bluuebunny/crossref_metadata_2025 huggingface dataset:
Deciphering the mechanical code of genome and epigenome
Authors: Basu Aakash , Bobrovnikov Dmitriy G. , Cieza Basilio , Qureshi Zan , Ha Taekjip
Published: August 2020

Sequence features have long been known to influence the local mechanical properties and shapes of DNA. However, a mechanical code (i.e. a comprehensive mapping between DNA sequence and mechanical properties), if it exists, has been difficult to experimentally determine because direct means of measuring the mechanical properties of DNA are typically limited in throughput. Here we use Loop-seq – a recently developed technique to measure the intrinsic cyclizabilities (a proxy for bendability) of DNA fragments in genomic-scale throughput – to characterize the mechanical code. We tabulate how DNA sequence features (distribution patterns of all possible dinucleotides and dinucleotide pairs) influence intrinsic cyclizability, and build a linear model to predict intrinsic cyclizability from sequence. Using our model, we predict that DNA mechanical landscape shapes nucleosome organization around the promoters of various organisms and at the binding site of the transcription factor CTCF, and that hyperperiodic DNA inC. elegansleads to globally curved DNA segments. By performing loop-seq on random libraries in the presence or absence of CpG methylation, we show that CpG methylation leads to global stiffening of DNA in a wide sequence context, and predict based on our model that CpG methylation widely changes the mechanical landscape around mouse promoters. It suggests how epigenetic modifications of DNA might alter gene expression and mediate cellular adaptation by affecting critical processes around promoters that require mechanical deformations of DNA, such as nucleosome organization and transcription initiation. Finally, we show that the genetic code and the mechanical code are linked: sequence-dependent mechanical properties of coding DNA constrains the amino acid sequence despite the degeneracy in the genetic code. Our measurements explain why the pattern of nucleosome organization along genes influences the distribution of amino acids in the translated polypeptide.
Light-emitting diode-based transcranial photoacoustic measurement of sagittal sinus oxyhemoglobin saturation in hypoxic neonatal piglets
Authors: Kang Jeeun , Koehler Raymond C. , Adams Shawn , Graham Ernest M. , Boctor Emad M.
Published: August 2020

We present a light-emitting diode (LED)-based transcranial photoacoustic measurement (LED-trPA) of oxyhemoglobin (HbO2) saturation at superior sagittal sinus (SSS) in hypoxic neonatal piglets. The optimal LED imaging wavelengths and frame averaging scheme were determined based onin vivocharacterization of transcranial sensitivity. Based on the framework (690/850 nm with >20 frame averaging), graded hypoxia was successfully identified in neonatal pigletsin vivowith less than 10.0 % of root mean squared error (RMSE). This preclinical study suggests the feasibility of a rapid, cost-effective, and safe LED-trPA monitoring of perinatal hypoxia-ischemia and prompt interventions for clinical use.
Climate change risk to southern African wild food plants
Authors: Wessels Carina , Merow Cory , Trisos Christopher H.
Published: August 2020

Climate change is a threat to food security. Wild-harvested food plants (WFPs) are important for the diets of millions of people and contribute to food security, especially in rural and low-income communities, but little is known about climate change risk to these species. Using species distribution models, we examined climate change risk to 1190 WFP species used by 19 native language groups in southern Africa. We project that 40% of species will experience a decrease in range extent within southern Africa by 2060–2080 under a low warming scenario (Representative Concentration Pathway (RCP) 2.6), increasing to 66% under a high warming scenario (RCP 8.5). Decreases in geographic range are projected for >70% of WFP species traditionally used by some language groups. Loss of suitable climatic conditions is projected to decrease WFP species richness most in north-eastern southern Africa – with losses of >200 species – while increases in species richness are projected in the south and east of South Africa. Availability of WFP species for food security during lean times is also projected to change. Specifically, in south-eastern South Africa, local diversity of WFPs is projected to increase, while maize and sorghum yields decrease. However, this potential WFP nutritional safety net may be lost in central parts of the region, where declines in both crop yield and WFPs are projected. By looking beyond conventional crops to the exceptional diversity of WFPs, this research makes a first step towards understanding the linkages between WFPs, traditional knowledge, agriculture, food security, and climate change.
Cytochromeb6fcomplex inhibition by antimycin-A requires Stt7 kinase activation but not PGR5
Authors: Buchert Felix , Hippler Michael
Published: August 2020

Ferredoxin-plastoquinone reductase (FQR) activity during cyclic electron flow (CEF) was first ascribed to the cytochromeb6fcomplex (b6f). However, this was later dismissed sinceb6finhibition by antimycin-A (AA) could not be reproduced. AA presumably fails to ligate with haembh, at variance with cytochromebc1complex, owing to a specific Qi-site occupation inb6f. Currently, PROTON GRADIENT REGULATION5 (PGR5) and the associated PGR5-Like1 are considered as FQR in the AA-sensitive CEF pathway. Here, we show that theb6fis conditionally inhibited by AA in a PGR5-independent manner when CEF is promoted. AA inhibition, demonstrated by singleb6fturnover and electron transfer measurements, coincided with an altered Qi-site function which required Stt7 kinase activation by a strongly reduced plastoquinone pool. Thus, PGR5 and Stt7 were necessary forb6factivity and AA-sensitive electron transfer in CEF-favouring conditions. Extending previous findings, a new FQR activity model of theb6fis discussed.
Base pairing and stacking contributions to double stranded DNA formation
Authors: Zacharias Martin
Published: August 2020

Double-strand (ds)DNA formation and dissociation are of fundamental biological importance. The negatively DNA charge influences the dsDNA stability. However, the base pairing and the stacking between neighboring bases are responsible for the sequence dependent stability of dsDNA. The stability of a dsDNA molecule can be estimated from empirical nearest-neighbor models based on contributions assigned to base pair steps along the DNA and additional parameters due to DNA termini. In efforts to separate contributions it has been concluded that base-stacking dominates dsDNA stability whereas base-pairing contributes negligibly. Using a different model for dsDNA formation we re-analyze dsDNA stability contributions and conclude that base stacking contributes already at the level of separate ssDNAs but that pairing contributions drive the dsDNA formation. The theoretical model also predicts that stability contributions of base pair steps that contain only guanine/cytosine, mixed steps and steps with only adenine/thymine follows the order 6:5:4, respectively, as expected based on the formed hydrogen bonds. The model is fully consistent with available stacking data and nearest-neighbor dsDNA parameters. It allows to assign a narrowly distributed value for the effective free energy contribution per formed hydrogen bond during dsDNA formation of −0.72 kcal·mol-1based entirely on experimental data.
Emap2sec+: Detecting Protein and DNA/RNA Structures in Cryo-EM Maps of Intermediate Resolution Using Deep Learning
Authors: Wang Xiao , Alnabati Eman , Aderinwale Tunde W. , Venkata Subramaniya Sai Raghavendra Maddhuri , Terashi Genki , Kihara Daisuke
Published: August 2020

An increasing number of density maps of macromolecular structures, including proteins and protein and DNA/RNA complexes, have been determined by cryo-electron microscopy (cryo-EM). Although lately maps at a near-atomic resolution are routinely reported, there are still substantial fractions of maps determined at intermediate or low resolutions, where extracting structure information is not trivial. Here, we report a new computational method, Emap2sec+, which identifies DNA or RNA as well as the secondary structures of proteins in cryo-EM maps of 5 to 10 Å resolution. Emap2sec+ employs the deep Residual convolutional neural network. Emap2sec+ assigns structural labels with associated probabilities at each voxel in a cryo-EM map, which will help structure modeling in an EM map. Emap2sec+ showed stable and high assignment accuracy for nucleotides in low resolution maps and improved performance for protein secondary structure assignments than its earlier version when tested on simulated and experimental maps.
Value Certainty in Drift-Diffusion Models of Preferential Choice
Authors: Lee Douglas , Usher Marius
Published: August 2020

Thedrift-diffusion model(DDM) is widely used and broadly accepted for its ability to account for binary choices (in both the perceptual and preferential domains) and response times (RT), as a function of the stimulus or the choice alternative (or option) values. The DDM is built on an evidence accumulation-to-bound concept, where, in the value domain, a decision maker repeatedly samples the mental representations of the values of the available options until satisfied that there is enough evidence (or support) in favor of one option over the other. As the signals that drive the evidence are derived from value estimates that are not known with certainty, repeated sequential samples are necessary to average out noise. The classic DDM does not allow for different options to have different levels of precision in their value representations. However, recent studies have shown that decision makers often report levels of certainty regarding value estimates that vary across choice options. There is therefore a need to extend the DDM to include an option-specific value certainty component. We present several such DDM extensions and validate them against empirical data from four previous studies. The data support best a DDM version in which the drift of the accumulation is based on a sort of signal-to-noise ratio of value for each option (rather than a mere accumulation of samples from the corresponding value distributions). This DDM variant accounts for the impact of value certainty on both choice consistency and response time present in the empirical data.
Adaptation across geographic ranges is consistent with strong selection in marginal climates and legacies of range expansion
Authors: Bontrager Megan , Usui Takuji , Lee-Yaw Julie A. , Anstett Daniel N. , Branch Haley A. , Hargreaves Anna L. , Muir Christopher D. , Angert Amy L.
Published: August 2020

Every species experiences limits to its geographic distribution. Some evolutionary models predict that populations at range edges are less well-adapted to their local environments due to drift, expansion load, or swamping gene flow from the range interior. Alternatively, populations near range edges might be uniquely adapted to marginal environments. In this study, we use a database of transplant studies that quantify performance at broad geographic scales to test how local adaptation, site quality, and population quality change from spatial and climatic range centers towards edges. We find that populations from poleward edges perform relatively poorly, both on average across all sites (15% lower population quality) and when compared to other populations at home (31% relative fitness disadvantage), consistent with these populations harboring high genetic load. Populations from equatorial edges also perform poorly on average (18% lower population quality) but, in contrast, outperform foreign populations (16% relative fitness advantage), suggesting that populations from equatorial edges have strongly adapted to unique environments. Finally, we find that populations from sites that are thermally extreme relative to the species’ niche demonstrate strong local adaptation, regardless of their geographic position. Our findings indicate that both nonadaptive processes and adaptive evolution contribute to variation in adaptation across species’ ranges.
Theoretical basis for stabilizing messenger RNA through secondary structure design
Authors: Wayment-Steele Hannah K. , Kim Do Soon , Choe Christian A. , Nicol John J. , Wellington-Oguri Roger , Watkins Andrew M. , Sperberg R. Andres Parra , Huang Po-Ssu , Participants Eterna , Das Rhiju
Published: August 2020

RNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery, and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. These computational tests were carried out on both model mRNAs and COVID-19 mRNA vaccine candidates. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term ‘superfolder’ mRNAs. These designs exhibit wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity, and their folding is robust to temperature, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1, and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.

Significance statement

Messenger RNA (mRNA) medicines that encode and promote translation of a target protein have shown promising use as vaccines in the current SARS-CoV-2 pandemic as well as infectious diseases due to their speed of design and manufacturing. However, these molecules are intrinsically prone to hydrolysis, leading to poor stability in aqueous buffer and major challenges in distribution. Here, we present a principled biophysical model for predicting RNA degradation, and demonstrate that the stability of any mRNA can be increased at least two-fold over conventional design techniques. Furthermore, the predicted stabilization is robust to post-design modifications. This conceptual framework and accompanying algorithm can be immediately deployed to guide re-design of mRNA vaccines and therapeutics to increase in vitro stability.
Plant traits that influence flower visits by birds in a montane forest
Authors: Gonzalez Oscar
Published: August 2020

In a bird-flowering plant network, birds select plants that present traits attractive to them. I studied plant characteristics that might predict flower visitation rate by the most common bird visitors in a bird-flowering plant network located in an elfin forest of the Andes. The nectarivorous birds which had the highest number of interactions with flowering plants in this network were the Coppery Metaltail (Metallura theresiae), the Great Sapphirewing (Pterophanes cyanopterus), and the Moustached Flowerpiercer (Diglossa mystacalis). I analyzed different flower traits (flower aggregation, nectar volume, nectar energy, color, orientation, and dimensions of the corolla) of the common plants that these birds visited with a principal component analysis. The plants most visited by birds wereBrachyotum lutescensandTristerix longebracteatus.While nectar traits of the plants seemed to be the best predictor for bird visitation, there was no statistical association between visitation and plant traits, except forMetallura theresiaein the dry season. I discuss the possible causes of resource partitioning for these nectarivorous birds.
Epigenetic reprogramming of plasmacytoid dendritic cells drives type I interferon-dependent differentiation of acute myeloid leukemias for therapeutic benefit
Authors: Salmon Jessica M. , Todorovski Izabela , Vervoort Stephin J. , Stanley Kym L. , Kearney Conor J. , Martelotto Luciano , Rossello Fernando , Semple Tim , Mir-Arnau Gisela , Zethoven Magnus , Bots Michael , Vidacs Eva , McArthur Kate , Gressier Elise , de Weerd Nicky , Lichte Jens , Kelly Madison J. , Cluse Leonie , Hogg Simon J. , Hertzog Paul J. , Kats Lev , de Carvalho Daniel D. , Scheu Stefanie , Bedoui Sammy , Kile Benjamin T. , Wei Andrew , Dominguez Pilar M. , Johnstone Ricky W.
Published: August 2020

Pharmacological inhibition of epigenetic enzymes can have therapeutic benefit, particularly against hematological malignancies. While these agents can affect tumor cell growth and proliferation, recent studies have demonstrated that pharmacological de-regulation of epigenetic modifiers may additionally mediate anti-tumor immune responses. Here we discovered a novel mechanism of immune regulation through the inhibition of histone deacetylases (HDACs). In a genetically engineered model of t(8;21) AML, leukemia cell differentiation and therapeutic benefit mediated by the HDAC inhibitor panobinostat required activation of the type I interferon (IFN) signaling pathway. Plasmacytoid dendritic cells (pDCs) were identified as the cells producing type I IFN in response to panobinostat, through transcriptional activation of IFN genes concomitant with increased H3K27 acetylation at these loci. Depletion of pDCs abrogated panobinostat-mediated activation of type I IFN signaling in leukemia cells and impaired therapeutic efficacy, while combined treatment of panobinostat and recombinant IFNα improved therapeutic outcomes. These discoveries offer a new therapeutic approach for t(8;21) AML and demonstrate that epigenetic rewiring of pDCs enhances anti-tumor immunity, opening the possibility of exploiting this cell type as a new target for immunotherapy.
Computational Modeling: Human Dynamic Model
Authors: Liu Lijia , Cooper Joseph L. , Ballard Dana H.
Published: August 2020

Improvements in quantitative measurements of human physical activity are proving extraordinarily useful for studying the underlying musculoskeletal system. Dynamic models of human movement support clinical efforts to analyze, rehabilitate injuries. They are also used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. In addition, they provide useful constraints for underlying neural circuits. This paper describes a physics-based movement analysis method for analyzing and simulating bipedal humanoid movements. A 48 degree of freedom dynamic model of humans has been developed to report humanoid movements’ energetic components. It has sufficient speed and accuracy to analyze and synthesize real-time interactive applications, such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to believably animate a humanoid character or estimate internal joint forces used during a movement for creating effort-contingent experimental stimuli. A virtual reality environment developed as part of this research supports controlled experiments for systematically recording human behaviors.
A genome-scale phylogeny of Fungi; insights into early evolution, radiations, and the relationship between taxonomy and phylogeny
Authors: Li Yuanning , Steenwyk Jacob L. , Chang Ying , Wang Yan , James Timothy Y. , Stajich Jason E. , Spatafora Joseph W. , Groenewald Marizeth , Dunn Casey W. , Hittinger Chris Todd , Shen Xing-Xing , Rokas Antonis
Published: August 2020

Phylogenomic studies based on genome-scale amounts of data have greatly improved understanding of the tree of life. Despite their diversity, ecological significance, and biomedical and industrial importance, large-scale phylogenomic studies of Fungi are lacking. Furthermore, several evolutionary relationships among major fungal lineages remain controversial, especially those at the base of the fungal phylogeny. To begin filling these gaps and assess progress toward a genome-scale phylogeny of the entire fungal kingdom, we compiled a phylogenomic data matrix of 290 genes from the genomes of 1,644 fungal species that includes representatives from most major fungal lineages; we also compiled 11 additional data matrices by subsampling genes or taxa based on filtering criteria previously shown to improve phylogenomic inference. Analyses of these 12 data matrices using concatenation- and coalescent-based approaches yielded a robust phylogeny of the kingdom in which ∼85% of internal branches were congruent across data matrices and approaches used. We found support for several relationships that have been historically contentious (e.g., for the placement of Wallemiomycotina (Basidiomycota), as sister to Agaricomycotina), as well as evidence for polytomies likely stemming from episodes of ancient diversification (e.g., at the base of Basidiomycota). By examining the relative evolutionary divergence of taxonomic groups of equivalent rank, we found that fungal taxonomy is broadly aligned with genome sequence divergence, but also identified lineages, such as the subphylum Saccharomycotina, where current taxonomic circumscription does not fully account for their high levels of evolutionary divergence. Our results provide a robust phylogenomic framework to explore the tempo and mode of fungal evolution and directions for future fungal phylogenetic and taxonomic studies.
Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns
Authors: Cui Qiaoling , Pamukcu Arin , Cherian Suraj , Chang Isaac Y. M. , Berceau Brianna L. , Xenias Harry S. , Higgs Mathew H. , Rajamanickam Shivakumar , Chen Yi , Du Xixun , Zhang Yu , McMorrow Hayley , Abecassis Zachary A. , Boca Simina M. , Justice Nicholas J. , Wilson Charles J. , Chan C. Savio
Published: August 2020

We have previously established that PV+neurons and Npas1+neurons are distinct neuron classes in the GPe— they have different topographical, electrophysiological, circuit, and functional properties. Aside from Foxp2+neurons, which are a unique subclass within the Npas1+class, we lack driver lines that effectively capture other GPe neuron subclasses. In this study, we examined the utility of Kcng4-Cre, Npr3-Cre, and Npy2r-Cre mouse lines (both males and females) for the delineation of GPe neuron subtypes. By using these novel driver lines, we have provided the most exhaustive investigation of electrophysiological studies of GPe neuron subtypes to date. Corroborating our prior studies, GPe neurons can be divided into two statistically distinct clusters that map onto PV+and Npas1+classes. By combining optogenetics and machine learning-based tracking, we showed that optogenetic perturbation of GPe neuron subtypes generated unique behavioral structures. Our findings further highlighted the dissociable roles of GPe neurons in regulating movement and anxiety-like behavior. We concluded that Npr3+neurons and Kcng4+neurons are distinct subclasses of Npas1+neurons and PV+neurons, respectively. Finally, by examining local collateral connectivity, we inferred the circuit mechanisms involved in the motor patterns observed with optogenetic perturbations. In summary, by identifying mouse lines that allow for manipulations of GPe neuron subtypes, we created new opportunities for interrogations of cellular and circuit substrates that can be important for motor function and dysfunction.

Significance statement

Within the basal ganglia, the external globus pallidus (GPe) has long been recognized for its involvement in motor control. However, we lacked an understanding of precisely how movement is controlled at the GPe level as a result of its cellular complexity. In this study, by using transgenic and cell-specific approaches, we showed that genetically-defined GPe neuron subtypes have distinct roles in regulating motor patterns. In addition, thein vivocontributions of these neuron subtypes are in part shaped by the local, inhibitory connections within the GPe. In sum, we have established the foundation for future investigations of motor function and disease pathophysiology.
MQF and buffered MQF: Quotient filters for efficient storage of k-mers with their counts and metadata
Authors: Shokrof Moustafa , Brown C. Titus , Mansour Tamer A.
Published: August 2020

Background

Specialized data structures are required for online algorithms to efficiently handle large sequencing datasets. The counting quotient filter (CQF), a compact hashtable, can efficiently store k-mers with a skewed distribution.

Result

Here, we present the mixed-counters quotient filter (MQF) as a new variant of the CQF with novel counting and labeling systems. The new counting system adapts to a wider range of data distributions for increased space efficiency and is faster than the CQF for insertions and queries in most of the tested scenarios. A buffered version of the MQF can offload storage to disk, trading speed of insertions and queries for a significant memory reduction. The labeling system provides a flexible framework for assigning labels to member items while maintaining good data locality and a concise memory representation. These labels serve as a minimal perfect hash function but are ~10 fold faster than BBhash, with no need to re-analyze the original data for further insertions or deletions.

Conclusion

The MQF is a flexible and efficient data structure that extends our ability to work with high throughput sequencing data.
Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy
Authors: Krieger Teresa G , Blanc Solange Le , Jabs Julia , Ten Foo Wei , Ishaque Naveed , Jechow Katharina , Debnath Olivia , Leonhardt Carl-Stephan , Giri Anamika , Eils Roland , Strobel Oliver , Conrad Christian
Published: August 2020

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished ‘classical’ pancreatic tumors from ‘basal-like’ tumors with more aggressive clinical behaviour. We derived PDAC organoids from primary tumors of 18 patients, together with two matched samples from liver metastases. By single-cell RNA sequencing, we show that PDAC organoids consist of ductal cells with patient-specific expression of several gene groups, including genes which encode cell surface proteins. We report ‘classical’ and ‘basal-like’ cells coexisting within single primary tumors or metastases, with greater intratumor subtype heterogeneity linked to higher tumor grade. Single-cell transcriptome analysis of PDAC organoids and primary PDAC identified distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. We show that these cell states are connected by a differentiation hierarchy, with ‘classical’ subtype cells concentrated at the endpoint of this hierarchy. In an imaging-based drug screen, expression of ‘classical’ subtype genes also correlates with better response to clinical drugs. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model forin vitrostudies of tumor heterogeneity.
Synthesis and Evaluation of a Stable Isostere of Malonyllysine
Authors: Bergholtz Sarah E. , Jing Yihang , Kulkarni Rhushikesh A. , Zengeya Thomas T. , Meier Jordan L.
Published: August 2020

Lysine malonylation is a recently characterized posttranslational modification involved in the regulation of energy metabolism and gene expression. Two unique features of this posttranslational modification are its negative charge and potential susceptibility to decarboxylation, both of which pose possible challenges to its study. As a step towards addressing these challenges, here we report the synthesis and evaluation of a stable isostere of malonyllysine. First, we find that synthetic substitution of the malonyl group with a tetrazole isostere results in amino acids resistant to thermal decarboxylation. Next, we demonstrate that protected variants of this amino acid are readily incorporated into peptides. Finally, we show that tetrazole isosteres of malonyllysine can be recognized by anti-malonyllysine antibodies, validating their ability to mimic features of the endogenous lysine modification. Overall, this study establishes a new chemical strategy for stably mimicking a metabolite-derived posttranslational modification, providing a foothold for tool development and functional analyses.
Developmental retrotransposon activation primes host immunity for future viral-clearance
Authors: Wang Lu , Tracy Lauren , Zhang ZZ Zhao
Published: August 2020

Transposons are thought to be largely suppressed under physiological conditions, ensuring that their mobilization is a rare event. By tracking mobilization, we show that during metamorphosis at theDrosophilapupal stage, theGypsyretrotransposon selectively mobilizes in regenerating tissues. In the newly formed tissues, this wave ofGypsyactivation primes the host’s innate immune system by inducing the production ofantimicrobialpeptides (AMPs). Moreover, early immune-priming functions ofGypsyare essential for combating viral invasion in adult flies: flies withGypsybeing silenced at the pupal stage are unable to clear viruses and succumb to viral infection. Our data reveal that regulated activation of transposons during animal developmental endows a long-term benefit in pathogen warfare.
Movie-watching outperforms rest for functional connectivity-based prediction of behavior
Authors: Finn Emily S. , Bandettini Peter A.
Published: August 2020

A major goal of human neuroscience is to relate differences in brain function to differences in behavior across people. Recent work has established that whole-brain functional connectivity patterns are relatively stable within individuals and unique across individuals, and that features of these patterns predict various traits. However, while functional connectivity is most often measured at rest, certain tasks may enhance individual signals and improve sensitivity to behavioral differences. Here, we show that compared to the resting state, functional connectivity measured during naturalistic viewing—i.e., movie watching—yields more accurate predictions of trait-like phenotypes in the both cognitive and emotional domains. Traits could be predicted using less than three minutes of data from single video clips, and clips with highly social content gave the most accurate predictions. Results suggest that naturalistic stimuli amplify individual differences in behaviorally relevant brain networks.
Whole-organism eQTL mapping at cellular resolution with single-cell sequencing
Authors: Ben-David Eyal , Boocock James , Guo Longhua , Zdraljevic Stefan , Bloom Joshua S. , Kruglyak Leonid
Published: August 2020

Genetic regulation of gene expression underlies variation in disease risk and other complex traits. The effect of expression quantitative trait loci (eQTLs) varies across cell types; however, the complexity of mammalian tissues makes studying cell-type eQTLs highly challenging. We developed a novel approach in the model nematodeCaenorhabditis elegansthat uses single cell RNA sequencing to map eQTLs at cellular resolution in a single one-pot experiment. We mapped eQTLs across cell types in an extremely large population of genetically distinctC. elegnasindividuals. We found cell-type-specifictrans-eQTL hotspots that affect the expression of core pathways in the relevant cell types. Finally, we found single-cell-specific eQTL effects in the nervous system, including an eQTL with opposite effects in two individual neurons. Our results show that eQTL effects can be specific down to the level of single cells.
Mating pattern, duration and multiple mating inChondromorpha severiniSilvestri (Diplopoda: Polydesmida)
Authors: Bhakat S.
Published: August 2020

Mating behaviour ofChondromorpha severini, a polydesmid millipede was studied in the field and in the laboratory condition. Copulating pair follows the general rule of love play before actual act of coitus. Mating duration varied from one to 25 minute with an average of eight minute. Mating frequency was maximum in early and late hours of day. In the multiple mate preference experiment, 10 pairs of male and female were used to calculate preference index (Pi) of individual sex. Preference index varies from 0.65 to 0.91. The implication of multiple mating has been discussed in detail. The study confirmed that i) the species belongs to polygynandrous mating system where males are the pursuers and females are the accomplishers ii) short and long duration mating is related to mate acquisition and mate guarding respectively
A chimera including aGROWTH-REGULATING FACTOR(GRF) and its cofactorGRF-INTERACTING FACTOR(GIF) increases transgenic plant regeneration efficiency
Authors: Debernardi Juan M. , Tricoli David M. , Ercoli Maria F. , Hayta Sadiye , Ronald Pamela , Palatnik Javier F. , Dubcovsky Jorge
Published: August 2020

Genome editing allows precise DNA manipulation, but its potential is limited in many crops by low regeneration efficiencies and few transformable genotypes. Here, we show that expression of a chimeric protein including wheat GROWTH-REGULATING FACTOR 4 (GRF4) and its cofactor GRF-INTERACTING FACTOR 1 (GIF1) dramatically increases the efficiency and speed of regeneration in wheat, triticale and rice and expands the number of transformable wheat genotypes. Moreover,GRF4-GIF1induces efficient wheat regeneration in the absence of exogenous cytokinins, which facilitates selection of transgenic plants without selectable markers. By combiningGRF4-GIF1and CRISPR-Cas9 technologies, we were able to generate large numbers of edited wheat plants. TheGRF4-GIF1transgenic plants were fertile and without obvious developmental defects, likely due to post-transcriptional regulatory mechanisms operating onGRF4in adult tissues. Finally, we show that a dicotGRF-GIFchimera improves regeneration efficiency in citrus suggesting that this strategy can be expanded to dicot crops.
Sleep and sleep deprivation differentially alter white matter microstructure: a mixed model design utilising advanced diffusion modelling
Authors: Voldsbekk Irene , Groote Inge , Zak Nathalia , Roelfs Daniël , Geier Oliver , Due-Tønnessen Paulina , Løkken Lise-Linn , Strømstad Marie , Blakstvedt Taran Y. , Kuiper Yvonne S. , Elvsåshagen Torbjørn , Westlye Lars T. , Bjørnerud Atle , Maximov Ivan I.
Published: August 2020

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across 4 time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.
Solving musculoskeletal biomechanics with machine learning
Authors: Smirnov Yaroslav , Smirnov Denis , Popov Anton , Yakovenko Sergiy
Published: August 2020

Deep learning is a relatively new computational technique for the description of the musculoskeletal dynamics. The experimental relationships of muscle geometry in different postures are the high-dimensional spatial transformations that can be approximated by relatively simple functions, which opens the opportunity for machine learning applications. In this study, we challenged general machine learning algorithms with the problem of approximating the posture-dependent moment arm and muscle length relationships of the human arm and hand muscles. We used two types of algorithms, light gradient boosting machine (LGB) and fully connected artificial neural network (ANN) solving the wrapping kinematics of 33 muscles spanning up to six degrees of freedom (DOF) each for the arm and hand model with 18 DOFs. The input-output training and testing datasets were generated by our previous phenomenological model based on the autogenerated polynomial structures (Sobinov et al., 2019). Both models achieved a similar level of errors: ANN model errors were 0.08±0.05% for muscle lengths and 0.53±0.29% for moment arms, and LGB model made similar errors—0.18±0.06% and 0.13±0.07%, respectively. LGB model reached the training goal with only 10^3 samples, while ANN required 10^6 samples; however, LGB models were about 39 slower than ANN models in the evaluation. The sufficient performance of developed models demonstrates the future applicability of machine learning for musculoskeletal transformations in a variety of applications, such as in advanced powered prosthetics.

Author Summary

The accurate decoding of arm and hand motor intent from biological signals remains a key challenge. Solving this task with machine learning requires vast posture- and task-dependent data for identifying structural and functional parameters within dynamic musculoskeletal relationships. This problem is related tothe curse of dimensionalitywhere the processing complexity grows exponentially with the number of degrees of freedom described by the model. Here, we developed a tool based on artificial neural networks (ANN) to solve the kinematic transformation from posture to muscle path length and muscle moment arms. We used an accurate model of posture-dependent muscle moment arms and length to train and test the ability of ANN to solve this high-dimensional and computationally intense transformation and compare it to the boosted decision tree approach. We demonstrated that model-driven training is an efficient method to handle the encoding of high-dimensional musculoskeletal relationships. Adding muscles to the transformation, which increases the input-output complexity, does not reduce the prediction accuracy and does not require the increase in the number of elements within the network demonstrating the viability of this approach for applications using musculoskeletal biomechanics.
Disinfection chemicals mode of action on the bacterial spore structure and their Raman spectra
Authors: Malyshev Dmitry , Dahlberg Tobias , Wiklund Krister , Andersson Per Ola , Henriksson Sara , Andersson Magnus
Published: August 2020

Contamination of toxic spore-forming bacteria is problematic since spores can survive a plethora of disinfection chemicals. It is also problematic to rapidly detect if the disinfection chemical was active, leaving spores dead. Robust decontamination strategies, as well as reliable detection methods to identify dead from viable spores, are thus critical. Vibrational detection methods such as Raman spectroscopy has been suggested for rapid diagnostics and differentiation of live and dead spores. We investigate in this work, using laser tweezers Raman spectroscopy, the changes in Raman spectra ofBacillus thuringiensisspores treated with sporicidal agents such as chlorine dioxide, peracetic acid, and sodium hypochlorite. We also imaged treated spores using SEM and TEM to verify if any changes to the spore structure can be correlated to the Raman spectra. We found that chlorine dioxide did not change the Raman spectrum or the spore structure; peracetic acid shows a time-dependent decrease in the characteristic DNA/DPA peaks and ∼20 % of the spores were degraded and collapsed; spores treated with sodium hypochlorite show an abrupt drop in DNA and DPA peaks within 20 minutes all though the spore structure was overall intact, however, the exosporium layer was reduced. Structural changes appeared over several minutes, compared to the inactivation time of the spores, which is less than a minute. We conclude that vibrational spectroscopy provides powerful means to detect changes in spores but it might be problematic to identify if spores are live or dead after a decontamination procedure.
Study of In silico Anti-Inflammatory Potential of Tyramine-Fe complex in Brotowali Plants
Authors: Wimbuh T.W. , Sutiman B.S. , Widyarti Sri , Djoko H. S
Published: August 2020

Tyramine-Fe complex is a bioinorganic complex that is formed in brotowali. The complex is thought to play a role in the anti-inflammatory activity of brotowali. The mechanism of anti-inflammatory drugs such as aspirin and ibuprofen is to inhibit the reaction of prostaglandin formation from COX2 and arachidonic acid. In this study, a docking simulation was performed between COX2 with single tyramine, tyramine-Fe complex ibuprofen, and aspirin. The results showed that the COX2-single tyramine bond overlapped with COX2-aspirin, while COX2-tyramine-Fe complex bond overlapped with COX2-ibuprofen. The energy required to form COX2-tyramine-Fe complex bond was smaller than that of single tyramine, aspirin, and ibuprofen. The number of bonds of COX2-tyramine-Fe complex bond is higher than that of single tyramine. These results proved that COX2-tyramine-Fe complex bond had anti-inflammatory activity and greater activity than single tyramine.
Discovery of NOvel CIP2A VAriant (NOCIVA) and its clinical relevance in myeloid leukemias
Authors: Mäkelä Eleonora , Pavic Karolina , Varila Taru , Salmenniemi Urpu , Löyttyniemi Eliisa , Nagelli Srikar , Kähäri Veli-Matti , Clark Richard E , Bachanaboyina Venkata Kumari , Lucas Claire , Itälä-Remes Maija , Westermarck Jukka
Published: August 2020

Cancerous inhibitor of PP2A (CIP2A) is a prevalent human oncoprotein that inhibits tumor suppressor PP2A-B56a. However,CIP2AmRNA and protein variants remain uncharacterized. Here, we report discovery of aCIP2Asplicing variantNOCIVA(NOvel CIp2a VAriant).NOCIVAcontainsCIP2Aexons 1-13 fused to a continuous stretch of 349 nucleotide fromCIP2Aintron 13. Intriguingly, the first 39 nucleotides of theNOCIVAspecific sequence are in coding frame with exon 13 ofCIP2A, and codes for a 13 amino acid peptide tail unhomologous to any known human protein sequence. Therefore, NOCIVA translates to a unique human protein. NOCIVA retains the capacity to bind to B56a, but whereas CIP2A is predominantly a cytoplasmic protein, NOCIVA translocates to nucleus. Indicative of prevalent alternative splicing fromCIP2AtoNOCIVAin myeloid malignancies, acute myeloid leukemia (AML) and chronic myeloid leukemia (CML) patient samples overexpressNOCIVA, but notCIP2AmRNA. In AML, highNOCIVAmRNA expression is a marker for adverse overall survival. In CML, highNOCIVAexpression associates with inferior event free survival among imatinib treated patients, but not among patients treated with dasatinib or nilotinib. Collectively, we describe discovery of a novel variant of oncoprotein CIP2A, and its clinical relevance in myeloid leukemias.

Key Points

Discovery and characterization of a first mRNA variant of one of the most prevalently deregulated human oncoproteins CIP2A

Unlike CIP2A, NOCIVA mRNA is overexpressed in AML and CML patient samples and associates with poor clinical response in both myeloid cancers
Determinants of consumers’ intention to use credit card: a perspective of multifaceted perceived risk
Authors: Trinh Hoang Nam , Tran Hong Ha , Vuong Duc Hoang Quan
Published: August 2020

Purpose

The purpose of this study is to develop a theoretical model for consumer behavioral intention by integrating the technology acceptance model (TAM) and the theory of perceived risk, which is tested on the intended use of credit cards in Vietnam.

Design/methodology/approach

The data were collected from 485 bank customers through a nationwide online survey. An exploratory and confirmatory factor analyzes were performed to validate the factor structure of the measurement items while structural equation modeling was used to validate the proposed model and testing the hypotheses.

Findings

The results of structural equation modeling reveal that perceived risk, perceived usefulness, social influence and perceived ease of use were significant determinants of consumer intention to use a credit card. Of them, only perceived risk discouraged the intended use of a credit card, which was synthesized from psychological, financial, performance, privacy, time, social and security risk.

Research limitations/implications

This study measured the first-order risk dimensions based on the payment function of the credit card only; these measurements missed potential losses relevant to credit function of credit cards.

Practical implications

This study can be beneficial to banks enacting policies to attract more consumers and to help decide how to allocate resources to retain and expand their customer base.

Originality/value

The study adds value to the literature on consumer behavior by confirming the impact of second-order perceived risk on the intended use of credit cards, which most previous studies have not demonstrated. The research also provides an empirical evidence to the academic research platform on e-banking services in Vietnam, especially related to the credit card industry.
The undergraduate simulation framework: standardising design and delivery
Authors: Irwin Pauletta Marie , Brown Robin A. , Butler Sonia
Published: August 2020

Purpose

Higher education organisations have the need and capacity to meet the expectations of industry partners to develop practice-ready graduates. Altered social and fiscal constraints have implications for the health workforce and, as such, decisions about how best to prepare undergraduate students should be considered. The purpose of this (conceptual) paper is to present the undergraduate simulation framework that has been designed to promote a standardised delivery of simulation, enabling graduates to have a higher capacity to meet workforce needs.

Design/methodology/approach

Education and simulation literature were explored to inform the development of the undergraduate simulation framework. A working knowledge of accreditation standards of health professions was key in designing a framework that could be applied across disciplines.

Findings

The framework encompasses tenets of a learner-centred pedagogy as well as professional and simulation standards. Experiential learning, behaviourism and social constructivism are viewed as foundational pillars when developing and delivering a simulation and have been considered in developing the framework. Other constructs of the undergraduate simulation framework are prebriefing, debriefing, repetition in the form of simulation cycles and the roles of student and educator.

Practical implications

It is recommended that this framework be incorporated into undergraduate health programmes to enhance student learning and potentiate the transference of knowledge and skills to the clinical setting.

Originality/value

The undergraduate simulation framework was developed to contribute to education and simulation research literature specific to health programmes to enhance student learning in readiness for the clinical environment.