bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oscillatory dynamics of sustained attention states
Authors: Solís-Vivanco Rodolfo , Barne Louise , Harris Anthony , Liu Xin , Lavie Nilli 
Published: September 2024

ABSTRACTSustained attention enables individuals to concentrate on a task over an extended period of time. This ability is known to fluctuate, resulting in periods of effective task focus (‘in the zone’) and periods of increased performance variability and susceptibility to errors (‘out of the zone’). Little is known about the oscillatory neural dynamics that underlie each of these states and their transitions during sustained attention tasks. To address this, we had thirty young adults perform the gradual onset continuous performance task (gradCPT), during which their EEG and behavioural responses were recorded. States of sustained attention (in vs. out of the zone) throughout the task were identified based on the variance time course of participants’ reaction times. Out of the zone states were associated with increased errors of commission and reduced perceptual sensitivity compared to in the zone states, as expected. Importantly, a significant decline in theta oscillations at mid-prefrontal regions was found in out of the zone (vs. in the zone) states over a ∼400 ms period around the transition point between stimuli, and the extent of this decline predicted commission errors, RT variability, and response bias. In addition, individual differences in the variability of frontal theta rhythm were associated with RT variability. Finally, participants exhibiting greater theta variability showed a more pronounced decline in perceptual sensitivity when out of the zone and less stable RTs compared to those with lower variability. Our results suggest that states of diminished sustained attention, even during short lapses, are characterized by a reduction in frontal theta activity, and that fluctuations in this rhythm covary with fluctuations in attentional control.
Lipophilic molecular rotor to assess the viscosity of oil core in nano-emulsion droplets
Authors: Elhassan Mohamed , Faivre Carla , Anton Halina , Conzatti Guillaume , Didier Pascal , Vandamme Thierry , Elamin Alteyeb S. , Collot Mayeul , Anton Nicolas 
Published: September 2024

AbstractHypothesisCharacterization of nanoscale formulations is a continuous challenge. Size, morphology and surface properties are the most common characterizations. However, physicochemical properties inside the nanoparticles, like viscosity, cannot be directly measured. Herein, we propose an original approach to measuring dynamic viscosity using a lipidic molecular rotor solubilized in the core of nano-formulations. These molecules undergo conformational changes in response to viscosity variations, leading to observable changes in fluorescence intensity and lifetime, able to sense the volume properties of dispersed nano-domains.ExperimentsThe lipophilic molecular rotor (BOPIDY derivatives) was specifically synthesized and characterized as oil viscosity sensing in large volumes. A second part of the study compares these results with rBDP-Toco in nano-emulsions. The objective is to evaluate the impact of the formulation, droplet size and composition on the viscosity of the droplet’s core.FindingsThe lipophilic rotor showed a universal behavior whatever the oil composition, giving a master curve. Applied to nano-formulations, it discloses the viscosity in the nano-emulsion droplets, enabling the detection of slight variations between reference oil samples and the nano-formulated ones. This new tool opens the way to the fine characterization of complex colloids and multi-domain nano and micro systems, potentially applied to hybrid materials and biomaterials.
A slippery slope: assessing the amphibian extinction crisis through the lens of climate refugia
Authors: Andersen Desiree , Borzée Amaël , Jang Yikweon 
Published: September 2024

AbstractIn a time of increasing climate uncertainty, it is ever important to identify and preserve refuges for species, optimizing the effort to cover the largest possible number of clades. Climatic refugia are areas of climatic stability that will remain suitable for species over time under multiple climate change scenarios. Amphibians are important indicators of biodiversity and ecosystem health, in addition to being the most threatened class of vertebrates and can therefore serve as proxies to designate protected areas. In this study, we use ecological modeling to delineate current distributions of all amphibian species with adequate data globally. We then projected these distributions to four climate change scenarios, and four time periods, under two climate models representing low and high climate sensitivity. Climate refugia by species were calculated as the average of all climate change scenarios and time periods and were calculated separately for the two climate models of low and high sensitivity. We additionally extracted areas of current distributions and refugia to geographic regions, Udvardy biomes, and global protected areas. With the high climate sensitivity model (CNRM-CM6-1), 2,959 species would experience a refugia area that is reduced from their current distribution, with 139 species having no refugia area. Under the low climate sensitivity model (MIROC6), 2,864 species would have a reduction in area, with 136 having no refugia. While both climate models yielded similar results in terms of percent change, the MIROC6 model overall had less of a negative impact on species’ refugia. The results of this study present a somber warning of the amphibian extinction crisis in contrast to some of the recent literature, as well as encouragement for managers to act in order to preserve species and the ecosystems they represent.
Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma
Authors: Kader Tanjina , Lin Jia-Ren , Hug Clemens , Coy Shannon , Chen Yu-An , de Bruijn Ino , Shih Natalie , Jung Euihye , Pelletier Roxanne J. , Leon Mariana Lopez , Mingo Gabriel , Omran Dalia Khaled , Lee Jong Suk , Yapp Clarence , Satravada Baby Anusha , Kundra Ritika , Xu Yilin , Chan Sabrina , Tefft Juliann B. , Muhlich Jeremy , Kim Sarah , Gysler Stefan M. , Agudo Judith , Heath James R. , Schultz Nikolaus , Drescher Charles , Sorger Peter K , Drapkin Ronny , Santagata Sandro 
Published: September 2024

ABSTRACTHigh-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC. Our findings reveal immune modulating mechanisms within precursor epithelium, characterized by chromosomal instability, persistent interferon (IFN) signaling, and dysregulated innate and adaptive immunity. FT precursors display elevated expression of MHC-class I, including HLA-E, and IFN-stimulated genes, typically linked to later-stage tumorigenesis. These molecular alterations coincide with progressive shifts in the tumor microenvironment, transitioning from immune surveillance in early STICs to immune suppression in advanced STICs and cancer. These insights identify potential biomarkers and therapeutic targets for HGSOC interception and clarify the molecular transitions from precancer to cancer.STATEMENT OF SIGNIFICANCEThis study maps the immune response in fallopian tube precursors of high-grade serous ovarian cancer, highlighting localized interferon signaling, CIN, and competing immune surveillance and suppression along the progression axis. It provides an explorable public spatial profiling atlas for investigating precancer mechanisms, biomarkers, and early detection and interception strategies.
Exploring the use of environment-agent-based models for risk assessment of Great Lakes piping plovers
Authors: Edwards Brandon P.M. , Jacobs Shoshanah , Gillis Daniel 
Published: September 2024

AbstractThe Piping PloverCharadrius melodusis an endangered species of shorebird endemic to North America. This species has been the centre of many modelling studies in the last decade. One model type that has been underused in Piping Plover studies is agent-based modelling, which can be used as an accurate risk assessment tool in simulating effects of anthropogenic activities on a given animal species. Recent innovations in ecological modelling have given rise to the environmental agent-based model (enviro-ABM), which efficiently stores information about spatially indexed environmental cells and treat those as agents. This restricts computation to only focus on environmental cells containing the species we are studying, allowing for a more efficient simulation. Using Python, a high-level programming language popular in scientific computing, we develop an enviro-ABM to provide simulations of Piping Plover hatchling growth during a given breeding season. We experiment with increasing levels of human presence and human exclosure size and observe their effects on the growth rate of the simulated Piping Plover hatchlings. Our simulations showed a clear decrease in Piping Plover growth rate as anthropogenic presence increased in the simulated environment. However, when we added a 100 m human exclosure around the nest, the effects of the anthropogenic presence were mitigated at each level. We conclude that an enviro-ABM can be used to assist with conservation and management decisions, with the caveat that the model be constantly updated and informed with results of field studies, especially those pertaining to foraging and energetics of Piping Plovers.
A joint framework for studying population structure using principal component analysis and F-statistics
Authors: Popli Divyaratan , Peter Benjamin M. 
Published: September 2024

AbstractPrincipal component analysis (PCA) andF-statistics are routinely used in population genetic and archaeogenetic studies. Here, we present a statistical framework to combine them into a joint analysis, showing where they coincide, and where slightly different assumptions made can lead to different outcomes. In particular, we discuss the differences of probabilistic PCA, Latent Subspace Estimation and classical PCA, and show thatF-statistics are more naturally interpreted in a probabilistic PCA framework. We also show that individual-basedF-statistics can be accurately estimated from probabilistic PCA in the presence of large amounts of missing data. We compare estimates from probabilistic PCA-based framework to ADMIXTOOLS 2 using simulations and published data, and show that this joint estimation framework addresses limitations of estimating F-statistics and PCA independently.
Leveraging cell type-specificity for gene set analysis of single cell transcriptomics
Authors: Frost H. Robert 
Published: September 2024

AbstractAlthough single cell RNA-sequencing (scRNA-seq) provides unprecedented insights into the biology of complex tissues, analyzing such data on a gene-by-gene basis is challenging due to the large number of tested hypotheses and consequent low statistical power and difficult interpretation. These issues are magnified by the increased noise, significant sparsity and multi-modal distributions characteristic of single cell data. One promising approach for addressing these challenges is gene set testing, or pathway analysis. Unfortunately, statistical and biological differences between single cell and bulk transcriptomic data make it challenging to use existing gene set collections, which were developed for bulk tissue analysis, on scRNA-seq data. In this paper, we describe a procedure for customizing gene set collections originally created for bulk tissue analysis to reflect the structure of gene activity within specific cell types. Our approach leverages information about mean gene expression in the 81 human cell types profiled via scRNA-seq by the Human Protein Atlas (HPA) Single Cell Type Atlas. This HPA information is used to compute cell type-specific gene and gene set weights that can be used to filter or weight gene set collections. As demonstrated through the analysis of immune cell scRNA-seq data using gene sets from the Molecular Signatures Database (MSigDB), accounting for cell type-specificity can significantly improve gene set testing power and interpretability. An example vignette along with gene and gene set weights for the 81 HPA SCTA cell types and the MSigDB collections are available athttps://hrfrost.host.dartmouth.edu/SCGeneSetOpt/.
Controlled release of microorganisms from engineered living materials
Authors: Kalairaj Manivannan Sivaperuman , George Iris , George Sasha M. , Farfán Sofía E. , Lee Yoo Jin , Rivera-Tarazona Laura K. , Wang Suitu , Abdelrahman Mustafa K. , Tasmim Seelay , Dana Asaf , Zimmern Philippe E. , Subashchandrabose Sargurunathan , Ware Taylor H. 
Published: September 2024

ABSTRACTProbiotics offer therapeutic benefits by modulating the local microbiome, the host immune response, and the proliferation of pathogens. Probiotics have the potential to treat complex diseases, but their persistence or colonization is required at the target site for effective treatment. Although probiotic persistence can be achieved by repeated delivery, no biomaterial that releases clinically relevant doses of metabolically active probiotics in a sustained manner has been previously described. Here, we encapsulate stiff probiotic microorganisms within relatively less stiff hydrogels and show a generic mechanism where these microorganisms proliferate and induce hydrogel fracture, resulting in microbial release. Importantly, this fracture-based mechanism leads to microorganism release with zero-order release kinetics. Using this mechanism, small (∼1 μL) engineered living materials (ELMs) release >108colony-forming-units (CFUs) ofE. coliin 2 h. This release is sustained for at least 10 days. Cell release can be varied by more than three orders of magnitude by varying initial cell loading and modulating the mechanical properties of encapsulating matrix. As the governing mechanism of microbial release is entirely mechanical, we demonstrate controlled release of model Gram-negative, Gram-positive, and fungal probiotics from multiple hydrogel matrices.SIGNIFICANCEProbiotics offer therapeutic benefits and have the potential to treat complex diseases, but their persistence at the target site is often required for effective treatment. Although probiotic persistence can be achieved by repeated delivery, no biomaterial that releases metabolically active probiotics in a sustained manner has been developed yet. This work demonstrates a generic mechanism where stiff probiotics encapsulated within relatively less stiff hydrogels proliferate and induce hydrogel fracture. This allows a zero-order release of probiotics which can be easily controlled by adjusting the properties of the encapsulating matrices. This generic mechanism is applicable for a wide range of probiotics with different synthetic matrices and has the potential to be used in the treatment of a broad range of diseases.
Cross-species evidence for a developmental origin of adult hypersomnia with loss of synaptic adhesion moleculesbeat-Ia/CADM2
Authors: Mace Kyla , Zimmerman Amber , Chesi Alessandra , Doldur-Balli Fusun , Kim Hayle , Almeraya Del Valle Erika , Pack Allan I. , Grant Struan F.A. , Kayser Matthew S. 
Published: September 2024

AbstractIdiopathic hypersomnia (IH) is a poorly-understood sleep disorder characterized by excessive daytime sleepiness despite normal nighttime sleep. Combining human genomics with behavioral and mechanistic studies in fish and flies, we uncover a role forbeat-Ia/CADM2, synaptic adhesion molecules of the immunoglobulin superfamily, in excessive sleepiness. Neuronal knockdown of Drosophilabeat-Iaresults in sleepy flies and loss of the vertebrate ortholog ofbeat-Ia,CADM2, results in sleepy fish. We delineate a developmental function forbeat-Iain synaptic elaboration of neuropeptide F (NPF) neurites projecting to the suboesophageal zone (SEZ) of the fly brain. Brain connectome and experimental evidence demonstrate these NPF outputs synapse onto a subpopulation of SEZ GABAergic neurons to stabilize arousal. NPF is the Drosophila homolog of vertebrate neuropeptide Y (NPY), and an NPY receptor agonist restores sleep to normal levels in zebrafish lackingCADM2. These findings point towards NPY modulation as a treatment target for human hypersomnia.
Elucidating the role of multiple feedback loops in regulating stem cell decisions
Authors: Shaikh Razeen , Reeves Gregory T. 
Published: September 2024

AbstractStem cell decisions are regulated by a complex network of gene regulatory pathways that determine the reproductive health of the tissue. TheDrosophilaovarian germline is a well-characterized model system which facilitates visualizing stem cell behavior in its native environment to attain a systems-level understanding of the stem cell dynamics. The asymmetric division of the Germline Stem Cells (GSCs) forms two daughter cells–a self-renewed GSC and a differentiated Cystoblast (CB). The highly conserved Bone Morphogenetic Protein (BMP) pathway ensures growth and maintenance of the GSCs, but is downregulated in the CBs, to allow for differentiation. BMP signal transduction upregulatesdadand represses Fused, both of which are negative regulators of the BMP pathway. Moreover, these regulatory mechanisms operate on a system of two cells which remain connected during a portion of the cell cycle. We developed a biologically-informed mathematical model of multi-compartment GSC division to investigate the dynamic roles Dad and Fused play in determining cell fate. We found that Dad optimally controls the BMP signal transduction to enable GSC homeostasis and differentiation. IndadKOmutants, GSCs were more likely to divide symmetrically. Our work identifies the synergistic role of Dad and Fused rendering robustness to stem cell division.
Maximizing memory capacity in heterogeneous networks
Authors: Zhang Kaining , Tavoni Gaia 
Published: September 2024

AbstractA central problem in neuroscience is identifying the features of neural networks that determine their memory capacity and assessing whether these features are optimized in the brain. In this study, we estimate the capacity of a general class of network models. Our derivation extends previous theoretical results, which assumed homogeneous connections and coding levels (i.e., activation rates of the neurons in memory patterns), to models with arbitrary architectures (varying constraints on the arrangement of connections between cells) and heterogeneous coding levels. Using our analytical results, we estimate the memory capacity of two types of brain-inspired networks: a general class of heterogeneous networks and a two-layer model simulating the CA3-Dentate Gyrus circuit in the hippocampus, known to be crucial for memory encoding. In the first case, we demonstrate that to maximize memory capacity, the number of inward connections and the coding levels of neurons must be correlated, presenting a normative prediction that is amenable to experimental testing. In the second case, we show that memory capacity is maximized when the connectivity and coding levels are consistent with the formation of memory “indices” in the Dentate Gyrus, which bind features in the CA3 layer. This suggests specific neural substrates for the hippocampal index theory of memory encoding and retrieval.
Ultra-Fast Multi-Organ Proteomics Unveils Tissue-Specific Mechanisms of Drug Efficacy and Toxicity
Authors: Xiong Yun , Tan Lin , Chan Wai-kin , Yin Eric S. , Donepudi Sri Ramya , Ding Jibin , Wei Bo , Tran Bao , Martinez Sara , Mahmud Iqbal , Stewart Hamish I. , Hermanson Daniel J. , Weinstein John N. , Lorenzi Philip L. 
Published: September 2024

AbstractRapid and comprehensive analysis of complex proteomes across large sample sets is vital for unlocking the potential of systems biology. We present UFP-MS, an ultra-fast mass spectrometry (MS) proteomics method that integrates narrow-window data-independent acquisition (nDIA) with short-gradient micro-flow chromatography, enabling profiling of >240 samples per day. This optimized MS approach identifies 6,201 and 7,466 human proteins with 1- and 2-min gradients, respectively. Our streamlined sample preparation workflow features high-throughput homogenization, adaptive focused acoustics (AFA)-assisted proteolysis, and Evotip-accelerated desalting, allowing for the processing of up to 96 tissue samples in 5 h. As a practical application, we analyzed 507 samples from 13 mouse tissues treated with the enzyme-drug L-asparaginase (ASNase) or its glutaminase-free Q59L mutant, generating a quantitative profile of 11,472 proteins following drug treatment. The MS results confirmed the impact of ASNase on amino acid metabolism in solid tissues. Further analysis revealed broad suppression of anticoagulants and cholesterol metabolism and uncovered numerous tissue-specific dysregulated pathways. In summary, the UFP-MS method greatly accelerates the generation of biological insights and clinically actionable hypotheses into tissue-specific vulnerabilities targeted by ASNase.
Ironing out the role of Nrf2 in cardiac iron metabolism during myocardial infarction
Authors: Jayakumar Deepthy , Narasimhan Kishore Kumar S. , Rajkumar Abinayaa , Panchalingam Gokul Prasanth , Chandrasekar Navvi , Ravikumar Varsha C. , Periandavan Kalaiselvi 
Published: September 2024

ABSTRACTBackground and PurposeIron plays a crucial role in maintaining cardiac health. However, existing research has focused on understanding how cardiac cells regulates intercellular iron levels through their own cell-autonomous cardiac hepcidin/ferroportin axis. In Addition, several studies have explored the mechanisms linking cardiac dysfunction with iron imbalance. Recent insights also emphasize the importance of Nrf2, a key transcriptional regulator that not only counteracts iron-mediated oxidative stress, but also governs several genes involved in iron metabolism. Consequently, the Nrf2/hepcidin/ferroportin axis is emerging as a central hub connecting cardiac iron metabolism with redox alterations. However, the precise mechanisms linking these components remain elusive. This study aims to elucidate how disruptions in the Nrf2/hepcidin/ferroportin axis contribute to the altered iron metabolism in Myocardial infarction (MI).Experimental ApproachMI was induced in adult Wistar rats by subcutaneous administration of isoproterenol (ISO; 85 mg/kg body weight) for two days. H9c2 cardiomyoblasts were differentiated into cardiomyocytes using all-trans-retinoic acid (ATRA, 2.5μM for 5-days) and subjected to hypoxic stress using CoCl2(100μM).In vitropharmacological suppression of Nrf2 was performed using brusatol (50nM).Key ResultsMorphological examination revealed maladaptive remodeling, and histopathological analysis demonstrated disoriented myofibrils with intense neutrophil infiltration and necrotic impressions in MI-affected animals. Furthermore, elevated levels of labile redox-active iron and inflammatory markers were observed in serum of ISO induced animals. qPCR & Western blot analysis indicated an increase in HIF-1α and hepcidin levels, and downregulation of FTH levels in MI-induced animals, with no significant changes observed in FPN-1. The transcriptional activity of Nrf2 is enhanced in the MI-heart. Moreover, increased levels of NCOA4, beclin-1, and LC3-II/LC3-I, along with decreased p62, suggest enhanced ferritinophagy in MI-induced hearts. Nrf2 was pharmacologically suppressed in differentiated H9c2 cardiomyocytes to explore its potential role in MI pathophysiology. Remarkably, this inhibition rescued CoCl2-induced hypoxic stress, as evidenced by the decreased ferritinophagy and apoptotic cell death.Conclusion and ImplicationsAugmented Nrf2-transcriptional activity disrupts iron metabolism through the hepcidin/ferroportin axis, leading to iron sequestration and promoting ferritinophagy within cardiomyocytes, thereby exacerbating MI.