Find research datasets worth reusing

opencc-by-4.0Dec 2010View details →

Figure 1. Mental space representation of "In the play, Mary is excited"-Representing Mental Spaces and Dynamics of Natural Language Semantics

Thus an entity can have a variable reality status depending on the mental space to which it belongs. The mental space constructed by the sentence Poirot is a Belgian detective is a non-real imaginary story space of which Poirot is an element. But when we say in reality, Poirot is not Belgian the constructed space is reality space in which Poirot (the actor, not the character) does not have the fictional nationality.

opencc-by-4.0Dec 2010View details →

Figure 2. Semantic representation of the sentence Peter finished the discussion in MultiNet after Helbig [8, p. 447].-Representing Mental Spaces and Dynamics of Natural Language Semantics

In Figure 3, semantic frame of the concept Finish realized in the form of the verb finish requires two C-roles: An agent represented by the relation AGT, and an affected entity represented by the relation AFF. Here agent is Peter and the affected entity is an abstract object ([SORT = ad] means the concept is a dynamic abstraction).

opencc-by-4.0Jan 2018View details →

Data used in article 'Tuning Charge Carrier Dynamics and Surface Passivation in Organolead Halide Perovskites with Capping Ligands and Metal Oxide Interfaces'

Data underlying the article 'Tuning Charge Carrier Dynamics and Surface Passivation in Organolead Halide Perovskites with Capping Ligands and Metal Oxide Interfaces' published in Advanced Optical Materials.

opencc-by-4.0Jan 2024View details →

Dynamics of heavy subaqueous spherical pendulums

Relevant data of the dynamics of heavy spherical pendulums underwater to reproduce the major findings of the article "Dynamics of heavy subaqueous spherical pendulums" published in Journal of Fluid Mechanics. The article has been published as open access: <a href="https://doi.org/10.1017/jfm.2023.1008">https://doi.org/10.1063/5.0086557</a>

opencc-zeroApr 2024View details →

Leak-resilient enzyme-free nucleic acid dynamical systems through shadow cancellation

DNA strand displacement (DSD) emerged as a prominent reaction motif for engineering nucleic acid-based computational devices with programmable behaviors. However, strand displacement circuits are susceptible to background noise that disrupts the circuit behavior, commonly known as leaks. The side effects of leaks are particularly severe in circuits with complex dynamical elements (e.g., feedback loops), as their leaks amplify nonlinearly, disrupting the circuit function. Shadow cancellation is a dynamic leak-elimination strategy originally proposed to control the leak growth in such circuits. However, the kinetic restrictions of the proposed method introduce a significant design overhead, making it less accessible. In this work, we use domain-level DSD simulations to examine the method's capabilities, the inner workings of its components, and, most importantly, robustness to practical deviations in its design requirements. First, we show that the method could stabilize the dynamics of several leak-affected catalytic and autocatalytic dynamical systems of practical importance. Then, through several probing experiments, we show that its design restrictions could be significantly relaxed without impacting the circuit function through simple adjustments to the circuit parameters. Finally, we discuss several ideas to tackle the practical challenges in applying the method to arbitrary DSD circuits, paving the way for future experimental work.

opencc-by-4.0Apr 2024View details →

Unveiling the substrate-dependent dynamics of mycotoxin production in Fusarium verticillioides using an OSMAC-metabolomics approach

UHPLC-HRMS raw data files from the article : "Unveiling the substrate-dependent dynamics of mycotoxin production in Fusarium verticillioides using an OSMAC-metabolomics approach"

opencc-by-4.0Nov 2023View details →

Results and code associated with «Predictability of ecological and evolutionary dynamics in a changing world»

Below you'll find results and code associated with the following article (*): Bozzuto, C, Ives, AR (2024): Predictability of ecological and evolutionary dynamics in a changing world. Proceedings of the Royal Society B, 291: 20240980. https://doi.org/10.1098/rspb.2024.0980 ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship. (*) previously a preprint on bioRxiv: https://doi.org/10.1101/2023.11.01.565089

opencc-by-4.0Feb 2021View details →

Рис. 7. Сезонная Δинамика соΔержимого цист H. glycines Fig. 7. Seasonal dynamics of H. glycines cysts content in Reproductive potential of Soybean Cyst Nematode Heterodera glycines - quarantine pest of soybean - in Primorsky Region conditions

Рис. 7. Сезонная Δинамика соΔержимого цист H. glycines Fig. 7. Seasonal dynamics of H. glycines cysts content

opencc-by-4.0Feb 2021View details →

Рис. 1. Àинамика посевных пΛощаΔей сои в Приморском крае в 1996–2018 гг. (по Δанным Àепартамента сеΛьского хозяйства и проΔовоΛьствия Приморского края) Fig. 1. The dynamic of soybean crop area at Primorsky Region in 1996–2018 (based on data from the Department of Agriculture and provision of the Primorsky Region) in Reproductive potential of Soybean Cyst Nematode Heterodera glycines - quarantine pest of soybean - in Primorsky Region conditions

Рис. 1. Àинамика посевных пΛощаΔей сои в Приморском крае в 1996–2018 гг. (по Δанным Àепартамента сеΛьского хозяйства и проΔовоΛьствия Приморского края) Fig. 1. The dynamic of soybean crop area at Primorsky Region in 1996–2018 (based on data from the Department of Agriculture and provision of the Primorsky Region)

opencc-by-4.0Feb 2021View details →

Рис. 4. Сезонная Δинамика размеров цист Heterodera glycines и чисΛа яиц в них. Размер цист в баΛΛах: 1 — меΛкие, 2 — среΔние, 3 — крупные Fig. 4. Seasonal dynamics of the size of Heterodera glycines cysts and the number of eggs in them. The size of cysts in classes: 1 — small, 2 — medium, 3 — large in Reproductive potential of Soybean Cyst Nematode Heterodera glycines - quarantine pest of soybean - in Primorsky Region conditions

Рис. 4. Сезонная Δинамика размеров цист Heterodera glycines и чисΛа яиц в них. Размер цист в баΛΛах: 1 — меΛкие, 2 — среΔние, 3 — крупные Fig. 4. Seasonal dynamics of the size of Heterodera glycines cysts and the number of eggs in them. The size of cysts in classes: 1 — small, 2 — medium, 3 — large

opencc-zeroApr 2024View details →

Structure and dynamics of enterovirus genotype networks

Like all biological populations, viral populations exist as networks of genotypes connected through mutation. Mapping the topology of these networks and quantifying population dynamics across them is crucial to understanding how populations adapt to changes in their selective environment. The influence of mutational networks is especially profound in viral populations which rapidly explore their mutational neighborhoods via high mutation rates. Using a novel single-cell sequencing method, scRNAseq-Enabled Acquisition of mRNA and Consensus Haplotypes Linking Individual Genotypes and Host Transcriptomes (SEARCHLIGHT), we captured and assembled viral haplotypes from hundreds of individual infected cells to reveal the complexity of viral populations. We obtained these genotypes in parallel with host cell transcriptome information, enabling us to link host cell transcriptional phenotypes to the genetic structures underlying virus adaptation. Our examination of these structures reveals the common evolutionary dynamics of enterovirus populations and illustrates how viral populations reach through mutational 'tunnels' to span evolutionary landscapes and maintain connection with multiple adaptive genotypes simultaneously.

opencc-zeroApr 2024View details →

Reinforcing Tunnel Network Exploration in Proteins using Gaussian Accelerated Molecular Dynamics (inputs, outputs, analysis)

<ul> <li>00_LinB-Wt.tar.gz - LinB-Wt: contains raw data that are used for analysis, also conatin folder for GaMD testing.</li> </ul>     1. cMD(Classical MD simulation) analysis files :              1. Analysis of catalytic residue’s RMSD, whole protein RMSD and RMSF along with whole protein’s Rg and sasa.         2. Inputs and output files of caver calculations.          3. H-bond raw distance files from all simulations named run1-run5.          4. Distance files used to calculate PCA and cluster analysis.         5. Input files and input structure used to run simulations along with output restart files from each stage of production.             2. GaMD(Gaussian Accelerated MD simulation) analysis files :            1. Analysis of catalytic residue’s RMSD, whole protein RMSD and RMSF along with whole protein’s Rg and sasa.         2. Inputs and output files of caver calculations.          3. H-bond raw distance files from all simulations named run1-run5.          4. Distance files used to calculate PCA and cluster analysis.         5. Input files and input structure used to run simulations along with output restart files from each stage of production.     3. GaMD-testing :         1. Input file of GaMD used to run testing and output gamd.log files for multiple run of σOP 1.2 - 1.4 and σOD 2.5.     4. Initial 200ns cMD simulation files used for cluster analysis :         1. Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and 200ns stripped water and ions simulation in Amber *.nc format         2. Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format in rst folder.         3. Ouput files from Simulation for each stage of the minimization, equilibration and production runs in Amber *.out format in out folder. <ul> <li>01_LinB-Open.tar.gz - LinB Open mutant: contains raw data that are used for analysis.</li> </ul>     1. cMD(Classical MD simulation) analysis files :              1. Analysis of catalytic residue’s RMSD, whole protein RMSD and RMSF along with whole protein’s Rg and sasa.         2. Inputs and output files of caver calculations.          3. H-bond raw distance files from all simulations named run1-run5.          4. Distance files used to calculate PCA and cluster analysis.         5. Input files and input structure used to run simulations along with output restart files from each stage of production.             2. GaMD(Gaussian Accelerated MD simulation) analysis files :            1. Analysis of catalytic residue’s RMSD, whole protein RMSD and RMSF along with whole protein’s Rg and sasa.         2. Inputs and output files of caver calculations.          3. H-bond raw distance files from all simulations named run1-run5.          4. Distance files used to calculate PCA and cluster analysis.         5. Input files and input structure used to run simulations along with output restart files from each stage of production.     3. Initial 200ns cMD simulation files used for cluster analysis :         1. Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and 200ns stripped water and ions simulation in Amber *.nc format         2. Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format in rst folder.         3. Ouput files from Simulation for each stage of the minimization, equilibration and production runs in Amber *.out format in out folder. <ul> <li>02_LinB-Closed.tar.gz - LinB Closed mutant: contains raw data that are used for analysis.</li> </ul>     1. cMD(Classical MD simulation) analysis files :              1. Analysis of catalytic residue’s RMSD, whole protein RMSD and RMSF along with whole protein’s Rg and sasa.         2. Inputs and output files of caver calculations.          3. H-bond raw distance files from all simulations named run1-run5.          4. Distance files used to calculate PCA and cluster analysis.         5. Input files and input structure used to run simulations along with output restart files from each stage of production.             2. GaMD(Gaussian Accelerated MD simulation) analysis files :            1. Analysis of catalytic residue’s RMSD, whole protein RMSD and RMSF along with whole protein’s Rg and sasa.         2. Inputs and output files of caver calculations.          3. H-bond raw distance files from all simulations named run1-run5.          4. Distance files used to calculate PCA and cluster analysis.         5. Input files and input structure used to run simulations along with output restart files from each stage of production.     3. Initial 200ns cMD simulation files used for cluster analysis :         1. Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and 200ns stripped water and ions simulation in Amber *.nc format         2. Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format in rst folder.         3. Ouput files from Simulation for each stage of the minimization, equilibration and production runs in Amber *.out format in out folder. <ul> <li>03_TT_analysis.tar.gz - TransportTools: contains config file and all the raw data from all set and subset of reclustered (using in-house python script) caver calculations used for running TT.</li> </ul>     1. Caver input data for comparison between 500ns, 1 us, 2.5 us and 5us between LinB-Wt and it’s mutants.     2. TransportTools log file.     3. Main statistics result of comparative analysis. <ul> <li>04_reweighting.tar.gz: directory contains reweighted .csv files after running in-house reweighting protocol.             1. GaMD log files from each simulation of LinB-Wt and it’s mutants.     2. CSV files from TT result folder.     3. Result *.csv file contained reweighted tunnel properties in folder reweighted_filtered_new.</li> <li>05_caverdock.tar.gz: contains raw data for caverdock calculations uisng 100 best tunnels with four ligands 2-bromoethanol (be), 1,2-dibromoethane (dbe), Bromide ion (br-) and water (h2o).</li> </ul>     1. Top 100 tunnels present in tunnel folder for all three tunnels ST, p1b and p3 with subdirectory containing three variants and four ligand, whichare used for running caverdock.     2. Ligand *.pdbqt file and receptor *.pdbqt are present in each 100 tunnel folder of respective caverdock calculation.     3. Inside each variant and each ligand, there is respective result of migration analysis with energy barrier calculation of respective tunnels *energy_barriers-new.log* and further simplied *.csv files that was used for preparing figure in manuscript.

Data from: Interactions of wood accumulations, channel dynamics, and geomorphic heterogeneity within a river corridor

Natural rivers are inherently dynamic. Spatial and temporal variations in water, sediment, and wood fluxes both cause and respond to an increase in geomorphic heterogeneity within the river corridor. We analyze 16 two-kilometer river corridor segments of the Swan River in Montana, USA to examine relationships between wood accumulations (wood accumulation distribution density, count, and persistence), channel dynamism (total sinuosity and average channel migration), and geomorphic heterogeneity (density, aggregation, interspersion, and evenness of patches in the river corridor). We hypothesize that i) more dynamic river segments correlate with a greater presence, persistence, and distribution of wood accumulations; ii) years with higher peak discharge correspond with greater channel dynamism and wood accumulations; and iii) all river corridor variables analyzed play a role in explaining river corridor spatial heterogeneity. Our results suggest that decadal-scale channel dynamism, as reflected in total sinuosity, corresponds to greater numbers of wood accumulations per surface area and greater persistence of these wood accumulations through time. Second, higher peak discharges correspond to greater values of wood distribution density, but not to greater channel dynamism. Third, persistent values of geomorphic heterogeneity, as reflected in the heterogeneity metrics of aggregation, interspersion, patch density, and evenness, are explained by potential predictor variables analyzed here. Our results reflect the complex interactions of water, sediment, and large wood in river corridors; the difficulties of interpreting causal relationships among these variables through time; and the importance of spatial and temporal analyses of past and present river processes to understand future river conditions

Engineering dynamic gates in binding pocket of penicillin G acylase to selectively degrade bacterial signaling molecules

(01-mutants_design.tar.gz) Mutants design: <ol> <li>Input structures of ecPGA from the PDB database (PDB IDs: 1GK9, 1GM7, and 1GM9), processed to resemble wild-type state, repaired by RepairPDB module of FoldX 4</li> <li>Double-point mutants preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA double-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA double-point mutants</li> </ol> </li> <li>Triple-point mutant preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA triple-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA triple-point mutants</li> </ol> </li> </ol> (02-docking.tar.gz) Preparation of protein-ligand complexes using molecular docking for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules: <ol> <li>PDB files of ligand, PDBQT files of the receptor and PDB files of the complexes selected from docking experiment:</li> </ol> Full names of presented protein variants: ecPGA_wt, wild-type Escherichia coli penicillin G acylase LAF, Phe138αLeu & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_22 LSF, Phe138αLeu & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_98 MAF, Phe138αMet & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_23 MSF, Phe138αMet & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_99 VAF, Phe138αVal & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_30 YAF, Phe138αTyr & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_33 Full names of presented AHLs: C06, N-hexanoyl-L-homoserine lactone; C06-3O, N-3-oxo-hexanoyl-L-homoserine lactone; C08, N-octanoyl-L-homoserine lactone; C08-3O, N-3-oxo-octanoyl-L-homoserine lactone; C10, N-decanoyl-L-homoserine lactone; C12-3O, N-3-oxo-dodecanoyl-L-homoserine lactone (03-protein_ligand_MDs.tar.gz) Ligand-enzyme complexes molecular dynamics for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules: <ol> <li>Force field parameters in Amber format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Output files generated during post-processing of production runs trajectories in a form of text files generated by cpptraj</li> </ol> (04-free_enzymes_MDs.tar.gz) Free enzymes molecular dynamics of 3 best triple-point ecPGA (VAF, YAF and MSF) mutants prioritized based on protein-ligand molecular dynamics simulations and experimental assays: <ol> <li>Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber format</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Post-processing analysis of generated trajectories: <ol> <li>Text files with distances, CSV files containing result of PCA and clustering, PNG files with clustered PCA results</li> <li>Inputs and outputs of MDpocket analysis and visualization of the pocket frequency grid as an isomesh</li> <li>CAVER input configuration files in text format, CAVER output data including parsed CSV and text files for visualization of entrance opening time evolution and cavity profiles inspection</li> <li>cpptraj generated text files including RMSD, distances and chi1 angles measurements</li> </ol> </li> </ol> All plots were generated using matplotlib or seaborn Python libraries. Figures containing structural representations were generated using PyMOL 2.0.1. (05-ecPGA_VAF_YAF_MSF_penG_MDs.tar.gz) PenG-enzyme complexes molecular dynamics for wild-type ecPGA and 3 best designed triple-point mutants (VAF, YAF, MSF): <ol> <li>PenG force field parameters in Amber (GAFF) format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format and analysis output files generated during post-processing of production runs trajectories in a form of text files</li> <li>Reactive Stabilization Score [RSS] statistics summarized in CSV files</li> </ol>

opencc-by-4.0Apr 2024View details →

Supplementary data: A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR

Content: This dataset provides supplementary data to "A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR". It contains trained Neural Network Potentials (NNP), energy and force data used for accuracy evaluation of the NNPs. Energy and forces are stored as ASE trajectory files (traj), readable by the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment </a>(ASE). In addition, this repository contains the generated training database with DFT (SCAN+D3(BJ)) energies and forces as SchNetPack1.0 database (SiAlOHNa.db) file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>.  Also, the structure files used to calculate NMR properties are involved. <ul> <li>"nnps.zip" - (pytorch) NNP model files (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>)</li> <li>"SiAlOHNa.db" - DFT (SCAN+D3(BJ)) training database as SchNetPack1.0 database file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a></li> <li>"error_stats.zip" - traj files storing energies/forces at the DFT (SCAN+D3(BJ)) and NNP level for all test simulations to calcuate energy/force errors</li> <li>"Structures_CHA17.zip" - the structures files of CHA(17). </li> </ul>

opencc-by-4.0May 2024View details →

Data on thermodynamic, gas-dynamic and electromagnetic parameters of gas discharge in poly-phase medium

Temperature, concentrations and electromagnetic parameters distribution in the model environment for main poly-phase medium types

A normative database of free-breathing pediatric thoracic 4D dynamic MRI images

In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. The shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dynamic magnetic resonance imaging (dMRI) images during one breathing cycle for each normal child and also 10 object segmentations at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right separately, are also reported. The database has 2,820 3D segmentations from 141 healthy children, which to our knowledge is the largest dMRI dataset of healthy children to date. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for healthy children. The database can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can be useful to advance future AI-based research on image-based object segmentation and analysis.

Data from: Dissecting gene activation and chromatin remodeling dynamics in single human cells undergoing reprogramming

During cell fate transitions, cells remodel their transcriptome, chromatin, and epigenome; however, it has been difficult to determine the temporal dynamics and cause-effect relationship between these changes at the single-cell level. Here, we employ the heterokaryon-mediated reprogramming system as a single-cell model to dissect key temporal events during early stages of pluripotency conversion using super-resolution imaging. We reveal that, following heterokaryon formation, the somatic nucleus undergoes global chromatin decompaction and removal of repressive histone modifications H3K9me3 and H3K27me3 without acquisition of active modifications H3K4me3 and H3K9ac. The pluripotency gene OCT4 (POU5F1) shows nascent and mature RNA transcription within the first 24 h after cell fusion without requiring an initial open chromatin configuration at its locus. NANOG, conversely, has significant nascent RNA transcription only at 48 h after cell fusion but, strikingly, exhibits genomic reopening early on. These findings suggest that the temporal relationship between chromatin compaction and gene activation during cellular reprogramming is gene context dependent.

Data from: Longitudinal gut microbiome dynamics in relation to age and senescence in a wild animal population

In humans, gut microbiome (GM) differences are often correlated with, and sometimes causally implicated in, ageing. However, it is unclear how these findings translate in wild animal populations. Studies that investigate how GM dynamics change within individuals, and with declines in physiological condition, are needed to fully understand links between chronological age, senescence, and the GM, but have rarely been done. Here, we use longitudinal data collected from a closed population of Seychelles warblers (Acrocephalus sechellensis) to investigate how bacterial GM alpha diversity, composition, and stability are associated with host senescence. We hypothesised that GM diversity and composition will differ, and become more variable, in older adults, particularly in the terminal year prior to death, as the GM becomes increasingly dysregulated due to senescence. However, GM alpha diversity and composition remained largely invariable with respect to adult age and did not differ in an individual's terminal year. Furthermore, there was no evidence that the GM became more heterogenous in senescent age groups (individuals older than 6 years), or in the terminal year. Instead, environmental variables such as season, territory quality, and time of day, were the strongest predictors of GM variation in adult Seychelles warblers. These results contrast with studies on humans, captive animal populations, and some (but not all) studies on non-human primates, suggesting that GM deterioration may not be a universal hallmark of senescence in wild animal species. Further work is needed to disentangle the factors driving variation in GM-senescence relationships across different host taxa.

Data from: Migratory singers dynamically overlap the signal space of a breeding warbler community

Migratory species inhabit many communities along their migratory routes. Across taxa, these species repeatedly move into and out of communities, interacting with each other and locally breeding species and competing for resources and niche space. However, their influence is rarely considered in analyses of ecological processes within the communities they temporarily occupy. Here, we explore the impact of migratory species on a breeding community using the framework of acoustic signal space, a limited resource in which sounds of species within communities co-exist. Migrating New World warblers (Parulidae, hereafter referred to as migrant species) often sing during refueling stops in areas and at times during which locally breeding warbler species (hereafter breeding species) are singing to establish territories and attract mates. We used eBird data to determine co-occurrence of 19 migrant and 11 breeding warbler species across spring migration in SW Michigan, generated a signal space from song recordings of these species, and examined patterns of signaling overlap experienced by breeding species as migrants moved through the community. Migrant species were present for two-thirds of the breeding season of local species, including periods when breeding species established territories and attracted mates. Signaling niche overlap experienced by individual breeding species was idiosyncratic and varied over time, yet niche overlap between migrant and breeding species occurred more commonly than between breeding species or between migrant species. Nevertheless, the proportion of niche overlap between migrant and breeding warblers was similar to overlap among breeding species. Our findings showed that singing by migrant species overlapped the signals of many breeding species, suggesting that migrants could have unexplored impacts on communication in breeding species, potentially affecting song detection and song evolution. Our study contributes to a growing body of research documenting impacts of migratory species on communities and ecosystems.