bluuebunny/crossref_metadata_2025_split huggingface dataset:
Meta-analysis of the public RNA-Seq data of the Western honeybeeApis melliferato construct reference transcriptome data
Authors: Yokoi Kakeru , Wakamiya Takeshi , Bono Hidemasa 
Published: September 2022

AbstractThe Western honeybee (Apis mellifera) is valuable in biological research and agriculture. Its genome sequence was published before those for other insect species. RNA-Seq data forA. melliferahave been applied in several recently published studies. Nevertheless, these data have not been prepared for use in subsequent meta-analyses. To promoteA. melliferatranscriptome analysis, we constructed reference transcriptome data using the reference genome sequence and RNA-Seq data curated from about 1,000 runs of public databases. The new reference transcriptome data construct comprised 149,685 transcripts, and 194,174 protein sequences were predicted. About 50–60% of the predicted protein sequences were functionally annotated using the protein sequence data for several model and insect species. Novel candidate immune-related transcripts were searched by meta-analysis using immune response-related RNA-Seq and reference transcriptome data. Three to 20 candidate transcripts includingautophagy related protein 3were upregulated or downregulated in response to both viral and bacterial infections. The constructed reference transcriptome data may facilitate future transcriptome analyses ofA. mellifera.Simple SummaryThe honeybee is an economically and ecologically essential insect species and a critical social behavior model. It is vital to honey production and pollinates. Therefore, it has been studied extensively in entomological research. The Western honeybee (Apis mellifera) is a representative species of honeybees. The reference transcriptome data are required to perform the meta-analyses using public RNA-Seq data and transcriptome analysis using newly sequenced RNA-Seq data. The reference transcriptome sequences was constructed, which consisted of 149,685 transcripts, and 194,174 predicted amino acid sequences. Half the predicted protein sequences were functionally annotated using protein sequence datasets for several model and insect species. We performed meta-analysis to search for novel immune response-related transcripts. We identified 3–20 transcripts that were upregulated or downregulated in response to both viral and bacterial infections. However, the immune-related transcripts were not included among them. Autophagy related protein 3 was downregulated by viral infections. The results suggested that autophagy was implicated in the viral immune responses, and autophagy was not regulated by the canonical immune pathways inA. mellifera. The results of the meta-analysis suggested that the reference transcriptome data could be used for transcriptome analysis inA. mellifera.
Synthesizing Images of Tau Pathology from Cross-modal Neuroimaging using Deep Learning
Authors: Lee Jeyeon , Burkett Brian J. , Min Hoon-Ki , Senjem Matthew L. , Dicks Ellen , Corriveau-Lecavalier Nick , Mester Carly T. , Wiste Heather J. , Lundt Emily S. , Murray Melissa E. , Nguyen Aivi T. , Reichard Ross R. , Botha Hugo , Graff-Radford Jonathan , Barnard Leland R. , Gunter Jeffrey L. , Schwarz Christopher G. , Kantarci Kejal , Knopman David S. , Boeve Bradley F. , Lowe Val J. , Petersen Ronald C. , Jack Clifford R. , Jones David T. 
Published: September 2022

AbstractGiven the prevalence of dementia and the development of pathology-specific disease modifying therapies, high-value biomarker strategies to inform medical decision making are critical. In-vivo tau positron emission tomography (PET) is an ideal target as a biomarker for Alzheimer’s disease diagnosis and treatment outcome measure. However, tau PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that impute tau PET images from more widely-available cross-modality imaging inputs. Participants (n=1,192) with brain MRI, fluorodeoxyglucose (FDG) PET, amyloid PET, and tau PET were included. We found that a CNN model can impute tau PET images with high accuracy, the highest being for the FDG-based model followed by amyloid PET and MRI. In testing implications of AI-imputed tau PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and MRI-based models utilized the non-local input from physically remote ROIs to estimate the tau PET, but this was not the case for the PiB-based model. This implies that the model can learn the distinct biological relationship between FDG PET, MRI, and tau PET from the relationship between amyloid PET and tau PET. Our study suggests that extending neuroimaging’s use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.
Localization of multiple hydrogels with MultiCUBE platform spatially guides 3D tissue morphogenesis in vitro
Authors: Suthiwanich Kasinan , Hagiwara Masaya 
Published: September 2022

AbstractLocalization of multiple hydrogels is expected to develop the structure of 3D tissue models in a location specific manner. Here, we successfully localize morphogenesis within individual tissues by exposing different hydrogel conditions to different parts of the tissues. We develop a unit-based scaffold with a unique frame design to trap hydrogel solutions inside their designated units. Interestingly, this unit-based scaffold within an optimal range of dimensional size and surface wettability can trap several cubic millimeters of hydrogels. This localization capability enables the spatial organization of hydrogel compositions, growth factors and physical conditions, as well as the position of biological samples (cells, spheroids, reconstituted tissues) relative to each hydrogel compartment. We succeed to localize the branching development of reconstituted human epithelial tissues according to the localized biomolecular and physical cues from hydrogels, regardless of the initial tissue configurations. Unlike 3D-bioprinting or microfluidics, the localization with this unit-based scaffold requires only manual pipetting and handling without any specialized equipment or skills, thus ready to use by researchers from any field. This scaffold-based localization provides a new promising route to spatially control morphogenesis, differentiation, and other developmental processes within organoids or other 3D tissues, resulting in 3D functional models for practical biomedical applications.
Heat dissipation drives the hump-shaped scaling of animal dispersal speed with body mass
Authors: Dyer Alexander , Brose Ulrich , Berti Emilio , Rosenbaum Benjamin , Hirt Myriam R. 
Published: September 2022

AbstractDispersal is critical to animal survival and thus biodiversity in fragmented landscapes. Increasing fragmentation in the Anthropocene necessitates predictions about the dispersal capabilities of the many species that inhabit natural ecosystems. This requires mechanistic, trait-based models of animal dispersal which are sufficiently general as well as biologically realistic. While larger animals should generally be able to travel greater distances, reported trends in their speeds across a range of body sizes suggest limited locomotor capacities among the largest species. Here, we show that this also applies to dispersal speeds and that this arises because of their limited heat-dissipation capacities. We derive a model considering how fundamental biophysical constraints of animal body mass associated with energy utilisation (i.e. larger animals have a lower metabolic energy cost of locomotion) and heat-dissipation (i.e. larger animals require more time to dissipate metabolic heat) limit sustained (i.e. aerobic) dispersal speeds. Using an extensive empirical dataset of animal dispersal speeds (531 species), we show that thisallometric heat-dissipation modelbest captures the hump-shaped trends in dispersal speed with body mass for flying, running and swimming animals. This implies that the inability to dissipate metabolic heat leads to the saturation and eventual decrease in dispersal speed with increasing body mass as larger animals must reduce their realised dispersal speeds in order to avoid hyperthermia during extended dispersal bouts. As a result, the highest dispersal speeds are achieved by animals of intermediate body mass, whereas the largest species might suffer from stronger dispersal limitations in fragmented landscapes than previously anticipated. Consequently, we provide a mechanistic understanding of animal dispersal speed that can be generalised across species, even when the details of an individual species’ biology are unknown, to facilitate more realistic predictions of biodiversity dynamics in fragmented landscapes.
Empirical methods for the validation of Time-To-Event mathematical models taking into account uncertainty and variability: Application to EGFR+ Lung Adenocarcinoma
Authors: Jacob Evgueni , Perrillat-Mercerot Angélique , Palgen Jean-Louis , L’Hostis Adèle , Ceres Nicoletta , Boissel Jean-Pierre , Bosley Jim , Monteiro Claudio , Kahoul Riad 
Published: September 2022

AbstractBackgroundOver the past several decades, metrics have been defined to assess the quality of various types of models and to compare their performance depending on their capacity to explain the variance found in real-life data. However, available validation methods are mostly designed for statistical regressions rather than for mechanistic models. To our knowledge, in the latter case, there are no consensus standards, for instance for the validation of predictions against real-world data given the variability and uncertainty of the data. In this work, we focus on the prediction of time-to-event curves using as an application example a mechanistic model of non-small cell lung cancer. We designed four empirical methods to assess both model performance and reliability of predictions: two methods based on bootstrapped versions of parametric statistical tests: log-rank and combined weighted log-ranks (MaxCombo); and two methods based on bootstrapped prediction intervals, referred to here as raw coverage and the juncture metric. We also introduced the notion of observation time uncertainty to take into consideration the real life delay between the moment when an event happens, and the moment when it is observed and reported.ResultsWe highlight the advantages and disadvantages of these methods according to their application context. We have shown that the context of use of the model has an impact on the model validation process. Thanks to the use of several validation metrics we have highlighted the limit of the model to predict the evolution of the disease in the whole population of mutations at the same time, and that it was more efficient with specific predictions in the target mutation populations. The choice and use of a single metric could have led to an erroneous validation of the model and its context of use.ConclusionsWith this work, we stress the importance of making judicious choices for a metric, and how using a combination of metrics could be more relevant, with the objective of validating a given model and its predictions within a specific context of use. We also show how the reliability of the results depends both on the metric and on the statistical comparisons, and that the conditions of application and the type of available information need to be taken into account to choose the best validation strategy.
Integrating gene annotation with orthology inference at scale
Authors: Kirilenko Bogdan M. , Munegowda Chetan , Osipova Ekaterina , Jebb David , Sharma Virag , Blumer Moritz , Morales Ariadna E. , Ahmed Alexis-Walid , Kontopoulos Dimitrios-Georgios , Hilgers Leon , Lindblad-Toh Kerstin , Karlsson Elinor K. ,   Zoonomia Consortium, Hiller Michael 
Published: September 2022

AbstractAnnotating coding genes and inferring orthologs are two classical challenges in genomics and evolutionary biology that have traditionally been approached separately, limiting scalability. We present TOGA, a method that integrates structural gene annotation and orthology inference. TOGA implements a different paradigm to infer orthologous loci, improves ortholog detection and annotation of conserved genes compared to state-of-the-art methods, and handles even highly-fragmented assemblies. TOGA scales to hundreds of genomes, which we demonstrate by applying it to 488 placental mammal and 501 bird assemblies, creating the largest comparative gene resources so far. Additionally, TOGA detects gene losses, enables selection screens, and automatically provides a superior measure of mammalian genome quality. Together, TOGA is a powerful and scalable method to annotate and compare genes in the genomic era.
Perturbations in podocyte transcriptome and biological pathways induced by FSGS associated circulating factors
Authors: Rashmi Priyanka , Sigdel Tara K. , Rychkov Dmitry , Damm Izabella , Da Silva Andrea Alice , Vincenti Flavio , Lourenco Andre L. , Craik Charles S. , Reiser Jochen , Sarwal Minnie M 
Published: September 2022

AbstractFocal segmental glomerulosclerosis (FSGS) is frequently associated with heavy proteinuria and progressive renal failure requiring dialysis or kidney transplantation. However, primary FSGS also has 40-80% risk of recurrence of disease in the transplanted kidney (rFSGS). Multiple circulating factors have been proposed to contribute to the pathogenesis of primary and rFSGS. However, neither the factors nor the downstream effectors specific to individual factors have been identified. The tumor necrosis factor, TNF pathway activation by one or more circulating factors present in the sera of patients with FSGS has been supported by multiple studies. The proposed circulating factors include soluble urokinase-type plasminogen activator receptor (suPAR) and patient derived CD40 autoantibody (CD40autoAb) in the development and recurrence of FSGS. In a human in vitro model, using two novel human antibodies-anti uPAR (2G10) and anti CD40 antibody, we show that the podocyte injury caused by sera from FSGS patients is at least in part mediated by CD40 and suPAR. Additionally, we employ gene expression studies to compare the molecules and pathways activated in response to CD40 autoantibody from rFSGS patients (rFSGS/CD40autoAb) and suPAR, and delineate the unique pathways associated with FSGS injury and transcriptional podocyte alterations with targeted blockade of suPAR and CD40 pathways.Clinical ImpactFocal Segmental Glomerulosclerosis remains a disease without specific therapy for primary disease and high rate of recurrence after kidney transplantation. Circulating factors are implicated in the pathogenesis of FSGS but targeting them for therapy has remained elusive. We propose two potential therapeutic molecules for rFSGS treatment-a human anti-uPAR antibody (2G10) and a humanized anti-CD40 blocking antibody (Bristol Meyer Squibb, 986090) that reverse podocyte injury associated with FSGS in cultured podocytes and can be further tested in pre-clinical and clinical models. Furthermore, we use microarray profiling to identify transcriptional pathways specific to podocyte injury from patient-derived CD40 autoantibodies (rFSGS/CD40autoAb) and suPAR and selective blockade of these pathways to abrogate podocyte injury.
MedDiC: high dimensional mediation analysis via difference in coefficients
Authors: Zhang Qi , Yang Zhikai , Yang Jinliang 
Published: September 2022

AbstractHigh dimensional mediation analysis has been receiving increasing popularity, largely motivated by the scientific problems in genomics and biomedical imaging. Previous literature has primarily focused on mediator selection for high dimensional mediators. In this paper, we aim at the estimation and inference of overall indirect effect for high dimensional exposures and high dimensional mediators. We propose MedDiC, a novel debiased estimator of the high dimensional overall indirect effect based on difference-in-coefficients approach. We evaluate the proposed method using intensive simulations and find that MedDiC provides valid inference and offers higher power and shorter computing time than the competitors for both low dimensional and high dimensional exposures. We also apply MedDiC to a mouse f2 dataset for diabetes study and a dataset composed of diverse maize inbred lines for flowering time, and show that MedDiC yields more biologically meaningful gene lists, and the results are reproduciable across analyses using different measures of identical biological signal or related phenotype as the outcome.Upon the acceptance of the paper, the code will be available on GitHub (https://github.com/QiZhangStat/MedDiC).
Injectable polymer-nanoparticle hydrogel for the sustained intravitreal delivery of bimatoprost
Authors: Meany Emily L. , Andaya Roxanne , Tang Shijia , Kasse Catherine M. , Fuji Reina N. , Grosskopf Abigail K. , d’Aquino Andrea l. , Bartoe Joshua T. , Ybarra Ryan , Shelton Amy , Pederson Zachary , Hu Chloe , Leung Dennis , Nagapudi Karthik , Ubhayakar Savita , Wright Matthew , Yen Chun-Wan , Appel Eric A. 
Published: September 2022

AbstractVision impairment resulting from chronic eye diseases, such as macular degeneration and glaucoma, severely impacts patients’ quality of life and poses an immense global financial burden. Current standard of care for such diseases includes daily eye drops or frequent intravitreal (ITV) injections, which are burdensome treatment modalities resulting in low patient compliance. There remains a growing need for easily administered long-acting delivery technologies for prolonging exposure of ocular therapeutics with each administration. Here, we deploy a supramolecular polymer-nanoparticle (PNP) hydrogel for ITV delivery of the glaucoma drug bimatoprost. PNP hydrogels are shear-thinning and self-healing, key properties for injectability, and enable slow release of molecular cargo in vitreous humor (VH) mimics. An in vivo study in New Zealand white rabbits demonstrated intravitreally injected PNP hydrogels form depots that degrade slowly over time, maintaining detectable levels of bimatoprost in the VH up to eight weeks following injection. Ophthalmic examinations and histopathology identified a mild foreign body response (FBR) to the hydrogel, characterized by rare clusters of foamy macrophages and giant cells associated with minimal, patchy fibroplasia. This work shows that PNP hydrogels exhibit numerous desirable traits for sustained drug delivery and further work will be necessary to optimize tolerability in the eye.
A high-quality chromosome-level genome assembly of rohu carp, Labeo rohita, and its utilization in SNP-based exploration of gene flow and sex determination
Authors: Arick Mark A. , Grover Corrinne E. , Hsu Chuan-Yu , Magbanua Zenaida , Pechanova Olga , Miller Emma R. , Thrash Adam , Youngblood Ramey C. , Ezzell Lauren , Alam Md Samsul , Benzie John A. H. , Hamilton Matthew G. , Karsi Attila , Lawrence Mark L. , Peterson Daniel G. 
Published: September 2022

AbstractLabeo rohita (rohu) is a carp important to aquaculture in South Asia, with a production volume close to Atlantic salmon. While genetic improvements to rohu are ongoing, the genomic methods commonly used in other aquaculture improvement programs have historically been precluded in rohu, partially due to the lack of a high quality reference genome. Here we present a high-quality de novo genome produced using a combination of next-generation sequencing technologies, resulting in a 946 Mb genome consisting of 25 chromosomes and 2,844 unplaced scaffolds. Notably, while approximately half the size of the existing genome sequence, our genome represents 97.9% of the genome size newly estimated here using flow cytometry. Sequencing from 120 individuals was used in conjunction with this genome to predict the population structure, diversity, and divergence in three major rivers (Jamuna, Padma, and Halda), in addition to infer a likely sex determination mechanism in rohu. These results demonstrate the utility of the new rohu genome in modernizing some aspects of rohu genetic improvement programs.
Scaling protein-water interactions in the Martini 3 coarse-grained force field to simulate transmembrane helix dimers in different lipid environments
Authors: Cabezudo Ainara Claveras , Athanasiou Christina , Tsengenes Alexandros , Wade Rebecca C. 
Published: September 2022

ABSTRACTMartini 3, the latest version of the widely used Martini force field for coarse-grained molecular dynamics simulations, is a promising tool to investigate proteins in phospholipid bilayers. However, simulating other lipid environments, such as detergent micelles, presents challenges due to the absence of validated parameters for their constituent molecules. Here, we propose parameters for the micelle-forming surfactant, dodecylphosphocholine (DPC). These result in micelle assembly with aggregation numbers in agreement with experimental values. However, we identified a lack of hydrophobic interactions between transmembrane helix protein dimers and the tails of DPC molecules, preventing insertion and stabilization of the protein in the micelles. This problem was also observed for protein insertion by self-assembling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) or dipalmitoylphosphatidylcholine (DPPC) bilayers. We propose the reduction of the non-bonded interactions between protein and water beads by 10% as a simple and effective solution to this problem that enables protein encapsulation in phospholipid micelles and bilayers without altering protein dimerization or bilayer structure.Abstract Figure
Conformational Changes Regulate Metal Coordination in the Catalytic Sites of Cas9
Authors: Das Anuska , Rai Jay , Roth Mitchell O. , Shu Yuerong , Medina Megan L. , Barakat MacKenzie R. , Li Hong 
Published: September 2022

AbstractThe control of CRISPR-Cas9 activities plays an essential role in its safe adoption for clinical and research applications. Previous studies have identified conformational dynamics of Cas9 as a key regulatory element for its enzymatic activity. The molecular basis for how conformations influence the catalytic processes at both nuclease domains, however, remains elusive. Here we present well-resolved cryo-EM structures of the activeAcidothermus cellulolyticusCas9 (AceCas9) complexes representing pre-cleavage (2.9 Å), two reaction intermediate (2.2 Å and 2.4 Å) and two post-cleavage (2.6 Å and 2.7 Å) states that reveal active site rearrangement during DNA binding and phosphodiester bond breakage by Cas9. Strikingly, large domain rearrangements in Cas9 triggered by the cognate DNA result in subtle changes in active sites that facilitate coordination of metal ions required for catalysis. The two reaction intermediate structures further reveal small oscillations in domain conformations, which alternates the reactive states of the two catalytic centers, thereby coupling cleavage of the two DNA strands. Consistent with the roles of conformations in organizing the active sites, adjustments of metal coordination ligands lead to altered metal specificity.