bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovery of indole-modified aptamers for highly specific recognition of protein glycoforms
Authors: Yoshikawa Alex M. , Rangel Alexandra , Feagin Trevor , Chun Elizabeth M. , Wan Leighton , Li Anping , Moekl Leonhard , Eisenstein Michael , Pitteri Sharon , Soh H. Tom 
Published: March 2021

AbstractGlycosylation is one of the most abundant forms of post-translational modification, and can have a profound impact on a wide range of biological processes and diseases. Unfortunately, efforts to characterize such modifications in the context of basic and clinical research are severely hampered by the lack of affinity reagents that can differentiate protein glycoforms. This lack of reagents is largely due to the challenges associated with generating affinity reagents that can bind to particular glycan epitopes with robust affinity and specificity. In this work, we use a fluorescence-activated cell sorting (FACS)-based approach to generate and screen aptamers with indole-modified bases in an effort to isolate reagents that can differentiate between protein glycoforms. Using this approach, we were able to select multiple aptamers that exhibit strong selectivity for specific glycoforms of two different proteins, with the capacity to discriminate between molecules with identical tertiary structures that differ only in terms of their glycan modifications.
MCKAT, a multi-dimensional copy number variant kernel association test
Authors: Esfahani Nastaran Maus , Catchpoole Daniel , Khan Javed , Kennedy Paul J. 
Published: March 2021

AbstractBackgroundCopy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia.Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods.ResultsWe address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets.ConclusionA multi-dimensional copy number variant kernel association test can detect significantly associated CNVs with any disease-related trait. MCKAT can help biologists detect significantly associated CNVs with any disease-related trait across a patient group instead of examining the CNVs case by case in each subject.
Gene duplications and phylogenomic conflict underlie major pulses of phenotypic evolution in gymnosperms
Authors: Stull Gregory W. , Qu Xiao-Jian , Parins-Fukuchi Caroline , Yang Ying-Ying , Yang Jun-Bo , Yang Zhi-Yun , Hu Yi , Ma Hong , Soltis Pamela S. , Soltis Douglas E. , Li De-Zhu , Smith Stephen A. , Yi Ting-Shuang 
Published: March 2021

AbstractInferring the intrinsic and extrinsic drivers of species diversification and phenotypic disparity across the Tree of Life is a major challenge in evolutionary biology. In green plants, polyploidy (or whole-genome duplication, WGD) is known to play a major role in microevolution and speciation1, but the extent to which WGD has shaped macroevolutionary patterns of diversification and phenotypic innovation across plant phylogeny remains an open question. Here we examine the relationship of various facets of genomic evolution—including gene and genome duplication, genome size, and chromosome number—with macroevolutionary patterns of phenotypic innovation, species diversification, and climatic occupancy in gymnosperms. We show that genomic changes, such as WGD and genome-size shifts, underlie the origins of most major extant gymnosperm clades, and notably our results support an ancestral WGD in the gymnosperm lineage. Spikes of gene duplication typically coincide with major spikes of phenotypic innovation, while increased rates of phenotypic evolution are typically found at nodes with high gene-tree conflict, representing historic population-level dynamics during speciation. Most shifts in gymnosperm diversification since the rise of angiosperms are decoupled from putative WGDs and instead are associated with increased rates of climatic occupancy evolution, particularly in cooler and/or more arid climatic conditions, suggesting that ecological opportunity, especially in the later Cenozoic, and environmental heterogeneity have driven a resurgence of gymnosperm diversification. Our study provides critical insight on the processes underlying diversification and phenotypic evolution in gymnosperms, with important broader implications for the major drivers of both micro- and macroevolution in plants.
A General LSTM-based Deep Learning Method for Estimating Neuronal Models and Inferring Neural Circuitry
Authors: Sheng Kaiwen , Qu Peng , Yang Le , Liu Xiaofei , He Liuyuan , Zhang Youhui , Ma Lei , Du Kai 
Published: March 2021

AbstractComputational neural models are essential tools for neuroscientists to study the functional roles of single neurons or neural circuits. With the recent advances in experimental techniques, there is a growing demand to build up neural models at single neuron or large-scale circuit levels. A long-standing challenge to build up such models lies in tuning the free parameters of the models to closely reproduce experimental recordings. There are many advanced machine-learning-based methods developed recently for parameter tuning, but many of them are task-specific or requires onerous manual interference. There lacks a general and fully-automated method since now. Here, we present a Long Short-Term Memory (LSTM)-based deep learning method, General Neural Estimator (GNE), to fully automate the parameter tuning procedure, which can be directly applied to both single neuronal models and large-scale neural circuits. We made comprehensive comparisons with many advanced methods, and GNE showed outstanding performance on both synthesized data and experimental data. Finally, we proposed a roadmap centered on GNE to help guide neuroscientists to computationally reconstruct single neurons and neural circuits, which might inspire future brain reconstruction techniques and corresponding experimental design. The code of our work will be publicly available upon acceptance of this paper.
Discovery of viral myosin genes with complex evolutionary history within plankton
Authors: Kijima Soichiro , Delmont Tom O. , Miyazaki Urara , Gaia Morgan , Endo Hisashi , Ogata Hiroyuki 
Published: March 2021

AbstractNucleocytoplasmic large DNA viruses (NCLDVs) infect diverse eukaryotes and form a group of viruses with capsids encapsulating large genomes. Recent studies are increasingly revealing a spectacular array of functions encoded in their genomes, including genes for energy metabolisms, nutrient uptake, as well as cytoskeleton. Here, we report the discovery of genes homologous to myosins, the major eukaryotic motor proteins previously unrecognized in the virosphere, in environmental genomes of NCLDVs from the surface of the oceans. Interestingly, these genes were often accompanied by kinesin genes in the environmental genomes, suggesting a role of these viral proteins in the intracellular viral particle transport. Phylogenetic analyses indicate that most viral myosins (named “virmyosins”) belong to theImiterviralesorder, except for one belonging to thePhycodnaviridaefamily. On the one hand, the phylogenetic positions of virmyosin-encodingImiterviralesare scattered within theImitervirales. On the other hand,Imiterviralesvirmyosin genes form a monophyletic group in the phylogeny of diverse myosin sequences. Furthermore, phylogenetic trends for the virmyosin genes and viruses containing them were incongruent. Based on these results, we argue that multiple transfers of myosin homologs have occurred not only from eukaryotes to viruses but also between viruses, supposedly during co-infections of the same host.
A Synthesis of the Many Errors and Learning Processes of Visuomotor Adaptation
Authors: Morehead J. Ryan , Orban de Xivry Jean-Jacques 
Published: March 2021

AbstractVisuomotor adaptation has one of the oldest experimental histories in psychology and neuroscience, yet its precise nature has always been a topic of debate. Here we offer a survey and synthesis of recent work on visuomotor adaptation that we hope will prove illuminating for this ongoing dialogue. We discuss three types of error signals that drive learning in adaptation tasks: task performance error, sensory prediction-error, and a binary target hitting error. Each of these errors has been shown to drive distinct learning processes. Namely, both target hitting errors and putative sensory prediction-errors drive an implicit change in visuomotor maps, while task performance error drives learning of explicit strategy use and non-motor decision-making. Each of these learning processes contributes to the overall learning that takes place in visuomotor adaptation tasks, and although the learning processes and error signals are independent, they interact in a complex manner. We outline many task contexts where the operation of these processes is counter-intuitive and offer general guidelines for their control, measurement and interpretation. We believe this new framework unifies several disparate threads of research in sensorimotor adaptation that often seem in conflict. We conclude by explaining how this more nuanced understanding of errors and learning processes could lend itself to the analysis of other types of sensorimotor adaptation, of motor skill learning, of the neural processing underlying sensorimotor adaptation in humans, of animal models and of brain computer interfaces.
Contrast adaptation improves spatial integration
Authors: Pinchuk-Yacobi Noga , Sagi Dov 
Published: March 2021

AbstractThe effects of contrast adaptation and contrast area summation were investigated using a contrast discrimination task. The task consisted of a target of variable size, and a pedestal with a fixed base contrast. Discrimination performance was examined for a condition in which the pedestal size was fixed, equal to the largest target size, and for a condition in which the pedestal size matched the target size and thus varied with it. Repeated performance of the task produced rapid within-session improvements for both conditions. For stimuli with a matching size of target and pedestal, the performance improved only for the larger targets, indicating the development of area summation, which was initially absent for these stimuli. However, the improvements were mostly temporary, and were not fully retained between subsequent sessions. The temporary nature of the sensitivity gains implies that they resulted, at least in part, from rapid adaptation to the stimulus contrast. We suggest that adaptation decorrelates and thus reduces the spatial noise generated by a high-contrast pedestal, leading to improved area summation and better contrast sensitivity. A decorrelation model successfully predicted our experimental results.
In-situ fiducial markers for 3D correlative cryo- fluorescence and FIB-SEM imaging
Authors: Scher Nadav , Rechav Katya , Paul-Gilloteaux Perrine , Avinoam Ori 
Published: March 2021

1.SummaryImaging of cells and tissues has improved significantly over the last decade. Dual-beam instruments with a focused ion beam mounted on a scanning electron microscope (FIB-SEM), which offer high-resolution 3D imaging of large volumes and fields-of-view are becoming widely used in the life sciences. FIB-SEM has most recently been implemented on fully hydrated, cryo-immobilized, biological samples. However, correlative light and electron microscopy (CLEM) workflows combining cryo-fluorescence microscopy (cryo-FM) and FIB-SEM are not yet commonly available. Here, we demonstrate that fluorescently labeled lipid droplets can serve asin-situfiducial markers for correlating cryo-FM and FIB-SEM datasets, and that this approach can be used to target the acquisition of large FIB-SEM stacks spanning tens of microns under cryogenic conditions. We also show that cryo-FIB-SEM imaging is particularly informative for questions related to organelle structure and inter-organellar contacts, nuclear organization and mineral deposits in cells.
The hidden effects of agrochemicals on plant metabolism and root-associated microorganisms
Authors: Cesco S. , Lucini L. , Miras-Moreno B. , Borruso L. , Mimmo T. , Pii Y. , Puglisi E. , Spini G. , Taskin E. , Tiziani R. , Zangrillo M. S. , Trevisan M. 
Published: March 2021

AbstractAgrochemicals are commonly used in agriculture to protect crops and ensure yields. Several of them are mobile within the plant and, being perceived as xenobiotics regardless of their protective/curative roles, they induce a reprogramming of secondary metabolism linked to the detoxification processes even in the absence of phenotype symptoms. Moreover, it is well documented that plants, thanks to the root exudation of different metabolites, are able to shape the microbial population at the rhizosphere and to significantly affect the processes occurring therein. Here we show that plant metabolic response to foliarly-applied pesticides is much broader than what previously thought and includes diverse and compound-specific hidden processes. Among others, stress-related metabolism and phytohormones profile underwent a considerable reorganization. Moreover, a distinctive microbial rearrangement of the rhizosphere was recorded following foliar application of pesticides. Such effects have unavoidably energetic and metabolic costs for the plant paving the way to both positive and negative aspects. The understanding of these effects is crucial for an increasingly sustainable use of pesticides in agriculture.HighlightThe foliar application of pesticides induces a broad metabolic reprogramming in plant and shapes the microbial population of the rhizosphere.
In VitroAssessment of Efficacy and Cytotoxicity ofPrunus africanaExtracts on Prostate Cancer C4-2 Cells
Authors: Asuzu Peace C. , Aryee Alberta N.A. , Trompeter Nicholas , Mann Yasmin , Besong Samuel A. , Duncan Randall L. , Cooper Carlton R. 
Published: March 2021

AbstractPhenolic compounds are products of secondary plant metabolism known for their biological activity including their antimicrobial, antioxidant, analgesic, stimulant, anti- carcinogenic, and aphrodisiac properties. The main objective of this study was to assess the potency/cytotoxic effects ofPrunus africanaextracts on prostate cancer cellsin vitro. Using different concentrations ofP. africanaextracts, prostate cancer C4-2 cells, a hormonally insensitive subline of LNCaP cells, were treated in a proliferation assay. A concentration dependent inhibition of cell growth in cells treated withP. africanabark and root extracts was present from days 1 through 3 of incubation, with the methanol extract of the bark showing the strongest effect. Compared to other plant parts, leaf extracts were significantly less cytotoxic at the same concentrations. As C4-2 cells are hormonally insensitive and designed to mimic advanced prostate cancer, crude extracts ofP. africanaare a possible treatment option, not only for hormone sensitive prostate cancer, but also advanced, hormonally insensitive prostate cancer.
Total number and ratio of GABAergic neuron types in the mouse lateral and basal amygdala
Authors: Vereczki Viktória K. , Müller Kinga , Krizsán Éva , Máté Zoltán , Fekete Zsuzsanna , Rovira-Esteban Laura , Veres Judit M. , Erdélyi Ferenc , Hájos Norbert 
Published: March 2021

AbstractGABAergic neurons are key circuit elements in cortical networks. In spite of growing evidence showing that inhibitory cells play a critical role in the lateral (LA) and basal (BA) amygdala functions, neither the number of GABAergic neurons nor the ratio of their distinct types have been determined in these amygdalar nuclei. Using unbiased stereology, we found that the ratio of GABAergic neurons in the BA (22 %) is significantly higher than in the LA (16 %) in both male and female mice. No difference was observed between the right and left hemispheres in either sexes. In addition, we assessed the ratio of the major inhibitory cell types in both amygdalar nuclei. Using transgenic mice and a viral strategy for visualizing inhibitory cells combined with immunocytochemistry, we estimated that the following cell types together compose the vast majority of GABAergic cells in the LA and BA: axo-axonic cells (5.5-6 %), basket cells expressing parvalbumin (17-20 %) or cholecystokinin (7-9 %), dendrite-targeting inhibitory cells expressing somatostatin (10-16 %), NPY-containing neurogliaform cells (14-15 %), VIP and/or calretinin-expressing interneuron-selective interneurons (29-38 %) and GABAergic projection neurons expressing somatostatin and neuronal nitric oxide synthase (nNOS, 5.5-8 %). Our results show that these amygdalar nuclei contain all major GABAergic neuron types as found in other cortical regions. Furthermore, our data offer an essential reference for future studies aiming to reveal changes in GABAergic cell number and in inhibitory cell types typically observed under different pathological conditions, and to model functioning amygdalar networks in health and disease.Significance statementGABAergic cells in cortical structures, like in the lateral and basal nucleus of the amygdala, have a determinant role in controlling circuit operation. In this study, we provide the first estimate for the total number of inhibitory cells in these two amygdalar nuclei. In addition, our study is the first to define the ratio of the major GABAergic cell types present in these cortical networks. Taking into account that hyper-excitability in the amygdala, arising from the imbalance between excitation and inhibition typifies many altered brain functions including anxiety, posttraumatic stress disorder, schizophrenia and autism, uncovering the number and ratio of distinct amygdalar inhibitory cell types offers a solid base for comparing the changes in inhibition in pathological brain states.
The obstacles and potential clues of prime editing applications in tomato, a dicot plant
Authors: Van Vu Tien , Kim Jihae , Das Swati , Lee Jinsu , Kim Jae-Yean 
Published: March 2021

ABSTRACTPrecision genome editing is highly desired for crop improvement. The recently emerged CRISPR/Cas technology offers great potential applications in precision plant genome engineering. A prime editing (PE) approach combining a reverse transcriptase (RT) with a Cas9 nickase and a “priming” extended guide RNA has shown a high frequency for precise genome modification in mammalian cells and several plant species. Nevertheless, the applications of the PE approach in dicot plants are still limited and inefficient. We designed and tested prime editors for precision editing of a synthetic sequence in a transient assay and for desirable alleles of 10 loci in tomato by stable transformation. Our data obtained by targeted deep sequencing also revealed only low PE efficiencies in both the tobacco and tomato systems. Further assessment of the activities of the PE components uncovered potential reasons for the inefficiency of the PE complexes. Modifying the pegRNA sequences by shortening or introducing mismatches to the primer binding sequences (PBS) in order to reduce their melting temperatures (Tm) did not enhance the PE efficiency at the SlBMP21, SlALC and SlALS1 loci. Our data show challenges of PE approach in tomato, indicating a further improvement of the PE system for the successful applications such as use of improved expression systems. Our work provides an important clue for the successful application of the PE approach in crop improvement.
In vitro and in vivo comparison of the MRI glucoCEST properties between native glucose and 3OMG in a murine tumor model
Authors: Anemone Annasofia , Capozza Martina , Arena Francesca , Zullino Sara , Bardini Paola , Terreno Enzo , Longo Dario Livio , Aime Silvio 
Published: March 2021

ABSTRACTPurposeD-Glucose and 3-O-Methyl-D-glucose (3OMG) have been shown to provide contrast in MRI-CEST images. However, a systematic comparison between these two molecules has not yet been performed. This study dealt with the assessment of the effect of pH, saturation power level (B1) and magnetic field strength (B0) on the MRI-CEST contrast with the aim of comparing thein vivoCEST contrast detectability of these two agents in the glucoCEST procedure.MethodsPhosphate buffered solutions of D-Glucose or 3OMG (20 mM) were prepared at different pH values and Z-spectra acquired at several B1levels and at 37°C.In vivoglucoCEST images were obtained at 3 T and 7 T over a period of 30 min after injection of D-Glucose or 3OMG (at the doses of 1.5 and 3 g/kg) in a murine melanoma tumour model.ResultsA markedly different pH dependence of CEST response was observed in vitro for D-Glucose and 3OMG. The glucoCEST contrast enhancement in the tumour region following the intravenous administration (at the dose 3 g/kg) resulted to be comparable for both the molecules: 1-2% at 3 T and 2-3% at 7 T. The ST% resulted almost constant for 3OMG over the 30 min period, whereas a significant increase in the case of D-Glucose was detected.ConclusionOur results show similar CEST contrast efficiency but different temporal kinetics for the metabolizable and the non-metabolizable glucose derivatives in tumour murine models when administered at the same doses.
The presentation, recognition and diagnosis of autism in women and girls
Authors: Driver Bethany , Chester Verity 
Published: March 2021

Purpose
Autistic women and girls have received comparatively less attention within clinical practice and research. Research suggests women tend to be diagnosed later than men, and are more likely to experience misdiagnosis.

Design/methodology/approach
This paper aims to report a narrative literature review that examines research on the presentation, recognition, and diagnosis of autistic women and girls.

Findings
Findings suggest that autistic females present differently to males and highlight low recognition of the female presentation of autism among the general public, in social spheres, educational, clinical and forensic settings. This lack of recognition appears to affect the likelihood of females being referred for diagnosis, the reliability of diagnostic assessments and subsequent access to support.

Originality/value
Recommendations for clinical practice focus on initiatives to increase awareness of the female presentation of autism, improving the diagnostic process for females, increasing female representation within autism training and for future research to support these goals.