Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,572 bioRxiv papers from 308,082 authors.
Most tweeted bioRxiv papers, last 24 hours
512 results found. For more information, click each entry to expand.
10 tweets neuroscience
Chiara Morelli, Laura Castaldi, Sam J. Brown, Lina L. Streich, Alexander Websdale, Francisco J Taberner, Blanka Cerreti, Alessandro Barenghi, Kevin M. Blum, Julie Sawitzke, Tessa Frank, Laura Steffens, Balint Doleschall, Joana Serrao, Stefan G Lechner, Robert Prevedel, Paul A Heppenstall
The vasculature is innervated by a network of peripheral afferents that sense and regulate blood flow. Here, we describe a system of non-peptidergic sensory neurons with cell bodies in the spinal ganglia that regulate vascular tone in the distal arteries. We identify a population of mechanosensitive neurons marked by TrkC and Tyrosine hydroxylase in the dorsal root ganglia that project to blood vessels. Local stimulation of these neurons decreases vessel diameter and blood flow, while systemic activation increases systolic blood pressure and heart rate variability via the sympathetic nervous system. Chemogenetic inactivation or ablation of the neurons provokes variability in local blood flow leading to a reduction in systolic blood pressure, increased heart rate variability and ultimately lethality within 48 hours. Thus, TrkC/Tyrosine hydroxylase positive sensory neurons form part of a sensory feedback mechanism that maintains cardiovascular homeostasis through the autonomic nervous system.
9 tweets neuroscience
Cortical microcircuits in a variety of brain regions express similar, highly nonrandom, synaptically-connected cell triplets. The origin of these universal network building blocks is unclear and was hypothesized to result from plasticity and learning processes. Here we combined in-silico modeling of dense cortical microcircuits with electrophysiological/anatomical studies to demonstrate that this recurring connectivity emerges primarily from the anisotropic morphology of cortical neurons and their embedding in the cortical volume. Using graph-theoretical and machine-learning tools, we developed a series of progressively more complex generative models for circuit connectivity that considers the geometry of cortical neurons. This framework provided predictions for the spatial alignment of cells composing particular cell-triplets which were directly validated via in-vitro whole-cell 12-patches recordings (7,309 triplets) in the rat somatosensory cortex. We concluded that the local geometry of cortical neurons imposes an innate, highly structured, global network structure, a skeleton upon which fine-grained structural and functional plasticity processes take place.
9 tweets bioinformatics
Many modern problems in medicine and public health leverage machine learning methods to predict outcomes based on observable covariates. In an increasingly wide array of settings, these predicted outcomes are used in subsequent statistical analysis, often without accounting for the distinction between observed and predicted outcomes. We call inference with predicted outcomes post-prediction inference . In this paper, we develop methods for correcting statistical inference using outcomes predicted with an arbitrary machine learning method. Rather than trying to derive the correction from the first principles for each machine learning tool, we make the observation that there is typically a low-dimensional and easily modeled representation of the relationship between the observed and predicted outcomes. We build an approach for the post-prediction inference that naturally fits into the standard machine learning framework. We estimate the relationship between the observed and predicted outcomes on the testing set and use that model to correct inference on the validation set and subsequent statistical models. We show our postpi approach can correct bias and improve variance estimation (and thus subsequent statistical inference) with predicted outcome data. To show the broad range of applicability of our approach, we show postpi can improve inference in two totally distinct fields: modeling predicted phenotypes in re-purposed gene expression data and modeling predicted causes of death in verbal autopsy data. We have made our method available through an open-source R package: https://github.com/SiruoWang/postpi
9 tweets ecology
The contribution of fungi to carbon (C) and nitrogen (N) cycling is related to their growth efficiency (amount of biomass produced per unit of substrate utilized). The concentration and availability of N influences the activity and growth efficiency of saprotrophic fungi. When N is scarce in soils, fungi have to invest more energy to obtain soil N, which could result in lower growth efficiencies. Yet, the effect of N on growth efficiencies of individual species of fungi in soil has not been studied extensively. In this study we investigated the influence of different concentrations of mineral N on the growth efficiency of two common soil fungi, Trichoderma harzanium and Mucor hiemalis in a soil-like environment. We hypothesized that a higher N availability will coincide with higher biomass production and growth efficiency. To test this, we measured fungal biomass production as well as the respiration fluxes in sand microcosms amended with cellobiose and mineral N at different C:N ratios. We found that for both fungal species lower C:N ratios resulted in the highest biomass production as well as the highest growth efficiency. This may imply that when N is applied concurrently with a degradable C source, a higher amount of N will be temporarily immobilized into fungal biomass.
9 tweets systems biology
Reversible protein phosphorylation regulates virtually every cellular process and is arguably the most well-studied post-translational modification. Still, less than 3% of the phosphorylation sites identified in humans have annotated functions. Functionally-relevant phosphorylation sites are known to trigger conformational changes to proteins and/or to regulate their interactions with other proteins, nucleic acids and small molecules - all of which can be reflected in the thermal stability of a protein. Thus, combining thermal proteome profiling (TPP) with phosphoproteomics (phospho-TPP) provides a way to assess the functional relevance of identified phosphorylation sites on a proteome-wide scale by comparing the melting behavior of a protein and its phosphorylated form(s). We performed phospho-TPP experiments in HeLa cells with an optimized protocol, and conclude that phosphorylation does affect protein thermal stability, but to a much lesser extent than previously reported.
9 tweets neuroscience
Michael Eyre, Sean P. Fitzgibbon, Judit Ciarrusta, Lucilio Cordero-Grande, Anthony N. Price, Tanya Poppe, Andreas Schuh, Emer Hughes, Camilla O'Keeffe, Jakki Brandon, Daniel Cromb, Katy Vecchiato, Jesper Andersson, Eugene Duff, Serena J. Counsell, Stephen M. Smith, Daniel Rueckert, Joseph V. Hajnal, Tomoki Arichi, Jonathan O'Muircheartaigh, Dafnis Batalle, A. David Edwards
The Developing Human Connectome Project (dHCP) is an Open Science project which provides the first large sample of neonatal functional MRI (fMRI) data with high temporal and spatial resolution. This data enables mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organisation in humans. Here, we characterise in unprecedented detail the maturation and integrity of resting-state networks (RSNs) at normal term age in 337 infants (including 65 born preterm). First, we applied group independent component analysis (ICA) to define 11 RSNs in term-born infants scanned at 43.5-44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37-43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder which occur frequently in preterm children. Overall, we find a robust, modular, symmetrical functional brain organisation at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher-order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.
9 tweets neuroscience
The prefrontal cortex (PFC) is characterized by delayed maturation that extends until adulthood. Although the adolescent PFC has been well investigated, the cellular mechanisms controlling the early development of prefrontal circuits are still largely unknown. Our study delineates the developmental cellular processes that are on-going in the mouse medial PFC (mPFC) during the second and third postnatal weeks and compares them to those in the barrel cortex (BC). We show that basal synaptic transmission decreases from the second to the third postnatal week in both brain areas due to increased spontaneous inhibitory currents and reduced excitatory ones. Furthermore, increasing GABAA receptor (GABAAR) activity leads to increased basal synaptic response of neonatal mPFC, but not BC. Additionally, the K-Cl co-transporter 2 (KCC2) expression is decreased in the neonatal mPFC compared to the pre-juvenile one as well as to the neonatal and pre-juvenile BC, suggesting that GABAAR function in the neonatal mPFC is non-inhibitory. Moreover, the intrinsic properties of both interneurons and pyramidal cells change with age and relate to augmented network activity across development.
9 tweets genomics
Kevin J. McKernan, Yvonne Helbert, Liam T Kane, Heather Ebling, Lei Zhang, Biao Liu, Zachary Eaton, Stephen McLaughlin, Sarah Kingan, Primo Baybayan, Gregory Concepcion, Mark Jordan, Alberto Riva, William Barbazuk, Timothy Harkins
Cannabis is a diverse and polymorphic species. To better understand cannabinoid synthesis inheritance and its impact on pathogen resistance, we shotgun sequenced and assembled a Cannabis trio (sibling pair and their offspring) utilizing long read single molecule sequencing. This resulted in the most contiguous Cannabis sativa assemblies to date. These reference assemblies were further annotated with full-length male and female mRNA sequencing (Iso-Seq) to help inform isoform complexity, gene model predictions and identification of the Y chromosome. To further annotate the genetic diversity in the species, 40 male, female, and monoecious cannabis and hemp varietals were evaluated for copy number variation (CNV) and RNA expression. This identified multiple CNVs governing cannabinoid expression and 82 genes associated with resistance to Golovinomyces chicoracearum, the causal agent of powdery mildew in cannabis. Results indicated that breeding for plants with low tetrahydrocannabinolic acid (THCA) concentrations may result in deletion of pathogen resistance genes. Low THCA cultivars also have a polymorphism every 51 bases while dispensary grade high THCA cannabis exhibited a variant every 73 bases. A refined genetic map of the variation in cannabis can guide more stable and directed breeding efforts for desired chemotypes and pathogen-resistant cultivars.
9 tweets ecology
While glacier ice cores provide climate information over tens to hundreds of thousands of years, study of microbes is challenged by ultra-low-biomass conditions, and virtually nothing is known about co-occurring viruses. Here we establish ultra-clean microbial and viral sampling procedures and apply them to two ice cores from the Guliya ice cap (northwestern Tibetan Plateau, China) to study these archived communities. This method reduced intentionally contaminating bacterial, viral, and free DNA to background levels in artificial-ice-core control experiments, and was then applied to two authentic ice cores to profile their microbes and viruses. The microbes differed significantly across the two ice cores, presumably representing the very different climate conditions at the time of deposition that is similar to findings in other cores. Separately, viral particle enrichment and ultra-low-input quantitative viral metagenomic sequencing from ~520 and ~15,000 years old ice revealed 33 viral populations (i.e., species-level designations) that represented four known genera and likely 28 novel viral genera (assessed by gene-sharing networks). In silico host predictions linked 18 of the 33 viral populations to co-occurring abundant bacteria, including Methylobacterium, Sphingomonas, and Janthinobacterium, indicating that viruses infected several abundant microbial groups. Depth-specific viral communities were observed, presumably reflecting differences in the environmental conditions among the ice samples at the time of deposition. Together, these experiments establish a clean procedure for studying microbial and viral communities in low-biomass glacier ice and provide baseline information for glacier viruses, some of which appear to be associated with the dominant microbes in these ecosystems.
9 tweets neuroscience
Animals engage in intricate action sequences that are constructed during instrumental learning. There is broad consensus that the basal ganglia play a crucial role in the formation and fluid performance of action sequences. To investigate the role of the basal ganglia direct and indirect pathways in action sequencing, we virally expressed Cre-dependent Gi-DREADDs in either the dorsomedial (DMS) or dorsolateral (DLS) striatum during and/or after action sequence learning in D1 and D2 Cre rats. Action sequence performance in D1 Cre rats was slowed down early in training when DREADDs were activated in the DMS, but sped up when activated in the DLS. Acquisition of the reinforced sequence was hindered when DREADDs were activated in the DLS of D2 Cre rats. Outcome devaluation tests conducted after training revealed that the goal-directed control of action sequence rates was immune to chemogenetic inhibition—rats suppressed the rate of sequence performance when rewards were devalued. Sequence initiation latencies were generally sensitive to outcome devaluation, except in the case where DREADD activation was removed in D2 Cre rats that previously experienced DREADD activation in the DMS during training. Sequence completion latencies were generally not sensitive to outcome devaluation, except in the case where D1 Cre rats experienced DREADD activation in the DMS during training and test. Collectively, these results suggest that the indirect pathway originating from the DLS is part of a circuit involved in the effective reinforcement of action sequences, while the direct and indirect pathways originating from the DMS contribute to the goal-directed control of sequence completion and initiation, respectively.
9 tweets bioinformatics
Motivation: Accurate prediction of liquid chromatographic retention times from small molecule structures is useful for reducing experimental measurements and for improved identification in targeted and untargeted MS. However, different experimental setups (e.g. differences in columns, gradients, solvents, or stationary phase) have given rise to a multitude of prediction models that only predict accurate retention times for a specific experimental setup. In practice this typically results in the fitting of a new predictive model for each specific type of setup, which is not only inefficient but also requires substantial prior data to be accumulated on each such setup. Results: Here we introduce the concept of generalized calibration, which is capable of the straightforward mapping of retention time models between different experimental setups. This concept builds on the database-controlled calibration approach implemented in PredRet, and fits calibration curves on predicted retention times instead of only on observed retention times. We show that this approach results in significantly higher accuracy of elution peak prediction than is achieved by setup-specific models.
9 tweets animal behavior and cognition
Whether changes in animal behavior allow for short-term earthquake predictions has been debated for a long time. During the 2016/2017 earthquake sequence in Italy, we instrumentally observed the activity of farm animals (cows, dogs, sheep) close to the epicenter of the devastating magnitude M6.6 Norcia earthquake (Oct-Nov 2016) and over a subsequent longer observation period (Jan-Apr 2017). Relating 5304 (in 2016) and 12948 (in 2017) earthquakes with a wide magnitude range (0.4 ≤ M ≤ 6.6) to continuously measured animal activity, we detected how the animals collectively reacted to earthquakes. We also found consistent anticipatory activity prior to earthquakes during times when the animals were in a stable, but not during their time on a pasture. We detect these anticipatory patterns not only in periods with high, but also in periods of low seismic activity. Earthquake anticipation times (1-20hrs) are negatively correlated with the distance between the farm and earthquake hypocenters. Our study suggests that continuous instrumental monitoring of animal collectives has the potential to provide statistically reliable patterns of pre-seismic activity that could allow for short-term earthquake forecasting.
9 tweets neuroscience
Stephen T Johnston, Sarah L Parylak, Stacy Kim, Nolan Mac, Christina Lim, Iryna Gallina, Cooper Bloyd, Alexander Newberry, Christian Saavedra, Ondrej Nov&aacutek, J Tiago Goncalves, Fred H. Gage, Matthew Shtrahman
Recombinant adeno-associated virus (rAAV) has been widely used as a viral vector across mammalian biology and has been shown to be safe and effective in human gene therapy. We demonstrate that neural progenitor cells (NPCs) and immature dentate granule cells (DGCs) within the adult murine hippocampus are particularly sensitive to rAAV-induced cell death. Cell loss is dose dependent and nearly complete at experimentally relevant viral titers. rAAV-induced cell death is rapid and persistent, with loss of BrdU-labeled cells within 18 hours post-injection and no evidence of recovery of adult neurogenesis at 3 months post-injection. The remaining mature DGCs appear hyperactive 4 weeks post-injection based on immediate early gene expression, consistent with previous studies investigating the effects of attenuating adult neurogenesis. In vitro application of AAV or electroporation of AAV2 inverted terminal repeats (ITRs) is sufficient to induce cell death. Efficient transduction of the dentate gyrus (DG)-without ablating adult neurogenesis-can be achieved by injection of rAAV2-retro serotyped virus into CA3. rAAV2-retro results in efficient retrograde labeling of mature DGCs and permits in vivo 2-photon calcium imaging of dentate activity while leaving adult neurogenesis intact. These findings expand on recent reports implicating rAAV-linked toxicity in stem cells and other cell types and suggest that future work using rAAV as an experimental tool in the DG and as a gene therapy for diseases of the central nervous system (CNS) should be carefully evaluated.
8 tweets cancer biology
Valentina Pita-Grisanti, Andrew W Dangel, Kristyn Gumpper, Andrea Ludwig, Olivia Ueltschi, Xiaokui Mo Mo, Maciej Pietrzak, Amy Webb, Rosa F Hwang, Madelyn Traczek, Niharika Badi, Zobeida Cruz-Monserrate
Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease with poor outcomes. Iron is known to signal cellular responses, and its levels are regulated by lipocalin-2 (LCN2) expression, a PDAC pro-tumorigenic molecule. However, how iron and LCN2 function in PDAC is unclear. Here we demonstrate that iron levels regulate PDAC cell proliferation, invasion, expression of epithelial to mesenchymal tumor markers, and pro-inflammatory cytokines. Iron chelation increased the expression of the LCN2 receptor SLC22A17 in pancreatic stellate cells and the anti-metastatic gene NDRG1 in PDAC cells. Deletion of Lcn2 in mouse tumor cells modulated the expression of genes involved in extracellular matrix deposition and cell migration. Moreover, cellular iron responses were dependent on the Kras mutation status of cells, and LCN2 expression levels. Deletion of Lcn2 expression in PDAC suggests a protective role against metastasis. Thus, iron modulation and LCN2 blockade could serve as potential therapeutic approaches against PDAC.
8 tweets bioinformatics
Jianing Liu, Arun S. Seetharam, Kapeel Chougule, Shujun Ou, Kyle William Swentowsky, Jonathan Isaiah Gent, Victor Llaca, Margaret Woodhouse, Nancy Manchanda, Gernot G Presting, David Kudrna, Magdy Alabady, Candice Hirsch, Kevin Fengler, Doreen Ware, Todd Michael, Matthew Hufford, Kelly Dawe
Creating gapless telomere-to-telomere assemblies of complex genomes is one of the ultimate challenges in genomics. We used long read technologies and an optical map based approach to produce a maize genome assembly composed of only 63 contigs. The B73-Ab10 genome includes gapless assemblies of chromosome 3 (236 Mb) and chromosome 9 (162 Mb), multiple highly repetitive centromeres and heterochromatic knobs, and 53 Mb of the Ab10 meiotic drive haplotype.
8 tweets bioinformatics
Open data has two principal uses: (i) to reproduce original findings and (ii) to allow researchers to ask new questions with existing data. The latter enables discoveries by allowing a more diverse set of viewpoints and hypotheses to approach the data, which is self-evidently advantageous for the progress of science. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives in the literature. Current practice suggests that the number of tests to be corrected is the number of simultaneous tests performed by a researcher. Here we demonstrate that sequential hypothesis testing on the same dataset by multiple researchers can inflate error rates. This finding is troubling because, as more researchers embrace an open dataset, the likelihood of false positives (i.e. type I errors) will increase. Thus, we should expect a dataset’s utility for discovering new true relations between variables to decay. We consider several sequential correction procedures. These solutions can reduce the number of false positives but, at the same time, can prompt undesired challenges to open data (e.g. incentivising restricted access).
8 tweets genomics
Motivation: The emergence of techniques for the analysis of 5′-monophosphate mRNA degradation intermediates necessitates development of tools for automated analysis of 5′ endpoint distribution for inference on ribosome dynamics, mRNA cleavage patterns, binding sites, etc. Results: Here we present fivepseq: an easy-to-use command-line application for analysis and visualization of 5′ endpoint count distribution from RNA-seq datasets. It produces interactive reports for ease of exploratory analysis that provide single-nucleotide resolution reports on ribosome dynamics and degradation patterns. Availability: Fivepseq is available from http://pelechanolab.com/software/fivepseq, under BSD 3-Clause License.
8 tweets cancer biology
The proto-oncogene YAP /Yki, a transcription co-factor of the Hippo pathway, has been linked to many cancers. YAP interacts with DNA-binding TEAD/Sd proteins to regulate expression of its transcriptional targets. Disruption of YAP-TEAD therefore offers a potential therapeutic strategy. The mammalian Vestigial Like (VGLL) protein, specifically its TONDU domain, has been shown to competitively inhibit YAP-TEAD interaction and a TONDU peptide can suppress YAP-induced cancer. As TONDU could potentially be developed into a therapeutic peptide for multiple cancers, we evaluated its efficacy in Yki-driven adult Intestinal Stem Cell (ISC) tumors in Drosophila. We show that oral uptake of the TONDU peptide is highly effective at inhibiting Yki-driven gut tumors by suppressing YAP-TEAD interaction. Comparative proteomics of early and late stage Yki-driven ISC tumors revealed enrichment of a number of proteins, including members of the integrin signaling pathway, such as Talin, Vinculin and Paxillin. These, in turn displayed a decrease in their levels in TONDU-peptide treated tumors. Further, we show that Sd binds to the regulatory region of integrin-coding gene, mew, which codes for αPS1, a key integrin of the ISCs. In support to a possible role of integrins in Yki-driven ISC tumors, we show that genetic downregulation of mew arrests Yki-driven ISC proliferation, reminiscent of the effects of TONDU peptide. Altogether, our findings present a novel platform for screening therapeutic peptides and provide insights into tumor suppression mechanisms.
8 tweets neuroscience
Many genes whose mutations cause, or increase the risk of, Parkinson's disease (PD) have been identified. An inactivating mutation (R258Q) in the Sac inositol phosphatase domain of synaptojanin 1 (SJ1/PARK20), a phosphoinositide phosphatase implicated in synaptic vesicle recycling, results in PD. The gene encoding Sac2/INPP5F, another Sac domain containing protein, was identified as a PD risk locus by GWAS. Knock-In mice carrying the SJ1 patient mutation (SJ1RQKI) exhibit PD features, while Sac2 knockout mice (Sac2KO) do not have obvious neurological defects. We report a "synthetic" effect of the SJ1 mutation and the KO of Sac2 in mice. Most mice with both mutations died perinatally. The occasional survivors had stunted growth, died within 3 weeks, and showed abnormalities of striatal dopaminergic nerve terminals at an earlier stage than SJ1RQKI mice. The abnormal accumulation of endocytic factors observed at synapses of cultured SJ1RQKI neurons was more severe in double mutant. Our results suggest that SJ1 and Sac2 have partially overlapping functions and are consistent with a potential role of Sac2 as a PD risk gene.
8 tweets bioinformatics
Mapping of reads to reference sequences is an essential step in a wide range of biological studies. The large size of datasets generated with next-generation sequencing technologies motivates the development of fast mapping software. Here, I describe URMAP, a new read mapping algorithm. URMAP is an order of magnitude faster than BWA and Bowtie2 with comparable accuracy on a benchmark test using simulated paired 150nt reads of a well-studied human genome. Software is freely available at https://drive5.com/urmap.
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