bluuebunny/crossref_metadata_2025 huggingface dataset:
Insights on SARS-CoV-2’s Mutations for Evading Human Antibodies: Sacrifice and Survival
Authors: Luan Binquan , Huynh Tien
Published: February 2021

Recent mutations on the receptor binding domain (RBD) of the SARS-CoV-2’s spike protein have been manifested as the major cause of the wide and rapid spread of the virus. Especially, the variant B.1.351 in South Africa with the hallmark of triple mutations (N501Y, K417N and E484K) is worrisome. Quickly after the outbreak of this new variant, several studies showed that both N501Y and E484K can enhance the binding between RBD and the human ACE2 receptor. However, the mutation K417N seems to be unfavorable because it removes one interfacial salt-bridge. So far, it is still not well understood why the K417N mutation is selected in the viral evolution. Here, we show that despite the loss in the binding affinity (1.48 kcal/mol) between RBD and ACE2 the K417N mutation abolishes a buried interfacial salt-bridge between RBD and the neutralizing antibody CB6 and thus substantially reduces their binding energy by 9.59 kcal/mol, facilitating the variants to efficiently elude CB6 (as well as many other antibodies). Thus, when proliferating from person to person the virus might have adapted to the human immune system through evasive mutations. Taking into account limited and relevant experimental works in the field, we show that our theoretical predictions are consistent with existing experimental findings. By harnessing the revealed molecular mechanism for variants, it becomes feasible to redesign therapeutic antibodies accordingly to make them more efficacious.
Long-term conservation effects of protected areas in stochastic population dynamics
Authors: Takashina Nao
Published: February 2021

Terrestrial and marine protected areas are essential tools in mitigating anthropogenic impacts and promoting population persistence and resource sustainability. Adequately implemented protected areas (PAs) promote long-term conservation effects. Stochasticity causes fluctuations in the conservation effects of PAs, and so it is important to investigate the variabilities of these conservation effects to inform their long-term conservation effects. To investigate long-term conservation effects, I develop and analyze new models of stochastic processes that encompass the fluctuations generated by demographic or environmental stochasticity in PAs management. The stochastic model is built upon individual processes. In the model, density-independent mortality, migration between PAs and non-PAs, and site preferences characterize the features of the PA. The effect of PAs size is also examined. The long-term conservation effects are quantified using the coefficient of variation (CV) of population size in PAs, where a lower CV indicates higher robustness in stochastic variations. Typically, the results from this study demonstrate that sufficiently reduced density-independent mortality in PAs and high site preference and immigration rate of PA are likely to decrease the CV. However, different types of stochasticity induce rather different consequences: under demographic stochasticity, the CV is always reduced when PAs increase the population size therein, but an increased population size by PAs does not always decrease the CV under environmental stochasticity. The deterministic dynamics of the model are investigated, facilitating effective management decisions.
Natural language processing for patient selection in phase I/II oncology clinical trials
Authors: Delorme Julie , Charvet Valentin , Wartelle Muriel , Lion François , Thuillier Bruno , Mercier Sandrine , Soria Jean-Charles , Azoulay Mikael , Besse Benjamin , Massard Christophe , Hollebecque Antoine , Verlingue Loic
Published: February 2021

Purpose

Early discontinuation affects over one-third of patients enrolled in early-phase oncology clinical trials. Early discontinuation is deleterious both for the patient and for the study, by inflating its duration and associated costs. We aimed at predicting the successful screening and dose-limiting toxicity period completion (SSD) from automatic analysis of consultation reports.

Materials and methods

We retrieved the consultation reports of patients included in phase I and/or phase II oncology trials for any tumor type at Gustave Roussy, France. We designed a pre-processing pipeline that transformed free-text into numerical vectors and gathered them into semantic clusters. These document-based semantic vectors were then fed into a machine learning model that we trained to output a binary prediction of SSD status.

Results

Between September, 2012 and July, 2020, 56,924 consultation reports were used to build the dictionary, and 1,858 phase I/II inclusion reports were used to train (75%), validate (15%) and test (15%) a Random Forest model. Pre-processing could efficiently cluster words with semantic proximity. On the unseen test cohort of 264 consultation reports, the performances of the model reached: F1 score 0.80, recall 0.81 and AUC 0.88. Using this model, we could have reduced the screen fail rate (including DLT period) from 39.8% to 12.8% (RR=0.322, 95%CI[0.209-0.498], p<0.0001) within the test cohort. Most important semantic clusters for predictions comprised words related to hematological malignancies, anatomo-pathological features and laboratory and imaging interpretation.

Conclusion

Machine learning with semantic conservation is a promising tool to assist physicians in selecting patients prone to achieve SSD in early-phase oncology clinical trials.
SplitStrains, a tool to identify and separate mixed Mycobacterium tuberculosis infections from WGS data
Authors: Gabbasov Einar , Moreno-Molina Miguel , Comas Iñaki , Libbrecht Maxwell , Chindelevitch Leonid
Published: February 2021

The occurrence of multiple strains of a bacterial pathogen such as M. tuberculosis or C. difficile within a single human host, referred to as a mixed infection, has important implications for both healthcare and public health. However, methods for detecting it, and especially determining the proportion and identities of the underlying strains, from WGS (whole-genome sequencing) data, have been limited.

In this paper we introduce SplitStrains, a novel method for addressing these challenges. Grounded in a rigorous statistical model, SplitStrains not only demonstrates superior performance in proportion estimation to other existing methods on both simulated as well as real M. tuberculosis data, but also successfully determines the identity of the underlying strains.

We conclude that SplitStrains is a powerful addition to the existing toolkit of analytical methods for data coming from bacterial pathogens, and holds the promise of enabling previously inaccessible conclusions to be drawn in the realm of public health microbiology.

Author summary

When multiple strains of a pathogenic organism are present in a patient, it may be necessary to not only detect this, but also to identify the individual strains. However, this problem has not yet been solved for bacterial pathogens processed via whole-genome sequencing. In this paper, we propose the SplitStrains algorithm for detecting multiple strains in a sample, identifying their proportions, and inferring their sequences, in the case of Mycobacterium tuberculosis. We test it on both simulated and real data, with encouraging results. We believe that our work opens new horizons in public health microbiology by allowing a more precise detection, identification and quantification of multiple infecting strains within a sample.
The changing characteristics of COVID-19 presentations: A regional comparison of SARS-CoV-2 hospitalised patients during the first and second wave
Authors: Atkin Catherine , Kamwa Vicky , Reddy-Kolanu V , Parekh D , Evison Felicity , Nightingale Peter , Gallier Suzy , Ball Simon , Sapey Elizabeth
Published: February 2021

Background

This study assesses COVID-19 hospitalised patient demography and outcomes during wave 1 and wave 2, prior to new variants of the virus.

Methods

All patients with a positive SARS-CoV-2 swab between 10th March 2020 and 5th July 2020 (wave 1) and 1st September 2020 and 16th November 2020 (wave 2) admitted to University Hospitals Birmingham NHS Foundation Trust were included (n=4856), followed for 28 days.

Results

Wave 2 patients were younger, more ethnically diverse, had less co-morbidities and disease presentation was milder on presentation. After matching for these factors, mortality was reduced, but without differences in intensive care admissions.

Conclusion

Prior to new SARS-CoV-2 variants, outcomes for hospitalised patients with COVID-19 were improving but with similar intensive care needs.
Limiting the loss of terrestrial ecosystems to safeguard nature for biodiversity and humanity
Authors: Simmonds Jeremy S. , Suarez-Castro Andres Felipe , Reside April E. , Watson James E.M. , Allan James R. , Borrelli Pasquale , Dudley Nigel , Edwards Stephen , Fuller Richard A. , Game Edward T. , Linke Simon , Maxwell Sean L. , Panagos Panos , Puydarrieux Philippe , Quétier Fabien , Runting Rebecca K. , Santini Talitha , Sonter Laura J. , Maron Martine
Published: February 2021

Humanity is on a pathway of unsustainable loss of the natural systems upon which we, and all life, rely. To date, global efforts to achieve internationally-agreed goals to reduce carbon emissions, halt biodiversity loss, and retain essential ecosystem services, have been poorly integrated. However, these different goals all rely on preserving natural ecosystems. Here, we show how to unify these goals by empirically deriving spatially-explicit, quantitative area-based targets for the retention of natural terrestrial ecosystems. We found that at least 67 million km2of Earth’s natural terrestrial ecosystems (~79% of the area remaining) require retention – via a combination of strict protection but more prominently through sustainably managed land use regimes complemented by restoration actions – to contribute to biodiversity, climate, soil and freshwater objectives under four United Nations’ Resolutions. This equates to retaining natural ecosystems across ~50% of the total terrestrial (excluding Antarctica) surface of Earth. Our results show where retention efforts could be focussed to contribute to multiple goals simultaneously. The retention targets concept that we present explicitly recognises that such management can and should co-occur alongside and be driven by the people who live in and rely on places where natural and semi-natural ecosystems remain on Earth.
Two distinct types of nodes of Ranvier support auditory nerve function in the mouse cochlea
Authors: Panganiban Clarisse H. , Barth Jeremy L. , Tan Junying , Noble Kenyaria V. , McClaskey Carolyn M. , Dias James W. , Harris Kelly C. , Lang Hainan
Published: February 2021

Glial cells of the auditory nerve regulate formation of the nodes of Ranvier that are needed for regeneration of action potentials and proper hearing function. Here we identify and describe the distinct features of two novel types of Ranvier nodes—the axonal node and the ganglion node—in the mouse auditory nerve that change across the lifespan, including during myelination and postnatal development, and degenerate during aging. Cellular, molecular, and structure-function correlation evaluations revealed that nodal types are critical for different aspects of auditory nerve function. Specifically, the length of the axonal node is associated with neural processing speed and neural synchrony, whereas ganglion node development is associated with amplitude growth of the action potential. Moreover, our data indicate that dysregulation of glial cells and associated degeneration of the ganglion node structure are an important and new mechanism of auditory nerve dysfunction in age-related hearing loss.
Resolving the conflict between antibiotic production and rapid growth by recognition of peptidoglycan of susceptible competitors
Authors: Maan Harsh , Friedman Jonathan , Kolodkin-Gal Ilana
Published: February 2021

Microbial communities employ a variety of complex strategies to compete successfully against competitors sharing their niche, with antibiotic production being a common strategy of aggression. Here, by systematic evaluation of all non-ribosomal peptides (NRP) produced byB. subtilisclade, we revealed that they acted either synergistically or additively to effectively eliminate phylogenetically distinct competitors. All four major NRP biosynthetic clusters were also imperative for the survival ofB. subtilisin a complex community extracted from the rhizosphere. The production of NRP came with a fitness cost manifested in growth inhibition, rendering NRP synthesis uneconomical when growing in proximity to a phylogenetically close species, carrying resistance against the same antibiotics. To resolve this conflict and ease the fitness cost, NRP production was only induced by the presence of peptidoglycan cue from a sensitive competitor. These results experimentally demonstrate a general ecological concept – closely related communities (“self”) are favoured during competition, due to compatibility in attack and defence mechanisms.
Ethanol-guided behavior inDrosophilalarvae
Authors: Schumann Isabell , Berger Michael , Nowag Nadine , Schäfer Yannick , Saumweber Juliane , Scholz Henrike , Thum Andreas S.
Published: February 2021

Chemosensory signals allow vertebrates and invertebrates not only to orient in its environment toward energy-rich food sources to maintain nutrition but also to avoid unpleasant or even poisonous substrates. Ethanol is a substance found in the natural environment ofDrosophila melanogaster. Accordingly,D. melanogasterhas evolved specific sensory systems, physiological adaptations, and associated behaviors at its larval and adult stage to perceive and process ethanol.

To systematically analyze howD. melanogasterlarvae respond to naturally occurring ethanol, we examined ethanol-induced behavior in great detail by parametrically reevaluating existing approaches and comparing them with new experiments. Using behavioral assays, we confirm that larvae are attracted to different concentrations of ethanol in their environment. This behavior is controlled both by olfactory and contact cues. It is independent of previous exposure to ethanol in their food. Moreover, moderate, naturally occurring ethanol concentration of 4% results in increased larval fitness. On the contrary, higher concentrations of 10% and 20% ethanol, which rarely or never appear in nature, increase larval mortality. Finally, ethanol also serves as a positive teaching signal in learning and memory and updates valence associated with simultaneously processed odor information.

Since information on how larvae perceive and process ethanol at the genetic and neuronal level is limited, the establishment of standardized assays described here is an important step towards their discovery.
Selection and structural characterisation of anti-TREM2 scFvs that reduce levels of shed ectodomain
Authors: Szykowska Aleksandra , Chen Yu , Smith Thomas B , Preger Charlotta , Yang Jingjing , Qian Dongming , Mukhopadhyay Shubhashish M , Wigren Edvard , Neame Stephen J , Gräslund Susanne , Persson Helena , Atkinson Peter J , Di Daniel Elena , Mead Emma , Wang John , Davis John B , Burgess-Brown Nicola A , Bullock Alex N
Published: February 2021

Single point mutations in TREM2, a receptor expressed by microglia in the brain, are associated with an increased risk of neurodegeneration including Alzheimer’s disease. Numerous studies support a role for TREM2 in sensing damaging stimuli and triggering signalling cascades necessary for neuroprotection. Despite its significant role, ligands and regulators of TREM2 activation, and the mechanisms governing TREM2-dependent responses and its cleavage from the membrane, remain poorly characterised. Here, we present phage display generated scFv antibody binders to human TREM2 ectodomain. Cocrystal structures revealed the binding of two scFvs to an epitope on the globular TREM2 domain distal to the putative ligand-binding site. Enhanced functional activity was observed for oligomeric scFv species which inhibited the production of soluble TREM2 in a HEK293 cell model. We hope that detailed characterisation of their epitopes and properties will facilitate the use of these renewable binders as structural and functional biology tools for TREM2 research.
Unsupervised selection of optimal single-molecule time series idealization criterion
Authors: Bandyopadhyay Argha , Goldschen-Ohm Marcel P.
Published: February 2021

Single-molecule (SM) approaches have provided valuable mechanistic information on many biophysical systems. As technological advances lead to ever-larger datasets, tools for rapid analysis and identification of molecules exhibiting the behavior of interest are increasingly important. In many cases the underlying mechanism is unknown, making unsupervised techniques desirable. The Divisive Segmentation and Clustering (DISC) algorithm is one such unsupervised method that idealizes noisy SM time series much faster than computationally intensive approaches without sacrificing accuracy. However, DISC relies on a user selected objective criterion (OC) to guide its estimation of the ideal time series. Here, we explore how different OCs affect DISC’s performance for data typical of SM fluorescence imaging experiments. We find that OCs differing in their penalty for model complexity each optimize DISC’s performance for time series with different properties such as signal-to-noise and number of sample points. Using a machine learning approach, we generate a decision boundary that allows unsupervised selection of OC based on the input time series to maximize performance for different types of data. This is particularly relevant for SM fluorescence datasets which often have signal-to-noise near the derived decision boundary and include time series of nonuniform length due to stochastic bleaching. Our approach allows unsupervised per-molecule optimization of DISC, which will substantially assist rapid analysis of high-throughput single-molecule datasets with noisy samples and nonuniform time windows.
Strain dynamics of specific contaminant bacteria modulate the performance of ethanol biorefineries
Authors: Lino Felipe Senne de Oliveira , Misiakou Maria-Anna , Kang Kang , Li Simone S. , da Costa Bruno Labate Vale , Basso Thiago Olitta , Panagiotou Gianni , Sommer Morten Otto Alexander
Published: February 2021

Bioethanol is a viable alternative for fossil fuels, and its use has lowered CO2emissions by over 500 million tonnes in Brazil alone by replacing more than 40% of the national gasoline consumption. However, contaminant bacteria reduce yields during fermentation. Our understanding of these contaminants is limited to targeted studies, and the interplay of the microbial community and its impact on fermentation efficiency remains poorly understood. Comprehensive surveying and longitudinal analysis using shotgun metagenomics of two major biorefineries over a production season revealed similar patterns in microbial community structure and dynamics throughout the entire fermentation system. Strain resolution metagenomics identified specificLactobacillus fermentumstrains as strongly associated with poor industrial performance and laboratory-scale fermentations revealed yield reductions of up to 4.63±1.35% depending on the specific contaminating strains. Selective removal of these strains could reduce emissions from the bioethanol industry by more than 2×106tonnes per year. Using the large-scale Brazilian ethanol fermentations as a model system for studying microbiome-phenotype relationships this study further demonstrates how high-resolution metagenomics can identify culprits of large scale industrial biomanufacturing.
Non-linear Dimensionality Reduction on Extracellular Waveforms Reveals Cell Type Diversity in Premotor Cortex
Authors: Lee Eric Kenji , Balasubramanian Hymavathy , Tsolias Alexandra , Anakwe Stephanie , Medalla Maria , Shenoy Krishna V. , Chandrasekaran Chandramouli
Published: February 2021

Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Currentin vivomethods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (WaveMAP) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We applyWaveMAPto extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. UsingWaveMAP, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches.WaveMAPtherefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.

Significance

How different cell types sculpt activity patterns in brain areas associated with decision-making is a fundamentally unresolved problem in neuroscience. In monkeys, and other species where transgenic access is not yet possible, identifying physiological typesin vivorelies on only a few discrete user-specified features of extracellular waveforms to identify cell types. Here, we show that non-linear dimensionality reduction with graph clustering applied to the entire extracellular waveform can delineate many different putative cell types and does so in an interpretable manner. We show that this method reveals previously undocumented physiological, functional, and laminar diversity in the dorsal premotor cortex of monkeys, a key brain area implicated in decision-making.
Epstein-Barr virus long non-coding RNARPMS1full-length spliceome in transformed epithelial tissue
Authors: Holmqvist Isak , Bäckerholm Alan , Xie Guojiang , Tian Yarong , Thorell Kaisa , Tang Ka-Wei
Published: February 2021

Epstein-Barr virus is associated with two types of epithelial neoplasms, nasopharyngeal carcinoma and gastric adenocarcinoma. The viral long non-coding RNARPMS1is the most abundantly expressed poly-adenylated viral RNA in these malignant tissues. TheRPMS1gene is known to contain two cassette exons, exon Ia and Ib, and several alternative splicing variants have been described in low-throughput studies. To characterize the entireRPMS1spliceome we combined long-read sequencing data from the nasopharyngeal cell line C666-1 and a primary gastric adenocarcinoma, with complementary short-read sequencing datasets. We developed FLAME, a Python-based bioinformatics package that can generate complete high resolution characterization of RNA splicing at full-length. Using FLAME, we identified 32 novel exons in theRPMS1gene, primarily within the large constitutive exons III, V and VII. Two of the novel exons contained retention of the intron between exon III and exon IV, and a novel cassette exon was identified between VI and exon VII. All previously described transcript variants ofRPMS1containing putative ORFs were identified at various levels. Similarly, native transcripts with the potential to form previously reported circular RNA elements were detected. Our work illuminates the multifaceted nature of viral transcriptional repertoires. FLAME provides a comprehensive overview of the relative abundance of alternative splice variants and allows for a wealth of previously unknown splicing events to be unveiled.
Spray-induced gene silencing as a potential tool to control potato late blight disease
Authors: Kalyandurg Pruthvi B. , Sundararajan Poorva , Dubey Mukesh , Ghadamgahi Farideh , Zahid Muhammad Awais , Whisson Stephen C. , Vetukuri Ramesh R.
Published: February 2021

Phytophthora infestanscauses late blight disease on potato and tomato and is currently controlled by resistant cultivars or intensive fungicide spraying. Here, we investigated an alternative means for late blight control by spraying potato leaves with double-stranded RNAs (dsRNA) that targetP. infestansgenes that are essential for infection. Through confocal microscopy, we show that the sporangia ofP. infestansexpressing Green Fluorescent Protein (GFP) can take upin vitrosynthesized dsRNAs homologous to GFP directly from their surroundings, including leaves, which leads to the reduced relative expression ofGFP. We further demonstrate the potential of spray induced gene silencing (SIGS) in controlling potato late blight disease by targeting developmentally important genes inP.infestanssuch as guanine-nucleotide binding (G) protein β-subunit (PiGPB1), haustorial membrane protein (PiHmp1), cutinase (PiCut3), and endo-1,3(4)-β-glucanase (PiEndo3). Our results demonstrate that SIGS can be potentially used to mitigate potato late blight; however, the degree of disease control is dependent on the selection of the target genes.
Chronic paternal morphine exposure increases sensitivity to morphine-derived antinociception
Authors: Toussaint Andre B. , Foster William , Jones Jessica M. , Kaufmann Samuel , Wachira Meghan , Hughes Robert , Bongiovanni Angela R. , Famularo Sydney T. , Dunham Benjamin P. , Schwark Ryan , Fried Nathan T. , Wimmer Mathieu E. , Abdus-Saboor Ishmail
Published: February 2021

Parental exposure to drugs of abuse such as opioids can have profound and long-lasting effects on reward processing and drug sensitivity across generations. However, little is known about the impact of long-term paternal exposure to morphine on offspring sensitivity to morphine-derived antinociception during painful experiences. To address this question, we constructed a rat pain scale at millisecond timescales to measure mechanical nociception in a multigenerational morphine exposure paradigm. Surprisingly, while developing the pain scale, we found that von Frey hair filaments (VFHs), the most common stimuli used in pain research, are not painful to rats and morphine did not change the touch-like responses elicited by VFHs. We next deployed this novel pain scale to determine whether chronic morphine exposure in sires impacted pain sensitivity in the next generation. Offspring produced from a cross of morphine-treated sires and drug-naïve dams, did not show any baseline changes in sensitivity to mechanical nociception. However, morphine-sired male progeny displayed a higher sensitivity to the antinociceptive properties of morphine, as measured by our pain scale. These findings demonstrate that long-term paternal exposure to morphine increases sensitivity to morphine-derived analgesia in the subsequent generation.
Phylogeny of the Damselfishes (Pomacentridae) and Patterns of Asymmetrical Diversification in Body Size and Feeding Ecology
Authors: McCord Charlene L. , Nash Chloe M. , Cooper W. James , Westneat Mark W.
Published: February 2021

The damselfishes (family Pomacentridae) inhabit near-shore communities in tropical and temperature oceans as one of the major lineages in coral reef fish assemblages. Our understanding of their evolutionary ecology, morphology and function has often been advanced by increasingly detailed and accurate molecular phylogenies. Here we present the next stage of multi-locus, molecular phylogenetics for the group based on analysis of 12 nuclear and mitochondrial gene sequences from 345 of the 422 damselfishes. The resulting well-resolved phylogeny helps to address several important questions about higher-level damselfish relationships, their evolutionary history and patterns of divergence. A time-calibrated phylogenetic tree yields a root age for the family of 55.5 mya, refines the age of origin for a number of diverse genera, and shows that ecological changes during the Eocene-Oligocene transition provided opportunities for damselfish diversification. We explored the idea that body size extremes have evolved repeatedly among the Pomacentridae, and demonstrate that large and small body sizes have evolved independently at least 40 times and with asymmetric rates of transition among size classes. We tested the hypothesis that transitions among dietary ecotypes (benthic herbivory, pelagic planktivory and intermediate omnivory) are asymmetric, with higher transition rates from intermediate omnivory to either planktivory or herbivory. Using multistate hidden-state speciation and extinction models, we found that both body size and dietary ecotype are significantly associated with patterns of diversification across the damselfishes, and that the highest rates of net diversification are associated with medium body size and pelagic planktivory. We also conclude that the pattern of evolutionary diversification in feeding ecology, with frequent and asymmetrical transitions between feeding ecotypes, is largely restricted to the subfamily Pomacentrinae in the Indo-West Pacific. Trait diversification patterns for damselfishes across a fully resolved phylogeny challenge many recent general conclusions about the evolution of reef fishes.
A theory of evolutionary dynamics on any complex spatial structure
Authors: Kuo Yang Ping , Arrieta César Nombela , Carja Oana
Published: February 2021

Understanding how the spatial arrangement of a population shapes its evolutionary dynamics has been of long-standing interest in population genetics. Most previous studies assume a small number of demes connected by migration corridors, symmetrical structures that most often act as well-mixed populations. Other studies use networks to model the more complex topologies of natural populations and to study the structures that suppress or amplify selection. However, they usually assume very small, regular networks, with strong constraints on the strength of selection considered. Here we build network generation algorithms, evolutionary simulations and derive general analytic approximations for probabilities of fixation in populations with complex spatial structure. By tuning network parameters and properties independent of each other, we systematically span across network families and show that both a network’s degree distribution, as well as its node mixing pattern shape the evolutionary dynamics of new mutations. We analytically write the relevant selective parameter, predictive of evolutionary dynamics, as a combination of network statistics. As one application, we use recent imaging datasets and build the cellular spatial networks of the stem cell niches of the bone marrow. Across a wide variety of parameters and regardless of the birth-death process used, we find these networks to be strong suppressors of selection, delaying mutation accumulation in this tissue. We also find that decreases in stem cell population size decrease the suppression strength of the tissue spatial structure, hinting at a potential diminishing spatial suppression in the bone marrow tissue as individuals age.
Poly(A) binding protein is required for mRNP remodeling to form P-bodies in mammalian cells
Authors: Xie Jingwei , Chen Yu , Wei Xiaoyu , Kozlov Guennadi
Published: February 2021

Compartmentalization of mRNA through formation of RNA granules is involved in many cellular processes, yet it is not well understood. mRNP complexes undergo dramatic changes in protein compositions, reflected by markers of P-bodies and stress granules. Here, we show that PABPC1, albeit absent in P-bodies, plays important role in P-body formation. Depletion of PABPC1 decreases P-body population in unstressed cells. Upon stress in PABPC1 depleted cells, individual P-bodies fail to form and instead P-body proteins assemble on PABPC1-containing stress granules. We hypothesize that mRNP recruit proteins via PABPC1 to assemble P-bodies, before PABPC1 is displaced from mRNP. Further, we demonstrate that GW182 can mediate P-body assembly. These findings help us understand the early stages of mRNP remodeling and P-body formation.

Summary statement

A novel role of poly(A) binding protein is reported in P-body formation
Structural and functional elucidation of NF-κB signaling by the p75 neurotrophin receptor through recruitment of TRADD
Authors: Zhang Ning , Kisiswa Lilian , Ramanujan Ajeena , Li Zhen , Sim Eunice Weiling , Yuan Wensu , Ibáñez Carlos F. , Lin Zhi
Published: February 2021

p75 neurotrophin receptor (p75NTR) is a critical mediator of neuronal death and tissue remodeling and has been implicated in various neurodegenerative diseases. The death domain (DD) of p75NTRis an intracellular signaling hub and has been shown to interact with diverse adaptor proteins. However, the structural mechanism and physiological relevance of the adaptor protein TRADD in neuronal p75NTRsignaling remain poorly understood. Here we report an NMR structure of the complex between p75NTR-DD and TRADD-DD and elucidate the structural basis of specific DD recognition in the p75NTR/TRADD signaling pathway. Furthermore, we identify spatiotemporal overlap of p75NTRand TRADD expression in developing cerebellar granule neurons (CGNs) at early postnatal stages and reveal the functional role of TRADD recruitment to p75NTRin the regulation of canonical NF-κB signaling and cell survival in CGNs. Our results provide a new structural framework for understanding how the recruitment of TRADD to p75NTRthrough DD interactions creates a membrane-proximal platform to propagate downstream signaling in developing neurons.
Consistent population activity on the scale of minutes in the mouse hippocampus
Authors: Liu Yue , Levy Samuel , Mau William , Geva Nitzan , Rubin Alon , Ziv Yaniv , Hasselmo Michael E. , Howard Marc W.
Published: February 2021

Neurons in the hippocampus fire in consistent sequence over the timescale of seconds during the delay period of some memory experiments. For longer timescales, firing of hippocampal neurons also changes slowly over minutes within experimental sessions. It was thought that these slow dynamics are caused by stochastic drift or a continuous change in the representation of the episode, rather than consistent sequences unfolding over minutes. This paper studies the consistency of contextual drift in three chronic calcium imaging recordings from the hippocampus CA1 region in mice. Computational measures of consistency show reliable sequences within experimental trials at the scale of seconds as one would expect from time cells or place cells during the trial, as well as across experimental trials on the scale of minutes within a recording session. Consistent sequences in the hippocampus are observed over a wide range of time scales, from seconds to minutes. Hippocampal activity could reflect a scale-invariant spatiotemporal context as suggested by theories of memory from cognitive psychology.
Disulfide-rich, cyclic peptides fromClitoria ternateaprotect against β-amyloid toxicity and oxidative stress in transgenicCaenorhabditis elegans
Authors: Kalmankar Neha V. , Hari Hrudya , Sowdhamini Ramanathan , Venkatesan Radhika
Published: February 2021

Neurotoxic aggregation of β-amyloid (Aβ) peptide is a hallmark of Alzheimer’s disease and increased reactive oxygen species (ROS) is known to be associated with this. Here, we report neuroprotective effects of disulfide-rich, circular peptides fromClitoria ternateaon Aβ-induced toxicity in transgenicCaenorhabditis elegans. We show that cyclotide-rich fractions from different plant tissues delay Aβ-induced paralysis in transgenic CL4176 strain expressing human muscle-specific Aβ1–42gene. It also improved Aβ-induced defects in chemotaxis in CL2355 expressing Aβ1-42in neuronal cells. ROS assay suggests that this is likely mediated by inhibition of Aβ oligomerization. Further, Aβ deposits were reduced in the strain, CL2006 treated with the fractions. Computational docking and molecular dynamics (MD) simulation support the findings since cyclotides bind effectively and stably to different forms of Aβ structures via hydrogen bonding and hydrophobic interactions. MD simulation further shows that cyclotides destabilize toxic amyloid assemblies. The study shows that cyclotides fromC. ternateacould be a source of novel pharmacophore scaffold against neurodegenerative diseases.
CASTLE: A database of synthetic lethal sets predicted from genome-scale metabolic networks
Authors: Senthamizhan Vimaladhasan , Subramaniam Sunanda , Raghavan Arjun , Raman Karthik
Published: February 2021

Genome-scale metabolic networks have been reconstructed for hundreds of organisms over the last two decades, with wide-ranging applications, including the identification of drug targets. Constraint-based approaches such as flux balance analysis have been effectively used to predict single and combinatorial drug targets in a variety of metabolic networks. We have previously developed Fast-SL, an efficient algorithm to rapidly enumerate all possible synthetic lethals from metabolic networks. Here, we introduce CASTLE, an online standalone database, which contains synthetic lethals predicted from the metabolic networks of over 130 organisms. These targets include single, double or triple lethal set of genes and reactions, and have been predicted using the Fast-SL algorithm. The workflow used for building CASTLE can be easily applied to other pathogenic models and used to identify novel therapeutic targets.

Availability

CASTLE is available athttps://ramanlab.github.io/CASTLE/

Contact

kraman@iitm.ac.in
TRF2-mediated ORC recruitment underlies telomere stability upon DNA replication stress
Authors: Higa Mitsunori , Matsuda Yukihiro , Yamada Jumpei , Sugimoto Nozomi , Yoshida Kazumasa , Fujita Masatoshi
Published: February 2021

Telomeres are intrinsically difficult-to-replicate regions of eukaryotic chromosomes. Telomeric repeat binding factor 2 (TRF2) binds to origin recognition complex (ORC) to facilitate the loading of ORC and the replicative helicase MCM complex onto DNA at telomeres. However, the biological significance of the TRF2-ORC interaction for telomere maintenance remains largely elusive. Here, we employed a separation-of-function TRF2 mutant with mutations in two acidic acid residues (E111A and E112A) that specifically inhibited the TRF2-ORC interaction in human cells without substantially inhibiting TRF2 interactions with its other binding partners. The TRF2 mutant was impaired in ORC recruitment to telomeres and showed increased replication stress-associated telomeric DNA damage and telomere instability. Furthermore, overexpression of an ORC1 fragment (amino acids 244–511), which competitively inhibited the TRF2-ORC interaction, increased telomeric DNA damage under replication stress conditions in human cells. Taken together, these findings suggest that TRF2-mediated ORC recruitment contributes to the suppression of telomere instability.
A strategy for using digital mindsets and knowledge technologies to move past pandemic conditions
Authors: Stewart Cherry , Khan Ashfaq Ahmad
Published: February 2021

Purpose

The purpose of this paper is to discuss the theoretical concepts of adult constructive development (ACD) in response to a requirement to teach fully online during the COVID-19 lockdown. However, responses have been unique for many university educators, regardless of the roles they have in supporting students during this time. How each person approaches the changing context can be enhanced by an understanding of their mindset as defined by Kegan’s theory.

Design/methodology/approach

An accounting academic and educational designer combine their expertise and engage a “digital mindset” to guide the re-design of the management accounting unit incorporating strategies that encourage students to be self-reliant yet learn from a broad diversity of perspectives.

Findings

Unexpected changes within an educational environment may be the catalyse needed to force significant rethinking of pedagogical practice within the online teaching space.

Practical implications

This paper offers practical thinking and design tips for creating interactive learning and teaching programs to develop a positive and supportive approach that challenges and facilitates cognitive growth in student knowledge, skills and learning behaviours.

Social implications

Stimulating student interaction via the creation of interactive and dynamic online curriculum design teachers may communicate more effectively with students as well as sharing their knowledge and skills with each other.

Originality/value

The authors explore Kegan’s ACD framework (1982, 1998, 2009) within the context of tertiary teaching and learning design for management accounting. The authors propose online strategies for each of the levels of development in the form of supports and challenges.
Modelling blockchain-based business processes: a comparative analysis of BPMN vs CMMN
Authors: Milani Fredrik , Garcia-Banuelos Luciano , Filipova Svitlana , Markovska Mariia
Published: February 2021

Purpose

Blockchain technology is increasingly positioned as a promising and disruptive technology. Such a promise has attracted companies to explore how blockchain technology can be used to gain significant benefits. Process models play a cardinal role when seeking to improve business processes as they are the foundation of process analysis and redesign. This paper examines how blockchain-oriented processes can be conceptually modelled with activity- (BPMN) and artifact-centric (CMMN) modelling paradigms.

Design/methodology/approach

This paper discusses how commonly occurring patterns, specific to block-chain-based applications, can be modelled with BPMN and CMMN. Furthermore, the advantages and disadvantages of both notations for accurately representing blockchain-specific patterns are discussed.

Findings

The main finding of this paper is that neither BPMN nor CMMN can adequately and accurately represent certain patterns specific for blockchain-oriented processes. BPMN, while supporting most of the patterns, does not provide sufficient support to represent tokenization. CMMN, on the other hand, does not provide support to distinguish between activities executed and data stored on-chain versus off-chain.

Originality/value

The paper provides insight into the strengths and weaknesses of BPMN and CMMN for modelling processes to be supported by blockchain. This will serve to aid analysts to produce better process models for communication purposes and, thereby, facilitate development of blockchain-based solutions.
Exploring the future impact of automation in Brazil
Authors: Lima Yuri , Strauch Julia Celia Mercedes , Esteves Maria Gilda Pimentel , de Souza Jano Moreira , Chaves Miriam Barbuda , Gomes Daniel Takata
Published: February 2021

Purpose

Brazil is struggling as the unemployment rate is 12.4% and nearly 13m people are unemployed. The fourth Industrial Revolution is advancing, and the country needs to consider how it will impact the labor market. This work explores the impact of automation on the Brazilian workforce to supply decision-makers with information about the subject.

Design/methodology/approach

The authors converted the probability of computerization from the seminal work of Frey and Osborne to each of the more than 2,500 occupations in Brazil. They then crossed the automation probability with socioeconomic information about workers and companies available in the Brazilian Ministry of Labor Database.

Findings

In total, 60% of employment in Brazil is expected to be highly impacted by automation in the coming decades, with eight out of the ten occupations with the biggest workforce being highly automatable. Automation probability decreases as workers' education level increases, with the most significant difference between workers with higher education and those without it. The results show other inequalities in the impact of automation: the higher the wage, the lower the automation probability of occupations; the bigger the company, the lower the automation index; and workers from 16 to 24 years old have considerably higher chances of being automated.

Originality/value

This work is the first to study, in the context of the fourth Industrial Revolution, the impact of automation in Brazil with a socioeconomic analysis.
A modified Li-He’s variational principle for plasma
Authors: He Ji-Huan
Published: February 2021

Purpose

It is extremely difficult to establish a variational principle for plasma. Kalaawy obtained a variational principle by using the semi-inverse method in 2016, and Li and He suggested a modification in 2017. This paper aims to search for a generalized variational formulation with a free parameter.

Design/methodology/approach

The semi-inverse method is used by suitable construction of a trial functional with some free parameters.

Findings

A modification of Li-He’s variational principle with a free parameter is obtained.

Originality/value

This paper suggests a new approach to construction of a trial-functional with some free parameters.
Experimental study on the accuracy and surface quality of printed versus machined holes in PEI Ultem 9085 FDM specimens
Authors: Gómez-Gras Giovanni , Pérez Marco A. , Fábregas-Moreno Jorge , Reyes-Pozo Guillermo
Published: February 2021

Purpose

This paper aims to investigate the quality of printed surfaces and manufacturing tolerances by comparing the cylindrical cavities machined in parts obtained by fused deposition modeling (FDM) with the holes manufactured during the printing process itself. The comparison focuses on the results of roughness and tolerances, intending to obtain practical references when making assemblies.

Design/methodology/approach

The experimental approach focuses on the comparison of the results of roughness and tolerances of two manufacturing strategies: geometric volumes with a through-hole and the through-hole machined in volumes that were initially printed without the hole. Throughout the study, both alternates are explained to make appropriate recommendations.

Findings

The study shows the best combinations of technological parameters, both machining and three-dimensional printing, which have been decisive for obtaining successful results. These conclusive results allow enunciating recommendations for use in the industrial environment.

Originality/value

This paper fulfills an identified need to study the dimensional accuracy of the geometries obtained by additive manufacturing, as no experimental evidence has been found of studies that directly address the problem of the FDM-printed part with geometric and dimensional tolerances and desirable surface quality for assembly.
Application of AI technology in modern digital marketing environment
Authors: Nair Kiran , Gupta Ruchi
Published: February 2021

Purpose

The purpose of this paper is to explore the various application of artificial intelligence (AI) to social media and digital advertising professionals and agencies to specialize to an advanced degree and maintain collaboration and creativity to bring a better return on investment.

Design/methodology/approach

Digital marketers are still oblivious to the importance of AI application, while some others simply do not know how to implement it. AI is currently acting as a significant disruption in digital and social media marketing worldwide.

Findings

Based on the literature review, the paper identifies the various AI applications in the field of digital media marketing.

Originality/value

This paper can serve as a useful guide for social media marketers to implement AI applications to impact digital marketing strategies better.