bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing farmed striped catfish (Pangasianodon hypophthalmus) robustness using dietary β-glucan
Authors: Bano Sheeza , Khan Noor , Fatima Mahroze , Khalique Anjum , Arslan Murat , Nazir Sadia , Asghar Muhammad , Khizar Ayesha , Davies Simon John , Wan Alex H. L. 
Published: September 2023

Abstractβ-glucan is a well-documented feed additive for its potent immunostimulatory properties in many farmed fish species. This study examined how it can also be a promising growth promoter, modulate antioxidant enzyme activities, and act as an anti-stress agent in striped catfish (Pangasianodon hypophthalmus). A 12-week feeding experiment was untaken to determine the effects of dietary β-glucan supplementation at graded levels (0, 0.5, 1.0, and 1.5 g kg-1). Measured indicators suggest that a dietary inclusion level of 1.5 g kg-1β-glucan gave the highest positive responses: weight gain (120.10 g fish-1), survival (98.30 %), and lower FCR (1.70) (P<0.05). Whole body proximate analysis had only revealed that crude protein was significantly affected by the dietary inclusion of β-glucan (P<0.05), with the highest protein content (19.70 %) being in fish that were fed with 1.5 g kg-1β-glucan. Although other inclusion levels (i.e., 0.5 and 1 g kg-1) of β-glucan did not enhance body protein content (P>0.05). The assessment of fatty acid composition in muscle, liver, and adipose tissues showed modifications with the inclusion of β-glucan. Antioxidative-related enzyme activities (inc. catalase, glutathione peroxidase, and superoxide dismutase) that were measured in the liver had higher levels when fed with β-glucan inclusion diets (P<0.05). Following the feed trial, fish were subjected to crowding stress treatment. It was subsequently found that catfish fed with β-glucan-based diet groups had lower levels of blood stress-related indicators compared to the control group with no dietary β-glucan. The use of 1.5 g kg-1of dietary β-glucan resulted in the lowest measured levels of cortisol (43.13 ng mL-1) and glucose (50.16 mg dL-1). This study has demonstrated that the dietary inclusion of β-glucan can have functional benefits beyond the immunological enhancements in striped catfish. Furthermore, its use can increase production levels and mitigate the stress associated with intensive farming practices.
The geometry of low- and high-level perceptual spaces
Authors: Waraich Suniyya A. , Victor Jonathan D. 
Published: September 2023

AbstractLow-level features are typically continuous (e.g., the gamut between two colors), but semantic information is often categorical (there is no corresponding gradient between dog and turtle) and hierarchical (animals live in land, water, or air). To determine the impact of these differences on cognitive representations, we characterized the geometry of perceptual spaces of five domains: a domain dominated by semantic information (animal names presented as words), a domain dominated by low-level features (colored textures), and three intermediate domains (animal images, lightly-texturized animal images that were easy to recognize, and heavily-texturized animal images that were difficult to recognize). Each domain had 37 stimuli derived from the same animal names. From 13 subjects (9F), we gathered similarity judgments in each domain via an efficient psychophysical ranking paradigm. We then built geometric models of each domain for each subject, in which distances between stimuli accounted for subjects’ similarity judgments and intrinsic uncertainty. Remarkably, the five domains had similar global properties: each required 5 to 7 dimensions, and a modest amount of spherical curvature provided the best fit. However, the arrangement of the stimuli within these embeddings depended on the level of semantic information: dendrograms derived from semantic domains (word, image, and lightly texturized images) were more ‘tree-like’ than those from feature-dominated domains (heavily texturized images and textures). Thus, the perceptual spaces of domains along this feature-dominated to semantic-dominated gradient have a similar global geometry, but the points within the spaces shift to a tree-like organization when semantic information dominates.Significance StatementUnderstanding the nature of knowledge representation is a fundamental goal of systems neuroscience. Low-level visual features (e.g., color), form continuous domains, while semantic information is typically organized into categories and subcategories. Here, using a novel psychophysical paradigm and computational modeling strategy, we find that despite these major differences, the mental representations of these domains lie in spaces with similar overall geometry. However, within these spaces, semantic information is arranged in a more tree-like representation, and the transition to tree-like representations is relatively abrupt once semantic information becomes apparent. These findings provide insight into visual stream processing at an algorithmic level. Furthermore, they support the idea that processing along the ventral stream reflects commonalities of intrinsic cortical function.
Comparative phylogenomic analyses of SNP versus full locus datasets: insights and recommendations for researchers
Authors: Suissa Jacob S. , De La Cerda Gisel Y. , Graber Leland C. , Jelley Chloe , Wickell David , Phillips Heather R. , Grinage Ayress D. , Moreau Corrie S. , Specht Chelsea D. , Doyle Jeff J. , Landis Jacob B. 
Published: September 2023

AbstractPremiseIn phylogenomic analyses, no consensus exists on whether using single nucleotide polymorphisms (SNPs) or including flanking regions (full ‘locus’) is best, nor how strictly missing data should be filtered. Moreover, empirical evidence on whether SNP-only trees are suitable for downstream phylogenetic comparative methods such as divergence time estimation and ancestral state reconstructions is lacking.MethodsUsing GBS data from 22 taxa ofGlycine, we addressed the effects of SNP vs. locus usage and filtering stringency on phylogenomic inference and phylogenetic comparative methods. We compared branch length, node support, and divergence time estimation across eight datasets with varying amounts of missing data and total size.ResultsOur results reveal five aspects of phylogenomic data usage:1. tree topology is largely congruent regardless of data type or filtering parameters;2. filtering missing data too strictly reduces the confidence in some relationships;3. absolute branch lengths vary by two orders of magnitude between datasets;4. data type and branch length variation have little effect on divergence time estimation;5. phylograms significantly alter the estimation of ancestral states.DiscussionWhen conducting phylogenomic analyses we recommend not to filter datasets too strictly to minimize the risk of misleading topologies, low support, and inaccurate divergence times.
Temporal Variability of Brain-Behavior Relationships in Fine-Scale Dynamics of Edge Time Series
Authors: Cutts Sarah A. , Chumin Evgeny J. , Betzel Richard F. , Sporns Olaf 
Published: September 2023

AbstractMost work on functional connectivity (FC) in neuroimaging data prefers longer scan sessions or greater subject count to improve reliability of brain-behavior relationships or predictive models. Here, we investigate whether systematically isolating moments in time can improve brain-behavior relationships and outperform full scan data. We perform optimizations using a temporal filtering strategy to identify time points that improve brain-behavior relationships across 58 different behaviors. We analyzed functional brain networks from resting state fMRI data of 352 healthy subjects from the Human Connectome Project. Templates were created to select time points with similar patterns of brain activity. Optimizations were performed to produce templates for each behavior that maximize brain-behavior relationships from reconstructed functional networks. With 10% of scan data, optimized templates of select behavioral measures achieved greater strength of brain-behavior correlations and greater transfer between groups of subjects than full FC across multiple cross validation splits of the dataset. Therefore, selectively filtering time points may allow for development of more targeted FC analyses and increased understanding of how specific moments in time contribute to behavioral prediction.Significance StatementIndividuals exhibit significant variations in brain functional connectivity, and these individual differences relate to variations in behavioral and cognitive measures. Here we show that the strength and similarity of brain-behavior associations across groups vary over time and that these relations can be improved by selecting time points that maximize brain-behavior correlations. By employing an optimization strategy for 58 distinct behavioral variables we find that different behaviors load onto different moments in time. Our work suggests new strategies for revealing brain signatures of behavior.
Deep Learning for Protein–peptide binding Prediction: Incorporating Sequence, Structural and Language Model Features
Authors: Chandra Abel , Sharma Alok , Dehzangi Iman , Tsunoda Tatsuhiko , Sattar Abdul 
Published: September 2023

ABSTRACTProtein-peptide interactions play a crucial role in various cellular processes and are implicated in abnormal cellular behaviors leading to diseases such as cancer. Therefore, understanding these interactions is vital for both functional genomics and drug discovery efforts. Despite a significant increase in the availability of protein-peptide complexes, experimental methods for studying these interactions remain laborious, time-consuming, and expensive. Computational methods offer a complementary approach but often fall short in terms of prediction accuracy. To address these challenges, we introduce PepCNN, a deep learning-based prediction model that incorporates structural and sequence-based information from primary protein sequences. By utilizing a combination of half-sphere exposure, position specific scoring matrices, and pre-trained transformer language model, PepCNN outperforms state-of-the-art methods in terms of specificity, precision, and AUC. The PepCNN software and datasets are publicly available athttps://github.com/abelavit/PepCNN.git.
A Quantitative Study of Inappropriate Image Duplication in the JournalToxicology Reports
Authors: David Sholto 
Published: September 2023

AbstractInappropriate image duplication is a type of scientific error that can be detected by examining published literature. Few estimates of the frequency of this problem have been published. This study aimed to quantify the rate of image duplication in the journalToxicology Reports. In total 1540 unique articles (identified by DOI) were checked for the presence of research related images (microscopy, photography, western blot scans, etc). Each research paper containing at least one such image was scrutinized for the presence of inappropriate duplications, first by manual review only, and subsequently with the assistance of an AI tool (ImageTwin.ai). Overall,Toxicology Reportspublished 715 papers containing relevant images, and 115 of these papers contained inappropriate duplications (16%). Screening papers with the use of ImageTwin.ai increased the number of inappropriate duplications detected, with 41 of the 115 being missed during the manual screen and subsequently detected with the aid of the software. In summary, the rate of inappropriate image duplication in this journal has been quantified at 16%, most of these errors could have been detected at peer review by careful reading of the paper and related literature. The use of ImageTwin.ai was able to increase the number of detected problematic duplications.
Accurate single-molecule spot detection for image-based spatial transcriptomics with weakly supervised deep learning
Authors: Laubscher Emily , Wang Xuefei (Julie) , Razin Nitzan , Dougherty Tom , Xu Rosalind J. , Ombelets Lincoln , Pao Edward , Graf William , Moffitt Jeffrey R. , Yue Yisong , Van Valen David 
Published: September 2023

AbstractImage-based spatial transcriptomics methods enable transcriptome-scale gene expression measurements with spatial information but require complex, manually-tuned analysis pipelines. We present Polaris, an analysis pipeline for image-based spatial transcriptomics that combines deep learning models for cell segmentation and spot detection with a probabilistic gene decoder to quantify single-cell gene expression accurately. Polaris offers a unifying, turnkey solution for analyzing spatial transcriptomics data from MERFSIH, seqFISH, or ISS experiments. Polaris is available through the DeepCell software library (https://github.com/vanvalenlab/deepcell-spots) andhttps://www.deepcell.org.
Egocentric vector coding of geometric vertex in the retrosplenial cortex
Authors: Park Kyerl , Yeo Yoonsoo , Shin Kisung , Kwag Jeehyun 
Published: September 2023

AbstractNeural representation of the environmental features in a self-centered, egocentric manner is important in constructing an egocentric cognitive map that is critical for goal-directed navigation and episodic memory formation1. To create a geometrically detailed egocentric cognitive map, neural representations of edges and vertices of environmental features are needed. While egocentric neural representations of edges, like egocentric boundary vector cells2–6and border cells exist7, those of vertices are unknown. Here we report that single neurons in the granular retrosplenial cortex (RSC) generate spatial receptive fields exclusively near the vertices of environmental geometries during free exploration, which we termed vertex cells. Each spatial receptive field of vertex cells occurred at a specific orientation and distance relative to the animal, tuned by head direction, indicating an egocentric vector coding of the vertex. The removal of physical boundaries that define the environmental geometry abolished egocentric vector coding vertex cells. Moreover, goal-directed navigation selectively strengthened the egocentric vertex vector coding at the vertex near the goal location. Overall, our results suggest that egocentric vector coding of vertex by granular RSC neurons help to construct a geometrically detailed egocentric cognitive map that guides goal-directed navigation.
Pathogen infection alters the gene expression landscape of transposable elements inDrosophila melanogaster: A meta-analysis
Authors: Mostoufi Sabrina L. , Singh Nadia D. 
Published: September 2023

ABSTRACTTransposable elements (TEs) are remnants of ancient viral infections and make up substantial proportions of eukaryotic genomes. Current research has begun to highlight the role TEs can play in the immune system response to infections. However, most of our knowledge about TE expression during infection is limited by the specific host and pathogen factors from each study, making it difficult to compare studies and develop broader patterns regarding the role of TEs during infection. Here, we use the tools and resources available in the model,Drosophila melanogaster, to analyze multiple RNAseq datasets of flies subject to bacterial, fungal, and viral infections. We analyzed differences in pathogen species, host genotype, host tissue, and sex to understand how these factors impact TE expression during infection. Our results highlight both shared and unique TE expression patterns between pathogens and suggest a larger effect of pathogen factors over host factors for influencing TE expression.AUTHOR SUMMARYTransposable elements (TEs) are short, repetitive genetic elements that make up substantial proportions of the genomes of all eukaryotic species. These TEs can become expressed during infections, either as a by-product of the infection itself or as a part of the defense mechanism of the immune system. Many studies have investigated TE activity during infection, often focusing on a single pathogen species, one specific host species and genotype, or even a small number of specific TEs. Though these studies provide important detail on these particular cases, less is known about broader patterns of TE activity during infections. Is TE expression the same across different types of infections, and how does the host affect these expression patterns? Here, we analyzed multiple gene expression datasets from infected flies to uncover these broader patterns in TE expression. We found that the type of infection, whether bacterial, fungal, or viral, has a large effect on TE expression. We also found that host factors, like sex, tissue, or genotype, have a much smaller effect on TE expression during infection compared to infection type. Our results offer a broader perspective on how TEs are activated during infections in flies.
Dietary14C reservoir effects and the chronology of prehistoric burials at Sakhtysh, central European Russia
Authors: Meadows John , Khramtsova Anastasia , Kostyleva Elena , Vasilyev Sergey , Veselovskaya Elizaveta , Dobrovolskaya Maria , Silva Nicolas da , Krause-Kyora Ben , Piezonka Henny 
Published: September 2023

AbstractWe present the first robust radiocarbon (14C) chronology for prehistoric burial activity at Sakhtysh, in European Russia, where nearly 180 inhumations attributed to Lyalovo and Volosovo pottery‐using hunter‐gatherer‐fishers represent the largest known mortuary populations of these groups. Past attempts at14C dating were restricted by poor preservation and limited understanding of diet and dietary14C reservoir effects (DREs). We obtained 32 new AMS (Accelerator Mass Spectrometry)14C dates on human petrous bones. Dietary stable isotopes (δ13C, δ15N) for all AMS‐dated human samples allow us to propose a novel DRE correction model, using differences in14C, δ13C and δ15N from bones and teeth of the same individuals to predict DREs of up to c.90014C years. Our chronological model for 40 individuals dates Lyalovo burials to the early 5thmillennium cal BC, and Volosovo burials to the mid‐4thto early 3rdmillennium. It reveals a previously unrecognised shift in the Volosovo subsistence economy at c.3300 cal BC, coinciding with a reorientation of trade networks, and shows that the last burial at Sakhtysh was the only one in a crouched position, which coincided with the beginning of Fatyanovo practices, the regional expression of the Yamnaya/Corded Ware expansion.
Cell layer specific roles for hormones in root development: Gibberellins suppress infection thread progression, promote nodule and lateral root development in the endodermis and interact with auxin and cytokinin
Authors: Velandia Karen , Correa-Lozano Alejandro , McGuiness Peter M. , Reid James B. , Foo Eloise 
Published: September 2023

SummaryGibberellins have a profound influence on the formation of lateral root organs. However, the precise role this hormone plays in the cell-specific events during lateral root formation, rhizobial infection and nodule organogenesis, including interactions with auxin and cytokinin, is not clear.We performed epidermal- and endodermal-specific complementation of the severely gibberellin-deficientnapea (Pisum sativum) mutant withAgrobacterium rhizogenes. Gibberellin mutants were used to examine the spatial expression pattern of cytokinin (TCSn) and auxin (DR5) responsive promoters and hormone levels.We found that gibberellins produced in the endodermis promote lateral root and nodule organogenesis and can induce a mobile signal(s) that suppresses rhizobial infection. In contrast, epidermal-derived gibberellins suppress infection but have little influence on root or nodule development. Gibberellins suppress the cytokinin-responsiveTCSnpromoter in the cortex and are required for normal auxin activation during nodule primordia formation.Our findings indicate that gibberellins regulate the checkpoints between infection thread penetration of the cortex and invasion of nodule primordial cells and promotes the subsequent progression of nodule development. It appears that gibberellins limit the progression and branching of infection threads in the cortex by restricting cytokinin response and activate auxin response to promote nodule primordia development.
EX VIVO GENE EDITING AND CELL THERAPY FOR HEREDITARY TYROSINEMIA TYPE 1
Authors: Ates Ilayda , Rathbone Tanner , Stuart Callie , Barzi Mercedes , He Gordon , Major Angela M. , Srinivasan Shanthi , Farris Alton Brad , Bissig Karl-Dimiter , Cottle Renee N. 
Published: September 2023

ABSTRACTBackground & AimsWe previously demonstrated the successful use ofin vivoCRISPR gene editing to delete 4-hydroxyphenylpyruvate dioxygenase (HPD) to rescue mice deficient in fumarylacetoacetate hydrolase (FAH), a disorder known as hereditary tyrosinemia type 1 (HT1). The goal of this study was to develop anex vivogene editing protocol and apply it as a cell therapy for HT1.MethodsWe isolated hepatocytes from wild-type (C57BL/6) andFah-/-mice and then used an optimized electroporation protocol to deliverHpd-targeting CRISPR-Cas9 ribonucleoproteins (RNP) into hepatocytes. Next, hepatocytes were transiently incubated in cytokine recovery media that we formulated to block apoptosis, followed by splenic injection into recipientFah-/-mice.ResultsWe observed robust engraftment and expansion of transplanted gene-edited hepatocytes from wild-type donors in the liver of recipient mice when transient incubation with our cytokine recovery media was used after electroporation and negligible engraftment without the media (mean 46.8% and 0.83%, respectively, p = 0.0025). Thus, the cytokine recovery media was a critical component of our electroporation protocol. When hepatocytes fromFah-/-mice were used as donors for transplantation, we observed 35% and 28% engraftment forHpd-Cas9 RNPs and Cas9 mRNA, respectively. Tyrosine, phenylalanine, and biochemical markers of liver injury normalized in bothHpd-targeting Cas9 RNP and mRNA groups independent of drug induced-inhibition of Hpd through nitisinone, indicating correction of disease indicators inFah-/-mice.ConclusionsThe successful liver cell therapy for HT1 validates our protocol and, despite the known growth advantage of HT1, showcaseex vivogene editing using electroporation in combination with liver cell therapy to cure a disease model. These advancements showcase the impacts of electroporation combined with transplantation as a cell therapy.
Structural Basis ofStreptomycesAntibiotic Regulatory Proteins Activating Transcription
Authors: Wang Yiqun , Yang Xu , Yu Feng , Deng Zixin , Lin Shuangjun , Zheng Jianting 
Published: September 2023

AbstractStreptomycetes are renowned antibiotic producers, withStreptomycesantibiotic regulatory proteins (SARPs) acting as activators for antibiotic biosynthesis. However, the precise mechanism underlying SARPs’ transcriptional activation remains elusive. Here, we used cryo-electron microscopy (cryo-EM) to unravel the interplay between SARP, DNA, and RNA polymerase (RNAP) during transcriptional activation. The SARP domain ofStreptomyces coelicolorAfsR (SAS) forms a side-by-side dimer contacting theafs boxcentered at −29.5 relative to the transcription start site. The upstream protomer binds to the direct repeat encompassing the −35 element while the σHrdBregion 4 (R4) is positioned on top of both protomers, causing the removal of R4 from the major groove of the −35 element. Both SAS protomers establish interactions with C-terminal domain of one RNAP α subunits, while specific regions of the RNAP β flap tip helix and β’ zinc-binding domain also engage with SAS. Key interfacial residues accounting for transcriptional activation were confirmed by mutational studies andin vitrotranscriptional assays. Overall, our results present a detailed molecular view of how SARPs serve to activate transcription.