bluuebunny/crossref_metadata_2025_split huggingface dataset:
The validation of a mobile sensor-based neurobehavioral assessment with machine learning analytics
Authors: Sloane Kelly L. , Glenn Shenly , Mefford Joel A. , Zhao Zilong , Xu Man , Zhou Guifeng , Mace Rachel , Wright Amy E , Hillis Argye E. 
Published: May 2021

AbstractBackgroundMild cognitive impairment is a common yet complex condition that is often underdiagnosed in the early stages. Miro Health is a mobile platform for the self-administration of sensor-based cognitive and behavioral assessments that was developed to measure factors typical of legacy neuropsychological tests in addition to behaviors that are currently left to subjective clinical impression such as eye movement, language, and processing speed.ObjectiveStudies were conducted to measure Miro Health’s concurrent validity, test-retest reliability, and amnestic MCI classification performance.MethodSpearman correlations were calculated to estimate the concurrent validity of Miro Health variables with legacy neuropsychological test variables using data from 160 study participants. Fifty-nine healthy controls were assessed at three time points to evaluate the test-retest reliability of Miro Health scores. Reliability was quantified with the scores’ intraclass correlations. Learning effects were measured as trends. In addition, a machine learning algorithm combined Miro Health variable scores into a Risk Score designed to distinguish 65 healthy controls (HC), 38 MCI participants (21 amnestic MCI (aMCI), and 17 non-amnestic MCI (naMCI)).ResultsSignificant correlations of Miro Health variables with legacy neuropsychological test variables were observed. Longitudinal studies show agreement of subsequent measurements and minimal learning effects. The Risk Score distinguished aMCI from healthy controls with an Area Under the Receiver Operator Curve (AUROC) of 0.97; the naMCI participants and controls were separated with an AUROC of 0.80, and the combined MCI group (aMCI + naMCI) was separated from healthy controls with an AUROC of 0.89.ConclusionMiro Health includes valid and reliable versions of variable scores that are analogous to legacy neuropsychological variable scores and a machine-learning derived risk score that effectively distinguishes HCs and individuals with MCI.
An 8-DNA methylation signature predicts recurrence risk of cervical cancer
Authors: Ma Jing-Hang , Huang Yu , Liu Lu-Yao , Feng Zhen 
Published: April 2021

AbstractPurposeCervical cancer is the leading cause of cancer-associated mortalities in female worldwide. DNA methylation have been demonstrated to have a regulatory role in the progression and could be novel biomarkers to predict the recurrence of the disease.MethodsDNA methylation and RNA expression data of cervical cancer were downloaded from TCGA. DMGs and DEGs were screened and extracted by correlation analysis. The SVM-based recurrence prediction model was established using the selected DMGs. Cox regression analysis and ROC analysis were used as self-evaluations. The GEO database was applied for external validation. Functional enrichment was determined by GO and KEGG analysis.ResultsThe eight-DNA methylation signature could identify patients with a high risk of recurrence (AUC=0.833). The SVM score was an independent risk factor for recurrence (HR = 0.418; 95% CI: 0.26-0.67, p-value <0.05). The independent GEO database further supported the result.ConclusionThe predictive function of the 8-DNA methylation signature for recurrence of cervical cancer was revealed in this study, which may help identify high-risk patients of recurrence and benefit the clinical treatment.
Modelling digital and manual contact tracing for COVID-19 Are low uptakes and missed contacts deal-breakers?
Authors: Rusu Andrei , Farrahi Katayoun , Emonet Rémi 
Published: May 2021

ABSTRACTComprehensive testing schemes, followed by adequate contact tracing and isolation, represent the best public health interventions we can employ to reduce the impact of an ongoing epidemic when no or limited vaccines are available and the implications of a full lockdown are to be avoided. However, the process of tracing can prove feckless for highly-contagious viruses such as SARS-Cov-2. The interview-based approaches often miss contacts and involve significant delays, while digital solutions can suffer from insufficient adoption rates or inadequate usage patterns. Here we present a novel way of modelling different contact tracing strategies using a generalizedmulti-site mean-fieldmodel, which can naturally assess the impact of both manual and digital approaches. Our methodology can readily be applied to any compartmental formulation, thus enabling the study of several complex pathogens. We use this technique to simulate a new epidemiological model, SEIR-T, and show that, given the right conditions, tracing in a COVID-19 epidemic can be effective even when digital uptakes are sub-optimal or interviewers miss a fair proportion of the contacts.
An Aerobic Anoxygenic Phototrophic Bacterium Fixes CO2via the Calvin-Benson-Bassham Cycle
Authors: Tang Kai , Liu Yang , Zeng Yonghui , Feng Fuying , Jin Ke , Yuan Bo 
Published: April 2021

AbstractAerobic anoxygenic phototrophic bacteria (AAnPB) are photoheterotrophs, which use light as auxiliary energy and require organic carbon (OC) for growth. Herein, we report the unusual strain B3, which is a true AAnPB because it requires oxygen for growth, harbours genes forcbb3- andbd-type cytochromes andacsF, and produces bacteriochlorophyll. The B3 genome encodes the complete metabolic pathways for AAnPB light utilization, CO2fixation via Calvin-Benson-Bassham (CBB) cycle and oxidation of sulfite and H2, and the transcriptome indicated that all components of these pathways were fully transcribed. Expression of the marker genes related to photosynthesis, includingpufM for light harnessing andrbcL for CO2fixation, and the activity of RubisCO, the key enzyme in the Calvin-Benson-Bassham (CBB) cycle, increased in response to decreased OC supply. Large amounts of cell biomass were obtained in liquid BG11 medium under illumination. The strain thus likely photoautotrophically grows using sulfite or H2as an electron donor. Similar GC contents between photosynthesis, the CBB cycle and 16S rRNA genes and the consistency of their phylogenetic topologies implied that light harnessing and carbon fixation genes evolved vertically from an anaerobic phototrophic ancestor of Rhodospirillaceae in Alphaproteobacteria. In conclusion, strain B3 represents a novel AAnPB characterized by photoautotrophy using the CBB cycle. This kind of AAnPB may be ecologically significant in the global carbon cycle.
The predictive potential of key adaptation parameters and proxy fitness traits between benign and stressful thermal environments
Authors: Cocciardi Jennifer M. , O’Brien Eleanor K. , Hoskin Conrad J. , Stoetzel Henry , Higgie Megan 
Published: April 2021

AbstractUnderstanding the adaptive potential of a species is key when predicting whether a species can contend with climate change. Adaptive capacity depends on the amount of genetic variation within a population for relevant traits. However, genetic variation changes in different environments, making it difficult to predict whether a trait will respond to selection when not measured directly in that environment. Here, we investigated how genetic variances, and phenotypic and genetic covariances, between a fitness trait and morphological traits changed between thermal environments in two closely-relatedDrosophila. If morphological traits strongly correlate with fitness, they may provide an easy-to-measure proxy of fitness to aid in understanding adaptation potential. We used a parent-offspring quantitative genetic design to test the effect of a benign (23°C) and stressful (28°C) thermal environment on genetic variances of fecundity and wing size and shape, and their phenotypic and genetic covariances. We found genetic variances were higher within the stressful environment for fecundity but lower within the stressful environment for wing size. We did not find evidence for significant phenotypic correlations. Phenotypic and genetic correlations did not reveal a consistent pattern between thermal environmentsorwithin or between species. This corroborates previous research and reiterates that conclusions drawn in one environment about the adaptive potential of a trait, and the relationship of that trait with fitness, cannot be extrapolated to other environmentsorwithin or between closely-related species. This confirms that researchers should use caution when generalising findings across environments in terms of genetic variation and adaptive potential.
The molecular structure and surface accumulation dynamics of hyaluronan at the water/air interface
Authors: Moll Carolyn J. , Giubertoni Giulia , Versluis Jan , Koenderink Gijsje H. , Bakker Huib J. 
Published: April 2021

AbstractHyaluronan is a biopolymer that is essential for many biological processes in the human body, like the regulation of tissue lubrication and inflammatory responses. Here we study the behavior of hyaluronan at aqueous surfaces using heterodyne-detected vibrational sum-frequency generation spectroscopy (HD-VSFG). We find that high-molecular weight hyaluronan (>1 MDa) does not come to the surface, even hours after addition of the polymer to the aqueous solution. In contrast, low-molecular weight hyaluronan (~150 kDa) gradually covers the water-air interface within hours, leading to a negatively charged surface and a reorientation of the interfacial water molecules. This strong dependence on the polymer molecular weight can be explainend from entanglements of the hyaluronan polymers. We also find that the migration kinetics of hyaluronan in aqueous media shows an anomalous dependence on the pH of the solution, which can be explained from the interplay of hydrogen-bonding and electrostatic interactions of the hyaluronan polymers.
Increased signal to noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components
Authors: Berry Jeffrey C. , Qi Mingsheng , Sonawane Balasaheb V. , Sheflin Amy , Cousins Asaph B. , Prenni Jessica , Schachtman Daniel P. , Liu Peng , Bart Rebecca S. 
Published: April 2021

ABSTRACTEnvironmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create micro-treatments throughout the field. To make matters worse, the variation within different soil properties is often non-randomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a tool with which sources of environmental variation in field data can be identified and removed, improving our ability to resolve effects of interest and to quantify subtle phenotypes.IMPORTANCEData from field experiments are notoriously noisy. Proper field designs with high replication aid in mitigating this challenge, yet true biological correlations are still often masked by environmental variability. This work identifies soil property composition as a spatially distributed source of variance to three types of characteristics: plant phenotype, microbiome composition, and leaf traits. We show that once identified, spatial principal component regression was able to account for these effects so that more precise estimates of experimental factors were obtained. This generalizable method is applicable to diverse field experiments.
Nucleosome induced homology recognition in chromatin
Authors: Hedley Jonathan G. , Teif Vladimir B. , Kornyshev Alexei A. 
Published: April 2021

ABSTRACTOne of the least understood properties of chromatin is the ability of its similar regions to recognise each other through weak interactions. Theories based on electrostatic interactions between helical macromolecules suggest that the ability to recognize sequence homology is an innate property of the non-ideal helical structure of DNA. However, this theory does not account for nucleosomal packing of DNA. Can homologous DNA sequences recognize each other while wrapped up in the nucleosomes? Can structural homology arise at the level of nucleosome arrays? Here we present a theoretical investigation of the recognition-potential-well between chromatin fibers sliding against each other. This well is different to the one predicted and observed for bare DNA; the minima in energy do not correspond to literal juxtaposition, but are shifted by approximately half the nucleosome repeat length. The presence of this potential-well suggests that nucleosome positioning may induce mutual sequence recognition between chromatin fibers and facilitate formation of chromatin nanodomains. This has implications for nucleosome arrays enclosed between CTCF-cohesin boundaries, which may form stiffer stem-like structures instead of flexible entropically favourable loops. We also consider switches between chromatin states, e.g., through acetylation/deacetylation of histones, and discuss nucleosome-induced recognition as a precursory stage of genetic recombination.
Reconstitution of prenyltransferase activity on nanodiscs by components of the rubber synthesis machinery of the Para rubber tree and guayule
Authors: Kuroiwa Fu , Nishino Akira , Mandal Yasuko , Suenaga-Hiromori Miki , Suzuki Kakeru , Takani Yukie , Miyagi-Inoue Yukino , Yamaguchi Haruhiko , Yamashita Satoshi , Takahashi Seiji , Tozawa Yuzuru 
Published: April 2021

AbstractPrenyltransferases mediate the biosynthesis of various types of polyisoprene compound in living organisms. Natural rubber (NR) of the Para rubber tree (Hevea brasiliensis) is synthesized as a result of prenyltransferase activity, with the proteins HRT1, HRT2, and HRBP having been identified as candidate components of the rubber biosynthetic machinery. To clarify the contribution of these proteins to prenyltransferase activity, we established a cell-free translation system for nanodisc-based protein reconstitution and measured the enzyme activity of the protein-nanodisc complexes. Cell-free synthesis of HRT1, HRT2, and HRBP in the presence of asolectin nanodiscs revealed that all three proteins were membrane associated. A complex of HRT1 and HRBP formed as a result of co-expression of the two proteins in the presence of nanodiscs manifested marked polyisoprene synthesis activity, whereas neither HRT1, HRT2, or HRBP alone nor a complex of HRT2 and HRBP exhibited such activity. Similar analysis of guayule (Parthenium argentatum) proteins revealed that three HRT1 homologs (CPT1–3) manifested prenyltransferease activity only if co-expressed with the homolog of HRBP (CBP). Our results thus indicate that the core prenyltransferase of the rubber biosynthetic machinery of both the Para rubber tree and guayule is formed by the assembly of heterologous subunits (HRT1 and HRBP in the former species).
Tissue-specific metabolic reprogramming during wound inducedde novoorgan formation in tomato hypocotyl explants
Authors: Larriba Eduardo , García Ana Belén Sánchez , Martínez-Andújar Cristina , Albacete Alfonso , Pérez-Pérez José Manuel 
Published: April 2021

SUMMARYPlants have remarkable regenerative capacity, which allows them to survive tissue damaging after biotic and abiotic stress. Some of the key transcription factors and the hormone crosstalk involved in wound-induced organ regeneration have been extensively studied in the model plantArabidopsis thaliana. However, little is known about the role of metabolism in wound-induced organ regeneration.Here, we performed detailed transcriptome analysis and targeted metabolomics approach duringde novoorgan formation in tomato hypocotyl explants and found tissue-specific metabolic differences and divergent developmental pathways after wounding.Our results indicate that callus growth in the apical region of the hypocotyl depends on a specific metabolic switch involving the upregulation of the photorespiratory pathway and the differential regulation of photosynthesis-related genes and of the gluconeogenesis pathway.The endogenous pattern of ROS accumulation in the apical and basal region of the hypocotyl during the time-course were dynamically regulated, and contributed to tissue-specific wound-induced regeneration.Our findings provide a useful resource for further investigation on the molecular mechanisms involved in wound-induced organ formation in a crop species such as tomato.One-sentence SummaryMetabolic switch during wound-induced regeneration
Gonococcal invasion into epithelial cells depends on both cell polarity and ezrin
Authors: Yu Qian , Wang Liang-Chun , Stein Daniel C. , Song Wenxia 
Published: April 2021

AbstractNeisseria gonorrhoeae(GC) establishes symptomatic infection in women from the cervix, lined with heterogeneous epithelial cells from non-polarized stratified at the ectocervix to polarized columnar at the endocervix. We have previously shown that GC differentially colonize and transmigrate across the ecto and endocervical epithelia. However, whether and how GC invade into heterogeneous cervical epithelial cells is unknown. This study examined GC entry of epithelial cells with various properties, using human cervical tissue explant and non-polarized/polarized epithelial cell line models. While adhering to non-polarized and polarized epithelial cells at similar levels, GC invaded into non-polarized more efficiently than polarized epithelial cells. The enhanced GC invasion in non-polarized epithelial cells was associated with increased ezrin phosphorylation, F-actin and ezrin recruitment to GC adherent sites, and the elongation of GC-associated microvilli. Inhibition of ezrin phosphorylation inhibited F-actin and ezrin recruitment and microvilli elongation, leading to a reduction in GC invasion. The reduced GC invasion in polarized epithelial cells was associated with non-muscle myosin II-mediated F-actin disassembly and microvilli ablation at GC adherence sites. Surprisingly, intraepithelial GC were only detected inside epithelial cells shed from the cervix, but neither in the ectocervix nor the endocervix, by immunofluorescence microscopy. We observed similar ezrin and F-actin recruitment in exfoliated cervical epithelial cells but not in those that remained in the ectocervical epithelium, as the luminal layer of ectocervical epithelial cells expressed ten-fold lower levels of ezrin than those beneath. However, GC inoculation induced F-actin reduction and myosin recruitment in the endocervix, similar to what was seen in polarized epithelial cells. Thus, polarized expression of ezrin at the apical surface of epithelial cells inhibits GC invasion, while non-polarized expression of ezrin promotes GC invasion by driving actin accumulation and microvilli elongation.
Can Hypnotic Susceptibility be Explained by Bifactor Models? Structural Equation Modeling of the Harvard Group Scale of Hypnotic Susceptibility - Form A
Authors: Zahedi Anoushiravan , Sommer Werner 
Published: April 2021

AbstractIndividuals differ in their responsiveness to hypnotic suggestions. However, defining and measuring hypnotizability is contentious because standardized scales, such as the Harvard group scale (HGSHS:A), measure a mixture of general suggestibility and its alteration due to hypnotic induction (hypnotizability). Exploratory factor analyses (FA) of standardized scales indicated their multidimensionality; however, the number and nature of latent factors are debated. We applied Confirmatory FA to the HGSHS:A scores of 477 volunteers and tested several theory-driven models. Scores were best explained by a bifactor model consisting of a G-factor and three correlated minor factors. The presented bifactor model shows that two sources of variability affect HGSHS:A simultaneously. Structural equation modeling revealed that the challenge-ideomotor factor predicts the other two minor factors, implying these suggestions might require more fundamental processes than other types. These results demonstrate the multifaceted and bifactorial structure of hypnotic suggestibility and underscore the desideratum for developing more differentiated scales.
Testing covariance models for MEG source reconstruction of hippocampal activity
Authors: O’Neill George C. , Barry Daniel N. , Tierney Tim M. , Mellor Stephanie , Maguire Eleanor A. , Barnes Gareth R. 
Published: April 2021

AbstractBeamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to distinguish between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral.
DNA methylation affects pre-mRNA transcriptional initiation and processing in Arabidopsis
Authors: Li Qiuhui , Chen Shengjie , Leung Amy Wing-Sze , Liu Yaqin , Xin Yan , Zhang Li , Lam Hon-Ming , Luo Ruibang , Zhang Shoudong 
Published: April 2021

AbstractBackgroundDNA methylation may regulate pre-mRNA transcriptional initiation and processing, thus affecting gene expression. Unlike animal cells, plants, especiallyArabidopsis thaliana, have relatively low DNA methylation levels, limiting our ability to observe any correlation between DNA methylation and pre-mRNA processing using typical short-read sequencing. However, with newly developed long-read sequencing technologies, such as Oxford Nanopore Technology Direct RNA sequencing (ONT DRS), combined with whole-genome bisulfite sequencing, we were able to precisely analyze the relationship between DNA methylation and pre-mRNA transcriptional initiation and processing using DNA methylation-related mutants.ResultsUsing ONT DRS, we generated more than 2 million high-quality full-length long reads of native mRNA for each of the wild type Col-0 and mutants defective in DNA methylation, identifying a total of 117,474 isoforms. We found that low DNA methylation levels around splicing sites tended to prevent splicing events from occurring. The lengths of the poly(A) tail of mRNAs were positively correlated with DNA methylation. DNA methylation before transcription start sites or around transcription termination sites tended to result in gene-silencing or read-through events.Furthermore, using ONT DRS, we identified novel transcripts that we could not have otherwise, since transcripts with intron retention and fusion transcripts containing the uncut intergenic sequence tend not to be exported to the cytoplasm. Using themet1-3mutant with activated constitutive heterochromatin regions, we confirmed the effects of DNA methylation on pre-mRNA processing.ConclusionThe combination of ONT DRS with whole-genome bisulfite sequencing was a powerful tool for studying the effects of DNA methylation on splicing site selection and pre-mRNA processing, and therefore regulation of gene expression.