory networks based on paired gene expression and chromatin accessibility data from a time course. TimeReg can be used to prioritize regulatory elements, to extract core regulatory modules at each time point, to identify key regulators driving changes of the cellular state, and to causally connect the modules across different time points. We applied the method to analyze paired chromatin accessibility and gene expression data from a retinoic acid (RA)–induced mouse embryonic stem cells (mESCs) differentiation experiment. The analysis identified 57,048 novel regulatory elements regulating cerebellar development, synapse assembly, and hindbrain morphogenesis, which substantially extended our knowledge of cis-regulatory elements during differentiation. Using single-cell RNA-seq data, we showed that the core regulatory modules can reflect the properties of different subpopulations of cells. Finally, the driver regulators are shown to be important in clarifying the relations between modules across adjacent time points. As a second example, our method on Ascl1-induced direct reprogramming from fibroblast to neuron time course data identified Id1/2 as driver regulators of early stage of reprogramming.

Cellular heterogeneity in gene expression is driven by cellular processes, such as cell cycle and cell-type identity, and cellular environment such as spatial location. The cell cycle, in particular, is thought to be a key driver of cell-to-cell heterogeneity in gene expression, even in otherwise homogeneous cell populations. Recent advances in single-cell RNA-sequencing (scRNA-seq) facilitate detailed characterization of gene expression heterogeneity and can thus shed new light on the processes driving heterogeneity. Here, we combined fluorescence imaging with scRNA-seq to measure cell cycle phase and gene expression levels in human induced pluripotent stem cells (iPSCs). By using these data, we developed a novel approach to characterize cell cycle progression. Although standard methods assign cells to discrete cell cycle stages, our method goes beyond this and quantifies cell cycle progression on a continuum. We found that, on average, scRNA-seq data from only five genes predicted a cell's position on the cell cycle continuum to within 14% of the entire cycle and that using more genes did not improve this accuracy. Our data and predictor of cell cycle phase can directly help future studies to account for cell cycle–related heterogeneity in iPSCs. Our results and methods also provide a foundation for future work to characterize the effects of the cell cycle on expression heterogeneity in other cell types.

Genome-wide association studies have implicated thousands of noncoding variants across common human phenotypes. However, they cannot directly inform the cellular context in which disease-associated variants act. Here, we use open chromatin profiles from discrete mouse cell populations to address this challenge. We applied stratified linkage disequilibrium score regression and evaluated heritability enrichment in 64 genome-wide association studies, emphasizing schizophrenia. We provide evidence that mouse-derived human open chromatin profiles can serve as powerful proxies for difficult to obtain human cell populations, facilitating the illumination of common disease heritability enrichment across an array of human phenotypes. We demonstrate that signatures from discrete subpopulations of cortical excitatory and inhibitory neurons are significantly enriched for schizophrenia heritability with maximal enrichment in cortical layer V excitatory neurons. We also show that differences between schizophrenia and bipolar disorder are concentrated in excitatory neurons in cortical layers II-III, IV, and V, as well as the dentate gyrus. Finally, we leverage these data to fine-map variants in 177 schizophrenia loci nominating variants in 104/177. We integrate these data with transcription factor binding site, chromatin interaction, and validated enhancer data, placing variants in the cellular context where they may modulate risk.

Molar element ratio analysis of element concentrations consists of four basic tools that provide substantial insight into the lithogeochemistry (and mineralogy) of rocks under examination. These tools consist of: (1) conserved element ratio analysis; (2) Pearce element ratio analysis; (3) general element ratio analysis; and (4) lithogeochemical mineral mode analysis. Conserved element ratio analysis is useful in creating a chemostratigraphic model for the host rocks to mineral deposits, whereas Pearce element ratio analysis and general element ratio analysis are primarily used to identify mineralogical and metasomatic controls on rock compositions and to investigate and quantify the extent of the material transfers that formed the host rocks and mineralization. Lithogeochemical mineral mode analysis converts element concentrations into mineral concentrations using a matrix-based change-of-basis operation, allowing lithogeochemical data to be interpreted in terms of mineral modes. It can be used to provide proper names to rocks, an important activity for an exploration geologist because of the implications that rock names have on genetic processes and mineral deposit models.

This paper provides a review of the theoretical foundations of each of these four tools and then illustrates how these techniques have been used in a variety of exploration applications to assist in the search for, evaluation and planning of, and the mining of mineral deposits. Examples include the evaluation of total digestion lithogeochemical datasets from mineral deposits hosted by igneous and sedimentary rocks and formed by hydrothermal and igneous processes. In addition, this paper illustrates a more recent geometallurgical application of these methods, whereby the mineral proportions determined by lithogeochemical mineral mode analysis are used to predict rock properties and obtain the ore body knowledge critical for resource evaluation, mine planning, mining and mine remediation.

Thematic collection: This article is part of the Exploration 17 collection available at: https://www.lyellcollection.org/cc/exploration-17

Multi-element geochemical surveys of rocks, soils, stream/lake/floodplain sediments and regolith are typically carried out at continental, regional and local scales. The chemistry of these materials is defined by their primary mineral assemblages and their subsequent modification by comminution and weathering. Modern geochemical datasets represent a multi-dimensional geochemical space that can be studied using multivariate statistical methods from which patterns reflecting geochemical/geological processes are described (process discovery). These patterns form the basis from which probabilistic predictive maps are created (process validation). Processing geochemical survey data requires a systematic approach to effectively interpret the multi-dimensional data in a meaningful way. Problems that are typically associated with geochemical data include closure, missing values, censoring, merging, levelling different datasets and adequate spatial sample design. Recent developments in advanced multivariate analytics, geospatial analysis and mapping provide an effective framework to analyse and interpret geochemical datasets. Geochemical and geological processes can often be recognized through the use of data discovery procedures such as the application of principal component analysis. Classification and predictive procedures can be used to confirm lithological variability, alteration and mineralization. Geochemical survey data of lake/till sediments from Canada and of floodplain sediments from Australia show that predictive maps of bedrock and regolith processes can be generated. Upscaling a multivariate statistics-based prospectivity analysis for arc-related Cu–Au mineralization from a regional survey in the southern Thomson Orogen in Australia to the continental scale, reveals a number of regions with a similar (or stronger) multivariate response and hence potentially similar (or higher) mineral potential throughout Australia.

Thematic collection: This article is part of the Exploration 17 collection available at: https://www.lyellcollection.org/cc/exploration-17

The bioprocessing industry uses recombinant mammalian cell lines to generate therapeutic biologic drugs. To ensure consistent product quality of the therapeutic proteins, it is imperative to have a controlled production process. Regulatory agencies and the biotechnology industry consider cell line "clonal origin" an important aspect of maintaining process control. Demonstration of clonal origin of the cell substrate, or production cell line, has received considerable attention in the past few years, and the industry has improved methods and devised standards to increase the probability and/or assurance of clonal derivation. However, older production cell lines developed before the implementation of these methods, herein referred to as "legacy cell lines," may not meet current regulatory expectations for demonstration of clonal derivation. In this article, the members of the IQ Consortium Working Group on Clonality present our position that the demonstration of process consistency and product comparability of critical quality attributes throughout the development life cycle should be sufficient to approve a license application without additional genetic analysis to support clonal origin, even for legacy cell lines that may not meet current day clonal derivation standards. With this commentary, we discuss advantages and limitations of genetic testing methods to support clonal derivation of legacy cell lines and wish to promote a mutual understanding with the regulatory authorities regarding their optional use during early drug development, subsequent to Investigational New Drug (IND) application and before demonstration of product and process consistency at Biologics License Applications (BLA) submission.

For manufacturers of both sterile and nonsterile pharmaceuticals, there is an expectation that the manufacturing process is performed in a manner that prevents extraneous contamination so that the products are provided in a safe, integral, pure, and unadulterated form. As part of that process, cleaning and disinfection are an absolute necessity. Although cleaning and disinfection support control of microbial contamination through preventive and corrective action, specific compendia methods do not currently exist. The intent of this paper is to provide a general guidance on how to perform disinfectant efficacy validation and implementation. This includes how to make sure the concepts are understood, how to interpret facility data and utilize it to demonstrate control awareness for your facilities, and how to leverage the data to reduce redundancies in validation or verification. This paper represents the thoughts and best practices of the authoring team and their respective companies and provides an efficient way to qualify disinfectants without impacting the quality of the study. If you choose to follow the recommendations in this paper, you must ensure that the appropriate rationale is sound and the scientific data is documented. It is the belief of the authoring team that only then will this approach meet regulatory requirements.

OBJECTIVE

There is a controversy over the association between obesity and end-stage renal disease (ESRD) in people with or without type 2 diabetes; therefore, we examined the effect of BMI on the risk of ESRD according to glycemic status in the Korean population.

Background:

Unnecessary antibiotic use in the community in Canada is not well defined. Our objective was to quantify unnecessary antibiotic prescribing in a Canadian primary care setting.

Background:

Previous studies examining potential sex and gender bias in the Canadian Resident Matching Service (CaRMS) match have had conflicting results. We examined the results of the CaRMS match over the period 2013–2019 to determine the potential association between applicants’ gender and the outcome of matching to their first-choice discipline.

In this retrospective study, whole-genome sequencing (WGS) data generated on an Ion Torrent platform was used to predict phenotypic drug resistance profiles for first- and second-line drugs among Swedish clinical Mycobacterium tuberculosis isolates from 2016 to 2018. The accuracy was ~99% for all first-line drugs and 100% for four second-line drugs. Our analysis supports the introduction of WGS into routine diagnostics, which might, at least in Sweden, replace phenotypic drug susceptibility testing in the future.

Treating malaria in HIV-coinfected individuals should consider potential drug-drug interactions. Artemether-lumefantrine is the most widely recommended treatment for uncomplicated malaria globally. Lumefantrine is metabolized by CYP3A4, an enzyme that commonly used antiretrovirals often induce or inhibit. A population pharmacokinetic meta-analysis was conducted using individual participant data from 10 studies with 6,100 lumefantrine concentrations from 793 nonpregnant adult participants (41% HIV-malaria-coinfected, 36% malaria-infected, 20% HIV-infected, and 3% healthy volunteers). Lumefantrine exposure increased 3.4-fold with coadministration of lopinavir-ritonavir-based antiretroviral therapy (ART), while it decreased by 47% with efavirenz-based ART and by 59% in the patients with rifampin-based antituberculosis treatment. Nevirapine- or dolutegravir-based ART and malaria or HIV infection were not associated with significant effects. Monte Carlo simulations showed that those on concomitant efavirenz or rifampin have 49% and 80% probability of day 7 concentrations <200 ng/ml, respectively, a threshold associated with an increased risk of treatment failure. The risk of achieving subtherapeutic concentrations increases with larger body weight. An extended 5-day and 6-day artemether-lumefantrine regimen is predicted to overcome these drug-drug interactions with efavirenz and rifampin, respectively.

Since 2018, the FDA has required that U.S. clinical trial results be reported to clinicaltrials.gov within a year of trial completion, but this mandate is often ignored. A recent study found that less than half of U.S. trials submitted results to the site by the deadline. Industry-led trials were the most likely to be reported on time.

Background:

Pancreatic cancer is the third leading cause of cancer death in the United States, and 80% of patients present with advanced, incurable disease. Risk markers for pancreatic cancer have been characterized, but combined models are not used clinically to identify individuals at high risk for the disease.

Background:

We assessed the ability to supplement existing epidemiologic/etiologic studies with data on treatment and clinical outcomes by linking to publicly available cancer registry and administrative databases.

Background:

The success of multisite collaborative research relies on effective data collection, harmonization, and aggregation strategies. Data Coordination Centers (DCC) serve to facilitate the implementation of these strategies. The utility of a DCC can be particularly relevant for research on rare diseases where collaboration from multiple sites to amass large aggregate datasets is essential. However, approaches to building a DCC have been scarcely documented.

Background:

Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel approach to simultaneously assess risks for multiple cancers to identify distinct multicancer configurations (multiple different cancer types that cluster in relatives) surrounding patients with familial bladder cancer.

Generative visuals and eerie sound design based on height maps of glaciers, canyons and estuaries. London-based motion graphic designer Sophie Marschner transforms real-world data into a delicate digital topography in Monolith. By using the height maps of various large-scale landmarks, including glaciers, canyons and estuaries, Marschner maps the outside world into a more intimate, digital […]

The post Sophie Marschner turns real-world data into a digital topography in Monolith appeared first on FACT Magazine.

AI can check satellite images of the ocean and distinguish between floating materials such as seaweed or plastics, which could help clean-up efforts

A new computational method for assigning the donor in single cell RNA sequencing experiments provides an accurate way to unravel data from a mixture of people. The Souporcell method could help study how genetic variants in different people affect which genes are expressed during infection or response to drugs, and help research into transplants, personalized medicine and malaria.

"If we don't have all the information in front of us to help us make decisions, then how do we flatten the curve and stop the spread?"

Unlikely to happen but interesting idea

Data leaks of this magnitude are virtually unheard of in Canada

Trying to make sense of calamities that have already caused more destruction to people’s livelihoods than the Great Recession

America can take its next steps toward reopening by placing an emphasis on emerging health data and closely examining how early states are performing, Housing and Urban Development Secretary Dr. Ben Carson asserted Saturday.

A new global simulation model offers the first long-term look at how urbanization -- the growth of cities and towns -- will unfold in the coming decades. The research team projects the total amount of urban areas on Earth can grow anywhere from 1.8 to 5.9-fold by 2100, building approximately 618,000 square miles.

The Dutch privacy watchdog said on Friday it would investigate how Chinese-owned social media app TikTok, which has become hugely popular during the COVID-19 pandemic, handles the data of millions of young users.

Equity markets rallied on Friday, hitting weekly highs, and oil prices gained as more governments around the world began gradually reopening their economies and Sino-American trade tensions eased.

A week packed with U.S. economic data is likely to provide investors with more evidence of the extent to which the coronavirus pandemic has hit growth, sharpening the debate on whether a rebound in stocks has been justified amid an unprecedented slowdown.

Read our live updates on coronavirus HERE Coronavirus: The symptoms

Bread for toasties, milk and toilet rolls were also best sellers

The number of people who have died in hospital after testing positive for coronavirus in the UK has reached 17,337, up from 16,509 in 24 hours.

Infection rates among NHS workers tested for Covid-19 were no higher for those treating patients face-to-face than for staff in non-clinical roles, a new study has found.

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Health officials fear Britons are starting to get complacent about the Covid-19 lockdown after traffic and mobile phone data revealed more of us are on the roads and looking for directions.

More than 4,300 people with coronavirus died in care homes in a fortnight, figures revealed today.

More than one million people have recovered from coronavirus worldwide, according to the latest figures from the John Hopkins University.

Pai’s “baffling” report ignores broadband gaps and high prices, Democrats say.

Comcast hasn't enforced data cap since March 13 because of pandemic.

Form requires sensitive data, including driver’s license and voided check scan.

Data can be retrieved even after owners perform a factory reset, researcher says.

The hacker had access to personal information, the ability to change passwords and two-factor authentication, and could steal valuable in-game items from some of the 'richest' players in the game