bluuebunny/crossref_metadata_2025_split huggingface dataset:
Memory Retrieval Effects as a Function of Differences in Phenomenal Experience
Authors: Schmidt Austin H. , Kirwan C. Brock 
Published: August 2023

AbstractConscious experience and perception are restricted to a single perspective. There is evidence to suggest differences in phenomenal experience can produce observable differences in behavior, however it is not well understood how these differences might influence memory. We used fMRI to scan n=49 participants while they encoded and performed a recognition memory test for faces and words. We calculated a cognitive bias score reflecting individual participants’ propensity toward either Visual Imagery or Internal Verbalization based on their responses to the Internal Representations Questionnaire (IRQ). We found weak positive correlations between memory performance for faces and a bias toward visual imagery and between memory performance for words and bias toward internal verbalization. There were typical patterns of activation differences between words and faces during both encoding and retrieval. There was no effect of internal representation bias on fMRI activation during encoding. At retrieval, however, a bias toward visualization was positively correlated with memory-related activation for both words and faces in inferior occipital gyri. Further, there was a crossover interaction in a network of brain regions such that visualization bias was associated with greater activation for words and verbalization bias was associated with greater activation for faces, consistent with increased effort for non-preferred stimulus retrieval. These findings suggest that individual differences in cognitive representations affect neural activation across different types of stimuli, potentially affecting memory retrieval performance.
Where top-down meets bottom-up: Cell-type specific connectivity map of the whisker system
Authors: Rault N. , Bergmans T. , Delfstra N. , Kleijnen BJ , Zeldenrust F. , Celikel T. 
Published: August 2023

AbstractSensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form action plans. In the rodent whisker system, a prime model of active sensing, evidence shows neuromodulatory neurotransmitters shape whisker control, affecting whisking frequency and amplitude. Since neuromodulatory neurotransmitters are mostly released from subcortical nuclei and have long-range projections that reach the rest of the central nervous system, mapping the circuits of top-down neuromodulatory control of sensorimotor nuclei will help to systematically address the mechanisms of active sensing. Therefore, we developed a neuroinformatic target discovery pipeline to mine the Allen Institute’s Mouse Brain Connectivity Atlas. Using network connectivity analysis, we identified new putative connections along the whisker system and anatomically confirmed the existence of 42 previously unknown monosynaptic connections. Using this data, we updated the sensorimotor connectivity map of the mouse whisker system and developed the first cell-type-specific map of the network. The map includes 157 projections across 18 principal nuclei of the whisker system and neuro-modulatory neurotransmitter-releasing. Performing a graph network analysis of this connectome, we identified cell-type specific hubs, sources, and sinks, provided anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and showed that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.
Octopus arm search strategies over complex surfaces
Authors: Sivitilli Dominic M. , Zulch Ariella , Gire David H 
Published: August 2023

AbstractDespite the extreme flexibility of the octopus’s arms and their resulting near infinite possible configurations, the octopus effectively controls its arms during a wide variety of behaviors, including locomotion, foraging, excavation, exploration, and manipulation. If appropriately characterized, the octopus’s biomechanical properties and control strategies could be implemented in the development of a soft robotic limb with the same range of capabilities. When operating without visual feedback, the octopus must rely on the complex chemotactile sensory system within its suckers, and in these conditions sucker recruitment plays a prominent role in search behavior, causing the arm to conform to surface features in the environment. However, how this mechanism is used to search over the complex and convoluted surfaces in the octopus’s natural habitat is unknown. Here, we investigate the strategies the octopus uses to search for a reward hidden among a row of multiple small openings of a task space, and how it uses multiple arms to search three parallel versions of this task space. We found that when the arm encounters multiple openings in a surface, it performs a distal to proximal search pattern, starting with the farthest openings within reach then working its way proximally with a preference for searching each opening in succession. This strategy would allow the octopus to use its highly flexible limbs to perform an exhaustive search pattern over complex surfaces.
Epigenetic regulation of Leukocyte associated immunoglobulin-like receptors 1 and 2 by interferon signaling in macrophages and T cells
Authors: Dorando Hannah K. , Mutic Evan C. , Li Joanna Y. , Perrin Ezri P. , Wurtz Mellisa , Quinn Chaz C. , Payton Jacqueline E. 
Published: August 2023

ABSTRACTBackgroundInhibitory immune receptors are important for maintaining immune homeostasis. We recently identified epigenetic alterations in two members of this group, LAIR1 and LAIR2, in patients with inflammatory tissue damage and recurrent skin and soft tissue infections. We therefore hypothesized that the expression of LAIR1 and LAIR2 may be controlled by immune stimuli acting on discrete transcriptional regulatory elements.MethodsWe used flow cytometry, qRT-PCR, and RNAseq to assay LAIR1 and LAIR2 expression in human and murine immune cell subsets at baseline and post-treatment with immune mediators, including type I and II interferons, tumor necrosis factor-alpha (TNF-ɑ), and lipopolysaccharide (LPS). Using chromatin immunoprecipitation sequencing (ChIP-seq), we identified candidate transcriptional regulatory elements of LAIR genes and evaluated their regulatory activity using luciferase reporters.ResultsBoth human and murine macrophages significantly upregulate LAIR1 expression as they differentiate from monocytes to macrophages. In response to interferons, LAIR1 protein levels increase, while LPS causes a relative reduction. Regulatory elements flanking LAIR genes exhibit distinct patterns of enhancer activity with variable responses to immune stimuli. These responses are related to discrete sets of transcription factors in inflammatory pathways that correlate with cell-specific LAIR expression patterns. In addition, we identifiedLAIR1andLAIR2regulatory elements that act as foci of 3D genome interactions with other highly active regulatory elements.ConclusionsOur findings define the complex regulatory landscapes of human and mouse LAIR genes and reveal new insights into the transcriptional regulatory mechanisms that control the expression of these important immune modulatory proteins.
MousiPLIER: A Mouse Pathway-Level Information Extractor Model
Authors: Zhang Shuo , Heil Benjamin J. , Mao Weiguang , Chikina Maria , Greene Casey S. , Heller Elizabeth A. 
Published: August 2023

AbstractHigh throughput gene expression profiling is a powerful approach to generate hypotheses on the underlying causes of biological function and disease. Yet this approach is limited by its ability to infer underlying biological pathways and burden of testing tens of thousands of individual genes. Machine learning models that incorporate prior biological knowledge are necessary to extract meaningful pathways and generate rational hypothesis from the vast amount of gene expression data generated to date. We adopted an unsupervised machine learning method, Pathway-level information extractor (PLIER), to train the first mouse PLIER model on 190,111 mouse brain RNA-sequencing samples, the greatest amount of training data ever used by PLIER. mousiPLER converted gene expression data into a latent variables that align to known pathway or cell maker gene sets, substantially reducing data dimensionality and improving interpretability. To determine the utility of mousiPLIER, we applied it to a mouse brain aging study of microglia and astrocyte transcriptomic profiling. We found a specific set of latent variables that are significantly associated with aging, including one latent variable (LV41) corresponding to striatal signal. We next performed k-means clustering on the training data to identify studies that respond strongly to LV41, finding that the variable is relevant to striatum and aging across the scientific literature. Finally, we built a web server (http://mousiplier.greenelab.com/) for users to easily explore the learned latent variables. Taken together this study provides proof of concept that mousiPLIER can uncover meaningful biological processes in mouse transcriptomic studies.Significance statementAnalysis of RNA-sequencing data commonly generates differential expression of individual genes across conditions. However, genes are regulated in complex networks, not as individual entities. Machine learning models that incorporate prior biological information are a powerful tool to analyze human gene expression. However, such models are lacking for mouse despite the vast number of mouse RNA-seq datasets. We trained a mouse pathway-level information extractor model (mousiPLIER). The model reduced the data dimensionality from over 10,000 genes to 196 latent variables that map to prior pathway and cell marker gene sets. We demonstrated the utility of mousiPLIER by applying it to mouse brain aging data and developed a web server to facilitate the use of the model by the scientific community.
Blueberry and cranberry pangenomes as a resource for future genetic studies and breeding efforts
Authors: Yocca Alan E. , Platts Adrian , Alger Elizabeth , Teresi Scott , Mengist Molla F. , Benevenuto Juliana , Felipe V. Ferrão Luis , Jacobs MacKenzie , Babinski Michal , Magallanes-Lundback Maria , Bayer Philipp , Golicz Agnieszka , Humann Jodi L , Main Dorrie , Espley Richard V. , Chagné David , Albert Nick W. , Montanari Sara , Vorsa Nicholi , Polashock James , Díaz-Garcia Luis , Zalapa Juan , Bassil Nahla V. , Munoz Patricio R. , Iorizzo Massimo , Edger Patrick P. 
Published: August 2023

AbstractDomestication of cranberry and blueberry began in the United States in the early 1800s and 1900s, respectively, and in part owing to their flavors and health-promoting benefits are now cultivated and consumed worldwide. The industry continues to face a wide variety of production challenges (e.g. disease pressures) as well as a demand for higher-yielding cultivars with improved fruit quality characteristics. Unfortunately, molecular tools to help guide breeding efforts for these species have been relatively limited compared with those for other high-value crops. Here, we describe the construction and analysis of the first pangenome for both blueberry and cranberry. Our analysis of these pangenomes revealed both crops exhibit great genetic diversity, including the presence-absence variation of 48.4% genes in highbush blueberry and 47.0% genes in cranberry. Auxiliary genes, those not shared by all cultivars, are significantly enriched with molecular functions associated with disease resistance and the biosynthesis of specialized metabolites, including compounds previously associated with improving fruit quality traits. The discovery of thousands of genes, not present in the previous reference genomes for blueberry and cranberry, will serve as the basis of future research and as potential targets for future breeding efforts. The pangenome, as a multiple-sequence alignment, as well as individual annotated genomes, are publicly available for analysis on the Genome Database for Vaccinium - a curated and integrated web-based relational database. Lastly, the core-gene predictions from the pangenomes will serve useful to develop a community genotyping platform to guide future molecular breeding efforts across the family.
Density Physics-Informed Neural Network reveals sources of cell heterogeneity in signal transduction
Authors: Jo Hyeontae , Hong Hyukpyo , Hwang Hyung Ju , Chang Won , Kim Jae Kyoung 
Published: August 2023

SummaryThe transduction time between signal initiation and final response provides valuable information on the underlying signaling pathway, including its speed and precision. Furthermore, multimodality in transduction-time distribution informs that the response is regulated by multiple pathways with different transduction speeds. Here, we developed Density physics-informed neural network (Density-PINN) to infer the transduction-time distribution, challenging to measure, from measurable final stress response time traces. We applied Density-PINN to single-cell gene expression data from 16 promoters regulated by unknown pathways in response to antibiotic stresses. We found that promoters with slower signaling initiation and transduction exhibit larger cell-to-cell heterogeneity in response intensity. However, this heterogeneity was greatly reduced when the response was regulated by slow and fast pathways together. This suggests a strategy for identifying effective signaling pathways for consistent cellular responses to disease treatments. Density-PINN can also be applied to understand various time delay systems, including infectious diseases.
Local climate change velocities explain multidirectional range shifts in a North American butterfly assemblage
Authors: da Silva Carmen R.B. , Diamond Sarah E. 
Published: August 2023

AbstractSpecies are often expected to shift their distributions poleward to evade warming climates. However, from 18 years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards the region that is warming the fastest (southeast). Butterflies shifted their centroids at a mean rate of 4.87 km yr-1. The rate of centroid shift was significantly associated with local climate change velocity (temperature and precipitation), but not with mean climate change velocity throughout the species’ ranges. Surprisingly, the centroid shift was also unrelated to species traits expected to mediate the shift response including thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability). Contrasting with a number of previous studies, we observed relatively high phylogenetic signal in the rate and direction species shifted their centroids, suggesting that evolutionary history helps to explain multidirectional range shift responses and that some groups of species will be better able to shift their ranges than others. This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species’ entire range.
“Patchiness” in Mechanical Stiffness across a Tumor as an Early-Stage Marker for Malignancy
Authors: Mirzakhel Zibah , Reddy Gudur Ashrith , Boman Jennifer , Manns Brianna , Van Teer Savannah , Katira Parag 
Published: August 2023

AbstractMechanical phenotyping of tumors, either at an individual cell level or tumor cell population level is gaining traction as a diagnostic tool. However, the extent of diagnostic and prognostic information that can be gained through these measurements is still unclear. In this work, we focus on the heterogeneity in mechanical properties of cells obtained from a single source such as a tissue or tumor as a potential novel biomarker. We believe that this heterogeneity is a conventionally overlooked source of information in mechanical phenotyping data. We use mechanics-based in-silico models of cell-cell interactions and cell population dynamics within 3D environments to probe how heterogeneity in cell mechanics drives tissue and tumor dynamics. Our simulations show that the initial heterogeneity in the mechanical properties of individual cells and the arrangement of these heterogenous sub-populations within the environment can dictate overall cell population dynamics and cause a shift towards the growth of malignant cell phenotypes within healthy tissue environments. The overall heterogeneity in the cellular mechanotype and their spatial distributions is quantified by a “patchiness” index, which is the ratio of the global to local heterogeneity in cell populations. We observe that there exists a threshold value of the patchiness index beyond which an overall healthy cell population of cells will show a steady shift towards a more malignant phenotype. Based on these results, we propose that the “patchiness” of a tumor or tissue sample, can be an early indicator for malignant transformation and cancer occurrence in benign tumors or healthy tissues. Additionally, we suggest that tissue patchiness, measured either by biochemical or biophysical markers, can become an important metric in predicting tissue health and disease likelihood just as landscape patchiness is an important metric in ecology.
Neurotrophic factor MANF regulates autophagy and lysosome function to promote proteostasis inC. elegans
Authors: Taylor Shane K. B. , Hartman Jessica H. , Gupta Bhagwati P. 
Published: August 2023

ABSTRACTThe conserved mesencephalic astrocyte-derived neurotrophic factor (MANF) protects dopaminergic neurons but also functions in several other tissues. Previously, we showed thatCaenorhabditis elegans manf-1null mutants have increased ER stress, dopaminergic neurodegeneration, protein aggregation, slower growth, and a reduced lifespan. The multiple requirements of MANF in different systems suggest its essential role in regulating cellular processes. However, how intracellular and extracellular MANF regulates broader cellular function remains unknown. Here, we report a novel mechanism of action formanf-1that involves the autophagy transcription factor HLH-30/TFEB-mediated signaling to regulate lysosomal function and aging. We generated multiple transgenic strains overexpressing MANF-1 and found that animals had extended lifespan, reduced protein aggregation, and improved neuronal health. Using a fluorescently tagged MANF-1, we observed different tissue localization of MANF-1 depending on the ER retention signal. Further subcellular analysis showed that MANF-1 localizes within cells to the lysosomes. These findings were consistent with our transcriptomic studies and, together with analysis of autophagy regulators, demonstrate that MANF-1 regulates protein homeostasis through increased autophagy and lysosomal activity. Collectively, our findings establish MANF as a critical regulator of the stress response, proteostasis, and aging.
A systematic review of the performance of actigraphy in measuring sleep stages
Authors: Yuan Hang , Hill Elizabeth A. , Kyle Simon D. , Doherty Aiden 
Published: August 2023

SummaryThe accuracy of actigraphy for sleep staging is assumed to be poor, but examination is limited. This systematic review aimed to assess the performance of actigraphy in sleep stage classification for adults. A systematic search was performed using MEDLINE, Web of Science, Google Scholar, and Embase databases. We identified eight studies that compared sleep architecture estimates between wrist-worn actigraphy and polysomnography. Large heterogeneity was found with respect to how sleep stages were grouped and the choice of metrics used to evaluate performance. Quantitative synthesis was not possible, so we performed a narrative synthesis of the literature. From the limited number of studies, we found that actigraphy-based sleep staging had some ability to classify different sleep stages compared with polysomnography.
Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning
Authors: Meehan Gavin R , Herder Vanessa , Allan Jay , Huang Xinyi , Kerr Karen , Mendonca Diogo Correa , Ilia Georgios , Wright Derek W , Nomikou Kyriaki , Gu Quan , Arias Sergi Molina , De Lorenzo Giuditta , Cowton Vanessa , Upfold Nicole , Palmalux Natasha , Brown Jonathan , Barclay Wendy , Filipe Ana Da Silva , Furnon Wilhelm , Patel Arvind H , Palmarini Massimo 
Published: August 2023

ABSTRACTSARS-CoV-2 has continued to evolve throughout the COVID-19 pandemic, giving rise to multiple variants of concern (VOCs) with different biological properties. As the pandemic progresses, it will be essential to test in near real time the potential of any new emerging variant to cause severe disease. BA.1 (Omicron) was shown to be attenuated compared to the previous VOCs like Delta, but it is possible that newly emerging variants may regain a virulent phenotype. Hamsters have been proven to be an exceedingly good model for SARS-CoV-2 pathogenesis. Here, we aimed to develop robust quantitative pipelines to assess the virulence of SARS-CoV-2 variants in hamsters. We used various approaches including RNAseq, RNAin situhybridization, immunohistochemistry, and digital pathology, including software assisted whole section imaging and downstream automatic analyses enhanced by machine learning, to develop methods to assess and quantify virus-induced pulmonary lesions in an unbiased manner. Initially, we used Delta and Omicron to develop our experimental pipelines. We then assessed the virulence of recent Omicron sub-lineages including BA.5, XBB, BQ.1.18, BA.2 and BA.2.75. We show that in experimentally infected hamsters, accurate quantification of alveolar epithelial hyperplasia and macrophage infiltrates represent robust markers for assessing the extent of virus-induced pulmonary pathology, and hence virus virulence. In addition, using these pipelines, we could reveal how some Omicron sub-lineages (e.g., BA.2.75) have regained virulence compared to the original BA.1. Finally, to maximise the utility of the digital pathology pipelines reported in our study, we developed an online repository containing representative whole organ histopathology sections that can be visualised at variable magnifications (https://covid-atlas.cvr.gla.ac.uk). Overall, this pipeline can provide unbiased and invaluable data for rapidly assessing newly emerging variants and their potential to cause severe disease.