bluuebunny/crossref_metadata_2025_split huggingface dataset:
MAW - The Reproducible Metabolome Annotation Workflow for Untargeted Tandem Mass Spectrometry
Authors: Zulfiqar Mahnoor , Gadelha Luiz , Steinbeck Christoph , Sorokina Maria , Peters Kristian 
Published: October 2022

AbstractMapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such asin silicogenerated spectra and molecular networking. Here, we present an automated and reproducibleMetabolomeAnnotationWorkflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS2) input data pre-processing, spectral and compound database matching with computational classification, andin silicoannotation. MAW takes the LC-MS2spectra as input and generates a list of putative candidates from spectral and compound databases. The databases are integrated via the R package Spectra and the metabolite annotation tool SIRIUS as part of the R segment of the workflow (MAW-R). The final candidate selection is performed using the cheminformatics tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned a chemical structure and can be imported to a chemical structure similarity network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable) principles and has been made available as the docker images, maw-r and mawpy. The source code and documentation are available on GitHub (https://github.com/zmahnoor14/MAW). The performance of MAW is evaluated on two case studies. MAW can improve candidate ranking by integrating spectral databases with annotation tools like SIRIUS which contributes to an efficient candidate selection procedure. The results from MAW are also reproducible and traceable, compliant with the FAIR guidelines. Taken together, MAW could greatly facilitate automated metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.
Small hand-designed convolutional neural networks outperform transfer learning in automated cell shape detection in confluent tissues
Authors: Combe L. , Durande M. , Delanoë-Ayari H. , Cochet-Escartin O. 
Published: October 2022

AbstractMechanical cues such as stresses and strains are now recognized as essential regulators in many biological processes such as cell division, gene expression or morphogenesis. Studying the interplay between these mechanical cues and biological responses requires experimental tools to measure these cues. In the context of large scale tissues, this can be achieved by segmenting individual cells to extract their shapes and deformations which in turn inform on their mechanical environment. Historically, this has been done by segmentation methods which are well known to be time consuming and error prone. In this context however, one doesn’t necessarily require a cell-level description and a coarse grained approach can be more efficient while using tools different than segmentation.The advent of machine learning and deep neural networks has revolutionized the field of image analysis in recent years, including in biomedical research. With the democratization of these techniques, more and more researchers are trying to apply them to their own biological systems. In this paper, we tackle a problem of cell shape measurement thanks to a large annotated dataset. We develop simple CNNs which we thoroughly optimize in terms of architecture and complexity to question construction rules usually applied. We find that increasing the complexity of the networks rapidly no longer yields improvements in performance and that the number of kernels in each convolutional layer is the most important parameter to achieve good results. In addition, we compare our step-by-step approach with transfer learning and find that our simple, optimized CNNs give better predictions, are faster in training and analysis and don’t require more technical knowledge to be implemented. Overall, we offer a rational roadmap to develop optimized models and argue that we should limit the complexity of such models. We conclude by illustrating this strategy on a similar problem and dataset.
CoRegNet: Unraveling Gene Co-regulation Networks from Public RNA-Seq Repositories Using a Beta-Binomial Statistical Model
Authors: Wang Jiasheng , Wan Ying-Wooi , Al-Ouran Rami , Huang Meichen , Liu Zhandong 
Published: October 2022

AbstractMillions of RNA sequencing samples have been deposited into public databases, providing a rich resource for biological research. These datasets encompass tens of thousands of experiments and offer comprehensive insights into human cellular regulation. However, a major challenge is how to integrate these experiments that acquired at different conditions. We propose a new statistical tool based on beta-binomial distributions that can construct robust gene co-regulation network (CoRegNet) across tens of thousands of experiments. Our analysis of over 12,000 experiments involving human tissues and cells shows that CoRegNet significantly outperforms existing gene co-expression-based methods. Although the majority of the genes are linearly co-regulated, we did discover an interesting set of genes that are non-linearly co-regulated; half of the time they change in the same direction and the other half they change in the opposite direction. Additionally, we identified a set of gene pairs that follows the Simpson’s paradox. By utilizing public domain data, CoRegNet offers a powerful approach for identifying functionally related gene pairs, thereby revealing new biological insights.
Phasic locus coeruleus activity enhances trace fear conditioning by increasing dopamine release in the hippocampus
Authors: Wilmot Jacob H. , Diniz Cassiano R.A.F. , Crestani Ana P. , Puhger Kyle , Roshgadol Jacob , Tian Lin , Wiltgen Brian J. 
Published: October 2022

AbstractLocus coeruleus (LC) projections to the hippocampus play a critical role in learning and memory. However, the precise timing of LC-hippocampus communication during learning and which LC-derived neurotransmitters are important for memory formation in the hippocampus are currently unknown. Although the LC is typically thought to modulate neural activity via the release of norepinephrine, several recent studies have suggested that it may also release dopamine into the hippocampus and other cortical regions. In some cases, it appears that dopamine release from LC into the hippocampus may be more important for memory than norepinephrine. Here, we extend these data by characterizing the phasic responses of the LC and its projections to the dorsal hippocampus during trace fear conditioning. We find that the LC and its projections to the hippocampus respond to task-relevant stimuli and that amplifying these responses with optogenetic stimulation can enhance long-term memory formation. We also demonstrate that LC activity increases both norepinephrine and dopamine content in the dorsal hippocampus and that the timing of hippocampal dopamine release during trace fear conditioning is similar to the timing of LC activity. Finally, we show that hippocampal dopamine is important for trace fear memory formation, while norepinephrine is not.
HALO: Hierarchical Causal Modeling for Single Cell Multi-Omics Data
Authors: Mao Haiyi , Jia Minxue , Di Marissa , Valenzi Eleanor , Cai Xiaoyu Tracy , Singh Harinder , Lafyatis Robert , Zhang Kun , Benos Panagiotis 
Published: October 2022

AbstractThough open chromatin may promote active transcription, gene expression responses may not be directly coordinated with changes in chromatin accessibility. Most existing methods for single-cell multi-omics data focus only on learning stationary and shared information among these modalities, overlooking modality-specific information delineating cellular states and dynamics resulting from causal relations among modalities. To account for this, the epigenome and transcriptome relationship can be characterized in relation to time as “coupled” (changing dependently) or “decoupled” (changing independently). We propose the framework HALO, which adopts a causal approach to model these temporal causal relations on two levels. On the representation level, HALO factorizes these two modalities into both coupled and decoupled latent representations, identifying the dynamic interplay between chromatin accessibility and transcription through temporal modulations in the latent space. On the individual gene level, HALO matches gene-peak pairs and characterizes changing dynamics between gene expression and local peaks with time. HALO reveals bipotency in a subset of AT2 cells that exhibit different decisions in lineage specification between systemic sclerosis (SSc) and normal conditions. We demonstrate that using coupled and decoupled information, HALO discovers analogous biological functions between modalities, distinguishes epigenetic factors for lineage specification, and identifies temporalcis-regulation interactions relevant to cellular differentiation and complex human diseases.
Oral Delivery of Kidney Targeting Nanotherapeutics for Polycystic Kidney Disease
Authors: Huang Yi , Wang Jonathan , Chin Deborah , Mancino Valeria , Pham Jessica , Li Hui , Jiang Kairui , Ram Aparna , Poon Christopher , Ho Pei-Yin , Gyarmati Georgina , Peti-Peterdi János , Hallows Kenneth R. , Chung Eun Ji 
Published: October 2022

AbstractAutosomal dominant polycystic kidney disease (ADPKD) is the most common inherited renal disorder. Although a variety of candidate drugs have been found to modulate cystogenesis in animal studies, results from clinical trials have often been unfavorable due to low renal bioavailability and drug-induced side effects. To mitigate this, nanoparticles can be designed to deliver drugs directly to the target organ to increase effective dose while limiting off-target side effects. Unfortunately, there are no kidney-targeted nanomedicines clinically available, and most of the existing FDA-approved nanoparticles require intravenous administration which is not suitable for ADPKD that require lifelong therapy. To address this, we developed an oral drug delivery system using chitosan nanoparticles (CS-NP) that were loaded with peptide amphiphile micelles carrying metformin (met), an ADPKD drug candidate (CS-KM-met). We previously showed that CS-NP can shield met in the gastrointestinal tract; thus, we hypothesized that CS-NP could also enhance bioavailability of kidney-targeting micelles (KMs) upon oral administration. Specifically, we measured the loading capacity of KM-met in CS-NP, evaluated the stability of CS-KM-met under acidic conditions that mimic the gastric environment, and measuredin vitrotherapeutic effects. Upon oral administration in C57BL/6J mice, CS-KM-met showed significantly greater bioavailability and accumulation in the kidneys as compared to KM-met without CS-NP or free met for up to 24 hours. As such, CS-KM-met showed enhanced therapeutic efficacyin vivoupon oral administration in PKD mice (Pkd1fl/fl; Pax8-rtTA; Tet-O-Cre) compared to KM-met only. Herein, we demonstrate the potential of an oral delivery nanoformulation for the treatment of chronic kidney diseases such as ADPKD for the first time.
A ten-year community reporting database reveals rising coyote boldness and associated human concern in Edmonton, Canada
Authors: Farr Jonathan J. , Pruden Matthew J. , Glover Robin , Murray Maureen H. , Sugden Scott A. , Harshaw Howard W. , Cassady St. Clair Colleen 
Published: October 2022

ABSTRACTIn cities throughout North America, sightings of coyotes (Canis latrans) have become common. Reports of human-coyote conflict are also rising, as is the public demand for proactive management to prevent negative human-coyote interactions. Effective and proactive management can be informed by the direct observations of community members, who can report their interactions with coyotes and describe the location, time, and context that led to their interactions. To assess the predictors of human-coyote conflict, we used a web-based reporting system to collect 9,134 community-supplied reports of coyotes in Edmonton, Canada, between January 2012 and December 2021. We used a standardized ordinal ranking system to score each report on two indicators of human-coyote conflict: coyote boldness, based on the reported coyote behaviour, and human perceptions about coyotes, determined from the emotions expressed by reporters. We assigned greater conflict scores to behaviours where coyotes followed, approached, charged or contacted pets or people, and to perceptions where reporters expressed fear, worry, concern, discomfort or alarm. Using ordered logistic regression and chi-square tests, we compared conflict scores for each response variable to spatial, temporal and contextual covariates. Our analysis showed that coyotes were bolder in less developed open areas and during the pup rearing season, but human perceptions were most negative in residential areas and during the dispersal season. Reports that mentioned dogs or cats were more likely to describe bolder coyote behaviour, and those that mentioned pets or children had more negative perceptions about coyotes. Coyote boldness and human perceptions both indicated rising human-coyote conflict in Edmonton over the 10 years of reporting.
Development of a clot-adhesive coating to improve the performance of thrombectomy devices
Authors: Skarbek Charles , Anagnostakou Vaia , Propocio Emanuele , Epshtein Mark , Raskett Christopher M. , Romagnoli Romeo , Iviglia Giorgio , Morra Marco , Antonucci Marta , Nicoletti Antonino , Caligiuri Giuseppina , Gounis Matthew J. 
Published: October 2022

ABSTRACTBackgroundThe first-pass complete recanalization by mechanical thrombectomy (MT) for the treatment of stroke remains limited due to the poor integration of the clot within current devices. Aspiration can help retrieval of the main clot but fails to prevent secondary embolism in the distal arterial territory. The dense meshes of extracellular DNA, recently described in stroke-related clots, might serve as an anchoring platform for MT devices.ObjectiveEvaluate the potential of DNA reacting surface toaid the retention of the main clot as well as of its small fragments within the thrombectomy deviceand improve the potential of MT procedures.MethodsDevice-suitable alloy experimental samples were coated with 15 different compounds and contacted with extracellular DNA or with human peripheral whole blood, to compare their binding to DNA versus flowing blood elements,in vitro. Clinical-grade MT devices were coated with two selected compounds and evaluated in functional bench tests aiming to studying clot retrieval and distal emboli release, concomitant with contact aspiration, using an M1 occlusion model.ResultsBinding properties of samples coated with all compounds were increased for DNA (≈ 3-fold) and decreased (≈ 5-fold) for blood elements, essentially platelet, as compared to the bare alloy samples,in vitro. Functional testing showed that surface modification with DNA-binding compounds improved clot retrieval and significantly reduced secondary embolism during experimental recanalization of occluded artery 3D model by thrombectomy procedures.ConclusionOur results suggest that device coating with DNA-binding compounds can considerably improve the outcome of MT procedures in stroke patients.What is already known on this topic –New mechanical thrombectomy device are being improved on the conformation and shape to increase the interaction clot on the physical point of view. However, none interact specifically with the structure or composition of the clot.What this study adds –The design of a chemical surface modification of the device opens the way for a specific targeting tool to increase the interaction with the clot on the molecular level.How this study might affect research, practice or policy –This new surface modification, which can be applied to all commercially available mechanical thrombectomy devices, leads to a decrease in secondary embolization which cannot and is not monitored during the procedure and responsible for new territory damage.
Efficient minimizer orders for large values ofkusing minimum decycling sets
Authors: Pellow David , Pu Lianrong , Ekim Baris , Kotlar Lior , Berger Bonnie , Shamir Ron , Orenstein Yaron 
Published: October 2022

AbstractMinimizers are ubiquitously used in data structures and algorithms for efficient searching, mapping, and indexing of high-throughput DNA sequencing data. Minimizer schemes select a minimumk-mer in everyL-long sub-sequence of the target sequence, where minimality is with respect to a predefinedk-mer order. Commonly used minimizer orders select morek-mers than necessary and therefore provide limited improvement in runtime and memory usage of downstream analysis tasks. The recently introduced universalk-mer hitting sets produce minimizer orders with fewer selectedk-mers. Unfortunately, generating compact universalk-mer hitting sets is currently infeasible fork> 13, and thus cannot help in the many applications that require minimizer orders for largerk.Here, we close the gap of efficient minimizer orders for large values ofkby introducingdecycling-set-based minimizer orders, new orders based on minimum decycling sets. We show that in practice these new minimizer orders select a number ofk-mers comparable to that of minimizer orders based on universalk-mer hitting sets, and can also scale up to largerk. Furthermore, we developed a method that computes the minimizers in a sequence on the fly without keeping thek-mers of a decycling set in memory. This enables the use of these minimizer orders for any value ofk. We expect the new orders to improve the runtime and memory usage of algorithms and data structures in high-throughput DNA sequencing analysis.
High-resolution methylome analysis in the clonalPopulus nigracv. ‘Italica’ reveals environmentally sensitive hotspots and drought-responsive TE superfamilies
Authors: Peña-Ponton C. , Diez-Rodriguez B. , Perez-Bello P. , Becker C. , McIntyre L.M. , Van der Putten W. , De Paoli E. , Heer K. , Opgenoorth L. , Verhoeven KJF. 
Published: October 2022

ABSTRACT/SUMMARYDNA methylation is environment-sensitive and can mediate plant stress responses. In long-lived trees, changing environments might cumulatively shape the methylome landscape over their lifetime. However, because high-resolution methylome studies usually focus on single environments, it remains unclear to what extent the methylation responses are generic or stress-specific, and how this relates to their long-term stability.Here, we studied the methylome plasticity of a single poplar genotype,Populus nigracv. ‘Italica’. Adult poplar trees with diverse environmental histories were clonally propagated, and the ramets exposed to experimental cold, heat, drought, herbivory, rust infection and salicylic acid treatments. Then, we identified and compared stress-induced vs. naturally occurring DNA methylation changes using whole genome bisulfite sequencing data.Methylation changes mainly targeted transposable elements and when occurring in CG/CHG contexts, the same regions were often affected by multiple stresses, indicating a generic response. Drought triggered a unique CHH hypermethylation response in transposable elements, affecting entire superfamilies and often occurring near drought-responsive genes. Stress-induced methylation variation in CG/CHG contexts showed striking overlap with methylation differences observed between trees from distinct geographical locations.Altogether, our results indicate that generic methylome stress responses can persist as epialleles in nature while some environments trigger more transient but large and specific responses, with possible functional consequences.
Spatio-temporal modeling of high-throughput multi-spectral aerial images improves agronomic trait genomic prediction in hybrid maize
Authors: Morales Nicolas , Anche Mahlet T. , Kaczmar Nicholas S. , Lepak Nicholas , Ni Pengzun , Romay Maria Cinta , Santantonio Nicholas , Buckler Edward S. , Gore Michael A. , Mueller Lukas A. , Robbins Kelly R. 
Published: October 2022

AbstractDesign randomizations and spatial corrections have increased understanding of genotypic, spatial, and residual effects in field experiments, but precisely measuring spatial heterogeneity in the field remains a challenge. To this end, our study evaluated approaches to improve spatial modeling using high-throughput phenotypes (HTP) via unoccupied aerial vehicle (UAV) imagery. The normalized difference vegetation index (NDVI) was measured by a multi-spectral MicaSense camera and ImageBreed. Contrasting to baseline agronomic trait spatial correction and a baseline multi-trait model, a two-stage approach that quantified NDVI local environmental effects (NLEE) was proposed. Firstly, NLEE were separated from additive genetic effects over the growing season using two-dimensional spline (2DSpl), separable autoregressive (AR1) models, or random regression models (RR). Secondly, the NLEE were leveraged within agronomic trait genomic best linear unbiased prediction (GBLUP) either modeling an empirical covariance for random effects, or by modeling fixed effects as an average of NLEE across time or split among three growth phases. Modeling approaches were tested using simulation data and Genomes-to-Fields (G2F) hybrid maize (Zea maysL.) field experiments in 2015, 2017, 2019, and 2020 for grain yield, grain moisture, and ear height. The two-stage approach improved heritability, model fit, and genotypic effect estimation compared to all baseline models. Electrical conductance and elevation from a 2019 soil survey significantly improved model fit, while 2DSpl NLEE were most correlated to the soil parameters and grain yield 2DSpl effects. Simulation of field effects demonstrated improved specificity for RR models. In summary, NLEE increased experimental accuracy and understanding of field spatio-temporal heterogeneity.