Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 65,351 bioRxiv papers from 289,483 authors.
Most downloaded bioRxiv papers, since beginning of last month
63,974 results found. For more information, click each entry to expand.
10,175 downloads scientific communication and education
Jason D Fernandes, Sarvenaz Sarabipour, Christopher T Smith, Natalie M Niemi, Nafisa M Jadavji, Ariangela J Kozik, Alex S Holehouse, Vikas Pejaver, Orsolya Symmons, Alexandre Wilson Bisson Filho, Amanda Haage
Many postdoctoral fellows in the STEM fields enter the academic job market with little knowledge of the process and expectations, and without any means to assess their qualifications relative to the general applicant pool. Demystifying this process is critical, as there is little information publicly available. In this work, we provide insight into the process of academic job searches by gathering data to establish background metrics for typical faculty job applicants, and further correlate these metrics with job search outcomes. We analyzed 317 responses to an anonymous survey for faculty job applicants from the May 2018 - May 2019 market cycle. Responses were about evenly split by gender, largely North American-centric and life science focused, and highly successful with 58% of applicants receiving at least one offer. Traditional metrics (funding, publications, etc.) of a positive research track record above a certain threshold of qualifications were unable to completely differentiate applicants that did and did not receive a job offer. Our findings suggest that there is no single clear path to a faculty job offer and that perhaps criteria not captured by our survey may also influence landing a faculty position above a certain threshold of qualification. Furthermore, our survey did capture applicants perception of the faculty job application process as unnecessarily stressful, time-consuming, and largely lacking in feedback, irrespective of a successful outcome. We hope that this study will provide an avenue for better data-driven decision making by the applicants and search committees, better evidence-based mentorship practices by principal investigators, and improved hiring practices by institutions.
9,059 downloads neuroscience
Brain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant package.
7,629 downloads molecular biology
Glycans modify lipids and proteins to mediate inter- and intramolecular interactions across all domains of life. RNA, another multifaceted biopolymer, is not thought to be a major target of glycosylation. Here, we challenge this view with evidence that mammalian cells use RNA as a third scaffold for glycosylation in the secretory pathway. Using a battery of chemical and biochemical approaches, we find that a select group of small noncoding RNAs including Y RNAs are modified with complex, sialylated N-glycans (glycoRNAs). These glycoRNA are present in multiple cell types and mammalian species, both in cultured cells and in vivo. Finally, we find that RNA glycosylation depends on the canonical N-glycan biosynthetic machinery within the ER/Golgi luminal spaces. Collectively, these findings suggest the existence of a ubiquitous interface of RNA biology and glycobiology suggesting an expanded role for glycosylation beyond canonical lipid and protein scaffolds.
6,752 downloads physiology
Objectives: This study explored the effects of gender-affirming treatment, which includes inhibition of endogenous sex hormones and replacement with cross-sex hormones, on muscle function, size and composition in 11 transwomen (TW) and 12 transmen (TM). Methods: Isokinetic knee extensor and flexor muscle strength was assessed at baseline (T00), 4 weeks after gonadal suppression of endogenous hormones but before hormone replacement (T0), and 3 (T3) and 11 (T12) months after hormone replacement. In addition, at T00 and T12, we assessed lower-limb muscle volume using MRI, and cross-sectional area (CSA) and radiological density using CT. Results: Thigh muscle volume increased (15%) in TM, which was paralleled by increased quadriceps CSA (15%) and radiological density (6%). In TW, the corresponding parameters decreased by -5% (muscle volume) and -4% (CSA), while density remained unaltered. The TM increased strength over the assessment period, while the TW generally maintained or slightly increased in strength. Baseline muscle volume correlated highly with strength (R>0.75), yet the relative change in muscle volume and strength correlated only moderately (R=0.65 in TW and R=0.32 in TM). The absolute levels of muscle volume and knee extension strength after the intervention still favored the TW. Conclusion: Cross-sex hormone treatment markedly affects muscle strength, size and composition in transgender individuals. Despite the robust increases in muscle mass and strength in TM, the TW were still stronger and had more muscle mass following 12 months of treatment. These findings add new knowledge that could be relevant when evaluating transwomen's eligibility to compete in the women's category of athletic competitions.
6,655 downloads neuroscience
Here we hypothesize that observing the visual stimuli of different categories trigger distinct brain states that can be decoded from noninvasive EEG recordings. We introduce an effective closed-loop BCI system that reconstructs the observed or imagined stimuli images from the co-occurring brain wave parameters. The reconstructed images are presented to the subject as a visual feedback. The developed system is applicable to training BCI-naive subjects because of the user-friendly and intuitive way the visual patterns are employed to modify the brain states.
6,588 downloads cancer biology
Chenchen Pan, Oliver Schoppe, Arnaldo Parra-Damas, Ruiyao Cai, Mihail Ivilinov Todorov, Gabor Gondi, Bettina von Neubeck, Alireza Ghasemi, Madita Alice Reimer, Javier Coronel, Boyan K. Garvalov, Bjoern Menze, Reinhard Zeidler, Ali Erturk
Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantifications in a model of spontaneous metastasis using human breast cancer cells allowed us to systematically analyze clinically relevant features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in whole mice. DeepMACT can thus considerably improve the discovery of effective therapeutic strategies for metastatic cancer.
5,968 downloads neuroscience
Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge. Towards this goal, we developed a deep learning-based framework to quantify and analyze the brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP). Our pipeline uses a fully convolutional network with a transfer learning approach for segmentation. We systematically analyzed vascular features of the whole brains including their length, bifurcation points and radius at the micrometer scale by registering them to the Allen mouse brain atlas. We reported the first evidence of secondary intracranial collateral vascularization in CD1-Elite mice and found reduced vascularization in the brainstem as compared to the cerebrum. VesSAP thus enables unbiased and scalable quantifications for the angioarchitecture of the cleared intact mouse brain and yields new biological insights related to the vascular brain function.
4,787 downloads molecular biology
Christopher D Go, James D R Knight, Archita Rajasekharan, Bhavisha Rathod, Geoffrey G Hesketh, Kento T Abe, Ji-Young Youn, Payman Samavarchi-Tehrani, Hui Zhang, Lucie Y Zhu, Evelyn Popiel, Jean-Philippe Lambert, Étienne Coyaud, Sally W T Cheung, Dushyandi Rajendran, Cassandra J Wong, Hana Antonicka, Laurence Pelletier, Brian Raught, Alexander F Palazzo, Eric A Shoubridge, Anne-Claude Gingras
Compartmentalization is an essential characteristic of eukaryotic cells, ensuring that cellular processes are partitioned to defined subcellular locations. High throughput microscopy and biochemical fractionation coupled with mass spectrometry have helped to define the proteomes of multiple organelles and macromolecular structures. However, many compartments have remained refractory to such methods, partly due to lysis and purification artefacts and poor subcompartment resolution. Recently developed proximity-dependent biotinylation approaches such as BioID and APEX provide an alternative avenue for defining the composition of cellular compartments in living cells. Here we report an extensive BioID-based proximity map of a human cell, comprising 192 markers from 32 different compartments that identifies 35,902 unique high confidence proximity interactions and localizes 4,145 proteins expressed in HEK293 cells. The recall of our localization predictions is on par with or better than previous large-scale mass spectrometry and microscopy approaches, but with higher localization specificity. In addition to assigning compartment and subcompartment localization for many previously unlocalized proteins, our data contain fine- grained localization information that, for example, allowed us to identify proteins with novel roles in mitochondrial dynamics. As a community resource, we have created humancellmap.org, a website that allows exploration of our data in detail, and aids with the analysis of BioID experiments.
3,423 downloads plant biology
Tatiana Mitiouchkina, Alexander S. Mishin, Louisa Gonzalez Somermeyer, Nadezhda M Markina, Tatiana V Chepurnyh, Elena B Guglya, Tatiana A Karataeva, Kseniia A Palkina, Ekaterina S Shakhova, Liliia I Fakhranurova, Sofia V Chekova, Aleksandra S Tsarkova, Yaroslav V Golubev, Vadim V Negrebetsky, Sergey A Dolgushin, Pavel V Shalaev, Olesya A Melnik, Victoria O Shipunova, Sergey M Deyev, Andrey I Bubyrev, Alexander S Pushin, Vladimir V Choob, Sergey V Dolgov, Fyodor A Kondrashov, Ilia V Yampolsky, Karen S. Sarkisyan
In contrast to fluorescent proteins, light emission from luciferase reporters requires exogenous addition of a luciferin substrate. Bacterial bioluminescence has been the single exception, where an operon of five genes is sufficient to produce light autonomously. Although commonly used in prokaryotic hosts, toxicity of the aldehyde substrate has limited its use in eukaryotes. Here we demonstrate autonomous luminescence in a multicellular eukaryotic organism by incorporating a recently discovered fungal bioluminescent system into tobacco plants. We monitored these light-emitting plants from germination to flowering, observing temporal and spatial patterns of luminescence across time scales from seconds to months. The dynamic patterns of luminescence reflected progression through developmental stages, circadian oscillations, transport, and response to injuries. As with other fluorescent and luminescent reporters, we anticipate that this system will be further engineered for varied purposes, especially where exogenous addition of substrate is undesirable.
3,259 downloads genetics
Francois Aguet, Alvaro N Barbeira, Rodrigo Bonazzola, Andrew Brown, Stephane E Castel, Brian Jo, Silva Kasela, Sarah Kim-Hellmuth, Yanyu Liang, Meritxell Oliva, Princy E Parsana, Elise Flynn, Laure Fresard, Eric R Gaamzon, Andrew R Hamel, Yuan He, Farhad Hormozdiari, Pejman Mohammadi, Manuel Muñoz-Aguirre, YoSon Park, Ashis Saha, Ayellet V Segrć, Benjamin J. Strober, Xiaoquan Wen, Valentin Wucher, Sayantan Das, Diego Garrido-Martín, Nicole R Gay, Robert E Handsaker, Paul J. Hoffman, Seva Kashin, Alan Kwong, Xiao Li, Daniel MacArthur, John M Rouhana, Matthew Stephens, Ellen Todres, Ana Viñuela, Gao Wang, Yuxin Zou, The GTEx Consortium, Christopher D Brown, Nancy Cox, Emmanouil Dermitzakis, Barbara E Engelhardt, Gad Getz, Roderic Guigo, Stephen B. Montgomery, Barbara E. Stranger, Hae Kyung Im, Alexis Battle, Kristin Ardlie, Tuuli Lappalainen
The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
3,093 downloads plant biology
Potential innovation in Plant research using gene-edited and genetically modified plants is currently being hindered by inefficient and costly plant transformation. We show that carbon dots formed from natural materials (quasi-spherical, <10nm nanoparticles) can act as a fast vehicle for carrying plasmids into mature plant cells, resulting in transient plant transformation in a number of important crop species with no negative impacts on photosynthesis or growth. We further show that GFP, Cas9, and gRNA introduced into wheat via foliar application (spraying on) of plasmid coated carbon dots are expressed and, in the case of Cas9, make genome edits in SPO11 genes. Therefore, we present a protocol for spray-on gene editing that is simple, inexpensive, fast, transforms in planta , and is applicable to multiple crop species. We believe this technique creates many opportunities for the future of plant transformation in research and shows great promise for plant protein production systems.
2,938 downloads genomics
Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5' unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.
2,865 downloads bioinformatics
Here we use deep transfer learning to quantify histopathological patterns across 17,396 H&E stained histopathology image slides from 28 cancer types and correlate these with underlying genomic and transcriptomic data. Pan-cancer computational histopathology (PC-CHiP) classifies the tissue origin across organ sites and provides highly accurate, spatially resolved tumor and normal distinction within a given slide. The learned computational histopathological features correlate with a large range of recurrent genetic aberrations, including whole genome duplications (WGDs), arm-level copy number gains and losses, focal amplifications and deletions as well as driver gene mutations within a range of cancer types. WGDs can be predicted in 25/27 cancer types (mean AUC=0.79) including those that were not part of model training. Similarly, we observe associations with 25% of mRNA transcript levels, which enables to learn and localise histopathological patterns of molecularly defined cell types on each slide. Lastly, we find that computational histopathology provides prognostic information augmenting histopathological subtyping and grading in the majority of cancers assessed, which pinpoints prognostically relevant areas such as necrosis or infiltrating lymphocytes on each tumour section. Taken together, these findings highlight the large potential of PC-CHiP to discover new molecular and prognostic associations, which can augment diagnostic workflows and lay out a rationale for integrating molecular and histopathological data.
2,745 downloads cancer biology
The U.S. National Toxicology Program (NTP) has carried out extensive rodent toxicology and carcinogenesis studies of radiofrequency radiation (RFR) at frequencies and modulations used in the U.S. telecommunications industry. This report presents partial findings from these studies. The occurrences of two tumor types in male Harlan Sprague Dawley rats exposed to RFR, malignant gliomas in the brain and schwannomas of the heart, were considered of particular interest and are the subject of this report. The findings in this report were reviewed by expert peer reviewers selected by the NTP and National Institutes of Health (NIH). These reviews and responses to comments are included as appendices to this report, and revisions to the current document have incorporated and addressed these comments. When the studies are completed, they will undergo additional peer review before publication in full as part of the NTP's Toxicology and Carcinogenesis Technical Reports Series. No portion of this work has been submitted for publication in a scientific journal. Supplemental information in the form of four additional manuscripts has or will soon be submitted for publication. These manuscripts describe in detail the designs and performance of the RFR exposure system, the dosimetry of RFR exposures in rats and mice, the results to a series of pilot studies establishing the ability of the animals to thermoregulate during RFR exposures, and studies of DNA damage. (1) Capstick M, Kuster N, Kuhn S, Berdinas-Torres V, Wilson P, Ladbury J, Koepke G, McCormick D, Gauger J, and Melnick R. A radio frequency radiation reverberation chamber exposure system for rodents; (2) Yijian G, Capstick M, McCormick D, Gauger J, Horn T, Wilson P, Melnick RL, and Kuster N. Life time dosimetric assessment for mice and rats exposed to cell phone radiation; (3) Wyde ME, Horn TL, Capstick M, Ladbury J, Koepke G, Wilson P, Stout MD, Kuster N, Melnick R, Bucher JR, and McCormick D. Pilot studies of the National Toxicology Program's cell phone radiofrequency radiation reverberation chamber exposure system; (4) Smith-Roe SL, Wyde ME, Stout MD, Winters J, Hobbs CA, Shepard KG, Green A, Kissling GE, Tice RR, Bucher JR, and Witt KL. Evaluation of the genotoxicity of cell phone radiofrequency radiation in male and female rats and mice following subchronic exposure.
2,707 downloads scientific communication and education
Understanding the growth of open access (OA) is important for deciding funder policy, subscription allocation, and infrastructure planning. This study analyses the number of papers available as OA over time. The models includes both OA embargo data and the relative growth rates of different OA types over time, based on the OA status of 70 million journal articles published between 1950 and 2019. The study also looks at article usage data, analyzing the proportion of views to OA articles vs views to articles which are closed access. Signal processing techniques are used to model how these viewership patterns change over time. Viewership data is based on 2.8 million uses of the Unpaywall browser extension in July 2019. We found that Green, Gold, and Hybrid papers receive more views than their Closed or Bronze counterparts, particularly Green papers made available within a year of publication. We also found that the proportion of Green, Gold, and Hybrid articles is growing most quickly. In 2019:- 31% of all journal articles are available as OA. - 52% of article views are to OA articles. Given existing trends, we estimate that by 2025: - 44% of all journal articles will be available as OA. - 70% of article views will be to OA articles. The declining relevance of closed access articles is likely to change the landscape of scholarly communication in the years to come.
2,536 downloads pharmacology and toxicology
While JUUL electronic cigarettes (ECs) have captured the majority of the EC market with a large fraction of their sales going to adolescents, little is known about their cytotoxicity and potential effects on health. The purpose of this study was to determine flavor chemical and nicotine concentrations in the eight currently marketed pre-filled JUUL EC cartridges (pods) and to evaluate the cytotoxicity of the different variants (e.g., Cool Mint and Creme Brulee) using in vitro assays. Nicotine and flavor chemicals were analyzed using gas chromatography/mass spectrometry in pod fluid before and after vaping and in the corresponding aerosols. 59 flavor chemicals were identified in JUUL pod fluids, and three were >1 mg/mL. Duplicate pods were similar in flavor chemical composition and concentration. Nicotine concentrations (average 60.9 mg/mL) were significantly higher than any EC products we have analyzed previously. Transfer efficiency of individual flavor chemicals that were >1mg/mL and nicotine from the pod fluid into aerosols was generally 35 - 80%. All pod fluids were cytotoxic at a 1:10 dilution (10%) in the MTT and neutral red uptake assays when tested with BEAS-2B lung epithelial cells. Most aerosols were cytotoxic in these assays at concentrations >1%. The cytotoxicity of aerosols was highly correlated with nicotine and ethyl maltol concentrations and moderately to weakly correlated with total flavor chemical concentration and menthol concentration. Our study demonstrates that: (1) some JUUL flavor pods have high concentrations of flavor chemicals that may make them attractive to youth, and (2) the concentrations of nicotine and some flavor chemicals (e.g. ethyl maltol) are high enough to be cytotoxic in acute in vitro assays, emphasizing the need to determine if JUUL products will lead to adverse health effects with chronic use.
2,334 downloads genomics
Single cell transcriptomics (scRNA-seq) has transformed our ability to discover and annotate cell types and states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, including high-dimensional immunophenotypes, chromatin accessibility, and spatial positioning, a key analytical challenge is to integrate these datasets into a harmonized atlas that can be used to better understand cellular identity and function. Here, we develop a computational strategy to "anchor" diverse datasets together, enabling us to integrate and compare single cell measurements not only across scRNA-seq technologies, but different modalities as well. After demonstrating substantial improvement over existing methods for data integration, we anchor scRNA-seq experiments with scATAC-seq datasets to explore chromatin differences in closely related interneuron subsets, and project single cell protein measurements onto a human bone marrow atlas to annotate and characterize lymphocyte populations. Lastly, we demonstrate how anchoring can harmonize in-situ gene expression and scRNA-seq datasets, allowing for the transcriptome-wide imputation of spatial gene expression patterns, and the identification of spatial relationships between mapped cell types in the visual cortex. Our work presents a strategy for comprehensive integration of single cell data, including the assembly of harmonized references, and the transfer of information across datasets. Availability: Installation instructions, documentation, and tutorials are available at: https://www.satijalab.org/seurat
2,025 downloads biochemistry
Methods to measure heterogeneity among cells are rapidly transforming our understanding of biology but are currently limited to molecular abundance measurements. We developed an approach to simultaneously measure biochemical activities and mRNA abundance in single cells to understand the heterogeneity of DNA repair activities across thousands of human lymphocytes, identifying known and novel cell-type-specific DNA repair phenotypes. Our approach provides a general framework for understanding functional heterogeneity among single cells.
2,023 downloads genomics
Xin Jin, Sean K Simmons, Amy X Guo, Ashwin S Shetty, Michelle Ko, Lan Nguyen, Elise B Robinson, Paul Oyler, Nathan Curry, Giulio Deangeli, Simona Lodato, Joshua Z Levin, Aviv Regev, Feng Zhang, Paola Arlotta
The thousands of disease risk genes and loci identified through human genetic studies far outstrip our current capacity to systematically study their functions. New experimental approaches are needed for functional investigations of large panels of genes in a biologically relevant context. Here, we developed a scalable genetic screen approach, in vivo Perturb-Seq, and applied this method to the functional evaluation of 35 autism spectrum disorder (ASD) de novo loss-of-function risk genes. Using CRISPR-Cas9, we introduced frameshift mutations in these risk genes in pools, within the developing brain in utero, and then performed single-cell RNA-Seq in the postnatal brain. We identified cell type-specific gene signatures from both neuronal and glial cell classes that are affected by genetic perturbations and pointed at elements of both convergent and divergent cellular effects across this cohort of ASD risk genes. In vivo Perturb-Seq pioneers a systems genetics approach to investigate at scale how diverse mutations affect cell types and states in the biologically relevant context of the developing organism.
2,002 downloads cancer biology
Recent studies have reported that CRISPR-Cas9 gene editing induces a p53 -dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations,. It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRISPR knockouts across the whole exome. Our analysis suggests that CRISPR gene editing can select for mutants of KRAS and VHL , at a level comparable to that reported for p53 . These predictions were further validated in a genome-wide manner by analyzing independent CRISPR screens and patients’ tumor data. Finally, we performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines, which further validated our predictions. In summary, our study systematically charts and points to the potential selection of specific cancer driver mutations during CRISPR-Cas9 gene editing. : #ref-11 : #ref-12
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