bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developmental coupling of cerebral blood flow and fMRI fluctuations in youth
Authors: Baller Erica B. , Valcarcel Alessandra M. , Adebimpe Azeez , Alexander-Bloch Aaron , Cui Zaixu , Gur Ruben C. , Gur Raquel E. , Larsen Bart L. , Linn Kristin A. , O’Donnell Carly M. , Pines Adam R. , Raznahan Armin , Roalf David. R. , Sydnor Valerie J. , Tapera Tinashe M. , Dylan Tisdall M. , Vandekar Simon , Xia Cedric H. , Detre John A. , Shinohara Russell T. , Satterthwaite Theodore D. 
Published: July 2021

ABSTRACTTo support brain development during youth, the brain must balance energy delivery and consumption. Previous studies in adults have demonstrated high coupling between cerebral blood flow and brain function as measured using functional neuroimaging, but how this relationship evolves over adolescence is unknown. To address this gap, we studied a sample of 831 children and adolescents (478 females, ages 8-22) from the Philadelphia Neurodevelopmental Cohort who were scanned at 3T with both arterial spin labeled (ASL) MRI and resting-state functional MRI (fMRI). Local coupling between cerebral blood flow (CBF, from ASL) and the amplitude of low frequency fluctuations (ALFF, from fMRI) was first quantified using locally weighted regressions on the cortical surface. We then used generalized additive models to evaluate how CBF-ALFF coupling was associated with age, sex, and executive function. Enrichment of effects within canonical functional networks was evaluated using spin-based permutation tests. Our analyses revealed tight CBF-ALFF coupling across the brain. Whole-brain CBF-ALFF coupling decreased with age, largely driven by coupling decreases in the inferior frontal cortex, precuneus, visual cortex, and temporoparietal cortex (pfdr <0.05). Females had stronger coupling in the frontoparietal network than males (pfdr <0.05). Better executive function was associated with decreased coupling in the somatomotor network (pfdr <0.05). Overall, we found that CBF-ALFF coupling evolves in development, differs by sex, and is associated with individual differences in executive function. Future studies will investigate relationships between maturational changes in CBF-ALFF coupling and the presence of psychiatric symptoms in youth.SIGNIFICANCEThe functions of the human brain are metabolically expensive and reliant on coupling between cerebral blood flow and neural activity. Previous neuroimaging studies in adults demonstrate tight physiology-function coupling, but how this coupling evolves over development is unknown. Here, we examine the relationship between blood flow as measured by arterial spin labeling and the amplitude of low frequency fluctuations from resting-state magnetic resonance imaging across a large sample of youth. We demonstrate regionally specific changes in coupling over age and show that variations in coupling are related to biological sex and executive function. Our results highlight the importance of CBF-ALFF coupling throughout development; we discuss its potential as a future target for the study of neuropsychiatric diseases.
Transgenic expression of Nix converts genetic females into males and allows automated sex sorting in Aedes albopictus
Authors: Lutrat Célia , Olmo Roenick P. , Baldet Thierry , Bouyer Jérémy , Marois Eric 
Published: July 2021

AbstractAedes albopictus is a major vector of arboviruses. Better understanding of its sex determination is crucial for developing mosquito control tools, especially genetic sexing strains. In Aedes aegypti, Nix is the primary gene responsible for masculinization and Nix-expressing genetic females develop into fertile, albeit flightless, males. In Ae. albopictus, Nix has also been implicated in masculinization but its role remains to be further characterized.In this work, we established Ae. albopictus transgenic lines ectopically expressing Nix. Several were composed exclusively of genetic females, with transgenic individuals being phenotypic and functional males due to the expression of the Nix transgene. Their reproductive fitness was marginally impaired, while their flight performance was similar to controls. Overall, our results show that Nix is sufficient for full masculinization in Ae. albopictus. Moreover, the transgene construct contains a fluorescence marker allowing efficient automated sex sorting. Consequently, such strains constitute valuable sexing strains for genetic control.
Pharmacokinetics and biodistribution of extracellular vesicles administered intravenously and intranasally to Macaca nemestrina
Authors: Driedonks Tom , Jiang Linglei , Carlson Bess , Han Zheng , Liu Guanshu , Queen Suzanne E. , Shirk Erin N. , Gololobova Olesia , Nyberg Lyle H. , Lima Gabriela , Paniushkina Liliia , Garcia-Contreras Marta , Schonvisky Kayla , Castell Natalie , Stover Mitchel , Guerrero-Martin Selena , Richardson Riley , Smith Barbara , Mahairaki Vasiliki , Lai Charles P. , Izzi Jessica M. , Hutchinson Eric K. , Pate Kelly A.M. , Witwer Kenneth W. 
Published: July 2021

AbstractExtracellular vesicles (EVs) have great potential as novel drug carriers for the treatment of various diseases. These lipid bilayer vesicles are naturally abundant in mammalian tissues and circulation, can be loaded with therapeutic small molecule drugs, (si)RNA, proteins and CRISPR/Cas9, and may be engineered for retention by specific tissues. However, many questions remain on the optimal dosing, administration route, and pharmacokinetics of EVs. Previous studies have addressed biodistribution and pharmacokinetics in rodents, but little evidence is available from larger animals. Here, we investigated the pharmacokinetics and biodistribution of Expi293F-derived EVs labelled with a highly sensitive nanoluciferase reporter (palmGRET) in a non-human primate model (Macaca nemestrina), comparing intravenous (IV) and intranasal (IN) administration over a 125-fold dose range. We report that EVs administered IV had markedly longer circulation times in plasma than previously reported in mice, and were detectable in cerebrospinal fluid (CSF) after 30-60 minutes. Already after one minute following IV administration, we observed EV uptake by PBMCs, most notably B-cells. EVs were detected in liver and spleen within one hour of IV administration. None of the IN doses resulted in readily detectable EV levels in plasma, CSF, or organs, suggesting that IN delivery of EVs in large animals including humans may require reconsideration or pretreatment approaches. Furthermore, EV circulation times strongly decreased after repeated IV administration, possibly due to immune responses and with clear implications for xenogeneic EV-based therapeutics. We hope that our findings from this baseline study in macaques will help to inform future research and therapeutic development of EVs.
Keratin 19 interacts with GSK3β to regulate its nuclear accumulation and degradation of cyclin D3
Authors: Sharma Pooja , Tiufekchiev Sarah , Lising Victoria , Chung Seung Woo , Suk Jung Soo , Chung Byung Min 
Published: July 2021

AbstractCyclin D3 regulates the G1/S transition and is frequently overexpressed in several cancer types including breast cancer, where it promotes tumor progression. Here, we show that a cytoskeletal protein keratin 19 (K19) physically interacts with a serine/threonine kinase GSK3β and prevents GSK3β-dependent degradation of cyclin D3. The absence of K19 allowed active GSK3β to accumulate in the nucleus and degrade cyclin D3. Specifically, the head domain of K19 was required to sustain inhibitory phosphorylation of GSK3β Ser9, prevent nuclear accumulation of GSK3β, and maintain cyclin D3 levels and cell proliferation. K19 was found to interact with GSK3β and K19-GSK3β interaction was mapped out to require Ser10 and Ser35 residues on the head domain of K19. Unlike wildtype K19, S10A and S35A mutants failed to maintain total and nuclear cyclin D3 levels and induce cell proliferation. Finally, we show that the K19-GSK3β-cyclin D3 pathway affected sensitivity of cells towards inhibitors to cyclin dependent kinase 4 and 6 (CDK4/6). Overall, these findings establish a role for K19 in the regulation of GSK3β-cyclin D3 pathway and demonstrate a potential strategy for overcoming resistance to CDK4/6 inhibitors.
Prediction of DNA from context using neural networks
Authors: Grønbæk Christian , Liang Yuhu , Elliott Desmond , Krogh Anders 
Published: July 2021

AbstractOne way to better understand the structure in DNA is by learning to predict the sequence. Here, we train a model to predict the missing base at any given position, given its left and right flanking contexts.Our best-performing model is a neural network that obtains an accuracy close to 54% on the human genome, which is 2% points better than modelling the data using a Markov model. In likelihood-ratio tests, we show that the neural network is significantly better than any of the alternative models by a large margin. We report on where the accuracy is obtained, observing first that the performance appears to be uniform over the chromosomes. The models perform best in repetitive sequences, as expected, although they are far from random performance in the more difficult coding sections, the proportions being ~ 70:40%. Exploring further the sources of the accuracy, Fourier transforming the predictions reveals weak but clear periodic signals. In the human genome the characteristic periods hint at connections to nucleosome positioning. To understand this we find similar periodic signals in GC/AT content in the human genome, which to the best of our knowledge have not been reported before.On other large genomes similarly high accuracy is found, while lower predictive accuracy is observed on smaller genomes. Only in mouse did we see periodic signals in the same range as in human, though weaker and of different type. Interestingly, applying a model trained on the mouse genome to the human genome results in a performance far below that of the human model, except in the difficult coding regions.Despite the clear outcomes of the likelihood ratio tests, there is currently a limited superiority of the neural network methods over the Markov model. We expect, however, that there is great potential for better modelling DNA using different neural network architectures.
Mitochondria dysfunction in Charcot Marie Tooth 2B Peripheral Sensory Neuropathy
Authors: Gu Yingli , Guerra Flora , Hu Mingzheng , Pope Alexander , Sung Kijung , Yang Wanlin , Jetha Simone , Shoff Thomas A. , Gunatilake Tessanya , Dahlkamp Owen , Shi Linda Zhixia , Manganelli Fiore , Nolano Maria , Zhou Yue , Ding Jianqing , Bucci Cecilia , Wu Chengbiao 
Published: July 2021

AbstractRecent evidence has uncovered an important role of Rab7 in regulating mitochondrial morphology and function. Missense mutation(s) of Rab7 underlies the pathogenesis of Charcot Marie Tooth 2B (CMT2B) peripheral neuropathy. Herein, we investigated how mitochondrial morphology and function were impacted by the CMT2B associated Rab7V162M mutation in fibroblasts from human CMT2B patients as well as in a knockin mouse model. In contrast to recently published results from studies of using heterologous overexpression systems, our results have demonstrated significant mitochondrial fragmentation in fibroblasts of both human CMT2B patients and CMT2B mouse embryonic fibroblasts (MEFs). Furthermore, we have shown that mitochondria were fragmented and axonal mitochondrial movement was dysregulated in primary cultured E18 dorsal root ganglion (DRG) sensory neurons, but not in E18 hippocampal and cortical primary neurons. We also show that inhibitors to either the mitochondrial fission protein Drp1 or to the nucleotide binding to Rab7 normalized the mitochondrial deficits in both MEFs and E18 cultured DRG neurons. Our study has revealed, for the first time, that expression of CMT2B Rab7 mutation at physiological level enhances Drp1 activity to promote mitochondrial fission, that may potentially underlie selective vulnerability of peripheral sensory neurons in CMT2B pathogenesis.
Full-length, single-cell RNA-sequencing of human bone marrow subpopulations reveals hidden complexity
Authors: Schmidt Marcel O. , Mays Anne Deslattes , Barefoot Megan E. , Riegel Anna T. , Wellstein Anton 
Published: July 2021

AbstractBone marrow progenitor cell differentiation has frequently been used as a model for studying cellular plasticity and cell-fate decisions. Recent analysis at the level of single-cells has expanded knowledge of the transcriptional landscape of human hematopoietic cell lineages. Using single-molecule real-time (SMRT) full-length RNA sequencing, we have previously shown that human bone marrow lineage-negative (Lin-neg) cell populations contain a surprisingly diverse set of mRNA isoforms. Here, we report from single cell, full-length RNA sequencing that this diversity is also reflected at the single-cell level. From fresh human bone marrow unselected and lineage-negative progenitor cells were isolated by droplet-based single-cell selection (10xGenomics). The single cell-derived mRNAs were analyzed by full-length SMRT and short-read sequencing. In both samples we detected an average of 8000 different genes using short-read sequencing. Differential expression analysis arranged the single-cells of the total bone marrow into only four clusters whereas the Lin-neg population was much more diverse with nine clusters. mRNA isoform analysis of the single-cell populations using full-length sequencing revealed that Lin-neg cells contain on average 24% more novel splice variants than the total bone marrow cells. Interestingly, among the most frequent genes expressing novel isoforms were members of the spliceosome, e.g. HNRNPs, DEAD box helicases and SRSFs. Mapping the isoforms from all genes to the cell type clusters revealed that total bone marrow cells express novel isoforms only in a small subset of clusters. On the other hand, lineage-negative progenitor cells expressing novel isoforms were present in nearly all subpopulations. In conclusion, on a single-cell level lineage-negative cells express a higher diversity of genes and more alternatively spliced novel isoforms suggesting that cells in this subpopulation are poised for different fates.Graphical abstract
Machine learning uncovers a data-driven transcriptional regulatory network for the Crenarchaeal thermoacidophile Sulfolobus acidocaldarius
Authors: Chauhan Siddharth M. , Poudel Saugat , Rychel Kevin , Lamoureux Cameron , Yoo Reo , Bulushi Tahani Al , Yuan Yuan , Palsson Bernhard O. , Sastry Anand V. 
Published: July 2021

AbstractDynamic cellular responses to environmental constraints are coordinated by the transcriptional regulatory network (TRN), which modulates gene expression. This network controls most fundamental cellular responses, including metabolism, motility, and stress responses. Here, we apply independent component analysis, an unsupervised machine learning approach, to 95 high-quality Sulfolobus acidocaldarius RNA-seq datasets and extract 45 independently modulated gene sets, or iModulons. Together, these iModulons contain 755 genes (32% of the genes identified on the genome) and explain over 70% of the variance in the expression compendium. We show that 5 modules represent the effects of known transcriptional regulators, and hypothesize that most of the remaining modules represent the effects of uncharacterized regulators. Further analysis of these gene sets results in: (1) the prediction of a DNA export system composed of 5 uncharacterized genes, (2) expansion of the LysM regulon, and (3) evidence for an as-yet-undiscovered global regulon. Our approach allows for a mechanistic, systems-level elucidation of an extremophile’s responses to biological perturbations, which could inform research on gene-regulator interactions and facilitate regulator discovery in S. acidocaldarius. We also provide the first global TRN for S. acidocaldarius. Collectively, these results provide a roadmap towards regulatory network discovery in archaea.
Using Bayesian Inference to Estimate Plausible Muscle Forces in Musculoskeletal Models
Authors: Johnson Russell T. , Lakeland Daniel , Finley James M. 
Published: July 2021

AbstractBackgroundMusculoskeletal modeling is currently a preferred method for estimating the muscle forces that underlie observed movements. However, these estimates are sensitive to a variety of assumptions and uncertainties, which creates difficulty when trying to interpret the muscle forces from musculoskeletal simulations. Here, we describe an approach that uses Bayesian inference to identify plausible ranges of muscle forces for a simple motion while representing uncertainty in the measurement of the motion and the objective function used to solve the muscle redundancy problem.MethodsWe generated a reference elbow flexion-extension motion by simulating a set of muscle excitation signals derived from the computed muscle control tool built into OpenSim. We then used a Markov Chain Monte Carlo (MCMC) algorithm to sample from a posterior probability distribution of muscle excitations that would result in the reference elbow motion trajectory. We constructed a prior over the excitation parameters which down-weighted regions of the parameter space with greater muscle excitations. We used muscle excitations to find the corresponding kinematics using OpenSim, where the error in position and velocity trajectories (likelihood function) was combined with the sum of the cubed muscle excitations integrated over time (prior function) to compute the posterior probability density.ResultsWe evaluated the muscle forces that resulted from the set of excitations that were visited in the MCMC chain (five parallel chains, 450,000 iterations per chain, runtime = 71 hours). The estimated muscle forces compared favorably with the reference motion from computed muscle control, while the elbow angle and velocity from MCMC matched closely with the reference with an average RMSE for angle and velocity equal to 0.008° and 0.18°/s, respectively. However, our rank plot analysis and potential scale reduction statistics, which we used to evaluate convergence of the algorithm, indicated that the parallel chains did not fully mix.ConclusionsWhile the results from this process are a promising step towards characterizing uncertainty in muscle force estimation, the computational time required to search the solution space with, and the lack of MCMC convergence indicates that further developments in MCMC algorithms are necessary for this process to become feasible for larger-scale models.
High-resolution protein fragment interactions using AVA-Seq on a human reference set
Authors: Schaefer-Ramadan Stephanie , Aleksic Jovana , Al-Thani Nayra M. , Mohamoud Yasmin A. , Hill David E. , Malek Joel A. 
Published: July 2021

AbstractProtein-protein interactions (PPIs) are important in understanding numerous aspects of protein function. Here, the recently developed all-vs-all sequencing (AVA-Seq) approach to determine protein-protein interactions was tested on a gold-standard human protein interaction set (hsPRS-v2). Initially, these data were interpreted strictly from a binary PPI perspective to compare AVA-Seq to other binary PPI methods tested on the same hsPRS-v2. AVA-Seq recovered 20 of 47 (43%) binary PPIs from this reference set comparing favorably with other methods. The same experimental data allowed for the determination of >500 known and novel PPIs including interactions between wildtype fragments of tumor protein p53 and minichromosomal maintenance complex proteins 2, and 5 (MCM2 and MCM5) that could be of interest in human disease. Additional results gave a better understanding of why interactions might be missed using AVA-Seq and aide future PPI experimental design for maximum recovery of information.
SUITOR: selecting the number of mutational signatures through cross-validation
Authors: Lee Donghyuk , Wang Difei , Yang Xiaohong R. , Shi Jianxin , Landi Maria Teresa , Zhu Bin 
Published: July 2021

AbstractFor de novo mutational signature analysis, the critical first step is to decide how many signatures should be expected in a cancer genomics study. An incorrect number could mislead downstream analyses. Here we present SUITOR (Selecting the nUmber of mutatIonal signaTures thrOugh cRoss-validation), an unsupervised cross-validation method that requires little assumptions and no numerical approximations to select the optimal number of signatures without overfitting the data. In vitro studies and in silico simulations demonstrated that SUITOR can correctly identify signatures, some of which were missed by other widely used methods. Applied to 2,540 whole-genome sequenced tumors across 22 cancer types, SUITOR selected signatures with the smallest prediction errors and almost all signatures of breast cancer selected by SUITOR were validated in an independent breast cancer study. SUITOR is a powerful tool to select the optimal number of mutational signatures, facilitating downstream analyses with etiological or therapeutic importance.
SARS-CoV-2 exposure in wild white-tailed deer (Odocoileus virginianus)
Authors: Chandler Jeffrey C. , Bevins Sarah N. , Ellis Jeremy W. , Linder Timothy J. , Tell Rachel M. , Jenkins-Moore Melinda , Root J. Jeffrey , Lenoch Julianna B. , Robbe-Austerman Suelee , DeLiberto Thomas J. , Gidlewski Thomas , Torchetti Mia K. , Shriner Susan A. 
Published: July 2021

AbstractWidespread human SARS-CoV-2 infections combined with human-wildlife interactions create the potential for reverse zoonosis from humans to wildlife. We targeted white-tailed deer (Odocoileus virginianus) for serosurveillance based on evidence these deer have ACE2 receptors with high affinity for SARS-CoV-2, are permissive to infection, exhibit sustained viral shedding, can transmit to conspecifics, and can be abundant near urban centers. We evaluated 624 pre- and post-pandemic serum samples from wild deer from four U.S. states for SARS-CoV-2 exposure. Antibodies were detected in 152 samples (40%) from 2021 using a surrogate virus neutralization test. A subset of samples was tested using a SARS-CoV-2 virus neutralization test with high concordance between tests. These data suggest white-tailed deer in the populations assessed have been exposed to SARS-CoV-2.One-Sentence SummaryAntibodies to SARS-CoV-2 were detected in 40% of wild white-tailed deer sampled from four U.S. states in 2021.
The three-dimensional structure of Drosophila melanogaster (6–4) photolyase at room temperature
Authors: Cellini Andrea , Yuan Wahlgren Weixiao , Henry Léocadie , Pandey Suraj , Ghosh Swagatha , Castillon Leticia , Claesson Elin , Takala Heikki , Kübel Joachim , Nimmrich Amke , Kuznetsova Valentyna , Nango Eriko , Iwata So , Owada Shigeki , Stojković Emina A. , Schmidt Marius , Ihalainen Janne A. , Westenhoff Sebastian 
Published: July 2021

(6–4) photolyases are flavoproteins that belong to the photolyase/cryptochrome family. Their function is to repair DNA lesions using visible light. Here, crystal structures of Drosophila melanogaster (6–4) photolyase [Dm(6–4)photolyase] at room and cryogenic temperatures are reported. The room-temperature structure was solved to 2.27 Å resolution and was obtained by serial femtosecond crystallography (SFX) using an X-ray free-electron laser. The crystallization and preparation conditions are also reported. The cryogenic structure was solved to 1.79 Å resolution using conventional X-ray crystallography. The structures agree with each other, indicating that the structural information obtained from crystallography at cryogenic temperature also applies at room temperature. Furthermore, UV–Vis absorption spectroscopy confirms that Dm(6–4)photolyase is photoactive in the crystals, giving a green light to time-resolved SFX studies on the protein, which can reveal the structural mechanism of the photoactivated protein in DNA repair.