bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fast and flexible Bayesian Jolly Seber models and application to populations with transients
Authors: Saracco James F. , Yackulic Charles B. 
Published: May 2023

AbstractJolly Seber (JS) models are an appealing class of capture-recapture models for modeling open populations because they allow for inferences about an array of population parameters, including abundance, survival, and recruitment. Multiple formulations of JS models have been developed and include both maximum likelihood and Bayesian approaches. Bayesian approaches offer greater flexibility; however, they are often extremely slow when applied to moderate to large populations because the latent states of all observed individuals, as well as any potential unobserved individuals (parameter-expanded data augmentation), must be simulated at each time step.JS model implementations can be sped up dramatically through marginalization, whereby the conditional likelihoods of states are tracked for unique capture histories, rather than the simulated states of all individuals. Here we describe a marginalized implementation of a multistate JS model and compare its performance to that of an implementation using simulated discrete states. We fit models to data generated under two scenarios, one in which no data was missing and another in which 25% of data was randomly removed. To illustrate how marginalization can accommodate more complex models and datasets, we describe a modified version of the model for application to populations with transients and fit the model to simulated data and to data collected on Kentucky Warblers (Geothlypis formosa) as part of the Monitoring Avian Productivity and Survivorship (MAPS) program.Both the discrete latent state and marginalized JS model implementations performed similarly with respect to bias and coverage; however, the marginalized implementation was roughly 1,000 times faster when no data were missing and 100 times faster when 25% of data was missing. The marginalized model accommodating transients also converged quickly and a more complex version of the model applied to the larger multi-site Kentucky Warbler data set yielded useful estimates of most parameters within a reasonable time frame (hours).Gains in efficiency provided by marginalization shown here should stimulate additional study and development of this useful class of models and provide new opportunities for real-world applications to large complex data sets.
Molecular Dynamics simulation of NRAS-Q61 oncogenes and new strategies forin silicodrug design
Authors: Hu Zheyao , Marti Jordi 
Published: May 2023

AbstractThe NRAS-mutant subset of melanoma represents the most aggressive and the deadliest types associated with poorer overall survival. Unfortunately, for more than 40 years, no therapeutic agent directly targeting NRAS mutations have been clinically approved yet. Herein, based on microsecond scale molecular dynamics simulations, the concept of NRAS-Q61 mutation classification was firstly proposed. NRAS Q61 positively charged mutations (Q61R and Q61K) was classified together, with a specific targetable pocket, while NRAS-Q61L classified into another category. Moreover, the isomer-sourced structure iteration (ISSI) method was developed for the in silico design of potential inhibitors (HM-516) targeting NRAS mutations. Overall, through this article, we hope to provide the academic and clinical community with new perspective and understanding of NRAS oncoproteins, and propose possible solution to this challenge.
Mapping oak wilt disease using phenological observations from space
Authors: Guzmán Q. J. Antonio , Pinto-Ledezma Jesús N. , Frantz David , Townsend Philip A. , Juzwik Jennifer , Cavender-Bares Jeannine 
Published: May 2023

ABSTRACTProtecting the future of forests relies on our ability to observe changes in forest health. Thus, developing tools for sensing diseases in a timely fashion is critical for managing threats at broad scales. Oak wilt —a disease caused by a pathogenic fungus (Bretziella fagacearum)— is threatening oaks, killing thousands yearly while negatively impacting the ecosystem services they provide. Here we propose a novel workflow for mapping oak wilt by targeting temporal disease progression through symptoms using land surface phenology (LSP) from spaceborne observations. By doing so, we hypothesize that phenological changes in pigments and photosynthetic activity of trees affected by oak wilt can be tracked using LSP metrics derived from the Chlorophyll/Carotenoid Index (CCI). We used dense time-series observations from Sentinel-2 to create Analysis Ready Data across Minnesota and Wisconsin and to derive three LSP metrics: the value of CCI at the start and end of the growing season, and the coefficient of variation of the CCI during the growing season. We integrate high-resolution airborne imagery in multiple locations to select pixels (n =3,872) from the most common oak tree health conditions: healthy, symptomatic for oak wilt, and dead. These pixels were used to train an iterative Partial Least Square Discriminant (PLSD) model and derive the probability of an oak tree (i.e., pixel) in one of these conditions and the associated uncertainty. We assessed these models spatially and temporally on testing datasets revealing that it is feasible to discriminate among the three health conditions with overall accuracy between 80-82%. Within conditions, our models suggest that spatial variations among three CCI-derived LSP metrics can predict healthily (Area Under the Curve (AUC) = 0.98), symptomatic (AUC = 0.89), and dead (AUC = 0.94) oak trees with low false positive rates. The model performance was robust across different years as well. The predictive maps were used to guide local stakeholders in locating disease hotspots for ground verification and subsequent decision-making for treatment. Our results highlight the capabilities of LSP metrics from dense spaceborne observations to map diseases and their importance for monitoring changes in biodiversity at large scales.
Plasticity-led evolution as an intrinsic property of developmental gene regulatory networks
Authors: Ng Eden Tian Hwa , Kinjo Akira R. 
Published: May 2023

ABSTRACTThe Modern Evolutionary Synthesis seemingly fails to explain how a population can survive a large environmental change: the pre-existence of heritable variants adapted to the novel environment is too opportunistic, whereas the search for new adaptive mutations after the environmental change is so slow that the population may go extinct. Plasticity-led evolution, the initial environmental induction of a novel adaptive phenotype followed by genetic accommodation, has been proposed to solve this problem. However, the mechanism enabling plasticity-led evolution remains unclear. Here, we present computational models that exhibit behaviors compatible with plasticity-led evolution by extending the Wagner model of gene regulatory networks. The models show adaptive plastic response and the uncovering of cryptic mutations under large environmental changes, followed by genetic accommodation. Moreover, these behaviors are consistently observed over distinct novel environments. We further show that environmental cues, developmental processes, and hierarchical regulation cooperatively amplify the above behaviors and accelerate evolution. These observations suggest plasticity-led evolution is a universal property of complex developmental systems independent of particular mutations.
Multimodal gradients of basal forebrain connectivity across the neocortex
Authors: Chakraborty Sudesna , Haast Roy A.M. , Onuska Kate M. , Kanel Prabesh , Prado Marco A.M. , Prado Vania F. , Khan Ali R. , Schmitz Taylor W. 
Published: May 2023

AbstractThe cholinergic innervation of the cortex originates almost entirely from populations of neurons in the basal forebrain (BF). Structurally, the ascending BF cholinergic projections are highly branched, with individual cells targeting multiple different cortical regions. However, it is not known whether the structural organization of basal forebrain projections reflects their functional integration with the cortex. We therefore used high-resolution 7T diffusion and resting state functional MRI in humans to examine multimodal gradients of BF cholinergic connectivity with the cortex. Moving from anteromedial to posterolateral BF, we observed reduced tethering between structural and functional connectivity gradients, with the most pronounced dissimilarity localized in the nucleus basalis of Meynert (NbM). The cortical expression of this structure-function gradient revealed progressively weaker tethering moving from unimodal to transmodal cortex, with the lowest tethering in midcingulo-insular cortex. We used human [18F] fluoroethoxy-benzovesamicol (FEOBV) PET to demonstrate that cortical areas with higher concentrations of cholinergic innervation tend to exhibit lower tethering between BF structural and functional connectivity, suggesting a pattern of increasingly diffuse axonal arborization. Anterograde viral tracing of cholinergic projections and [18F] FEOBV PET in mice confirmed a gradient of axonal arborization across individual BF cholinergic neurons. Like humans, cholinergic neurons with the highest arborization project to cingulo-insular areas of the mouse isocortex. Altogether, our findings reveal that BF cholinergic neurons vary in their branch complexity, with certain subpopulations exhibiting greater modularity and others greater diffusivity in the functional integration of their cortical targets.
What can New Zealand bats tell us about Coronaviruses?
Authors: Tortosa Pablo , McInnes Kate , O’Donnell Colin F. J. , Pryde Moira , Gomard Yann , Lebarbenchon Camille , Poulin Robert 
Published: May 2023

AbstractThe current Covid-19 pandemic emphasizes the dramatic consequences of emerging zoonotic pathogens and stimulates the need for an assessment of the evolution and natural cycle of such microbes in a One Health framework. A number of recent studies have revealed an astonishing diversity of bat-borne Coronaviruses, including in insular environments, which can be considered as simplified biological systems suited for the exploration of the transmission cycles of these viruses in nature. In this work, we present two new lineages of alpha Coronaviruses detected by screening the only two extant New Zealand bat species: the lesser short-tailed bat (Mystacina tuberculata) and the long-tailed bat (Chalinolobus tuberculatus). Infection prevalence reaching 60% in long-tailed bats makes this host-pathogen model relevant for the investigation of maintenance mechanisms in a bat reservoir with peculiar physiological adaptations to temperate climates. A phylogenetic analysis shows that these viral lineages do cluster with Coronaviruses hosted by bat sister species from Australia, supporting co-diversification processes and confirming that the evolution of these viruses is tightly linked to that of their hosts. These patterns provide an interesting framework for further research aiming at elucidating the natural history and biological cycles of these economically-devastating zoonotic viruses.
Sorgoleone degradation by sorghum-associated bacteria; an opportunity for enforcing plant growth promotion
Authors: Oda Yasuhiro , Elmore Joshua R. , Nelson William C. , Wilson Andrew , Farris Yuliya , Shrestha Ritu , Garcia Citlali Fonseca , Pettinga Dean , Ogden Aaron J. , Baldino Henri , Alexander William G. , Deutschbauer Adam M , Hurtado Catalina Vega , McDermott Jason E. , Guss Adam M. , Coleman-Derr Devin , McClure Ryan , Harwood Caroline S. , Egbert Robert G. 
Published: May 2023

AbstractMetabolite exchange between plant roots and their associated rhizosphere microbiomes underpins plant growth promotion by microbes.Sorghum bicoloris a cereal crop that feeds animals and humans and is used for bioethanol production. Its root tips exude large amounts of a lipophilic benzoquinone called sorgoleone. Sorgoleone is an allelochemical that suppresses the growth of competing plant seedlings and is mineralized by microbes in soil. As an avenue to understand how sorghum and its root microbiome may be connected through root exudates, we identified the molecular determinants of microbial sorgoleone degradation and the distribution of this trait among microbes. We isolated and studied from sorghum-associated soils, three bacterial strains classified asAcinetobacter,Burkholderia, andPseudomonasspecies that grow with sorgoleone as a sole carbon and energy source. The genomes of these strains were sequenced and subjected to transcriptomic and gene fitness analyses to identify candidate sorgoleone degradation genes. Follow up mutational analysis showed that sorgoleone catabolism is dependent on four contiguous genes that are conserved among the species we sequenced. Phylogenetic analysis of the sorgoleone degradation gene cluster showed that sorgoleone catabolism is enriched in sorghum-associatedStreptomycesstrains. The discovery of bacteria that grow on a compound like sorgoleone that is plant specific and not widely distributed in the environment, provides an opportunity to study how a plant exudate can enforce the development of a rhizosphere specific microbiome for the mutual benefit of plant and microbe.SignificanceThe grain crop sorghum exudes an herbicidal compound called sorgoleone from its root tips, which inhibits the growth of other plants. We isolated bacteria that grow on sorogleone and identified a cluster of bacterial genes required for sorogleone degradation that can be used as a biomarker for this trait. An approach to improve the production of crops in stressful conditions such as drought, is to encourage their association with plant growth promoting bacteria. Our discovery of sorgoleone degradation genes opens the door to engineering bacteria that receive benefit from sorghum in the form of a plant-specific growth substrate, and in return promote the growth of this crop.
ABI1 regulates transcriptional activity of Androgen Receptor by novel DNA and AR binding mechanism
Authors: Porter Baylee A. , Li Xiang , Arya Neeru , Zhang Fan , Kung Sonia H. Y. , Fazli Ladan , Zarni Oo Htoo , Li Yinan , Marincin Kenneth , Kukkonen Konsta , Urhonen Henna , Ortiz Maria A. , Kemraj Allysa P. , Corey Eva , Dong Xuesen , Kuznetsov Vladimir A. , Nykter Matti , Gleave Martin E. , Bratslavsky Gennady , Urbanucci Alfonso , Frueh Dominique , Bah Alaji , Kotula Leszek 
Published: May 2023

ABSTRACTTranscription regulates key functions of living organisms in normal and disease states, including cell growth and development, embryonic and adult tissue organization, and tumor progression. Here we identify a novel mechanism of transcriptional regulation by an actin regulatory and signaling protein, Abelson Interactor 1 (ABI1). Using prostate cancer models, we uncover a reciprocal regulation between ABI1 and the Androgen Receptor (AR). ABI1 is a direct, androgen-regulated target; in turn, ABI1 interacts with AR and its splice variant ARv7, and co-regulates a subset of specific transcriptional targets. ABI1 directs transcription through transient yet well-defined interaction of its intrinsically disordered region with DNA. Clinical evaluation shows that the ABI1-DNA binding (through Exon 4 splicing) and ABI1-AR interaction are regulated during androgen deprivation therapy and prostate cancer progression, thus controlling tumor plasticity through connecting actin cytoskeleton and cellular signaling to transcriptional regulation. We propose ABI1 as epigenetic regulator of transcriptional homeostasis in AR-driven cancers.Statement of importanceThis study describes fundamental discovery in prostate cancer identifying novel mechanism of transcription by unique DNA binding mechanism involving actin cytoskeleton regulatory protein ABI1. ABI1-DNA binding activity predicts survival of prostate cancer patients. Moreover, we discover ABI1-AR reciprocal regulation that has far reaching implications for tumor plasticity and androgen-sensitive pathogenesis.
ORPA: A Fast and Efficient Method for Constructing Genome-Wide Alignments of Organelle Genomes for Phylogenetic Analysis
Authors: Bi Guiqi , Luan Xinxin , Yan Jianbin 
Published: May 2023

SUMMARYCreating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually, a process that can be time-consuming and prone to errors. The HomBlocks pipeline has been created to eliminate the inaccuracies arising from manual operations. The processing of a large number of sequences, however, remains a time-consuming task. To conquer this challenge, we have developed a speedy and efficient method called ORPA. ORPA quickly generates multiple sequence alignments for whole-genome comparisons by parsing the result files of NCBI BLAST, completing the task in just one minute. With increasing data volume, ORPA’s efficiency is even more pronounced, over 300 times faster than HomBlocks in aligning 60 high-plant chloroplast genomes. The tool’s phylogenetic tree outputs demonstrate equivalent results to HomBlocks, indicating its outstanding efficiency. Due to its speed and accuracy, ORPA can identify species-level evolutionary conflicts, providing valuable insights into evolutionary cognition.
AATF-mediated Liver Damage and Inflammation to Cancer: Therapeutic Intervention by Curcumin in Experimental MASH-HCC
Authors: Srinivas Akshatha N. , Suresh Diwakar , Chidambaram Saravana Babu , Santhekadur Prasanna K. , Kumar Divya P. 
Published: May 2023

AbstractIn tandem with the expanding obesity pandemic, the prevalence of metabolic dysfunction associated steatohepatitis (MASH, formerly known as NASH)-driven hepatocellular carcinoma (HCC) is predicted to rise globally, creating a significant need for therapeutic interventions. We previously identified the upregulation of apoptosis antagonizing transcription factor (AATF), which is implicated in facilitating the progression from MASH to HCC. The objective of this study was to examine whether the intervention of curcumin could alleviate AATF-mediated MASH, inhibit tumor growth, and elucidate the underlying mechanism. A preclinical murine model mimicking human MASH-HCC was employed, subjecting mice to either a chow diet normal water (CDNW) or western diet sugar water (WDSW) along with very low dose of carbon tetrachloride (CCl4-0.2 μl/g, weekly). Mice receiving curcumin (CUR) alongside WDSW/CCl4exhibited significant improvements, including reduced liver enzymes, dyslipidemia, steatosis, inflammation, and hepatocellular ballooning. Curcumin treatment also suppressed hepatic expression of inflammatory, fibrogenic, and oncogenic markers. Of note, there was a significant reduction in the expression of AATF upon curcumin treatment in WDSW/CCl4mice and human HCC cells. In contrast, curcumin upregulated Kruppel-like factor 4 (KLF4) in MASH liver and HCC cells, which is known to downregulate sp1 (specificity protein-1) expression. Thus, curcumin treatment effectively inhibited the progression of MASH to HCC by downregulating the expression of AATF via the KLF4-Sp1 signaling pathway. These preclinical findings establish a novel molecular connection between curcumin and AATF in reducing hepatocarcinogenesis, and provide a strong rationale for the development of curcumin as a viable treatment for MASH-HCC in humans.
Syntenin and CD63 Promote Exosome Biogenesis from the Plasma Membrane by Blocking Cargo Endocytosis
Authors: Ai Yiwei , Guo Chenxu , Garcia-Contreras Marta , Sánchez B. Laura S. , Saftics Andras , Shodubi Oluwapelumi , Raghunandan Shankar , Xu Junhao , Tsai Shang Jui , Dong Yi , Li Rong , Jovanovic-Talisman Tijana , Gould Stephen J. 
Published: May 2023

AbstractExosomes are small extracellular vesicles important in health and disease. Syntenin is thought to drive the biogenesis of CD63 exosomes by recruiting Alix and the ESCRT machinery to endosomes, initiating an endosome-mediated pathway of exosome biogenesis. Contrary to this model, we show here that syntenin drives the biogenesis of CD63 exosomes by blocking CD63 endocytosis, thereby allowing CD63 to accumulate at the plasma membrane, the primary site of exosome biogenesis. Consistent with these results, we find that inhibitors of endocytosis induce the exosomal secretion of CD63, that endocytosis inhibits the vesicular secretion of exosome cargo proteins, and that high-level expression of CD63 itself also inhibits endocytosis. These and other results indicate that exosomes bud primarily from the plasma membrane, that endocytosis inhibits their loading into exosomes, that syntenin and CD63 are expression-dependent regulators of exosome biogenesis, and that syntenin drives the biogenesis of CD63 exosomes even in Alix knockout cells.
Simulating the cellular context in synthetic datasets for cryo-electron tomography
Authors: Martinez-Sanchez Antonio , Lamm Lorenz , Jasnin Marion , Phelippeau Harold 
Published: May 2023

AbstractCryo-electron tomography (cryo-ET) allows to visualize the cellular context at macromolecular level. To date, the impossibility of obtaining a reliable ground truth is limiting the application of deep learning-based image processing algorithms in this field. As a consequence, there is a growing demand of realistic synthetic datasets for training deep learning algorithms. In addition, besides assisting the acquisition and interpretation of experimental data, synthetic tomograms are used as reference models for cellular organization analysis from cellular tomograms. Current simulators in cryo-ET focus on reproducing distortions from image acquisition and tomogram reconstruction, however, they can not generate many of the low order features present in cellular tomograms.Here we propose several geometric and organization models to simulate low order cellular structures imaged by cryo-ET. Specifically, clusters of any known cytosolic or membrane bound macromolecules, membranes with different geometries as well as different filamentous structures such as microtubules or actin-like networks. Moreover, we use parametrizable stochastic models to generate a high diversity of geometries and organizations to simulate representative and generalized datasets, including very crowded environments like those observed in native cells.These models have been implemented in a multiplatform open-source Python package, including scripts to generate cryo-tomograms with adjustable sizes and resolutions. In addition, these scripts provide also distortion-free density maps besides the ground truth in different file formats for efficient access and advanced visualization. We show that such a realistic synthetic dataset can be readily used to train generalizable deep learning algorithms.