Most tweeted biology preprints, last 24 hours
*There are gaps in historical Twitter data, most notably in spring 2020. This may result in some preprints appearing with less tweets than they should.
157 results found. For more information, click each entry to expand.
6 tweets bioRxiv microbiology
The competence pili of transformable Gram-positive species form a subset of the diverse and widespread class of extracellular filamentous organelles known as type IV pili (T4P). In Gram-negative bacteria, T4P act through dynamic cycles of extension and retraction to carry out diverse activities including attachment, motility, protein secretion, and DNA uptake. It remains unclear whether T4P in Gram-positive species exhibit this same dynamic activity, and their mechanism of action for DNA uptake remains unclear. They are hypothesized to either (1) passively form transient cavities in the cell wall to facilitate DNA passage, (2) act as static adhesins to enrich DNA near the cell surface for subsequent uptake by membrane-embedded transporters, or (3) play an active role in translocating bound DNA via their dynamic activity. Here, using a recently described pilus labeling approach, we demonstrate that pneumococcal competence pili are highly dynamic structures that rapidly extend and retract from the cell surface. By labeling ComGC with bulky adducts, we further demonstrate that pilus retraction is essential for natural transformation. Together, our results indicate that Gram-positive type IV competence pili are dynamic and retractile structures that play an active role in DNA uptake.
6 tweets bioRxiv biochemistry
SARS-CoV-2 is constantly evolving, with more contagious mutations spreading rapidly. Using in vitro evolution to affinity maturate the receptor-binding domain (RBD) of the spike protein towards ACE2, resulted in the more contagious mutations, S477N, E484K, and N501Y to be among the first selected. This includes the British and South-African variants. Plotting the binding affinity to ACE2 of selected RBD mutations against their incidence in the population shows a strong correlation between the two. Further in vitro evolution enhancing binding by 600-fold provides guidelines towards potentially new evolving mutations with even higher infectivity. Yet, the high-affinity RBD is also an efficient drug, inhibiting SARS-CoV-2 infection. The 2.9[A] Cryo-EM structure of the high-affinity complex, including all rapidly spreading mutations provides structural basis for future drug development.
5 tweets bioRxiv cancer biology
(1) Background: Adaptive therapy aims to tackle cancer drug resistance by leveraging intra-tumoral competition between drug-sensitive and resistant cells. Motivated by promising results in prostate cancer there is growing interest in extending this approach to other cancers. Here we present a theoretical study of intra-tumoral competition during adaptive therapy, to identify under which circumstances it will be superior to aggressive treatment; (2) Methods: We use a 2-D, on-lattice, agent-based tumour model to examine the impact of different microenvironmental factors on the comparison between continuous drug administration and adaptive therapy. (3) Results: We show that the degree of crowding, the initial resistance fraction, the presence of resistance costs, and the rate of tumour cell turnover are key determinants of the benefit of adaptive therapy, and we study in detail how these factors alter competition between cells. We find that intra-specific competition between resistant cells plays an unexpectedly important role in the ability to control resistance. To conclude we show how differences in resistance cost and turnover change the tumour's spatial organisation and may explain differences in cycling speed observed in a cohort of 67 prostate cancer patients undergoing intermittent androgen deprivation therapy; (4) Conclusion: Our work provides insights into how adaptive therapy leverages inter- and intra-specific competition to control resistance, and shows that the tumour's spatial architecture will likely be an important factor in determining the quantitative benefit of adaptive therapy in patients.
5 tweets bioRxiv neuroscience
The physical basis of consciousness remains one of the most elusive concepts in current science. One influential conjecture is that consciousness is to do with some form of causality, measurable through information. The integrated information theory of consciousness (IIT) proposes that conscious experience, filled with rich and specific content, corresponds directly to a hierarchically organised, irreducible pattern of causal interactions; i.e. an integrated informational structure among elements of a system. Here, we tested this conjecture in a simple biological system (fruit flies), estimating the information structure of the system during wakefulness and general anesthesia. We found that causal interactions among populations of neurons during wakefulness collapsed to isolated clusters of interactions during anesthesia. We used classification analysis to quantify the accuracy of discrimination between wakeful and anesthetised states, and found that informational structures inferred conscious states with greater accuracy than a scalar summary of the structure, a measure which is generally championed as the main measure of IIT. Spatially, we found that the information structures collapsed rather uniformly across the fly brain. Our results speak to the potential utility of the novel concept of an 'informational structure' as a measure for level of consciousness, above and beyond simple scalar values. ### Competing Interest Statement The authors have declared no competing interest.
4 tweets bioRxiv plant biology
Bidirectional root-shoot signalling is likely key in orchestrating stress responses and ensuring plant survival. Here we show that Arabidopsis thaliana responses to microbial root commensals and light are interconnected along a microbiota-root-shoot axis. Microbiota and light manipulation experiments in a gnotobiotic system reveal that low photosynthetically active radiation (LP) perceived by leaves induce longdistance modulation of root bacterial, but not fungal or oomycetal communities. Reciprocally, bacterial root commensals and particularly Pseudomomas isolates are necessary for rescuing plant growth under LP. RNA-Seq, combined with leaf inoculation experiments with biotrophic and necrotrophic microbial pathogens indicate that microbiota-induced growth under LP coincides with transcriptional repression of immune responses, thereby increasing susceptibility to both pathogens. Inspection of a set of A. thaliana mutants demonstrates that orchestration of this light-dependent growth-defence trade-off requires the transcriptional regulator MYC2. Our work indicates that aboveground stress responses in plants can be governed by signals from microbial root commensals. ### Competing Interest Statement The authors have declared no competing interest.
4 tweets bioRxiv genomics
Single nucleotide mutation rates have critical implications for human evolution and genetic diseases. Accurate modeling of these mutation rates has long remained an open problem since the rates vary substantially across the human genome. A recent model, however, explained much of the variation by considering higher order nucleotide interactions in the local (7-mer) sequence context around mutated nucleotides. Despite this model's predictive value, we still lack a clear understanding of the biophysical mechanisms underlying the variations in genome-wide mutation rates. DNA shape features are geometric measurements of DNA structural properties, such as helical twist and tilt, and are known to capture information on interactions between neighboring nucleotides within a local context. Motivated by this characteristic of DNA shape features, we used them to model mutation rates in the human genome. These DNA shape feature based models improved both the accuracy (up to 14%) and the interpretability over the current nucleotide sequence-based models. The models also discovered the specific shape features that capture the most variability in mutation rates, and distinguished between the most and the least mutated sequence contexts, thus characterizing mutation promoting properties of the genomic DNA. To our knowledge, this is the first attempt that demonstrates the structural underpinnings of nucleotide mutations in the human genome and lays the groundwork for future studies to incorporate DNA shape information in modeling genetic variations.
4 tweets bioRxiv bioengineering
Epidural electrical stimulation (EES) of lumbosacral sensorimotor circuits improves leg motor control in animals and humans with spinal cord injury (SCI). Upper-limb motor control involves similar circuits, located in the cervical spinal cord, suggesting that EES could also improve arm and hand movements after quadriplegia. However, the ability of cervical EES to selectively modulate specific upper-limb motor nuclei remains unclear. Here, we combined a realistic computational model of EES of the cervical spinal cord with experiments in macaque monkeys to explore the mechanisms of this modulation and characterize the recruitment selectivity of cervical stimulation interfaces. Our results indicate that interfaces with lateral electrodes can target individual posterior roots and achieve selective modulation of arm motoneurons via the direct recruitment of pre-synaptic pathways. Intraoperative recordings suggested similar properties in humans. These results provide a framework for the design of neuro-technologies to improve arm and hand control in humans with quadriplegia.
4 tweets bioRxiv evolutionary biology
Ecological divergence is a main source of trait divergence between closely related species. Despite its importance in generating phenotypic diversity, the genetic architecture of most ecologically relevant traits is poorly understood. Differences in elevation can impose substantial selection for phenotypic divergence of both complex, correlated suites of traits (such as life history), as well as novel adaptations. Here, we use the Mimulus guttatus species complex to assess if divergence in elevation is accompanied by trait divergence in a group of closely related perennial species, and determine the genetic architecture of this divergence. We find that divergence in elevation is associated with differences in multivariate quantitative life history traits, as well as a unique trait; the production of rhizomes, which may play an important role in overwintering survival. However, the extent of phenotypic divergence among species depended on ontogeny, suggesting that species also diverged in investment strategies across development. Lastly, we show that the genetic architecture of life history divergence between two species is simple, involving few mid to large effect Quantitative Trait Loci (QTLs), and that the genetic architecture of the ability to produce rhizomes changes through development, which has potential implications for hybrid fitness in the wild.
3 tweets bioRxiv genomics
In this paper, we report a pipeline, AsmMix, which is capable of producing both contiguous and high-quality diploid genomes. The pipeline consists of two steps. In the first step, two sets of assemblies are generated: one is based on co-barcoded reads, which are highly accurate and haplotype-resolved but contain many gaps, the other assembly is based on single-molecule sequencing reads, which is contiguous but error-prone. In the second step, those two sets of assemblies are compared and integrated into a haplotype-resolved assembly with fewer errors. We test our pipeline using a dataset of human genome NA24385, perform variant calling from those assemblies and then compare against GIAB Benchmark. We show that AsmMix pipeline could produce highly contiguous, accurate, and haplotype-resolved assemblies. Especially the assembly mixing process could effectively reduce small-scale errors in the long read assembly.
3 tweets bioRxiv immunology
Christian Gaebler, Zijun Wang, Julio C. C. Lorenzi, Frauke Muecksch, Shlomo Finkin, Minami Tokuyama, Alice Cho, Mila Jankovic, Dennis Schaefer-Babajew, Thiago Y. Oliveira, Melissa Cipolla, Charlotte Viant, Christopher O. Barnes, Yaron Bram, Gaëlle Breton, Thomas Hägglöf, Pilar Mendoza, Arlene Hurley, Martina Turroja, Kristie Gordon, Katrina G Millard, Victor Ramos, Fabian Schmidt, Yiska Weisblum, Divya Jha, Michael Tankelevich, Gustavo Martinez-Delgado, Jim Yee, Roshni Patel, Juan Dizon, Cecille Unson-O’Brien, Irina Shimeliovich, Davide F. Robbiani, Zhen Zhao, Anna Gazumyan, Robert E. Schwartz, Theodora Hatziioannou, Pamela J. Bjorkman, Saurabh Mehandru, Paul D. Bieniasz, Marina Caskey, Michel C. Nussenzweig
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected 78 million individuals and is responsible for over 1.7 million deaths to date. Infection is associated with development of variable levels of antibodies with neutralizing activity that can protect against infection in animal models. Antibody levels decrease with time, but the nature and quality of the memory B cells that would be called upon to produce antibodies upon re-infection has not been examined. Here we report on the humoral memory response in a cohort of 87 individuals assessed at 1.3 and 6.2 months after infection. We find that IgM, and IgG anti-SARS-CoV-2 spike protein receptor binding domain (RBD) antibody titers decrease significantly with IgA being less affected. Concurrently, neutralizing activity in plasma decreases by five-fold in pseudotype virus assays. In contrast, the number of RBD-specific memory B cells is unchanged. Memory B cells display clonal turnover after 6.2 months, and the antibodies they express have greater somatic hypermutation, increased potency and resistance to RBD mutations, indicative of continued evolution of the humoral response. Analysis of intestinal biopsies obtained from asymptomatic individuals 4 months after coronavirus disease-2019 (COVID-19) onset, using immunofluorescence, or polymerase chain reaction, revealed persistence of SARS-CoV-2 nucleic acids and immunoreactivity in the small bowel of 7 out of 14 volunteers. We conclude that the memory B cell response to SARS-CoV-2 evolves between 1.3 and 6.2 months after infection in a manner that is consistent with antigen persistence.
3 tweets bioRxiv genomics
Adrian A Pater, Michael S Bosmeny, Christopher L Barkau, Katy N Ovington, Ramdevi Chilamkurthy, Mansi Parasrampuria, Seth B Eddington, Abadat O Yinusa, Adam A White, Paige E Metz, Rourke J Sylvain, Madison M Hebert, Scott W Benzinger, Koushik T Sinha, Keith T Gagnon
Genomic surveillance can lead to early identification of novel viral variants and inform pandemic response. Using this approach, we identified a new variant of the SARS-CoV-2 virus that emerged in the United States (U.S.). The earliest sequenced genomes of this variant, referred to as 20C-US, can be traced to Texas in late May of 2020. This variant circulated in the U.S. uncharacterized for months and rose to recent prevalence during the third pandemic wave. It initially acquired five novel, relatively unique non-synonymous mutations. 20C-US is continuing to acquire multiple new mutations, including three independently occurring spike protein mutations. Monitoring the ongoing evolution of 20C-US, as well as other novel emerging variants, will be essential for understanding SARS-CoV-2 host adaptation and predicting pandemic outcomes.
3 tweets bioRxiv neuroscience
Here we introduce HySyn, a system designed to rewire neural connectivity in vivo by reconstituting a functional heterologous synapse. We demonstrate that genetically targeted expression of the two HySyn components, a Hydra-derived neuropeptide and its receptor, creates de novo neuromodulatory transmission in a mammalian neuronal tissue culture model and rewires a behavioral circuit in vivo in the nematode Caenorhabditis elegans. HySyn can interface with existing optogenetic, chemogenetic and pharmacological approaches to functionally probe synaptic transmission, dissect neuropeptide signaling, or modulate specific neural circuits.
3 tweets bioRxiv bioinformatics
The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impractical due to the large size and high-dimensionality of IMS datasets. Instead, we propose an interpretable machine learning workflow that automatically identifies biomarker candidates by their mass-to-charge ratios, and that quantitatively estimates their relevance to recognizing a given biological class using Shapley additive explanations (SHAP). The task of biomarker candidate discovery is translated into a feature ranking problem: given a classification model that assigns pixels to different biological classes on the basis of their mass spectra, the molecular species that the model uses as features are ranked in descending order of relative predictive importance such that the top-ranking features have a higher likelihood of being useful biomarkers. Besides providing the user with an experiment-wide measure of a molecular species biomarker potential, our workflow delivers spatially localized explanations of the classification models decision-making process in the form of a novel representation called SHAP maps. SHAP maps deliver insight into the spatial specificity of biomarker candidates by highlighting in which regions of the tissue sample each feature provides discriminative information and in which regions it does not. SHAP maps also enable one to determine whether the relationship between a biomarker candidate and a biological state of interest is correlative or anticorrelative. Our automated approach to estimating a molecular species potential for characterizing a user-provided biological class, combined with the untargeted and multiplexed nature of IMS, allows for the rapid screening of thousands of molecular species and the obtention of a broader biomarker candidate shortlist than would be possible through targeted manual assessment. Our biomarker candidate discovery workflow is demonstrated on mouse-pup and rat kidney case studies. HighlightsO_LIOur workflow automates the discovery of biomarker candidates in imaging mass spectrometry data by using state-of-the-art machine learning methodology to produce a shortlist of molecular species that are differentially expressed with regards to a user-provided biological class. C_LIO_LIA model interpretability method called Shapley additive explanations (SHAP), with observational Shapley values, enables us to quantify the local and global predictive importance of molecular species with respect to recognizing a user-provided biological class. C_LIO_LIBy providing spatially localized explanations for a classification models decision-making process, SHAP maps deliver insight into the spatial specificity of biomarker candidates and enable one to determine whether (and where) the relationship between a biomarker candidate and the class of interest is correlative or anticorrelative. C_LI
3 tweets bioRxiv cancer biology
Ashley L. Kiemen, Alicia M. Braxton, Mia P. Grahn, Kyu S. Han, Jaanvi Mahesh Babu, Rebecca Reichel, Falone Amoa, Seung-Mo Hong, Toby C. Cornish, Elizabeth D Thompson, Laura D. Wood, Ralph H. Hruban, Pei-Hsun Wu, Denis Wirtz
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest forms of cancer. Accumulating evidence indicates the tumor microenvironment is highly associated with tumorigenesis through regulation of cellular physiology, signaling systems, and gene expression profiles of cancer cells. Yet the mechanisms by which the microenvironment evolves from normal pancreas architecture to precursor lesions and invasive cancer is poorly understood. Obtaining high-content and high-resolution information from a complex tumor microenvironment in large volumetric landscapes represents a key challenge in the field of cancer biology. To address this challenge, we established a novel method to reconstruct three-dimensional (3D) centimeter-scale tissues containing billions of cells from serially sectioned histological samples, utilizing deep learning approaches to recognize eight distinct tissue subtypes from hematoxylin and eosin stained sections at micrometer and single-cell resolution. Using samples from a range of normal, precancerous, and invasive pancreatic cancer tissue, we map in 3D modes of cancer invasion in the tumor microenvironment, and emphasize the need for further 3D quantification of biological systems.
3 tweets bioRxiv immunology
The devastating coronavirus disease 2019 (COVID-19) pandemic, due to SARS-CoV-2, has caused more than 47 million confirmed cases and more than 1.2 million human deaths around the globe, and most of the severe cases of COVID-19 in humans are associated with neurological symptoms such as anosmia and ageusia, and uncontrolled inflammatory immune response. Among therapeutic options, the use of the anti-parasitic drug ivermectin (IVM), has been proposed, given its possible anti-SARS-CoV-2 activity. Ivermectin is a positive allosteric modulator of the alpha-7 nicotinic acetylcholine receptor, which has been suggested to represent a target for the control of Covid-19 infection, with a potential immunomodulatory activity. We assessed the effects of IVM in SARS-CoV-2-intranasally-inoculated golden Syrian hamsters. Even though ivermectin had no effect on viral load, SARS-Cov-2-associated pathology was greatly attenuated. IVM had a sex-dependent and compartmentalized immunomodulatory effect, preventing clinical deterioration and reducing olfactory deficit in infected animals. Importantly, ivermectin dramatically reduced the Il-6/Il-10 ratio in lung tissue, which likely accounts for the more favorable clinical presentation in treated animals. Our data support IVM as a promising anti-COVID-19 drug candidate.
3 tweets bioRxiv cell biology
Micronuclei, whole or fragmented chromosomes which are spatially separated from the main nucleus, are strongly associated with genomic instability and have been identified as drivers of tumorigenesis. Paradoxically, Kif18a mutant mice produce micronuclei due to unaligned chromosomes in vivo but do not develop spontaneous tumors, raising questions about whether all micronuclei contribute similarly to genomic instability and cancer. We report here that micronuclei in Kif18a mutant mice form stable nuclear envelopes. Challenging Kif18a mutant mice via deletion of the Trp53 gene led to formation of thymic lymphoma with elevated levels of micronuclei. However, loss of Kif18a had modest or no effect on survival of Trp53 homozygotes and heterozygotes, respectively. To further explore micronuclear envelope stability in KIF18A KO cells, we compared micronuclei induced via different insults in cultured cells. Micronuclei in KIF18A KO cells form stable nuclear envelopes characterized by increased recruitment of core and non-core nuclear envelope components and successful expansion of decondensing chromatin compared to those induced by microtubule drug washout or exposure to radiation. We also observed that lagging chromosomes, which lead to micronucleus formation, were positioned closer to the main chromatin masses, and further from the central spindle, in KIF18A KO cells. Our studies provide in vivo support to models suggesting that micronuclear fate depends on the sub-cellular location of late lagging chromosomes and suggest that not all micronuclei actively promote tumorigenesis.
3 tweets bioRxiv ecology
Spatial capture-recapture (SCR) models have become the preferred tool for estimating densities of carnivores. Within this family of models are variants requiring identification of all individuals in each encounter (SCR), a subset of individuals only (generalized spatial mark-resight, gSMR), or no individual identification (spatial count or spatial presence-absence). Although each technique has been shown through simulation to yield unbiased results, the consistency and relative precision of estimates across methods in real-world settings are seldom considered. We tested a suite of models ranging from those only requiring detections of unmarked individuals to others that integrate remote camera, physical capture, genetic, and global positioning system (GPS) data into a "hybrid" model, to estimate population densities of black bears, bobcats, cougars, and coyotes. For each species we genotyped fecal DNA collected with detection dogs during a 20-day period. A subset of individuals from each species was affixed with GPS collars bearing unique markings and resighted by remote cameras over 140 days contemporaneous with scat collection. Camera-based gSMR models produced density estimates that differed by less than 10% from genetic SCR for bears, cougars, and coyotes once important sources of variation (sex or behavioral status) were controlled for. For bobcats, SCR estimates were 33% higher than gSMR. The cause of the discrepancies in estimates was likely attributable to challenges designing a study compatible for species with disparate home range sizes and the difficulty of collecting sufficient data in a timeframe in which demographic closure could be assumed. Unmarked models estimated densities that varied greatly from SCR, but estimates became more consistent in models wherein more individuals were identifiable. Hybrid models containing all data sources exhibited the most precise estimates for all species. For studies in which only sparse data can be obtained and the strictest model assumptions are unlikely to be met, we suggest researchers use caution making inference from models lacking individual identity. For best results, we further recommend the use of methods requiring at least a subset of the population is marked and that multiple datasets are incorporated when possible.
3 tweets bioRxiv biophysics
Motile cells migrate directionally in the electric field in a process known as galvanotaxis. Galvanotaxis is important in wound healing, development, cell division, and nerve growth. Different cell types migrate in opposite directions in electric fields, to either cathode, or anode, and the same cell can switch the directionality depending on chemical conditions. We previously reported that individual fish keratocyte cells sense electric fields and migrate to the cathode, while inhibition of PI3K reverses single cells to the anode. Many physiological processes rely on collective, not individual, cell migration, so here we report on directional migration of cohesive cell groups in electric fields. Uninhibited cell groups of any size move to the cathode, with speed decreasing and directionality increasing with the group size. Surprisingly, large groups of PI3K-inhibited cells move to the cathode, in the direction opposite to that of individual cells, which move to the anode, while such small groups are not persistently directional. In the large groups, cells' velocities are distributed unevenly: the fastest cells are at the front of the uninhibited groups, but at the middle and rear of the PI3K-inhibited groups. Our results are most consistent with the hypothesis, supported by the computational model, that cells inside and at the edge of the groups interpret directional signals differently. Namely, cells in the group interior are directed to the cathode independently of their chemical state. Meanwhile, edge cells behave like the individual cells: they are directed to the cathode/anode in uninhibited/PI3K-inhibited groups, respectively. As a result, all cells drive uninhibited groups to the cathode, but a mechanical tug-of-war between the inner and edge cells directs large PI3K-inhibited groups with cell majority in the interior to the cathode, while rendering small groups non-directional.
3 tweets bioRxiv microbiology
Zoonotic pandemics, like that caused by SARS-CoV-2, can follow the spillover of animal viruses into highly susceptible human populations. Their descendants have adapted to the human host and evolved to evade immune pressure. Coronaviruses acquire substitutions more slowly than other RNA viruses, due to a proofreading polymerase. In the spike glycoprotein, we find recurrent deletions overcome this slow substitution rate. Deletion variants arise in diverse genetic and geographic backgrounds, transmit efficiently, and are present in novel lineages, including those of current global concern. They frequently occupy recurrent deletion regions (RDRs), which map to defined antibody epitopes. Deletions in RDRs confer resistance to neutralizing antibodies. By altering stretches of amino acids, deletions appear to accelerate SARS-CoV-2 antigenic evolution and may, more generally, drive adaptive evolution.
3 tweets bioRxiv biophysics
To maintain membrane proteins soluble in aqueous solution, amphipathic compounds are used to shield the hydrophobic patch of their membrane insertion, which forms a belt around the protein. This hydrophobic belt is seldom looked at due to the difficulty to visualize it. Cryo-EM is now offering this possibility, where belts are visible in 3D reconstructions. We investigated membrane proteins solved in nanodiscs, amphipols or detergents to analyze whether the nature of the amphipathic compound influences the belt size in 3D reconstructions. We identified belt boundaries in map-density distributions and measured distances for every reconstruction. We showed that all the belts create on average similar reconstructions, whether they originate from the same protein, or from protein from different shapes and structures. There is no difference among detergents or types of nanodisc used. These observations illustrate that the belt observed in 3D reconstructions corresponds to the minimum ordered layer around membrane proteins.
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
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- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
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