bluuebunny/crossref_metadata_2025_split huggingface dataset:
Peripheral blood transcriptomic profiling indicates molecular mechanisms commonly regulated by binge-drinking and placebo-effects
Authors: Shetty Amol Carl , Sivinski John , Cornell Jessica , Sadzewicz Lisa , Mahurkar Anup , Wang Xing-Qun , Colloca Luana , Lin Weihong , Kane Maureen A. , Seneviratne Chamindi 
Published: March 2023

ABSTRACTMolecular changes associated with alcohol consumption arise from complex interactions between pharmacological effects of alcohol, psychological/placebo context surrounding drinking, and other environmental and biological factors. The goal of this study was to tease apart molecular mechanisms regulated by pharmacological effects of alcohol - particularly at binge-drinking, from underlying placebo effects. Transcriptome-wide RNA-seq analyses were performed on peripheral blood samples collected from healthy heavy social drinkers (N=16) enrolled in a 12-day randomized, double-blind, cross-over human laboratory trial testing three alcohol doses: Placebo, moderate (0.05g/kg (men), 0.04g/kg (women)), and binge (1g/kg (men), 0.9g/kg (women)), administered in three 4-day experiments, separated by minimum of 7-day washout periods. Effects of beverage doses on the normalized gene expression counts were analyzed within each experiment compared to its own baseline using paired-t-tests. Differential expression of genes (DEGs) across experimental sequences in which each beverage dose was administered, as well as responsiveness to regular alcohol compared to placebo (i.e., pharmacological effects), were analyzed using generalized linear mixed-effects models. The 10% False discovery rate-adjusted DEGs varied across experimental sequences in response to all three beverage doses. We identified and validated 22 protein coding DEGs potentially responsive to pharmacological effects of binge and medium doses, of which 11 were selectively responsive to binge dose. Binge-dose significantly impacted the Cytokine-cytokine receptor interaction pathway (KEGG: hsa04060) across all experimental-sequences that it was administered in, and during dose-extending placebo. Medium dose and placebo impacted pathways hsa05322, hsa04613, and hsa05034, in the first two and last experimental sequences, respectively. In summary, our findings add novel, and confirm previously reported data supporting dose-dependent effects of alcohol on molecular mechanisms and suggest that the placebo effects may induce molecular responses within the same pathways regulated by alcohol. Innovative study designs are required to validate molecular correlates of placebo effects underlying drinking.
Deep learning for quantitative MRI brain tumor analysis
Authors: Tampu Iulian Emil , Haj-Hosseini Neda , Blystad Ida , Eklund Anders 
Published: March 2023

ABSTRACTThe infiltrative nature of malignant gliomas results in active tumor spreading into the peritumoral edema, which is not visible in conventional magnetic resonance imaging (cMRI) even after contrast injection. MR relaxometry (qMRI) measures relaxation rates dependent on tissue properties, and can offer additional contrast mechanisms to highlight the non-enhancing infiltrative tumor. The aim of this study is to investigate if qMRI data provides additional information compared to cMRI sequences (T1w, T1wGd, T2w, FLAIR), when considering deep learning-based brain tumor (1) detection and (2) segmentation. A total of 23 patients with histologically confirmed malignant glioma were retrospectively included in the study. Quantitative MR imaging was used to obtain R1(1/T1), R2(1/T2) and proton density maps pre- and post-gadolinium contrast injection. Conventional MR imaging was also performed. A 2D CNN detection model and a 2D U-Net were trained on transversal slices (n=528) using either cMRI or a combination of qMRI pre- and post-contrast data for tumor detection and segmentation, respectively. Moreover, trends in quantitative R1and R2rates of regions identified as relevant for tumor detection by model explainability methods were qualitatively analyzed. Tumor detection and segmentation performance for models trained with a combination of qMRI pre- and post-contrast was the highest (detection MCC=0.72, segmentation Dice=0.90), however, improvements were not statistically significant compared to cMRI (detection MCC=0.67, segmentation Dice=0.90). The analysis of the relaxation rates of the relevant regions identified using model explainability methods showed no differences between models trained on cMRI or qMRI. Relevant regions which fell outside the annotation showed changes in relaxation rates after contrast injection similar to those within the annotation, when looking at majority of the individual cases. A similar trend could not be seen when looking at relaxation trends over all the dataset. In conclusion, models trained on qMRI data obtain similar performance to those trained on cMRI data, with the advantage of quantitatively measuring brain tissue properties within the scan time (11.8 minutes for qMRI with and without contrast, and 12.2 minutes for cMRI). Moreover, when considering individual patients, regions identified by model explainability methods as relevant for tumor detection outside the manual annotation of the tumor showed changes in quantitative relaxation rates after contrast injection similar to regions within the annotation, suggestive of infiltrative tumor in the peritumoral edema.
standard-GEM: standardization of open-source genome-scale metabolic models
Authors: Anton Mihail , Almaas Eivind , Benfeitas Rui , Benito-Vaquerizo Sara , Blank Lars M. , Dräger Andreas , Hancock John M. , Kittikunapong Cheewin , König Matthias , Li Feiran , Liebal Ulf W. , Lu Hongzhong , Ma Hongwu , Mahadevan Radhakrishnan , Mardinoglu Adil , Nielsen Jens , Nogales Juan , Pagni Marco , Papin Jason A. , Patil Kiran Raosaheb , Price Nathan D. , Robinson Jonathan L. , Sánchez Benjamín J. , Suarez-Diez Maria , Sulheim Snorre , Svensson L. Thomas , Teusink Bas , Vongsangnak Wanwipa , Wang Hao , Zeidan Ahmad A. , Kerkhoven Eduard J. 
Published: March 2023

ABSTRACTThe field of metabolic modelling at the genomescale continues to grow with more models being created and curated. This comes with an increasing demand for adopting common principles regarding transparency and versioning, in addition to standardisation efforts regarding file formats, annotation and testing. Here, we present a standardised template for git-based and GitHub-hosted genome-scale metabolic models (GEMs) supporting both new models and curated ones, following FAIR principles (findability, accessibility, interoperability, and reusability), and incorporating bestpractices.standard-GEMfacilitates the reuse of GEMs across web services and platforms in the metabolic modelling field and enables automatic validation of GEMs. The use of this template for new models, and its adoption for existing ones, paves the way for increasing model quality, openness, and accessibility with minimal effort.Availabilitystandard-GEMis available fromgithub.com/MetabolicAtlas/standard-GEMunder the conditions of the CC BY 4.0 licence along with additional supporting material.
Transcriptomic Prediction of Breeding Values in Loblolly Pine
Authors: Festa Adam R , Whetten Ross 
Published: March 2023

AbstractPhenotypic variation in forest trees can be partitioned into subsets controlled by genetic variation and by environmental factors, and heritability expressed as the proportion of total phenotypic variation attributed to genetic variation. Applied tree breeding programs can use matrices of relationships, based either on recorded pedigrees in structured breeding populations or on genotypes of molecular genetic markers, to model genetic covariation among related individuals and predict genetic values for individuals for whom no phenotypic measurements are available. This study tests the hypothesis that genetic covariation among individuals of similar genetic value will be reflected in shared patterns of gene expression. We collected gene expression data by high-throughput sequencing of RNA isolated from pooled seedlings from parents of known genetic value, and compared alternative approaches to data analysis to test this hypothesis. Selection of specific sets of transcripts increased the predictive power of models over that observed using all transcripts. Using information on presence of putative mutations in protein-coding sequences increased predictive accuracy for some traits but not for others. Known pedigree relationships are not required for this approach to modeling genetic variation, so it has potential to allow broader application of genetic covariance modeling to natural populations of forest trees.
READRetro: Natural Product Biosynthesis Planning with Retrieval-Augmented Dual-View Retrosynthesis
Authors: Lee Seul , Kim Taein , Choi Min-Soo , Kwak Yejin , Park Jeongbin , Hwang Sung Ju , Kim Sang-Gyu 
Published: March 2023

AbstractElucidating the biosynthetic pathways of natural products has been a major focus of biochemistry and pharmacy. However, predicting the whole pathways from target molecules to metabolic building blocks remains a challenge. Here we propose READRetro as a practical bio-retrosynthesis tool for planning the biosynthetic pathways of natural products. READRetro effectively resolves the tradeoff between generalizability and memorability in bio-retrosynthesis by implementing two separate modules; each module is responsible for either generalizability or memorability. Specifically, READRetro utilizes a rule-based retriever for memorability and an ensemble of two dual-representation-based deep learning models for generalizability. Through extensive experiments, READRetro was demonstrated to outperform existing models by a large margin in terms of both generalizability and memorability. READRetro was also capable of predicting the known pathways of complex plant secondary metabolites such as monoterpene indole alkaloids, demonstrating its applicability in the real-world bio-retrosynthesis planning of natural products. A website (https://readretro.net) and open-source code have been provided for READRetro, a practical tool with state-of-the-art performance for natural product biosynthesis research.
Determining the neuronal ensembles underlying sex-specific social impairments following adolescent intermittent ethanol exposure
Authors: Towner Trevor T. , Goyden Matt A. , Coleman Harper J. , Drumm Mary K. , Ritchie Isabella P. , Lieb Kayla R. , Varlinskaya Elena I. , Werner David F. 
Published: March 2023

AbstractBinge drinking during adolescence can have behavioral and neurobiological consequences. We have previously found that adolescent intermittent ethanol (AIE) exposure produces a sex-specific social impairment in rats. The prelimbic cortex (PrL) regulates social behavior, and alterations within the PrL resulting from AIE may contribute to social impairments. The current study sought to determine whether AIE-induced PrL dysfunction underlies social deficits in adulthood. We first examined social stimulus-induced neuronal activation of the PrL and several other regions of interest implicated in social behavior. Male and female cFos-LacZ rats were exposed to water (control) or ethanol (4 g/kg, 25% v/v) via intragastric gavage every other day between postnatal day (P) 25 and 45 (total 11 exposures). Since cFos-LacZ rats express β-galactosidase (β-gal) as a proxy for cFos, activated cells that express of β-gal can be inactivated by Daun02. β-gal expression in most ROIs was elevated in socially tested adult rats relative to home cage controls, regardless of sex. However, differences in social stimulus-induced β-gal expression between controls and AIE-exposed rats was evident only in the PrL of males. A separate cohort underwent PrL cannulation surgery in adulthood and were subjected to Daun02-induced inactivation. Inactivation of PrL ensembles previously activated by a social stimulus led to a reduction of social behavior in control males, with no changes evident in AIE-exposed males or females. These findings highlight the role of the PrL in male social behavior and suggest an AIE-associated dysfunction of the PrL may contribute to social deficits following adolescent ethanol exposure.
Utilizing flow cytometry sorting signal width to enrich for cells positive to endogenous gene integration of fluorescent proteins
Authors: Faber Gabriel P. , Hauschner Hagit , Atrash Mohammad Khaled , Bilinsky Liat , Shav-Tal Yaron 
Published: March 2023

AbstractEndogenous gene knock-in using CRIPSR is becoming the standard for fluorescent tagging of endogenous proteins. Some protocols, particularly those that utilize insert cassettes that carry a fluorescent protein tag, can yield many types of cells with off-target insertions that have diffuse fluorescent signal throughout the whole cell in addition to scarce cells with on-target gene insertions that show the correct sub-cellular localization of the tagged protein. As such, when searching for cells with on-target integration using flow cytometry, the off-target fluorescent cells yield a high percentage of false positives. Here, we show that by changing the gating used to select for fluorescence during flow cytometry sorting, namely utilizing the width of the signal as opposed to the area, we can highly enrich for positively integrated cells. Reproducible gates were created to select for even minuscule percentages of correct subcellular signal, and these parameters were validated by fluorescence microscopy. This method is a powerful tool to rapidly enhance the generation of cell-lines with correctly integrated gene knock-ins encoding endogenous fluorescent proteins.
Arteries are finely tuned thermosensors regulating myogenic tone and blood flow
Authors: Phan Thieu X. , Sahibzada Niaz , Ahern Gerard P. 
Published: March 2023

AbstractIn response to changing blood pressure, arteries adjust their caliber to control perfusion. This vital autoregulatory property, termed vascular myogenic tone, stabilizes downstream capillary pressure. We discovered that tissue temperature critically determines myogenic tone. Heating steeply activates tone in skeletal muscle, gut, brain and skin arteries with temperature coefficients (Q10) of ∼11-20. Further, arterial thermosensitivity is tuned to resting tissue temperatures, making myogenic tone sensitive to small thermal fluctuations. Interestingly, temperature and intraluminal pressure are sensed largely independently and integrated to trigger myogenic tone. We show that TRPV1 and TRPM4 mediate heat-induced tone in skeletal muscle arteries. Variations in tissue temperature are known to alter vascular conductance; remarkably, thermosensitive tone counterbalances this effect, thus protecting capillary integrity and fluid balance. In conclusion, thermosensitive myogenic tone is a fundamental homeostatic mechanism regulating tissue perfusion.One-Sentence SummaryArterial blood pressure and temperature are integrated via thermosensitve ion channels to produce myogenic tone.
Parabrachial nucleus activity in nociception and pain in awake mice
Authors: Smith Jesse Andrew , Ji Yadong , Lorsung Rebecca , Breault Macauley Smith , Koenig Jeffrey , Cramer Nathan , Masri Radi , Keller Asaf 
Published: March 2023

AbstractThe parabrachial nuclear complex (PBN) is a nexus for aversion, and for the sensory and affective components of pain perception. We have previously shown that, during chronic pain, PBN neurons in anesthetized rodents have amplified activity. We report a method to record from PBN neurons of behaving, head-restrained mice, while applying reproducible noxious stimuli. We find that both spontaneous and evoked activity are higher in awake animals, compared to urethane anesthetized mice. Fiber photometry of calcium responses from CGRP-expressing PBN neurons demonstrates that these neurons respond to nociceptive stimuli. In both males and females with neuropathic or inflammatory pain, responses of PBN neurons remain amplified for at least 5 weeks, in parallel with increased pain metrics. We also show that PBN neurons can be rapidly conditioned to respond to innocuous stimuli, after pairing with nociceptive stimuli. Finally, we demonstrate that changes in PBN neuronal activity are correlated with changes in arousal, measured as changes in pupil diameter.Significance StatementThe parabrachial complex is a nexus of aversion, including pain. We report a method to record from parabrachial nucleus neurons of behaving mice, while applying reproducible noxious stimuli. This allowed, for the first time, tracking the activity of these neurons over time in animals with neuropathic or inflammatory pain. It also allowed us to show that the activity of these neurons correlates with arousal states, and that these neurons can be conditioned to respond to innocuous stimuli.
Distances and their visualization in studies of spatial-temporal genetic variation using single nucleotide polymorphisms (SNPs)
Authors: Georges Arthur , Mijangos Luis , Kilian Andrzej , Patel Hardip , Aitkens Mark , Gruber Bernd 
Published: March 2023

AbstractDistance measures are widely used for examining genetic structure in datasets that comprise many individuals scored for a very large number of attributes. Genotype datasets composed of single nucleotide polymorphisms (SNPs) typically contain bi-allelic scores for tens of thousands if not hundreds of thousands of loci.We examine the application of distance measures to SNP genotypes and sequence tag presence-absences (SilicoDArT) and use real datasets and simulated data to illustrate pitfalls in the application of genetic distances and their visualization.Euclidean Distance is the metric of choice in many distance studies. However, other measures may be preferable because of their underlying models of divergence, population demographic history and linkage disequilibrium, because it is desirable to down-weight joint absences, or because of other characteristics specific to the data or analyses. Distance measures for SNP genotype data that depend on the arbitrary choice of reference and alternate alleles (e.g. Bray-Curtis distance) should not be used. Careful consideration should be given to which state is scored zero when applying binary distance measures to sequence tag presence-absences (e.g. Jaccard distance).Missing values that arise in the SNP discovery process can cause displacement of affected individuals from their natural groupings and artificial inflation of confidence envelopes, leading to potential misinterpretation. Filtering on missing values then imputing those that remain avoids distortion in visual representations. Failure of a distance measure to conform to metric and Euclidean properties is important but only likely to create unacceptable outcomes in extreme cases. Lack of randomness in the selection of individuals (e.g. inclusion of sibs) and lack of independence of both individuals and loci (e.g. polymorphic haploblocks), can lead to substantial and otherwise inexplicable distortions of the visual representations and again, potential misinterpretation.
Individualized Electrode Subset Improves the Calibration Accuracy of an EEG P300-design Brain-Computer Interface for People with Severe Cerebral Palsy
Authors: Tou Si Long Jenny , Warschausky Seth A. , Karlsson Petra , Huggins Jane E. 
Published: March 2023

AbstractObjectiveThis study examined the effect of individualized electroencephalogram (EEG) electrode location selection for non-invasive P300-design brain-computer interfaces (BCIs) in people with varying severity of cerebral palsy (CP).ApproachA forward selection algorithm was used to select the best performing 8 electrodes (of an available 32) to construct an individualized electrode subset for each participant. BCI accuracy of the individualized subset was compared to accuracy of a widely used default subset.Main ResultsElectrode selection significantly improved BCI calibration accuracy for the group with severe CP. Significant group effect was not found for the group of typically developing controls and the group with mild CP. However, several individuals with mild CP showed improved performance. Using the individualized electrode subsets, there was no significant difference in accuracy between calibration and evaluation data in the mild CP group, but there was a reduction in accuracy from calibration to evaluation in controls.SignificanceThe findings suggested that electrode selection can accommodate developmental neurological impairments in people with severe CP, while the default electrode locations are sufficient for many people with milder impairments from CP and typically developing individuals.
Single-cell transcriptomics of adult skin VE-cadherin expressing lineages during hair cycle
Authors: Chovatiya Gopal , Li Kefei Nina , Ghuwalewala Sangeeta , Tumbar Tudorita 
Published: March 2023

AbstractAdult skin homeostasis involves global reorganization of dermal lineages at different stages of the mouse hair growth cycle. Vascular endothelial cadherin (VE-cadherin encoded byCdh5) expressing cells from blood and lymphatic vasculature structures are known to remodel during the adult hair cycle. Here we employ single-cell RNA-sequencing (scRNA-seq) 10x-genomics analysis of FACS-sorted VE-cadherin expressing cells marked via Cdh5-CreER genetic labeling at resting (telogen) and growth (anagen) stage of hair cycle. Our comparative analysis between the two stages uncovers a persistent Ki67+proliferative EC population and documents changes in EC population distribution and gene expression. Global gene expression changes in all the analyzed populations revealed bioenergetic metabolic changes that may drive vascular remodeling during HF growth phase, alongside a few highly restricted cluster-specific gene expression differences. This study uncovers active cellular and molecular dynamics of adult skin endothelial lineages during hair cycle that may have broad implications in adult tissue regeneration and for understanding vascular disease.
AG3D: A low-cost educational 3D printable toolkit for agarose gel electrophoresis
Authors: Barwick Matthew W , Fanucci Sidne , Mbanxa Siso , Buthelezi Khanyisile , Jukes Michael D , Abrahams Garth L , Prinsloo Earl 
Published: March 2023

AbstractAccess to desktop additive manufacturing is growing and the argument could be made for 3D printers to be standard laboratory equipment. The power of the printers lies in the democratisation of scientific equipment. Traditional agarose gel electrophoresis forms a cornerstone of molecular biology research, teaching and learning. Reliable electrophoresis is dependent on a number of factors which include standardized commercial equipment with respect to casting trays, combs, horizontal tanks and power supplies. The aforementioned systems come at a high initial cost; this is before factoring in the costs of standard electrophoresis grade agarose and associated reagent pricing. Here, we present a basic method for the additive manufacturing of a simple 3D printable agarose gel electrophoresis (AGE) unit with a built-in gel casting tray for standard size microscope slide-based AGE; named AG3D. The system presented was validated using different standard agarose-buffers (Tris Acetate EDTA and Tris Borate EDTA) and commercially available base-pair ladders. We provide a comparison between the AG3D and a commercial AGE system in respect to resolving power of the electrophoresis unit and discuss the overall reduction in cost afforded by the AG3D electrophoresis toolkit. The method presented has the potential for application in low resource educational environments by:Significantly lowering costs through the reduction of reagents (agarose, buffers etc).Allow for the use of low sample volumes.Providing an open-source toolkit for modification whether for research or teaching & learningGraphical abstractSpecifications table