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527 results for “helpers”
Logical model for Model checking to assess T-helper cell plasticity
<p>Logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant to convey external stimuli, or environmental cues. In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors (e.g. stable states). The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity.</p> <p>In <a href="https://dx.doi.org/10.3389/fbioe.2014.00086">[1]</a>, it is presented an extended version of a published logical model of T-helper cell differentiation and plasticity, which accounts for novel cellular subtypes. The model encompasses 20 signaling pathways, a dozen of transcription factors, and about 30 cytokines, amounting to 101 components in total.</p> <p>Computational methods recently developed to efficiently analyze large models <a href="http://ginsim.org/node/185#ref1">[1]</a> are first used to study static properties of the model (i.e. stables states). Symbolic model checking is then applied to get further insights into reachability properties between Th canonical subtypes upon changes of specific prototypic environmental cues.</p> <p>The model reproduces novel reported Th subtypes (Tfh, Th9, Th22) and predicts additional Th hybrid subtypes in term of stables states. Using the model checker NuSMV-ARCTL, an abstract view of the dynamics, called reprograming graph, is produced providing a global and synthetic view of Th plasticity. The model is consistent with experimental data showing the polarization of naïve Th cells into the canonical Th subtypes. The model further predicts substancial plasticity of Th subtypes depending on the signalling environment.</p>
Replication package of "Good Things Come In Threes: Improving Search-based Crash Reproduction With Helper Objectives"
<p>The replication package for the study about using new helper objectives (MOHO) for crash reproduction. This study has been accepted at ASE 2020.</p> <p> </p> <p>Abstract:</p> <p>Evolutionary intelligence approaches have been successfully applied to assist developers during debugging by generating a test case reproducing reported crashes. These approaches use a single fitness function called <em>Crash Distance</em> to guide the search process toward reproducing a target crash. Despite the reported achievements, these approaches do not always successfully reproduce some crashes due to a lack of test diversity (premature convergence). In this study, we introduce a new approach, called <em>MO-HO</em>, that addresses this issue via multi-objectivization. In particular, we introduce two new Helper-Objectives for crash reproduction, namely <em>test length</em> (to minimize) and <em>method sequence diversity</em> (to maximize), in addition to <em>Crash Distance</em>.</p> <p>We assessed <em>MO-HO</em> using five multi-objective evolutionary algorithms (NSGA-II, SPEA2, PESA-II, MOEA/D, FEMO) on 124 hard-to-reproduce crashes stemming from open-source projects. Our results indicate that SPEA2 is the best-performing multi-objective algorithm for <em>MO-HO</em>.</p> <p>We evaluated this best-performing algorithm for <em>MO-HO</em> against the state-of-the-art: single-objective approach (Single-Objective Search) and decomposition-based multi-objectivization approach (<em>De-MO</em>). Our results show that <em>MO-HO</em> reproduces five crashes that cannot be reproduced by the current state-of-the-art. Besides, <em>MO-HO</em> improves the effectiveness (+10% and +8% in reproduction ratio) and the efficiency in 34.6% and 36% of crashes (i.e., significantly lower running time) compared to Single-Objective Search and <em>De-MO</em>, respectively. For some crashes, the improvements are very large, being up to +93.3% for reproduction ratio and -92% for the required running time. </p>
Coordination of care by breeders and helpers in the cooperatively breeding long-tailed tit, Aegithalos caudatus
<p><span>In species with biparental and cooperative brood care, multiple carers cooperate by contributing costly investment to raise a shared brood. However, shared benefits and individual costs also give rise to conflict among carers over investment. Coordination of provisioning visits has been hypothesized to facilitate the resolution of this conflict, preventing exploitation, and ensuring collective investment in the shared brood. We used a 26-year study of long-tailed tits, <em>Aegithalos caudatus</em>, a facultative cooperative breeder, to investigate whether care by parents and helpers is coordinated, whether there are consistent differences in coordination between individuals and reproductive roles, and whether coordination varies with helper relatedness to breeders. Coordination takes the form of turn-taking (alternation) or feeding within a short time interval of another carer (synchrony), and both behaviors were observed to occur more than expected by chance, i.e. 'active' coordination. First, we found that active alternation decreased with group size while active synchrony occurred at all group sizes. Secondly, we show that alternation was repeatable between observations at the same nest, while synchrony was repeatable between observations of the same individual. Active synchrony varied with reproductive status, with helpers synchronizing visits more than breeders, although active alternation did not vary with reproductive status. Finally, we found no significant effect of relatedness on either alternation or synchrony exhibited by helpers. In conclusion, we demonstrate active coordination of provisioning by carers and conclude that coordination is a socially plastic behavior depending on reproductive status and the number of carers raising the brood.</span></p>
Coordination of care by breeders and helpers in the cooperatively breeding long-tailed tit, Aegithalos caudatus
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Investigating the role of non-helpers in group living thrips
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Identifying drivers of Florida Scrub-Jay reproductive success in the absence of helpers, 1989-2021
Florida Scrub-Jays (FSJ) are federally Threatened, cooperatively breeding birds, where about half of breeding pairs typically have helpers. Factors affecting reproductive success of this species in the absence of helpers has received little attention. This dataset contains reproductive and environmental data relevant to a subset of known age breeding pairs that did not have helpers at Archbold Biological Station (ABS) from 1989 to 2021. Generalized linear mixed models were used to explain variation in reproductive output (offspring survived to 75 days) in relation to: male and female breeding experience and environmental variables (acorn abundance, fire history, and territory size), with year and territory ID included as random effects. Reproductive output was associated with female breeding experience and all three environmental variables. The findings highlight the importance of fire-maintained oak scrub in FSJ reproductive success, which is consistent with management recommendations for this species.
Complex effects of helper relatedness on female extra-pair reproduction in a cooperative breeder
<p>In cooperatively-breeding species, the presence of male helpers in a group often reduces the breeding female's fidelity to her social partner, possibly because there is more than one potential sire in the group. Using a long-term study of cooperatively-breeding superb fairy-wrens (Malurus cyaneus) and records of paternity in 1936 broods, we show that the effect of helpers on rates of extra-pair paternity varied according to the helpers' relatedness to the breeding female. The presence of unrelated male helpers in a group increased average rates of extra-pair paternity, from 57% for groups with no unrelated helpers, to 74% with one unrelated helper, to 86% with 2+ unrelated helpers. However, this increase was due in equal part to helpers within the group and males in other groups achieving increased paternity. In contrast, helpers who were sons of the breeding female did not gain paternity, nor did they affect the level of extra-group paternity (which occurred at rates of 60%, 58%, 61% in the presence of 0, 1, 2+ helper-sons respectively). There was no evidence of effects of helpers' relatedness to the female on nest productivity or nestling performance. Because the presence of helpers per se did not elevate extra-pair reproduction rates, our results undermine the 'constrained female hypothesis' explanation for an increase in extra-pair paternity with helper number in cooperative breeders. However, they indicate that dominant males are disadvantaged by breeding in 'cooperative' groups. The reasons why the presence of unrelated helpers, but not of helper-sons, results in higher rates of extra-group reproduction are not clear.</p>
Meerkat helpers buffer the detrimental effects of adverse environmental conditions on fecundity, growth and survival
<p>1. Recent comparative studies show that cooperative breeding is positively correlated with harsh and unpredictable environments and it is suggested that this association occurs because helpers buffer the negative effects of adverse ecological conditions on fitness.</p> <p>2. In the Kalahari, rainfall varies widely between- and within years, affecting primary production and the availability of the principal prey of cooperatively breeding Kalahari meerkats, Suricata suricatta. Our study aimed to establish whether the presence and number of helpers buffer the negative effects of variation in rainfall on the fecundity and body mass of breeding females, and the survival and growth of pups.</p> <p>3. We investigate the relationship between group size and variation in rainfall on dominant female fecundity, body mass, and offspring survival and growth using an additive modeling approach on twenty-one years of individual-based records of the life histories of individual meerkats.</p> <p>4. We show that breeding female fecundity is reduced during periods of low rainfall but that the effects of low rainfall are mitigated by increases in group size and body mass because heavier females and those in larger groups have increased fecundity and reduced interbirth intervals. Pup growth and survival are also reduced during periods of low rainfall, but more so in smaller groups.</p> <p>5. Our results support the suggestion that cooperative breeding mitigates the detrimental effects of adverse environmental conditions and may enhance the capacity of species to occupy environments where food availability is low and unpredictable.</p>
Dataset used in "Helper NLR immune protein NRC3 evolved to evade inhibition by a cyst nematode virulence effector"
<p><strong>[Figs 1 and S2]</strong></p> <p> </p> <p><strong>00_cloned_NRC123.fasta</strong></p> <p> </p> <p>FASTA file containing NRC1, NRC2 and NRC3 sequences tested in HR cell death assay.</p> <p> </p> <p><strong>01_NRCX0123_4species.fasta</strong></p> <p> </p> <p>FASTA file containing NRC0, NRC1, NRC2, NRC3 and NRCX of <em>N. benthamiana</em>, <em>C. annuum</em> (pepper), <em>S. tuberosum</em> (potato) and <em>S. lycopersicum</em> (tomato). In addition to a previously published dataset (Selvaraj et al., 2023), we included the NbNRC2, CaNRC3 and StNRC3 sequences from 00_cloned_NRC123.fasta.</p> <p> </p> <p><strong>02_NRCX0123_4species.local_aln.fasta</strong></p> <p> </p> <p>FASTA file containing the protein sequence alignment of 01_NRCX0123_4species.fasta. We used MAFFT for the alignment (Katoh & Standley, 2013).</p> <p> </p> <p><strong>03_NRCX0123_4species.local_aln.clip.fasta</strong></p> <p> </p> <p>FASTA file containing the trimmed protein sequence alignment of 02_NRCX0123_4species.local_aln.fasta. We used ClipKIT for trimming (Steenwyk et al., 2020).</p> <p> </p> <p><strong>04_NRCX0123_4species.local_aln.clip.fasta.treefile</strong></p> <p><strong> </strong></p> <p>Newick file containing the phylogenetic tree reconstructed based on 03_NRCX0123_4species.local_aln.clip.fasta. We used IQ-TREE to create a phylogenetic tree (Minh et al., 2020).</p> <p> </p> <p><strong>[Fig 2B]</strong></p> <p><strong> </strong></p> <p><strong>05_cloned_NRC123.local_aln.fasta</strong></p> <p><strong> </strong></p> <p>FASTA file containing the protein sequence alignment of 00_cloned_NRC123.fasta. We used MAFFT for the alignment (Katoh & Standley, 2013).</p> <p> </p> <p><strong>[Fig 5 and Table S1]</strong></p> <p> </p> <p><strong>06_NRCH_cds_23-06-20.min2400max2800.fasta</strong></p> <p><strong> </strong></p> <p>FASTA file containing the nucleotide sequences of helper NRC sequences from 124 Solanaceae genomes (Sugihara et al., 2023; Huang et al., 2023). We filtered out sequences shorter than 2,400 or longer than 2,800 bases, resulting in 1,748 sequences.</p> <p> </p> <p><strong>07_NRCH_cds_23-06-20.min2400max2800.aa.fasta</strong></p> <p> </p> <p>FASTA file of the amino acid sequences translated from 06_NRCH_cds_23-06-20.min2400max2800.fasta.</p> <p> </p> <p><strong>08_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.fasta</strong></p> <p> </p> <p>FASTA file containing the amino acid sequences of NB-ARC module corresponding to the sequences in 07_NRCH_cds_23-06-20.min2400max2800.aa.fasta.</p> <p> </p> <p><strong>09_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta</strong></p> <p> </p> <p>FASTA file containing the trimmed protein sequence alignment of 02_NRCX0123_4species.local_aln.fasta. We used MAFFT and ClipKIT for the alignment and trimming, respectively (Katoh & Standley, 2013; Steenwyk et al., 2020).</p> <p> </p> <p><strong>10_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta.treefile</strong></p> <p> </p> <p>Newick file containing the phylogenetic tree reconstructed based on 09_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta. We used IQ-TREE to create a phylogenetic tree (Minh et al., 2020).</p> <p> </p> <p><strong>11_NRCX123_cds_23-06-20.min2400max2800.fasta</strong></p> <p> </p> <p>FASTA file containing the the nucleotide sequences of NRC1/2/3X clades identified based on 10_NRCH_cds_23-06-20.min2400max2800.aa.NBARC.local_aln.clip.fasta.treefile.</p> <p> </p> <p><strong>12_NRCX123_nt_codon_ancseq_v1.2.1.zip</strong></p> <p> </p> <p>Results of ancestral sequence reconstruction. We used ancseq to perform ancestral sequence reconsturction (Sugihara, 2024). "NRCX123_cds_23-06-20.min2400max2800.nt_codon.local_aln.manual.clip.uniq.rm_4sp.fasta" is an input alignment and "NRCX123_cds_23-06-20.min2400max2800.nt_codon.local_aln.manual.clip.uniq.rm_4sp.fasta.treefile" is a tree file. Regarding the output files for ancseq, please refer to the <a href="https://github.com/YuSugihara/ancseq?tab=readme-ov-file#outputs">GitHub repository</a>.</p> <p> </p> <p><strong>[Fig S7]</strong></p> <p> </p> <p><strong>13_logo_plot.zip</strong></p> <p> </p> <p>Sequence alignments and script used in Fig S7. To generate the consensus sequence shown in Fig S7, we concatenated interfaces 1, 2 and 3 with SS15 and visualized the results using logomaker (Tareen and Kinney, 2020).</p> <p> </p> <p><strong>References</strong></p> <p> </p> <p>Huang C-Y, Huang Y-S, Sugihara Y, Wang H-Y, Huang L-T, Lopez-Agudelo JC, Chen Y-F, Lin K-Y, Chiang B-J, Toghani A, Kourelis J, Derevnina L, Wu C-H. 2023. Functional divergence shaped the network architecture of plant immune receptors. <em>bioRxiv</em>. 2023:2023.12.12.571219. DOI: 10.1101/2023.12.12.571219.</p> <p>Katoh K, Standley DM. 2013. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. <em>Molecular Biology and Evolution</em> 30:772–780. DOI: 10.1093/molbev/mst010.</p> <p>Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, Lanfear R. 2020. IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era. <em>Molecular Biology and Evolution</em> 37:1530–1534. DOI: 10.1093/molbev/msaa015.</p> <p>Selvaraj M, Toghani A, Pai H, Sugihara Y, Kourelis J, Yuen ELH, Ibrahim T, Zhao H, Xie R, Maqbool A, Concepcion JCD la, Banfield MJ, Derevnina L, Petre B, Lawson DM, Bozkurt TO, Wu C-H, Kamoun S, Contreras MP. 2023. Activation of plant immunity through conversion of a helper NLR homodimer into a resistosome. <em>bioRxiv</em>. 2023:2023.12.17.572070. DOI: 10.1101/2023.12.17.572070.</p> <p>Steenwyk JL, Iii TJB, Li Y, Shen X-X, Rokas A. 2020. ClipKIT: A multiple sequence alignment trimming software for accurate phylogenomic inference. <em>PLOS Biology</em> 18:e3001007. DOI: 10.1371/journal.pbio.3001007.</p> <p>Sugihara Y. 2024. YuSugihara/ancseq: v1.2.1. <em>Zenodo</em>. DOI: 10.5281/zenodo.10808871.</p> <p>Sugihara Y, Toghani A, Kamoun S, Kourelis J. 2023. NLRome dataset from 124 genomes of plants in the Solanaceae family. <em>Zenodo</em>. DOI: 10.5281/zenodo.10354350.</p> <p>Tareen A, Kinney JB. 2020. Logomaker: beautiful sequence logos in Python. Bioinformatics 36:2272–2274. doi:10.1093/bioinformatics/btz921</p> <p> </p>
Quantitative comparison of tracking performance using TrackMate-Helper.
<p>TrackMate now offers multiple detections and linking algorithms. Each of these algorithms needs to be configured with a parameter set that can take a wide range of values. While adequate values for these parameters can often be estimated intuitively, a systematic approach is often desirable. Indeed optimizing tracking parameters through visual assessment can be difficult when following many objects.</p> <p>To this end, we developed a new tool called TrackMate-Helper, which performs automatic parameter sweeps over any combination of detector and tracker available in TrackMate and measures the tracking results accuracy using the Cell-Tracking-Challenge (CTC) metrics. TrackMate-Helper requires an input image and the corresponding tracking ground-truth. Importantly, TrackMate-Helper is built as an end-user tool with a user-friendly interface that conveniently allows configuring parameter sweeps over many combinations of tracking parameters. We envision that this systematic approach will benefit medium and high-throughput automatic tracking studies. By optimizing the tracking parameters on one movie, users will be able to find optimal tracking parameters for the rest of their dataset. </p> <p>Here, we used TrackMate-Helper to assess the performance of TrackMate on four datasets that cover a wide range of biological and imaging situations:</p> <ol> <li> <p>Migrating cancer cells imaged using fluorescence microscopy to visualize their nuclei. In this dataset, the cells are densely packed and divided during the experiment . </p> </li> <li> <p>Migrating T-cells imaged using phase-contrast microscopy). </p> </li> <li> <p>Neisseria meningitidis bacterial growth on agar pads. The bacteria are fluorescently labeled to visualize their membrane. Starting from a few single bacteria, the cells quickly divide several times and swarm the field of view.</p> </li> <li> <p>Glioblastoma-astrocytoma cells imaged using bright-field microscopy at high resolution.</p> </li> </ol> <p>The table included reports the best results for each detector and tracker combination. We tested from 3000 to 20000 different parameter settings for each combination.</p>
Giant babax (Babax Waddelli) helpers cheat at provisioning nestlings in poor conditions
<p><span>In cooperatively breeding species, helpers take higher risks of getting lower return of investment than breeders due to the incongruity between helping and breeding. Helpers can deal with the risk by curtailing their investment or, if possible, claiming immediate rewards in the cooperation. Given breeders may rely largely on the aid of helpers to raise their offspring, it can be hypothesized that helpers are more likely to make adaptive responses to the incongruity-associated risk in adverse habitats than in good ones. This hypothesis was tested in the giant babax (<em>Babax</em> <em>waddelli</em>) by comparing helpers' provisioning behaviors between two breeding populations in adverse high-altitude and good low-altitude environments. These two populations differed significantly in their egg size and nestlings' growth patterns. Helpers in both populations made great contributions to the raising of offspring. During provisioning, helpers in the high-altitude population exhibited significantly higher feeding rates but delivered fewer insects per feeding bout than their counterparts in the low-altitude population. Helpers in both populations displayed a cheating strategy of 'non-feeding' to reduce investment in provisioning. They pursued immediate excess rewards via kleptoparasitism of nestling fecal sacs in the high-altitude population but not in the low-altitude one. Accordingly, breeders made different antagonistic actions toward the cheating helpers between populations. Our findings confirm that helpers are prone to deceiving cooperation under poor breeding conditions and that breeders' tolerance of the cheating behavior of helpers is determined by their dependence on the helpers' aid.</span></p>
Group augmentation on trial: helpers in small groups enhance antipredator defence of eggs
<p>Mechanisms selecting for the evolution of cooperative breeding are hotly debated. While kin selection theory has been the central paradigm to explain the seemingly altruistic behaviour of non-reproducing helpers, it is increasingly recognized that direct fitness benefits may be highly relevant. The group augmentation hypothesis proposes that alloparental care may evolve to enhance group size when larger groups yield increased survival and/or reproductive success. However, there is a lack of empirical tests. Here we use the cooperatively breeding cichlid fish Neolamprologus pulcher, in which group size predicts survival and group stability, to test this hypothesis experimentally by prompting two cooperative tasks: defence against an egg predator and digging out sand from the breeding shelter. We controlled for alternative mechanisms such as kin selection, load-lightening and coercion. As predicted by the group augmentation hypothesis, helpers increased defence against an egg predator in small compared to large groups. This difference was only evident in large helpers due to size-specific task specialization. Furthermore, helpers showed more digging effort in the breeding chamber compared to alternative personal shelters, indicating that digging was an altruistic service to the dominant breeders.</p>
Ausband_Bassing_helper_plasticity
<p>Data associated with whether a mature, nonbreeding wolf stayed in a group or left after breeder turnover. </p>
Data from: Helper plasticity in response to breeder turnover in gray wolves
<p>Nonbreeding helpers can greatly improve the survival of young and reproductive fitness of breeders in many cooperatively breeding species. Breeder turnover, in turn, can have profound effects on dispersal decisions made by helpers. Despite its importance in explaining group size and predicting population demography of cooperative breeders, our current understanding of how individual traits influence animal behavior after disruptions to social structure is incomplete particularly for terrestrial mammals. We used 12 years of genetic sampling and group pedigrees of gray wolves (<em>Canis lupus</em>) in Idaho, USA, to ask questions about how breeder turnover affected the apparent decisions by mature helpers (<u>></u>2-year-old) to stay or leave a group over a one-year time interval. We found that helpers showed plasticity in their responses to breeder turnover. Most notably, helpers varied by sex and appeared to base dispersal decisions on the sex of the breeder that was lost as well. Male and female helpers stayed in a group slightly more often when there was breeder turnover of the same sex, although males that stayed were often recent adoptees in the group. Males, however, appeared to remain in a group less often when there was breeding female turnover likely because such vacancies were typically filled by related females from the males' natal group (i.e., inbreeding avoidance). We show that helpers exploit instability in the breeding pair to secure future breeding opportunities for themselves. The confluence of breeder turnover, helper sex, and dispersal and breeding strategies merge to influence group composition in gray wolves.</p>
SupplementaryData_A_helper_NLR_targets_organellar_membranes_to_trigger_immunity
<p>Supplementary data for "A_helper_NLR_targets_organellar_membranes_to_trigger_immunity" including:</p> <p>1.Phylogenetics analysis - Data S1 to 6) - Fig. 1A and S1</p> <p>2.AlphaFold3 Models - Data S7 - Fig. 1B and S2</p> <p>3.NRG1_delta14(Nb)_delta16(At) alignment - Data S8</p> <p>4.nrg1 KO plants genotyping (Data S9) - more details in Materials and Methods.</p> <p>5.HR_index_data - Data S10 - raw HR data presented in manuscript.</p> <p>6.Movie S1 - NRG1 puncta upon XopQ activation.</p>
MD data for Ionizable cationic lipids and helper lipids synergistically contribute to RNA packing and protection in lipid-based nanomaterials
<p>The data stored in this repository is part of the journal article: Zimmer, D. N., Schmid, F., & Settanni, G. (2024). Ionizable Cationic Lipids and Helper Lipids Synergistically Contribute to RNA Packing and Protection in Lipid-Based Nanomaterials. <em>The Journal of Physical Chemistry B</em> <a href="https://doi.org/10.1021/acs.jpcb.4c05057" target="_blank" rel="noopener">https://doi.org/10.1021/acs.jpcb.4c05057</a></p> <p> </p> <p>Data of multiscale simulations of DLinDMA:DOPE:Cholesterol, DLinDMA:DSPC:Cholesterol, DLinDAP:DOPE:Cholesterol and DLinDAP:DSPC:Cholesterol in the presence of RNA. For each formulation, data is provided with different coarse-grained parameterizations (generic, adapted) and differents treatments of the RNA (ELN, noELN). Provided are the first and the final frame of each run, the associated topologies, and the respective gromacs input files.</p> <p><strong>> M_PE, M_PC, P_PE, P_PC</strong></p> <p>DLinDMA:DOPE:Cholesterol, DLinDMA:DSPC:Cholesterol, DLinDAP:DOPE:Cholesterol and DLinDAP:DSPC:Cholesterol in presence of a 40mer RNA fragment. </p> <ul> <li>cg_<strong>generic</strong>+aa: <ul> <li>cg: 2 microsecond production run based on a generic MARTINI parametrization <ul> <li>md_0.gro: first frame</li> <li>md_10.gro: final frame </li> <li>cg_rna_bilayer.top: Topology of the system</li> <li>cg_DLD{M/P}_lipid.itp: generic MARTINI topology of DLinDMA/DLinDAP</li> <li>martini_v2.0_CHOL_02.itp, martini_v2.0_DSPC_01.itp, martini_v2.0_ions, martini_v2.1.itp, martini_v2.1-dna.itp: Several MARTINI topology files for molecules not included in MARTINI</li> <li>Nucleic_A.itp or Nucleic_A_eln.itp: Topology of the RNA fragment for MARTINI</li> </ul> </li> <li>aa: 300/600 nanosecond production run based on CHARMM36 <ul> <li>md_0.gro: first frame</li> <li>md_60.gro: final frame </li> <li>backmapped.top: Topology of the system (including the parametrization of DLinDMA/DLinDAP)</li> <li>CHOL.itp, DOPE.itp, DSPC.itp, 40mer_autopsf.itp: topology files for Cholesterol, DOPE, DSPC and RNA fragment as they are not part of the standard molecules in CHARMM36.</li> </ul> </li> <li>ELN and noELN indicate presence or absence of an elastic network to fix the structure of the RNA during the cg runs. </li> <li>cgmdp: Gromacs input files for the cg runs</li> <li>aamdp: Gromacs input files for the aa runs</li> </ul> </li> <li>cg_<strong>adapted</strong>+aa: <ul> <li>cg: starting and ending frame of a 2 microsecond production run based on an adapted MARTINI parametrization <ul> <li>md_0.gro: first frame</li> <li>md_10.gro: final frame </li> <li>cg_rna_bilayer.top: Topology of the system</li> <li>martini_v2.0_DIDMA_20 or martini_v2.0_DIDAP_20: generic MARTINI topology of DLinDMA/DLinDAP</li> <li>martini_v2.0_CHOL_02.itp, martini_v2.0_DSPC_01.itp, martini_v2.0_ions, martini_v2.1-dna_cr1_POL_NACL.itp: Several MARTINI topology files for molecules not included in MARTINI</li> <li>Nucleic_A.itp or Nucleic_A_eln.itp: Topology of the RNA fragment for MARTINI</li> </ul> </li> <li>aa: 300/600 nanosecond production run based on CHARMM36 <ul> <li>md_0.gro: first frame</li> <li>md_60.gro: final frame </li> <li>backmapped.top: Topology of the system (including the parametrization of DLinDMA/DLinDAP)</li> <li>CHOL.itp, DOPE.itp, DSPC.itp, 40mer_autopsf.itp: topology files for Cholesterol, DOPE, DSPC and RNA fragment as they are not part of the standard molecules in CHARMM36.</li> </ul> </li> <li>ELN and noELN indicate presence or absence of an elastic network to fix the structure of the RNA during the cg runs. </li> <li>cgmdp: Gromacs input files for the cg runs</li> <li>aamdp: Gromacs input files for the aa runs</li> </ul> </li> </ul>
PopV pretrained models for Tabula sapiens reference and helper files
<p>This repository contains PopV pretrained models for all organs published in Tabula sapiens <a href="https://cellxgene.cziscience.com/collections/e5f58829-1a66-40b5-a624-9046778e74f5">https://cellxgene.cziscience.com/collections/e5f58829-1a66-40b5-a624-9046778e74f5</a>. Datasets are available from <a href="https://zenodo.org/record/7587774">https://zenodo.org/record/7587774</a>.</p> <p>The code to train all models will be released in a Github reproducibility repository.</p>
Data from: Helpers don't help when it's hot in a cooperatively breeding bird, the Southern Pied Babbler
<p><span>Cooperative breeding, where more than two individuals invest in rearing a single brood, occurs in many bird species globally and often contributes to improved breeding outcomes. However, high temperatures are associated with poor breeding outcomes in many species, including cooperative species. We used data collected over three austral summer breeding seasons to investigate the contribution that helpers make to daytime incubation in a cooperatively breeding species, the Southern Pied Babbler <em>Turdoides bicolor,</em> and the ways in which their contribution is influenced by temperature. </span><span>Helpers spent a significantly higher percentage of their time foraging</span><span> (41.8 ± 13.7%) and a significantly lower percentage of their time incubating (18.5 ± 18.8%) than members of the breeding pair (31.3 ± 11% foraging & 37.4 ± 15.7% incubating). In groups with only one helper, the helper's contribution to incubation was similar to that of breeders. However, helpers in larger groups contributed less to incubation, individually, with some individuals investing no time in incubation on a given observation day. Helpers significantly decrease their investment in incubation on hot days (>35.5°C), while breeders tend to maintain incubation effort as temperatures increase. Our results demonstrate that</span><span> pied babblers share the workload of incubation unequally between breeders and helpers, and this inequity is more pronounced during hot weather. These results may help to explain why recent studies have found that larger group size does not buffer against the impacts of high temperatures in this and other cooperatively breeding species.</span></p>
The impact of helping experience on helper life-history and fitness in a cooperatively breeding bird
<p>The data and accompanying .R scripts were used to test whether having experience as a helper affected a number of different breeding and fitness related parameters in the Seychelles warbler (<em>Acrocephalus sechellensis</em>) in the paper "The impact of helping experience on helper life-history and fitness in a cooperatively breeding bird." </p> <p><strong>Datasets</strong><br><em>statusInfo.xlsx</em>: data collected over a focal individual's lifetime. <br><em>natalInfo.xlsx</em>: data pertaining to the natal environment of the focal bird. <br><em>lastSeen.xlsx</em>: data used to calculate when the bird was last seen alive. <br><em>summerIndex.xlsx</em>: data used to determine whether a particular field period was during a summer or winter season.<br><em>territoryQuality.xlsx</em>: data used to determine the territory quality of each territory during a particular field period.</p> <p><strong>Statistical analyses </strong><br><em>experiencePrep.R</em>: the script used to prepare the data and calculate the necessary model variables prior to running the analyses. <br><em>experienceAnalyses.R</em>: the script used to run the analyses and generate the related graphs. </p> <p>More detailed information regarding the contents of each dataset can be found in the READ.ME</p> <p>From this, we found that helping experience had no significant association with any of the metrics considered, except that individuals with helping experience had an older age at first dominance, and dominant females with helping experience had longer lifespans than those that had never helped. In addition, we found that females with co-breeding experience produced more adult offspring (≥1 year old) after acquiring dominance, and had a higher lifetime reproductive success than females that had never co-bred.</p>
A Phase 1/2A, Randomized Study of a T Follicular Helper (TFH)-Targeting Genetic Vaccine Strategy Designed to Induce Broad, Durable Immune Responses
ClinicalTrials.gov study NCT06810934. IPD Sharing: YES. Countries: 1. Publications: 10.
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