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Rxivist combines biology preprints from bioRxiv and medRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 128,741 papers from 551,614 authors.

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127,436 results found. For more information, click each entry to expand.

100881: Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars
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Posted 27 Aug 2020

Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars
203 downloads bioRxiv plant biology

Alexander Calderwood, Jo Hepworth, Shannon Woodhouse, Lorelei Bilham, Marc Jones, Eleri J Tudor, Mubarak Ali, Caroline Dean, Rachel Wells, Judith Irwin, Richard J Morris

The timing of the floral transition affects reproduction and yield, however its regulation in crops remains poorly understood. Here, we use RNA-Seq to determine and compare gene expression dynamics through the floral transition in the model species Arabidopsis thaliana and the closely related crop Brassica rapa. A direct comparison of gene expression over time between species shows little similarity, which could lead to the inference that different gene regulatory networks are at play. However, these differences can be largely resolved by synchronisation, through curve registration, of gene expression profiles. We find that different registration functions are required for different genes, indicating that there is no common 'developmental time' to which Arabidopsis and B. rapa can be mapped through gene expression. Instead, the expression patterns of different genes progress at different rates. We find that co-regulated genes show similar changes in synchronisation between species, suggesting that similar gene regulatory sub-network structures may be active with different wiring between them. A detailed comparison of the regulation of the floral transition between Arabidopsis and B. rapa, and between two B. rapa accessions reveals different modes of regulation of the key floral integrator SOC1, and that the floral transition in the B. rapa accessions is triggered by different pathways, even when grown under the same environmental conditions. Our study adds to the mechanistic understanding of the regulatory network of flowering time in rapid cycling B. rapa under long days and highlights the importance of registration methods for the comparison of developmental gene expression data. ### Competing Interest Statement The authors have declared no competing interest.

100882: Conformational entropy limits the transition from nucleation to elongation in amyloid aggregation
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Posted 23 Jun 2020

Conformational entropy limits the transition from nucleation to elongation in amyloid aggregation
203 downloads bioRxiv biophysics

Tien M. Phan, Jeremy D. Schmit

The formation of amyloid fibrils in Alzheimer's disease and other neurodegenerative disorders is limited by a slow nucleation step due to the entropic cost to initiate the ordered cross-beta structure. While the barrier can be lowered if the molecules maintain conformational disorder, poorly ordered clusters provide a poor binding surface for new molecules. To understand these opposing factors, we used all-atom simulations to parameterize a lattice model that treats each amino acid as a binary variable with beta-sheet and non-beta states. We find that the optimal degree of order in a nucleus depends on protein concentration. Low concentration systems require more ordered nuclei to capture infrequent monomer attachments. The nucleation phase transitions to the elongation phase when the beta-sheet core becomes large enough to overcome the initiation cost, at which point further ordering becomes favorable and the nascent fibril efficiently captures new molecules. ### Competing Interest Statement The authors have declared no competing interest.

100883: GENVISAGE: Rapid Identification of Discriminative and Explainable Feature Pairs for Genomic Analysis
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Posted 05 Feb 2020

GENVISAGE: Rapid Identification of Discriminative and Explainable Feature Pairs for Genomic Analysis
203 downloads bioRxiv bioinformatics

Silu Huang, Charles Blatti, Saurabh Sinha, Aditya Parameswaran

Motivation. A common but critical task in genomic data analysis is finding features that separate and thereby help explain differences between two classes of biological objects, e.g., genes that explain the differences between healthy and diseased patients. As lower-cost, high-throughput experimental methods greatly increase the number of samples that are assayed as objects for analysis, computational methods are needed to quickly provide insights into high-dimensional datasets with tens of thousands of objects and features. Results . We develop an interactive exploration tool called G ENVISAGE that rapidly discovers the most discriminative feature pairs that best separate two classes in a dataset, and displays the corresponding visualizations. Since quickly finding top feature pairs is computationally challenging, especially when the numbers of objects and features are large, we propose a suite of optimizations to make G ENVISAGE more responsive and demonstrate that our optimizations lead to a 400X speedup over competitive baselines for multiple biological data sets. With this speedup, G ENVISAGE enables the exploration of more large-scale datasets and alternate hypotheses in an interactive and interpretable fashion. We apply G ENVISAGE to uncover pairs of genes whose transcriptomic responses significantly discriminate treatments of several chemotherapy drugs. Availability. Free webserver at http://genvisage.knoweng.org:443/ with source code at https://github.com/KnowEnG/Genvisage

100884: MEIS1 down-regulation by MYC mediates prostate cancer development through elevated HOXB13 expression and AR activity
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Posted 20 Nov 2019

MEIS1 down-regulation by MYC mediates prostate cancer development through elevated HOXB13 expression and AR activity
203 downloads bioRxiv cancer biology

Nichelle C. Whitlock, Shana Y. Trostel, Scott Wilkinson, Nicholas T. Terrigino, S. Thomas Hennigan, Ross Lake, Nicole V. Carrabba, Rayann Atway, Elizabeth D. Walton, Berkley Gryder, Brian J. Capaldo, Huihui Ye, Adam G. Sowalsky

Localized prostate cancer develops very slowly in most men, with the androgen receptor (AR) and MYC transcription factors amongst the most well-characterized drivers of prostate tumorigenesis. Canonically, MYC up-regulation in luminal prostate cancer cells functions to oppose the terminally differentiating effects of AR. However, the effects of MYC up-regulation are pleiotropic and inconsistent with a poorly proliferative phenotype. Here we show that increased MYC expression and activity are associated with the down-regulation of MEIS1, a HOX-family transcription factor. Using RNA-seq to profile a series of human prostate cancer specimens laser capture microdissected on the basis of MYC immunohistochemistry, MYC activity and MEIS1 expression were inversely correlated. Knockdown of MYC expression in prostate cancer cells increased expression of MEIS1 and increased occupancy of MYC at the MEIS1 locus. Finally, we show in laser capture microdissected human prostate cancer samples and the prostate TCGA cohort that MEIS1 expression is inversely proportional to AR activity as well as HOXB13, a known interacting protein of both AR and MEIS1. Collectively, our data demonstrate that elevated MYC in a subset of primary prostate cancers functions in a negative role in regulating MEIS1 expression, and that this down-regulation may contribute to MYC-driven development and progression.

100885: Development of LSTM&CNN Based Hybrid Deep Learning Model to Classify Motor Imagery Tasks
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Posted 20 Sep 2020

Development of LSTM&CNN Based Hybrid Deep Learning Model to Classify Motor Imagery Tasks
203 downloads bioRxiv bioengineering

Caglar Uyulan

Recent studies underline the contribution of brain-computer interface (BCI) applications to the enhancement process of the life quality of physically impaired subjects. In this context, to design an effective stroke rehabilitation or assistance system, the classification of motor imagery (MI) tasks are performed through deep learning (DL) algorithms. Although the utilization of DL in the BCI field remains relatively premature as compared to the fields related to natural language processing, object detection, etc., DL has proven its effectiveness in carrying out this task. In this paper, a hybrid method, which fuses the one-dimensional convolutional neural network (1D CNN) with the long short-term memory (LSTM), was performed for classifying four different MI tasks, i.e. left hand, right hand, tongue, and feet movements. The time representation of MI tasks is extracted through the hybrid deep learning model training after principal component analysis (PCA)-based artefact removal process. The performance criteria given in the BCI Competition IV dataset A are estimated. 10-folded Cross-validation (CV) results show that the proposed method outperforms in classifying electroencephalogram (EEG)-electrooculogram (EOG) combined motor imagery tasks compared to the state of art methods and is robust against data variations. The CNN-LSTM classification model reached 95.62 % ({+/-}1.2290742) accuracy and 0.9462 ({+/-}0.01216265) kappa value for datasets with four MI-based class validated using 10-fold CV. Also, the receiver operator characteristic (ROC) curve, the area under the ROC curve (AUC) score, and confusion matrix are evaluated for further interpretations.

100886: Pazopanib induces dramatic but transient contraction of myeloid suppression compartment in favor of adaptive immunity
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Posted 01 May 2020

Pazopanib induces dramatic but transient contraction of myeloid suppression compartment in favor of adaptive immunity
203 downloads bioRxiv cancer biology

Darawan Rinchai, Elena Verzoni, Veronica Huber, Agata Cova, Paola Squarcina, Loris De Cecco, Filippo de Braud, Raffaele Ratta, Matteo Dugo, Luca Lalli, Viviana Vallacchi, Monica Rodolfo, Jessica Roelands, Chiara Castelli, Damien Chaussabel, Giuseppe Procopio, Davide Bedognetti, Licia Rivoltini

Anti-angiogenic tyrosine-kinase inhibitors (TKIs) and immune checkpoint blockade (ICB) constitute the backbone of metastatic renal cell carcinoma (mRCC) treatment. The development of the optimal combinatorial or sequential approach is hindered by the lack of comprehensive data regarding TKI-induced immunomodulation and its kinetics. Through the use of orthogonal transcriptomic and phenotyping platforms combined with functional analytic pipelines, we demonstrated that the anti-angiogenic TKI pazopanib induces a dramatic and coherent reshaping of systemic immunity in mRCC patients, downsizing the myeloid-derived suppressor cell (MDSC) compartment in favor of a strong enhancement of cytotoxic T and Natural Killer (NK) cell effector functions. The intratumoral expression level of a MDSC signature here generated was strongly associated with poor prognosis in mRCC patients. The marked but transient nature of this immunomodulation, peaking at the 3rd month of treatment, provides the rationale for the use of TKIs as a preconditioning strategy to improve the efficacy of ICB. ### Competing Interest Statement EV reports personal fees for advisory boards from Pfizer, Ipsen, Novartis outside of the submitted work. No potential conflicts of interest were disclosed by the other authors. * DC : Dendritic cell iDC : Immature dendritic cell mDC : Myeloid dendritic cells pDC : Plasmacytoid dendritic cells ICB : Immune checkpoint blockade IFN : Interferon IPA : Ingenuity Pathway Analysis MDSC : Myeloid derived suppressor cells G-MDSC : Granulocytic Myeloid derived suppressor cells M-MDSC : Monocytic Myeloid derived suppressor cells mRCC : Metastatic renal cell carcinoma NK : Natural killer cell PCA : Principal component analysis PBMCs : Peripheral blood mononuclear cells Tcm : Central memory T cell Tem : Effector memory T cells Tfh : T follicular helper cells Th2 cells : T helper 2 cells Th1 cells : T helper 1 cells Th17 cells : T helper 17 cells Tgd : T gamma delta cells Treg : Regulatory T cell TKI : Tyrosine-kinase inhibitor VEGF : Vascular endothelial growth factor

100887: Mutations in MYLPF cause a novel segmental amyoplasia that manifests as distal arthrogryposis
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Posted 08 May 2020

Mutations in MYLPF cause a novel segmental amyoplasia that manifests as distal arthrogryposis
203 downloads bioRxiv genetics

Jessica X. Chong, Jared C. Talbot, Emily M Teets, Samantha Previs, Brit L. Martin, Kathryn M Shively, Colby T Marvin, Arthur S Aylsworth, Reem Saadeh-Haddad, Ulrich A Schatz, Francesca Inzana, Tawfeg Ben-Omran, Fatima Almusafri, Mariam Al-Mulla, Kati J Buckingham, Tamar Harel, Hagar Mor-Shaked, Periyasamy Radhakrishnan, Katta M Girisha, Shalini S Nayak, Anju Shukla, Klaus Dieterich, Julien Faure, John Rendu, Yline Capri, Xenia Latypova, Deborah A. Nickerson, David Warshaw, Paul M Janssen, University of Washington Center for Mendelian Genomics, Sharon L. Amacher, Michael J. Bamshad

We identified ten persons in six consanguineous families with Distal Arthrogryposis (DA) who had congenital contractures, scoliosis, and short stature. Exome sequencing revealed that each affected person was homozygous for one of two different rare variants (c.470G>T, p.(Cys157Phe) or c.469T>C, p.(Cys157Arg)) affecting the same residue of myosin light chain, phosphorylatable, fast skeletal muscle (MYLPF). In a seventh family, a c.487G>A, p.(Gly163Ser) variant in MYLPF arose de novo in a father, who transmitted it to his son. In an eighth family comprised of seven individuals with dominantly-inherited DA, a c.98C>T, p.(Ala33Val) variant segregated in all four persons tested. Variants in MYLPF underlie both dominant and recessively inherited DA. Mylpf protein models suggest that the residues associated with dominant DA interact with myosin whereas the residues altered in families with recessive DA only indirectly impair this interaction. Pathological and histological exam of a foot amputated from an affected child revealed complete absence of skeletal muscle (i.e., segmental amyoplasia). To investigate the mechanism for this finding, we generated an animal model for partial MYLPF impairment by knocking out zebrafish mylpfa. The mylpfa mutant had reduced trunk contractile force and complete pectoral fin paralysis, demonstrating that mylpf impairment most severely affects limb movement. mylpfa mutant muscle weakness was most pronounced in an appendicular muscle and was explained by reduced myosin activity and fiber degeneration. Collectively, our findings demonstrate that partial loss of MYLPF function can lead to congenital contractures, likely as a result of degeneration of skeletal muscle in the distal limb. ### Competing Interest Statement The authors have declared no competing interest.

100888: Macrophage-derived miR-21 drives overwhelming glycolytic and inflammatory response during sepsis via repression of the PGE2/IL-10 axis.
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Posted 10 May 2020

Macrophage-derived miR-21 drives overwhelming glycolytic and inflammatory response during sepsis via repression of the PGE2/IL-10 axis.
203 downloads bioRxiv immunology

Paulo Melo, Annie Rocio Pineros Alvarez, C. Henrique Serezani

Myeloid cells play a critical role in the development of systemic inflammation and organ damage during sepsis. The mechanisms the development of aberrant inflammatory response remains to be elucidated. MicroRNAs are small non-coding RNAs that could prevent the expression of inflammatory molecules. Although the microRNA-21 (miR-21) is abundantly expressed in macrophages, the role of miR-21 in sepsis is controversial. Here we showed that miR-21 is upregulated in neutrophils and macrophages from septic mice. We found that myeloid-specific miR-21 deletion enhances animal survival, followed by decreased bacterial growth and organ damage during sepsis. Increased resistance against sepsis was associated with a reduction of aerobic glycolysis (as determined by reduced extracellular acidification rate (ECAR) and expression of glycolytic enzymes) and systemic inflammatory response (IL-1b, TNFa, and IL-6). While miR-21-/- macrophages failed to induce aerobic glycolysis and production of pro-inflammatory cytokines, we observed increased levels of the anti-inflammatory mediators prostaglandin E2 (PGE2) and IL10. Using blocking antibodies and pharmacological tools, we further discovered that increased survival and decreased systemic inflammation in miR21deltamyel during sepsis is dependent on the PGE2/IL10-mediated glycolysis inhibition. Together, we are showing a heretofore unknown role of macrophage miR21 in the orchestrating the balance between anti-inflammatory mediators and metabolic reprogramming that drives cytokine storm and tissue damage during sepsis. ### Competing Interest Statement The authors have declared no competing interest.

100889: High incidence of glucocorticoid-induced hyperglycaemia in inflammatory bowel disease; metabolic and clinical predictors identified by machine learning
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Posted 23 Jun 2020

High incidence of glucocorticoid-induced hyperglycaemia in inflammatory bowel disease; metabolic and clinical predictors identified by machine learning
203 downloads medRxiv gastroenterology

Martin J McDonnell, Richard J Harris, Florina Borca, Tilly Mills, Louise Downey, Suranga Dharmasiri, Mayank Patel, Benjamin Zare, Matt Stammers, Trevor R Smith, Richard Felwick, JR Fraser Cummings, Hang TT Phan, Markus Gwiggner

Background Glucocorticosteroids (GC) are long-established, widely used agents for induction of remission in inflammatory bowel disease (IBD). Hyperglycaemia is a known complication of GC treatment with implications for morbidity and mortality. Published data on prevalence and risk factors for GC-induced hyperglycaemia in the IBD population are limited. We prospectively characterise this complication in our cohort, employing machine-learning methods to identify key predictors of risk. Methods We conducted a prospective observational study of IBD patients receiving intravenous hydrocortisone (IVH). Electronically triggered three times daily capillary blood glucose (CBG) monitoring was recorded alongside diabetes mellitus (DM) history, IBD biomarkers, nutritional and IBD clinical activity scores. Hyperglycaemia was defined as CBG [≥] 11.1mmol/L and undiagnosed DM as HbA1c [≥]48 mmol/mol. Random Forest regression models were used to extract predictor-patterns present within the dataset. Findings 94 consecutive IBD patients treated with IVH were included. 60% (56/94) of the cohort recorded an episode of hyperglycaemia, including 57% (50/88) of those with no prior history of DM, of which 19% (17/88) and 5% (4/88) recorded a CBG [≥]14mmol/L and [≥]20mmol/L, respectively. The Random Forest models identified increased CRP followed by a longer IBD duration as leading risk predictors for significant hyperglycaemia. Interpretation Hyperglycaemia is common in IBD patients treated with intravenous GC, therefore CBG monitoring should be included in routine clinical practice. Machine learning methods can identify key risk factors for clinical complications. Physicians should consider steroid-sparing strategies in high-risk patients such as those with high admission CRP or a longer IBD duration. There is an emergent case for research to explore steroid-free treatment regimens for hospitalised patients with severe IBD flares. Funding No specific funding was received for this study.

100890: Scalable Models of Antibody Evolution and Benchmarking of Clonal Tree Reconstruction Methods
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Posted 20 Sep 2020

Scalable Models of Antibody Evolution and Benchmarking of Clonal Tree Reconstruction Methods
203 downloads bioRxiv immunology

Chao Zhang, Andrey V. Bzikadze, Yana Safonova, Siavash Mirarab

Affinity maturation (AM) of antibodies through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal trees of antibodies produced by B cells that have evolved from a common naive B cell. Recent advances in high-throughput sequencing have enabled deep scans of antibody repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture micro-evolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal tree evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal tree evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modelling selective pressure due to changes in affinity binding; it enables scalable simulations of millions of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and for measuring their properties. Our benchmarking results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a very simple postprocessing of their results, where super short branches are contracted, leads to inferences that are better than alternative methods. ### Competing Interest Statement The authors have declared no competing interest.

100891: Genome sequencing and functional characterization of a Dictyopanus pusillus fungal extract offers a promising alternative for lignocellulose pretreatment of oil palm residues
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Posted 23 Dec 2019

Genome sequencing and functional characterization of a Dictyopanus pusillus fungal extract offers a promising alternative for lignocellulose pretreatment of oil palm residues
203 downloads bioRxiv bioengineering

Andrés M. Rueda, Yossef López de los Santos, Antony T Vincent, Myriam Létourneau, Inés Hernández, Clara I. Sánchez, Daniel Molina V., Sonia A. Ospina, Frédéric J. Veyrier, Nicolas Doucet

The pretreatment of biomass is a critical requirement of bio-renewable fuel production from lignocellulose. Although current processes primarily involve chemical and physical approaches, the biological breakdown of lignin using enzymes and microorganisms is quickly becoming an interesting eco-friendly alternative to classical processes. As a result, bioprospection of wild fungi from naturally occurring lignin-rich sources remains a suitable method to uncover and isolate new species exhibiting ligninolytic activity. In this study, wild species of white rot fungi were collected from Colombian forests based on their natural wood decay ability and high capacity to secrete oxidoreductases with high affinity for phenolic polymers such as lignin. Based on high activity obtained from solid-state fermentation using a lignocellulose source from oil palm as matrix, we describe the isolation and whole-genome sequencing of Dictyopanus pusillus , a wild basidiomycete fungus exhibiting ABTS oxidation as an indication of laccase activity. Functional characterization of a crude enzymatic extract identified laccase activity as the main enzymatic contributor to fungal extracts, an observation supported by the identification of 13 putative genes encoding for homologous laccases in the genome. To the best of our knowledge, this represents the first report of an enzymatic extract exhibiting laccase activity in the Dictyopanus genera, offering means to exploit this species and its enzymes for the delignification process of lignocellulosic by-products from oil palm.

100892: Determinants for forming a supramolecular myelin-like proteolipid lattice
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Posted 07 Feb 2020

Determinants for forming a supramolecular myelin-like proteolipid lattice
203 downloads bioRxiv biochemistry

Salla Ruskamo, Oda C Krokengen, Julia Kowal, Tuomo Nieminen, Mari Lehtimäki, Arne Raasakka, Venkata P Dandey, Ilpo Vattulainen, Henning Stahlberg, Petri Kursula

Myelin protein P2 is a peripheral membrane protein of the fatty acid binding protein family. It functions in the formation and maintenance of the peripheral nerve myelin sheath, and several P2 mutations causing human Charot-Marie-Tooth neuropathy have been reported. Here, electron cryomicroscopy of myelin-like proteolipid multilayers revealed a three-dimensionally ordered lattice of P2 molecules between stacked lipid bilayers, visualizing its possible assembly at the myelin major dense line. A single layer of P2 is inserted between two bilayers in a tight intermembrane space of ~3 nm, implying direct interactions between P2 and two membrane surfaces. Further details on lateral protein organization were revealed through X-ray diffraction from bicelles stacked by P2. Surface mutagenesis of P2 coupled to structural and functional experiments revealed a role for both the portal region and the opposite face of P2 in membrane interactions. Atomistic molecular dynamics simulations of P2 on myelin-like and model membrane surfaces suggested that Arg88 is an important residue for P2-membrane interactions, in addition to the helical lid domain on the opposite face of the molecule. Negatively charged myelin lipid headgroups anchor P2 stably on the bilayer surface. Membrane binding may be accompanied by opening of the P2 β barrel structure and ligand exchange with the apposing lipid bilayer. Our results provide an unprecedented view into an ordered, multilayered biomolecular membrane system induced by the presence of a peripheral membrane protein from human myelin. This is an important step towards deciphering the 3-dimensional assembly of a mature myelin sheath at the molecular level.

100893: Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture
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Posted 13 Nov 2020

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture
203 downloads bioRxiv plant biology

Haichao Guo, Habtamu Ayalew, Anand Seethepalli, Kundan Dhakal, Marcus D Griffiths, Xue-feng Ma, Larry M. York

The root economics space is a useful framework for plant ecology, but rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer for analyzing scanned images. We uncovered substantial variation for specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and construction costs. Multiple linear regression estimated that lateral root tips had the greatest SRR, and the residuals of this model were used as a new trait. SRR was negatively correlated with plant mass. Network analysis using a Gaussian graphical model identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with aspects of the root economics space, with underlying gene candidates. Combining functional phenomics and root economics is a promising approach to understand crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems. ### Competing Interest Statement The authors have declared no competing interest.

100894: Gold nanorod based delivery system could bring about superior therapy effect of Ramucirumab through direct cytotoxicity to cancer cell mediated by differential regulation of phagocytosis in gastric cancer cell
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Posted 30 Dec 2019

Gold nanorod based delivery system could bring about superior therapy effect of Ramucirumab through direct cytotoxicity to cancer cell mediated by differential regulation of phagocytosis in gastric cancer cell
203 downloads bioRxiv bioengineering

Linyang Fan, Minzhi Zhao

Gastric Cancer (GC) is one of the most serious cancers with high incidence and mortality all over the world. Chemotherapy hadn't led to desirable effect and targeted therapy brings about a new stage to cancer treatment. Ramucirumab is the first FDA-approved therapy for advanced gastric cancer. It is well known that gold nanorod, a nontoxic biocompatible nanomaterial, is an especially promising candidate for cancer theranostic. In this study, Ramucirumab (Ab) were first modified by gold nanoparticles to enhance uptake efficiency. The simple Nano-delivery system had taken perfect aggregation effect in vivo even better than 5-fold Ab treatment. Gold nanomaterials, especially gold nanorod (AuNR), could induce direct cytotoxic effect to cancer cell in the presence of Ab, while Ab or gold nanoparticle themselves couldn't lead to such direct killing effect even at an extremely high concentration. Proteomic and transcriptomic analyses revealed this direct cytotoxicity derived predominantly from Ab-mediated phagocytose, and the high affinity receptor for Fc gamma CD64 showed differential up-regulation only in gastric cancer cell treated by these nanodrugs compared with Ab, especially for AuNR group. This was the first time to discover that nanoparticle could induce regulation of immune related pathways and Fcγ receptor in the target cancer cell. Simplified and powerful designs of smart nanoparticles are highly desired for clinical. The dramatic enhancement of Ab accumulation with simple composition, combined with direct cytotoxic effect specific to cancer cells brought perfect therapeutic effects in vivo than Ab, which would promote further clinical application of gold nanorod in the diagnosis and therapeutics of gastric cancer.

100895: Pacing strategy in horse racing
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Posted 11 Jun 2020

Pacing strategy in horse racing
203 downloads bioRxiv physiology

Quentin Mercier, Amandine Aftalion

Thanks to  velocity data on races in Chantilly (France), we set  a mathematical model which provides the optimal pacing strategy for horses on a fixed distance. It relies on mechanics, energetics (both aerobic and anaerobic) and motor control. We identify the parameters useful for the model from the data. Then it allows to understand the velocity, the oxygen uptake  evolution in a race, as well as the energy or the propulsive force and  predict the changes in pacing according to  the properties (altitude and bending) of the track.

100896: NSC348884 cytotoxicity is not mediated by inhibition of nucleophosmin oligomerization
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Posted 07 Feb 2020

NSC348884 cytotoxicity is not mediated by inhibition of nucleophosmin oligomerization
203 downloads bioRxiv cell biology

Markéta Šašinková, Petr Heřman, Aleš Holoubek, Dita Strachotová, Petra Otevřelová, Dana Grebeňová, Kateřina Kuželová, Barbora Brodská

Oligomerization of the nucleolar phosphoprotein nucleophosmin (NPM) is mediated by its N-terminal domain. In acute myeloid leukemia, a frequent NPM mutation occurring at the C-terminus causes NPM delocalization to the cytoplasm. Due to formation of NPM heterooligomers, the wild-type NPM as well as many of NPM interaction partners are also delocalized. Proper localization and function of mislocalized proteins in the cells with mutated NPM may be restored by targeting NPM oligomerization. We introduce a reliable set of complementary methods for monitoring NPM oligomerization in both cell lysates and live cells. Using this methodological background we show that a putative inhibitor of NPM oligomerization, NSC348884, does not prevent formation of NPM oligomers in leukemia cells. Instead, we reveal that the observed cytotoxic effect of NSC348884 is associated with changes in cell adhesion signaling.

100897: Forecasting the potential distribution of the invasive vegetable leafminer using "top-down" and "bottom-up" models
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Posted 06 Dec 2019

Forecasting the potential distribution of the invasive vegetable leafminer using "top-down" and "bottom-up" models
203 downloads bioRxiv ecology

James L. Maino, Elia I. Pirtle, Peter M. Ridland, Paul A. Umina

The vegetable leafminer, Liriomyza sativae, is an internationally significant pest of vegetable and flower crops, that was detected for the first time on the Australian mainland in 2015. Due to the early stage of its invasion in Australia, it is unclear how climatic conditions are likely to support and potentially restrict the distribution of L. sativae as it expands into a novel range and threatens agricultural production regions. Here we predicted the future establishment potential of L. sativae in Australia, using both a novel "bottom-up" process-based model and a popular "top-down" correlative species distribution model (SDM), leveraging the unique strengths of each approach. Newly compiled global distribution data spanning 42 countries was used to validate the process-based model of establishment potential based on intrinsic population growth rates, as well as parameterise the correlative SDM. Both modelling approaches successfully captured the international distribution of L. sativae based on environmental variables and predicted the high suitability of non-occupied ranges, including northern regions of Australia. The largely unfilled climatic niche available to L. sativae in Australia demonstrates the early stage of its Australian invasion, and highlights locations where important vegetable and nursery production regions in Australia are highly vulnerable to L. sativae establishment.

100898: Radiomics Features of 18F-fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer
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Posted 30 Dec 2019

Radiomics Features of 18F-fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer
203 downloads medRxiv oncology

Jeonghyun Kang, Jae-Hoon Lee, Hye Sun Lee, Eun-Suk Cho, Eun Jung Park, Seung Hyuk Baik, Kang Young Lee, Chihyun Park, Yunku Yeu, Jean René Clemenceau, Sunho Park, Hongming Xu, Changjin Hong, Tae Hyun Hwang

PurposeThe aim of this study was to investigate the prognostic value of radiomics signatures derived from 18F-fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET) in patients with colorectal cancer (CRC). MethodsFrom April 2008 to Jan 2014, we identified CRC patients who underwent 18F-FDG-PET before starting any neoadjuvant treatments and surgery. Radiomics features were extracted from the primary lesions identified on 18F-FDG-PET. Patients were divided into a training and a validation set by random sampling. A least absolute shrinkage and selection operator (LASSO) Cox regression model was applied for prognostic signature building with progression-free survival (PFS) using the training set. Using the calculated radiomics score, a nomogram was developed, and the clinical utility of this nomogram was assessed in the validation set. ResultsThree-hundred-and-eight-one patients with surgically resected CRC patients (training set 228 vs. validation set 153) were included. In the training set, a radiomics signature called a rad_score was generated using two PET-derived features such as Gray Level Run Length Matrix_Long-Run Emphasis (GLRLM_LRE) and Grey-Level Zone Length Matrix_Short-Zone Low Gray-level Emphasis (GLZLM_SZLGE). Patients with a high-rad_score in the training and validation set had shorter PFS. Multivariable analysis revealed that the rad_score was an independent prognostic factor in both training and validation sets. A radiomics nomogram, developed using rad_score, nodal stage, and lymphovascular invasion, showed good performance in the calibration curve and comparable predictive power with the staging system in the validation set. ConclusionTextural features derived from 18F-FDG-PET images may enable more detailed stratification of prognosis in patients with CRC.

100899: Local Bilayer Hydrophobicity Modulates Membrane Protein Stability
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Posted 01 Sep 2020

Local Bilayer Hydrophobicity Modulates Membrane Protein Stability
203 downloads bioRxiv biophysics

Dagan C Marx, Karen G Fleming

Through the insertion of nonpolar side chains into the bilayer, the hydrophobic effect has long been accepted as a driving force for membrane protein folding. However, how the changing chemical composition of the bilayer affects the magnitude side chain transfer free energies ({Delta}G{degrees}sc) has historically not been well understood. A particularly challenging region for experimental interrogation is the bilayer interfacial region that is characterized by a steep polarity gradient. In this study we have determined the {Delta}G{degrees}sc for nonpolar side chains as a function of bilayer position using a combination of experiment and simulation. We discovered an empirical correlation between the surface area of nonpolar side chain, the transfer free energies, and local water concentration in the membrane that allows for {Delta}G{degrees}sc to be accurately estimated at any location in the bilayer. Using these water-to-bilayer {Delta}G{degrees}sc values, we have calculated the interface-to-bilayer transfer free energy ({Delta}G{degrees}(i,b)). We find that the {Delta}G{degrees}(i,b) are similar to the biological, translocon-based transfer free energies, indicating that the translocon energetically mimics the bilayer interface. Together these findings can be applied to increase the accuracy of computational workflows used to identify and design membrane proteins, as well bring greater insight into our understanding of how disease-causing mutations affect membrane protein folding and function.

100900: Frequency Conservation Score (FCS): the power of conservation and allele frequency for variant pathogenic prediction
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Posted 15 Oct 2019

Frequency Conservation Score (FCS): the power of conservation and allele frequency for variant pathogenic prediction
203 downloads bioRxiv bioinformatics

Jose Luis Cabrera, Jose Antonio Enriquez, Fatima Sanchez-Cabo

Background: Prediction of pathogenic variants is one of the biggest challenges for researchers and clinicians in the time of next-generation sequencing technologies. Stratification of individuals based on truly pathogenic variants might lead to improved, personalized treatments. Results: We present Frequency Conservation Score (FCS) and Frequency Conservation Score for Mitochondrial DNA (FCSMt) two methods for the detection of pathogenic single nucleotide variants in nuclear and mitochondrial DNA, respectively. These scores are based in a random forest model trained over a set of potentially relevant predictors: (i) conservation scores (PhastCons and phyloP); (ii) locus variability at each genomic position built from gnomAD database and (iii) physicochemical distance for amino acids substitutions and the impact/consequence over the canonical transcript. FCS showed an AUC of 98% for deleteriousness in an independent validation dataset, outperforming other scores such as metaLR, metaSVM, REVEL, DANN, CADD, SIFT, PROVEAN or FATHMM-MKL. Moreover, FCSMt presented an AUC=0.92 for pathogenic mitochondrial SNVs detection. The tool is available at http://bioinfo.cnic.es/FCS . Conclusions: FCS and FCS-Mt improve pathogenic mutation detection, allowing the prioritization of relevant variants in Whole Exome and Whole Genome Sequencing Analysis.

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