bluuebunny/crossref_metadata_2025_split huggingface dataset:
Generalized disformal Horndeski theories: Cosmological perturbations and consistent matter coupling
Authors: Takahashi Kazufumi , Minamitsuji Masato , Motohashi Hayato 
Published: November 2022

Abstract
Invertible disformal transformations are a useful tool to investigate ghost-free scalar–tensor theories. By performing a higher-derivative generalization of the invertible disformal transformation on Horndeski theories, we construct a novel class of ghost-free scalar–tensor theories, which we dub generalized disformal Horndeski theories. Specifically, these theories lie beyond the quadratic/cubic DHOST class. We explore cosmological perturbations to identify a subclass where gravitational waves propagate at the speed of light and clarify the conditions for the absence of ghost/gradient instabilities for tensor and scalar perturbations. We also investigate the conditions under which a matter field can be consistently coupled to these theories without introducing unwanted extra degrees of freedom.
The chloroplast envelope localization of protoporphyrinogen oxidase 2 prevents full complementation of Arabidopsisppo1
Authors: Hedtke Boris , Strätker Sarah Melissa , Chiappe Pullido Andrea C. , Grimm Bernhard 
Published: November 2022

AbstractAll land plants encode two isoforms of protoporphyrinogen oxidase (PPO). While PPO1 is predominantly expressed in green tissues and its loss is seedling-lethal in Arabidopsis, the effects of PPO2 deficiency have not been investigated in detail. We identified twoppo2T-DNA insertion mutants from publicly available collections, one of which (ppo2-2) is a knock-out mutant. While the loss of PPO2 did not result in any obvious phenotype, significant changes in PPO activity were measured in etiolated and root tissues. However,ppo1ppo2double mutants are embryo-lethal. To shed light on possible functional differences between the two isoforms, PPO2 was overexpressed in theppo1background. Although theppo1phenotype was partially complemented, even strong overexpression of PPO2 was unable to fully compensate for the loss of PPO1. Analysis of its subcellular localization revealed that PPO2 is found exclusively in chloroplast envelopes, while PPO1 accumulates in thylakoid membranes. A mitochondrial localization of PPO2 in Arabidopsis was ruled out. SinceA. thaliana PPO2does not encode a cleavable transit peptide, integration of the protein into the chloroplast envelope must make use of a non-canonical import route. However, when a chloroplast transit peptide was fused to the N-terminus of PPO2, the enzyme was detected predominantly in thylakoid membranes, and was able to fully complementppo1. Thus, the two PPO isoforms in Arabidopsis are functionally equivalent, but spatially separated. Their distinctive localizations within plastids thus enable the synthesis of discrete sub-pools of the PPO product protoprophyrin IX, which may serve different cellular needs.
An Early SARS-CoV-2 Omicron Outbreak in a Dormitory in Saint-Petersburg, Russia
Authors: Klink Galya V. , Danilenko Daria M. , Komissarov Andrey B. , Yolshin Nikita , Shneider Olga V. , Shcherbak Sergey , Nabieva Elena , Shvyrev Nikita , Konovalova Nadezhda , Zheltukhina Alyona , Fadeev Artem , Komissarova Kseniya , Ksenafontov Andrey , Musaeva Tamila , Eder Veronica , Pisareva Maria , Nekrasov Petr , Shchur Vladimir , Bazykin Georgii A. , Lioznov Dmitry 
Published: November 2022

AbstractThe Omicron variant of SARS-CoV-2 has rapidly spread globally in late 2021 - early 2022, displacing the previously prevalent Delta variant. Before December 16, 2021, community transmission had already been observed in tens of countries globally. However, in Russia, the majority of reported cases at that time had been sporadic and associated with travel. Here, we report an Omicron outbreak at a student dormitory in Saint Petersburg between December 16 - 29, 2021, which was the earliest known instance of large-scale community transmission in Russia. Out of the 465 sampled residents of the dormitory, 180 (38.7%) tested PCR positive. Among the 118 residents for whom the variant has been tested by whole-genome sequencing, 111 (94.1%) carried the Omicron variant. Among these 111 residents, 60 (54.1%) were vaccinated or had reported previous COVID-19. Phylogenetic analysis confirmed that the outbreak was caused by a single introduction of the BA.1.1 sublineage of Omicron. The dormitory-derived clade constituted a significant proportion of BA.1.1 samples in Saint-Petersburg and has spread to other regions of Russia and other countries. The rapid spread of Omicron in a population with preexisting immunity to previous variants underlines its propensity for immune evasion.
ArabidopsisORP2A positively regulates glucose signaling by interacting with AtRGS1 and promoting AtRGS1 degradation
Authors: Yu Qian , Zou Wenjiao , Liu Kui , Sun Jialu , Chao Yanru , Sun Mengyao , Zhang Qianqian , Wang Xiaodong , Wang Xiaofei , Ge Lei 
Published: November 2022

SUMMARYHeterotrimeric GTP-binding proteins (G proteins) are a group of regulators essential for signal transmission into cells. AtRGS1 (Regulator of G protein Signaling 1) with intrinsic GTPase-accelerating protein (GAP) activity could suppress G protein and glucose signal transduction inArabidopsis. However, how AtRGS1 activity is regulated is currently poor understood. Here we identified a knockout mutantorp2a-1(oxysterol-binding protein(OSBP)-related protein 2A) which shows phenotypes similar toagb1-2(arabidopsis g-protein beta 1). With overexpression of ORP2A, transgenic lines display short hypocotyl, hypersensitivity to sugar and lower intracellular AtRGS1 level than control. Consistently, ORP2A shows interaction with AtRGS1in vitroandvivo. Tissue specificity of ORP2A with two alternative protein forms imply its functions in organ size and shape controlling. Bioinformatic data and phenotypes oforp2a-1, agb1-2and double mutant reveal genetic interactions in the regulation of G protein signaling and sugar response between ORP2A and Gβ. Both alternative splicing forms of ORP2A locate in the ER, PM (Plasma Membrane) and EPCS (ER-PM Contact Sites), and interact with VAP27-1 mediated by a FFAT-like motifin vivoandvitro. ORP2A also displays differential phosphatidyl phosphoinositide binding activity mediated by its PH domain invitro. Taken together, it is suggested thatArabidopsismembrane protein ORP2A interacts with AtRGS1 and VAP27-1 to positively regulate G protein and sugar signaling by facilitating AtRGS1 degradation.
Differential leaf flooding resilience inArabidopsis thalianais controlled by age-dependent ORESARA1 activity
Authors: Rankenberg Tom , van Veen Hans , Sedaghatmehr Mastoureh , Liao Che-Yang , Devaiah Muthanna Biddanda , Balazadeh Salma , Sasidharan Rashmi 
Published: November 2022

AbstractThe volatile phytohormone ethylene is a major regulator of plant adaptive responses to flooding. In flooded plant tissues, it quickly increases to high concentrations due to its low solubility and diffusion rates in water. The passive, quick and consistent accumulation of ethylene in submerged plant tissues makes it a reliable cue to trigger flood-acclimative responses, including metabolic adjustments to cope with flood-induced hypoxia. However, persistent ethylene accumulation also accelerates leaf senescence. Stress-induced senescence hampers the photosynthetic capacity and stress recovery. In submergedArabidopsisshoots, senescence follows a strict age-dependent pattern starting with the older leaves. Although mechanisms underlying ethylene-mediated senescence have been uncovered, it is unclear how submerged plants avoid an indiscriminate breakdown of leaves despite high systemic ethylene accumulation. Here we demonstrate inArabidopsisplants that even though submergence triggers a leaf-age independent activation of ethylene signaling via EIN3, senescence was initiated only in the old leaves, and independent of the N-degron pathway of oxygen sensing. This EIN3 stabilization also led to the overall transcript and protein accumulation of the senescence-promoting transcription factor ORESARA1 (ORE1). ORE1 protein accumulated in both old and young leaves during submergence. However, leaf age-dependent senescence could be explained by ORE1 protein activation specifically in old leaves, independent of the previously identified age-dependent control ofORE1via miR164. Our results unravel a mechanism by which plants regulate the speed and pattern of senescence during environmental stresses like flooding. The age-dependent activity of ORE1 ensures that older expendable leaves are dismantled first, thus prolonging the life of younger leaves and meristematic tissues vital to whole plant survival.Significance statementFlooded plants systemically accumulate saturating concentrations of the senescence promoting volatile hormone ethylene. Yet, leaf senescence follows a strict age-dependent gradient, thus prolonging the survival of young leaves and meristematic tissue. Here we show that in flooded plants, age-independent activation of ethylene signaling via EIN3, induces the systemic accumulation of the senescence-inducing transcription factor ORE1. Premature senescence of younger tissues is prevented by the posttranslational activation of ORE1 specifically in old leaves, where it induces the transcription of senescence-associated genes. Our results highlight how a systemic stress signal (ethylene accumulation upon flooding) induces a signaling cascade that diverges in an age-dependent manner, and eventually leads to an age-dependent physiological output (leaf senescence).
Survivor bias drives overestimation of stability in reconstructed ancestral proteins
Authors: Thomas Adam , Evans Benjamin D. , van der Giezen Mark , Harmer Nicholas J. 
Published: November 2022

AbstractAncestral sequence reconstruction has been broadly employed over the past two decades to probe the evolutionary history of life. Many ancestral sequences are thermostable, supporting the “hot-start” hypothesis for life’s origin. Recent studies have observed thermostable ancient proteins that evolved in moderate temperatures. These effects were ascribed to “consensus bias”. Here, we propose that “survivor bias” provides a complementary rationalisation for ancestral protein stability in alignment-based methods. As thermodynamically unstable proteins will be selected against, ancestral or consensus sequences derived from extant sequences are selected from a dataset biased towards the more stabilising amino acids in each position. We thoroughly explore the presence of survivor bias using a highly parameterizablein silicomodel of protein evolution that tracks stability at the population, protein, and amino acid levels. We show that ancestors and consensus sequences derived from populations evolved under selective pressure for stability throughout their history are significantly biased toward thermostability. Our work proposes a complementary explanation of the origin of thermostability in the burgeoning engineering tools of ancestral sequence reconstruction and consensuses. It provides guidance for the thorough derivation of conclusions from future ancestral sequence reconstruction work.
Patterns of genetic differentiation imply distinct evolutionary histories of the sibling mosquito speciesAnopheles messeaeandAnopheles daciaein Eurasia
Authors: Brusentsov Ilya I. , Gordeev Mikhail I. , Yurchenko Andrey A. , Karagodin Dimitriy A. , Moskaev Anton V. , Hodge James M. , Burlak Vladimir A. , Artemov Gleb N. , Sibataev Anuarbek K. , Becker Norbert , Sharakhov Igor V. , Baricheva Elina M. , Sharakhova Maria V. 
Published: November 2022

AbstractDetailed knowledge of phylogeography is important for control of mosquito species involved in transmission of human infectious diseases.Anopheles messeaeis a geographically widespread and genetically diverse dominant vector of malaria in Eurasia. A closely related sibling species,An. daciae, was distinguished fromAn. messeaebased on a few nucleotide differences in its ribosomal DNA. However, the mechanisms of speciation and their evolutionary histories are poorly understood. Here, we performed a large-scale population genetics analysis of 3694 mosquitos from Eurasia to understand the species divergence, diversity, and population structure using the Internal Transcribed Spacer 2 of ribosomal DNA for species identification and frequencies of 11 polymorphic chromosomal inversions as genetic markers. The study revealed striking differences in the geographical distribution of the sibling species. The largest genetic differences betweenAn. messeaeandAn. daciaewere detected in the X sex chromosome suggesting that this chromosome plays a role in speciation. The frequencies of autosomal inversions differed significantly between the species, strongly supporting a restricted gene flow. The clinal variability of some inversion frequencies was revealed in both species implicating their possible involvement in climate adaptations. Statistical analysis of inversion polymorphism clearly distinguished two clusters associated with the two species and demonstrated much higher genetic diversity withinAn. messeae. Overall, the frequencies of hybrids in all locations were extremely low with the exception of several southeastern populations, where putative hybrids were abundant. Thus, the pattern of genetic differentiation implies dramatic differences in geographic distribution, population structure, and evolutionary histories of the sibling speciesAn. messeaeandAn. daciae.
Simulation-based assessment of the performance of hierarchical abundance estimators for camera trap surveys
Authors: Martijn Bollen , Jim Casaer , Natalie Beenaerts , Thomas Neyens 
Published: November 2022

AbstractThe need for knowledge about abundance to guide conservation and management strategies in combination with low detectability of many species has led to a widespread use in ecology and management of a range of hierarchical models (HMs) for abundance. These models also appear like good candidates for inference about local abundance in nature reserves studied by camera traps. However, the best choice among these models is unclear, particularly how they perform in the face of several complicating features of realistic populations that include: (i) movements relative to sites, (ii) multiple detections of unmarked individuals within a single survey, and (iii) low probabilities of detection. We conducted a simulation-based comparison of three HMs (Royle-Nichols, binomial N-mixture and Poisson N-mixture model) in the context of small populations of elusive animals in a single study area, where animals cannot be distinguished individually and hence double counting occurs. We generated count data by simulating camera traps monitoring individuals moving according to a Gaussian random walk. Under the simulated scenarios none of the three HMs yielded accurate abundance estimates. Moreover, the performance of each HM depended on the interpretation of abundance. By pooling abundance estimates for trend estimation, each models’ performance markedly improves. Overall, the Royle-Nichols and Poisson N-mixture models outperform a binomial N-mixture model. This emphasizes the importance of choosing the appropriate HM for the data problem.
Pattern formation and travelling waves in a multiphase moving boundary model of tumour growth
Authors: Jepson Jacob M. , O’Dea Reuben D. , Billingham John , Fadai Nabil T. 
Published: November 2022

AbstractWe analyse a multiphase, moving boundary model that describes solid tumour growth. We consider the evolution of a motile, viscous cell phase and an inviscid extracellular liquid phase. The model comprises two partial differential equations that govern the cell volume fraction and the cell velocity, together with a moving boundary condition for the tumour edge. Numerical simulations of the model indicate that patterned solutions can be obtained, which correspond to multiple regions of high cell density separated by regions of low cell density. In other parameter regimes, solutions of the model can develop into a forward- or backward-moving travelling wave, corresponding to tumour growth or extinction, respectively. A travelling-wave analysis allows us to find the corresponding wave speed, as well as criteria for the growth or extinction of the tumour. Furthermore, a stability analysis of these travelling-wave solutions provides us with criteria for the occurrence of patterned solutions. Finally, we discuss how the initial cell distribution, as well as parameters related to cellular motion and cell-liquid drag, control the qualitative features of patterned solutions.
Immune engineered extracellular vesicles to modulate T cell activation in the context of type 1 diabetes
Authors: Becker Matthew W. , Peters Leeana D. , Myint Thinzar , Brusko Todd M. , Phelps Edward A. 
Published: November 2022

AbstractExtracellular vesicles (EVs) are small, biologically active, cell-secreted vesicles that can affect immune responses through antigen presentation and co-stimulation or co-inhibition. We generated designer EVs to modulate autoreactive T cells in the context of type 1 diabetes by engineering K562 cells to express HLA-A*02 (HLA-A2) alongside co-stimulatory CD80 and/or co-inhibitory PD-L1. EVs presenting HLA-A2 and CD80 activated CD8+T cells in a dose, antigen, and HLA-specific manner. Adding PD-L1 to these EVs produced an immunoregulatory response, reducing CD8+T cell activation and cytotoxicityin vitro. EVs alone could not stimulate T cells without antigen presenting cells (APCs), suggesting that EVs act by cross-dressing APCs. EVs lacking CD80 were ineffective at modulating CD8+T cell activation, suggesting that both peptide-HLA complex and costimulatory molecules are required for EV-mediated immune modulation through APC cross-dressing. These results provide mechanistic insight into the rational design of EVs as a cell-free, yet precision medicine-based approach to immunotherapy that can be tailored to promote antigen-specific immune tolerance or pro-inflammatory responses.
The impact of functional correlations on task information coding
Authors: Ito Takuya , Murray John D. 
Published: November 2022

ABSTRACTState-dependent neural correlations can be understood from a neural coding framework. Noise correlations – trial-to-trial or moment-to-moment co-variability – can be interpreted only if the underlying signal correlation – similarity of task selectivity between pairs of neural units – is known. Despite many investigations in local spiking circuits, it remains unclear how this coding framework applies to large-scale brain networks. Here we investigated relationships between large-scale noise correlations and signal correlations in a multi-task human fMRI dataset. We found that task-state noise correlation changes (e.g., functional connectivity) did not typically change in the same direction as their underlying signal correlation (e.g., tuning similarity of two regions). This suggests that 1) trial-by-trial variability typically decreases between similarly tuned regions, and 2) stimulus-driven activity does not linearly superimpose atop the network’s background activity. Crucially, noise correlations that changed in the opposite direction as their signal correlation (i.e., anti-aligned correlations) improved information coding of these brain regions. In contrast, noise correlations that changed in the same direction (aligned noise correlations) as their signal correlation did not. Interestingly, these aligned noise correlations were primarily correlation increases, suggesting that most functional correlation increases across fMRI networks actually degrade information coding. These findings illustrate that state-dependent noise correlations shape information coding of functional brain networks, with interpretation of correlation changes requiring knowledge of underlying signal correlations.
Hierarchical Modular Structure of the Drosophila Connectome
Authors: Kunin Alexander B. , Guo Jiahao , Bassler Kevin E. , Pitkow Xaq , Josić Krešimir 
Published: November 2022

ABSTRACTThe structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem we applied novel community detection methods to analyze the synapse-level reconstruction of an adult fruit fly brain containing over 20 thousand neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts.
Predicting Gastrointestinal Absorption of Prodrugs and their Drugs with the ANDROMEDA by Prosilico Software
Authors: Fagerholm Urban , Hellberg Sven , Alvarsson Jonathan , Spjuth Ola 
Published: November 2022

AbstractIntroductionSome prodrugs are developed in order to improve gastrointestinal absorption properties such as permeability and solubility/dissolution. Prediction of the uptake of prodrugs and their drugs is challening for reasons including gastrointestinal hydrolysis and active transport.Objective and MethodologyThe objective was to use the ANDROMEDA software by Prosilico to predict absorption characteristics - passive fraction absorbed (fa,passive), dose-adjusted dissolution potential (fdiss) and total fa(fa) - of prodrugs and their drugs (including drugs and their active metabolites), and to evaluate how they differ between prodrugs and drugs and the predictive accuracy of the software.Results70 prodrug-drug pairs were found and selected for the study. The mean predicted fa,passiveand fdissfor the prodrugs were 0.74 and 0.94, respectively. Corresponding estimates for the drugs were 0.72 and 0.98, respectively. For non-hydrolyzed prodrugs, the median relative and absolute prediction errors for fawere 1.17-fold and 0.08, respectively. Corresponding values for drugs were 1.11-fold and 0.07, respectively. The correlation between predicted and observed fafor non-hydrolyzed ester prodrugs and drugs combined (predictive accuracy) was 0.6.ConclusionProdrugs and drugs had similar average predicted fa,passiveand fdiss, and most had or were predicted to have at least 50 % fa. The fafor about 1/3 of non-hydrolyzed prodrugs was higher than for corresponding drugs, showing successful prodrug design. Adequate prediction accuracy validates ANDROMEDA for prediction of prodrug and drug absorption in man.