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7,327 results for “pathways”
COP21: Results and Implications for Pathways and Policies for Low Emissions European Societies
<p>This database contains national and global level modelling scenario results produced under the COP21:RIPPLES project <a href="https://www.cop21ripples.eu/">https://www.cop21ripples.eu/</a></p> <p>The data is also hosted in the IIASA RIPPLES Scenario Explorer <a href="https://data.ene.iiasa.ac.at/cop21ripples/#/login">https://data.ene.iiasa.ac.at/cop21ripples/#/login</a></p> <p>The National Determined Contributions (NDCs) provide important indications regarding the future GHG emissions and related policies, in relation to the international energy market, technological, economic, trade and financial context. This key information on the development trajectories of major economies is essential for EU policy development as it will determine the global context in which EU policies will evolve. Nevertheless, the NDCs adopt a medium-term horizon and do not provide all the required information to fully characterize the detailed energy system pathways that meet the Paris Agreement (PA) goals. NDCs therefore fall short of characterizing the global trajectories at a sufficiently granular and long-term perspective for informing EU policies.</p> <p>To close this knowledge gap, COP21:RIPPLES aims at analysing the underlying transformations required in the different sectors of the economy to meet the PA mitigation targets. To this purpose, COP21:RIPPLES uses existing scenarios as well as a number of new national and global scenarios. These new scenarios are not conceived themselves as an output of the project but rather as methodological tool to answer specific questions across different Work Packages. For description of the models and scenarios included in each Excel file, see the documentation "RIPPLES_ScenarioExplorer_Doc_v4.docx".</p> <p>For more information on these models and scenarios, see the COP21:RIPPLES Deliverables D2.6, D3.2 and D3.5.</p>
Septicemia of Subterranean Termites Coptotermes curvignathus Caused by Disturbance of Bacteria Isolated from Termite Gut and Its Foraging Pathways
<p><span><span>Microbial pathogens continue to attract a great deal of attention to manage termite population. Every bacterium has its own mode of action and in fact, the mechanisms used by bacteria to attack termites remains elusive at the moment.</span></span><span> </span>Hence, the objective of this study was to evaluate the susceptibility of subterranean termites <i>Coptotermes curvignathus</i> to opportunistic pathogens using culturable aerobic bacteria isolated from the termite gut and its foraging pathways. Bacterial suspensions were prepared in concentrations of 10<sup>3</sup>, 10<sup>6</sup>, and 10<sup>9</sup> CFU/mL and introduced to the termites via oral-contact and physical contact treatment. The data shows that contact method acted slower and gave lower mortality, compared to oral-contact method. <i>C. curvignathus</i> were highly susceptible to<i> Serratia marcescens and</i> <i>Pseudomonas aeruginosa</i>. <i>Serratia marcescens </i>showed the highest mortality percentage of 68% and 54% at bacterial concentration of 10<sup>9 </sup>CFU/mL via oral-contact and contact method, respectively. <i>S. marcescens </i>was also defined as the bacteria with the highest ability to induce high mortality of <i>C. curvignathus</i> with the lowest concentration of bacterial suspension at a given time under laboratory condition. The results of this study indicate that <i>P. aeruginosa</i> and <i>S. </i><i>marcescens</i> in particular may be attractive candidates worth further examination as a possible biocontrol agent against <i>C. curvignathus</i> in the field and, to evaluate environmental and ecological risks of the biocontrol.</p>
The Photoisomerization Pathway(s) of Push-Pull Phenylazoheteroarenes
<p>Azoheteroarenes are the most recent derivatives targeted to further improve the properties of azo‐based photoswitches. Their light‐induced mechanism for trans‐cis isomerization is assumed to be very similar to that of the parent azobenzene. As such, they inherited from the controversy about the dominant isomerization pathway (rotation vs. inversion) depending on the excited state (nπ* vs. ππ*). While the controversy seems settled in azobenzene, the extent to which the same conclusions apply to the more structurally‐diverse family of azoheteroarenes is unclear. Here, we unravel by means of non‐adiabatic molecular dynamics, the photoisomerization mechanism of three prototypical phenyl‐azoheteroarenes with an increasing push‐pull character. The evolution of the rotational and inversion conical intersection energies, the preferred pathway, and the associated kinetics upon both nπ* and ππ* excitations can be linked directly with the push‐pull substitution effects. Overall, we clarify the working conditions of this family of azo‐dyes and identify a possibility to exploit push‐pull substituents to tune their photoisomerization mechanism, with potential impact on their quantum yield.</p>
Atmospheric transport is a major pathway of microplastics to remote regions
<p>In the recent years, a large attention has been given to pollution from plastic products as a major environmental problem. Plastics degrade into smaller particles in the environment via photodegradation, physical abrasion, hydrolysis and biodegradation. Microplastics (1 um to 5 mm size particles) have been reported to affect coral reefs, marine and terrestrial animals, as well as humans. It has been reported that about 30% of microplastics in freshwater and oceanic ecosystems are tire wear particles (TWPs), while brake wear particle (BWP) emissions constitute 55% of all non-exhaust traffic-related particle emissions and 21% of all traffic-related PM emissions. There is a general conviction that the relative contribution of TWP and BWP emissions to total transport-related emissions will grow in the near future, due to the continuous reduction of exhaust traffic-related emissions. Although transport of TWPs and BWPs via runoff and wash-out processes to the marine and/or freshwater ecosystem has been studied extensively, very little is known about how these particles are dispersed in the atmosphere and where they are deposited. This is important due to the aforementioned impact in animals and humans. They also have an environmental impact as they are derived by materials made from fossil fuels such as ethylene and propylene. Thus, larger needs of plastics result in larger emissions of greenhouse gases. Since TWPs and BWPs can become airborne and have been detected already in remote areas, they may absorbe light decreasing surface albedo and accelerating ice melting.<br> Here, we present for the first time the results of the atmospheric dispersion and deposition of traffic-related microplastics (TWPs and BWPs). We assess the suggested emissions using two methods, one indirect based on CO2 country ratios with road microplastics and extrapolation, and another employing an emissions model, which has been extensively used to determine global emissions of various substances by IIASA-International Institute for Applied Systems Analysis (GAINS model). We calculate that 34.4–290 kt y<sup>-1</sup> (mean: 100 kt y<sup>-1</sup>), out of 102–787 kt y<sup>-1</sup> (mean: 284 kt y<sup>-1</sup>) of PM10 TWPs emitted, were deposited in the World Ocean, while the respective annual terrestrial and riverine discharges are about 64 kt y-1. This shows that direct deposition of airborne road microplastics is likely the most important source for the ocean and marine biota. The calculated transport of PM10 road microplastics shows a relatively high efficiency over remote regions such as the Arctic Ocean (14%). High latitudes and the Arctic are highlighted as an important receptor of mid-latitude microplastic emissions, which may imply a future climatic risk taking into account that TWPs and BWPs constitute a small portion of the total plastic emissions. As of now, snow concentrations of road microplastics are 100 times lower than those of black carbon or polymers of larger usage (e.g., PVC or PPC). Around 15% of the PM2.5 road microplastic emissions were deposited in the Atlantic Ocean, whereas coarse particles were less efficiently deposited there (10-11%). The efficiency of PM2.5 deposition (TWPs: 19% - BWPs: 18%) over the Pacific Ocean was even more strongly enhanced relative to PM10 deposition (TWPs: 12% - BWPs: 11%), due to their smaller size. Transport efficiencies of coarse particles were up to twice of those for the fine particles in areas surrounded by microplastic emissions sources (e.g., Alps, Mediterranean, Baltic and South China Seas).</p>
Relabeling metabolic pathway data with groups to improve prediction outcomes
<p>We include samples of various data types used in the work "Relabeling metabolic pathway data with groups to improve prediction outcomes"</p> <p>More information about the software package and instructions are provided in <a href="https://github.com/hallamlab/reMap">hallamlab/reMap</a></p>
Simulated dataset from 'Quantifying the causal pathways contributing to natural selection'
<p>This dataset (Antechinus.csv) relates to the worked example in the appendix of the paper:</p> <p>Henshaw JM, Morrissey MB, Jones AG (2020). Quantifying the causal pathways contributing to natural selection. Evolution (doi:10.1111/evo.14091)</p> <p>The worked example concerns a hypothetical study of female antechinus. These are small carnivorous marsupials that use torpor to reduce energy consumption from late summer to early winter. They reproduce once per year in late winter or early spring, following which most individuals die. We suppose that researchers tracked female antechinus from mid summer to the end of the breeding season. They recorded the animals' body size, their date of last torpor, whether they survived to breed, their number of mates, and their fecundity. I simulated the dataset resulting from this hypothetical study in Wolfram Mathematica (see Methods below). In the above paper, we analyse the causal structure of natural selection in this dataset (the R code for the causal analysis is included here as 'AntechinusAnalysis.R').</p> <p>The variables in the dataset are: body size in unspecified units (BodySize); the date of last torpor (TorporDate), standardized as the number of days before/after an unspecificed reference date; whether the individual survived to breed, given as a binary variable (Survival); an individual's number of mates (Mates); and her fecundity (Fecundity).</p>
Multi-label Pathway Prediction based on Active Dataset Subsampling
<p>We include samples of various data types used in the work "Multi-label Pathway Prediction based on Active Dataset Subsampling" (under-review)</p> <p>More information about the software package and instructions are provided in <a href="https://github.com/hallamlab/leADS">hallamlab/leADS</a></p>
Personality composition determines social learning pathways within shoaling fish
<p>In shaping how individuals explore their environment and interact with others, personality may mediate both individual and social learning. Yet increasing evidence indicates that personality expression is contingent on social context, suggesting that group personality composition may be key in determining how individuals learn about their environment. Here, we used recovery latency following simulated predator attacks to identify Trinidadian guppies (<em>Poecilia reticulata</em>) that acted in a consistently bold or shy manner. We then employed network-based diffusion analysis to track the spread of a novel foraging behaviour through groups containing different proportions of bold and shy fish. Informed associates promoted learning to a greater extent in bold individuals, but only within groups composed predominately of bold fish. As the proportion of shy fish within groups increased, bold individuals instead emerged as especially effective demonstrators that facilitated learning in others. Individuals were also more likely to learn overall within shy-dominated groups than in bold-dominated ones. We demonstrate that how individuals learn is conditional on group personality composition, indicating that selection may favour traits enabling individuals to better match their behavioural phenotype to their social environment.</p>
Differentially evolutionary pathways and their interactions in genes expressed in brain of human and macaque
As the key organ that separates human from other non-human primates, brain has continuously evolved to adapt to the changes of environments and climates. Although human shares most genetic, molecular and cellular features with primates like macaque, there are significant differences in the structure and function in brain of human and these species. Thus, exploring the differences between brains of human and non-human primates in the context of evolution will provide insights into the development, function and diseases of human nervous system. Since the genes involved in many aspects of human brain are under common pressures of natural selection, their evolutionary features can be analyzed collectively at pathway-level. In this study, we tried to explore the molecular mechanisms underlying human brain by comparing the evolutionary features of pathways enriched in genes expressed in human brain and macaque brain. We identified 31 differentially evolutionary pathways in the brain of human and macaque, among which included those related to neurological diseases, signaling transduction, immune and metabolism. By analyzing differentially expressed genes in brain regions and development stages between human and macaque, we also found that ten and four pathways with evolutionary differences, respectively. We further performed crosstalk analysis of pathways to obtain an intuitive correlation between the pathways, which is helpful to understand the mechanism of interaction between pathways. Our results shed light on a comprehensive view of the evolutionary pathways of the human nervous system and provide a reference for the study of human brain development.
Data from: Mapping molar shapes on signaling pathways
<p><span>A major challenge in evolutionary developmental biology is to understand how genetic mutations underlie phenotypic changes. In principle, selective pressures on the phenotype screen the gene pool of the population. Teeth are an excellent model for understanding evolutionary changes in the genotype-phenotype relationship since they exist throughout vertebrates. Genetically modified mice (mutants) with abnormalities in teeth have been used to explore tooth development. The relationship between signaling pathways and molar shape, however, remains elusive due to the high intrinsic complexity of tooth crowns. This hampers our understanding of the extent to which developmental factors explored in mutants explain developmental and phenotypic variation in natural species that represent the consequence of natural selection. Here we combine a novel morphometric method with two kinds of data mining techniques to extract data sets from the three-dimensional surface models of lower first molars: i) machine learning to maximize classification accuracy of 22 mutants, and ii) phylogenetic signal for 31 Murinae species. Major shape variation among mutants is explained by the number of cusps and cusp distribution on a tooth crown. The distribution of mutant mice in morphospace suggests a nonlinear relationship between the signaling pathways and molar shape variation. Comparative analysis of mutants and wild murines reveals that mutant variation overlaps naturally occurring diversity, including more ancestral and derived morphologies. However, taxa with transverse lophs are not fully covered by mutant variation, suggesting experimentally unexplored developmental factors in the evolutionary radiation of Murines.</span></p>
Roundup causes embryonic development failure, alters metabolic pathways and gut microbiota functionality in non-target species
<p><b>Background: </b>Research around the weedkiller Roundup is among the most contentious of the 21<sup>st</sup> century. Scientists have provided inconclusive evidence that the weedkiller causes cancer and other life-threatening diseases, while industry-paid research reports that the weedkiller has no adverse effect on humans or animals. Much of the controversial evidence on Roundup is rooted in the approach used to determine safe use of chemicals, defined by outdated toxicity tests.We apply a system biology approach to the biomedical and ecological model species <i>Daphnia</i> to quantify the impact of Glyphosate and of its commercial formula, Roundup, on fitness, genome-wide transcription and gut microbiota, taking full advantage of clonal reproduction in <i>Daphnia. </i>We then <span>apply </span>machine learning-based statistical analysis to identify and prioritize correlations between genome-wide transcriptional and microbiota changes.</p> <p><b>Results: </b>We demonstrate that chronic exposure to ecologically relevant concentrations of Glyphosate and Roundup at the approved regulatory threshold for drinking water in the US induce embryonic developmental failure, significant DNA damage (genotoxicity), and interfere with signaling. Furthermore, chronic exposure to the weedkiller alters the gut microbiota functionality and composition interfering with carbon and fat metabolism, as well as homeostasis. Using the 'Reactome', we identify conserved pathways across the Tree of Life, which are potential targets for Roundup in other species, including liver metabolism, inflammation pathways and collagen degradation, responsible for the repair of wounds and tissue remodeling.</p> <p><b>Conclusions: </b>Our results show that chronic exposure to concentrations of Roundup and Glyphosate at the approved regulatory threshold for drinking water causes embryonic development failure, and alteration of key metabolic functions via direct effect on the host molecular processes and indirect effect on the gut microbiota. The ecological model species <i>Daphnia</i> occupies a central position in the food web of aquatic ecosystems, being the preferred food of small vertebrates and invertebrates as well as a grazer of algae and bacteria. The impact of the weedkiller on this keystone species has cascading effects on aquatic food webs, affecting their ability to deliver critical ecosystem services.</p>
Pan-cancer Aberrant Pathway Activity Analysis (PAPAA)
<p>Information about the dataset files:</p> <p>1) pancan_rnaseq_freeze.tsv.gz: Publicly available gene expression data for the TCGA Pan-cancer dataset. File: PanCanAtlas EBPlusPlusAdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.tsv was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [http://api.gdc.cancer.gov/data/3586c0da-64d0-4b74-a449-5ff4d9136611] [<a href="https://doi.org/10.1016/j.celrep.2018.03.046">https://doi.org/10.1016/j.celrep.2018.03.046</a>]</p> <p>2) pancan_mutation_freeze.tsv.gz: Publicly available Mutational information for TCGA Pan-cancer dataset. File: mc3.v0.2.8.PUBLIC.maf.gz was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [http://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc] [https://doi.org/10.1016/j.celrep.2018.03.046] </p> <p>3) pancan_GISTIC_threshold.tsv.gz: Publicly available Gene- level copy number information of the TCGA Pan-cancer dataset. This file is processed using script process_copynumber.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. The files copy_number_loss_status.tsv.gz and copy_number_gain_status.tsv.gz generated from this data are used as inputs in our Galaxy pipeline. [https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443] [<a href="https://doi.org/10.1016/j.celrep.2018.03.046">https://doi.org/10.1016/j.celrep.2018.03.046</a>]</p> <p>4) mutation_burden_freeze.tsv.gz: Publicly available Mutational information for TCGA Pan-cancer dataset mc3.v0.2.8.PUBLIC.maf.gz was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [https://github.com/greenelab/pancancer/][http://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc] [https://doi.org/10.1016/j.celrep.2018.03.046]</p> <p>5) sample_freeze.tsv or sample_freeze_version4_modify.tsv: The file lists the frozen samples as determined by TCGA PanCancer Atlas consortium along with raw RNAseq and mutation data. These were previously determined and included for all downstream analysis All other datasets were processed and subset according to the frozen samples.[https://github.com/greenelab/pancancer/]</p> <p>6) cosmic_cancer_classification.tsv: Compendium of OG and TSG used for the analysis. Added additional genes from the cosmic database to volgelstein_cancer_classification.tsv [https://github.com/greenelab/pancancer/]</p> <p>7) CCLE_DepMap_18Q1_maf_20180207.txt.gz Publicly available Mutational data for CCLE cell lines from Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://depmap.org/portal/download/api/download/external?file_name=ccle%2FCCLE_DepMap_18Q1_maf_20180207.txt]</p> <p>8) ccle_rnaseq_genes_rpkm_20180929_mod.tsv.gz: Publicly available Expression data for 1019 cell lines (RPKM) from Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://depmap.org/portal/download/api/download/external?file_name=ccle%2Fccle_2019%2FCCLE_RNAseq_genes_rpkm_20180929.gct.gz]</p> <p>9) CCLE_MUT_CNA_AMP_DEL_binary_Revealer.tsv: Publicly available merged Mutational and copy number alterations that include gene amplifications and deletions for the CCLE cell lines. This data is represented in the binary format and provided by the Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://data.broadinstitute.org/ccle_legacy_data/binary_calls_for_copy_number_and_mutation_data/CCLE_MUT_CNA_AMP_DEL_binary_Revealer.gct]</p> <p>10) GDSC_cell_lines_EXP_CCLE_names.tsv.gz Publicly available RMA normalized expression data for Genomics of Drug Sensitivity in Cancer(GDSC) cell-lines. File gdsc_cell_line_RMA_proc_basalExp.csv was downloaded. This data was subsetted to 389 cell lines that are common among CCLE and GDSC. All the GDSC cell line names were replaced with CCLE cell line names for further processing. [https://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources//Data/preprocessed/Cell_line_RMA_proc_basalExp.txt.zip]</p> <p>11) GDSC_CCLE_common_mut_cnv_binary.tsv.gz: A subset of merged Mutational and copy number alterations that include gene amplifications and deletions for common cell lines between GDSC and CCLE. This file is generated using CCLE_MUT_CNA_AMP_DEL_binary_Revealer.tsv and a list of common cell lines. </p> <p>12) gdsc1_ccle_pharm_fitted_dose_data.txt.gz: Pharmacological data for GDSC1 cell lines. [ftp://ftp.sanger.ac.uk/pub/project/cancerrxgene/releases/current_release/GDSC1_fitted_dose_response_15Oct19.xlsx]</p> <p>13) gdsc2_ccle_pharm_fitted_dose_data.txt.gz: Pharmacological data for GDSC2 cell lines. [ftp://ftp.sanger.ac.uk/pub/project/cancerrxgene/releases/current_release/GDSC2_fitted_dose_response_15Oct19.xlsx]</p> <p>14) compounds_of_interest.txt: list of pharmacological compounds tested for our analysis, taken from ftp://ftp.sanger.ac.uk/pub4/cancerrxgene/releases/release-8.1/screened_compounds_rel_8.1.csv. </p> <p>15) tcga_dictonary.tsv: list of cancer types used in the analysis. </p> <p>16) seg_based_scores.tsv: Measurement of total copy number burden, Percent of genome altered by copy number alterations. This file was used as part of the Pancancer analysis by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [https://github.com/greenelab/pancancer/]</p> <p>17) GSE69822_pi3k_sign.txt: File with values assigned for tumor [1] or normal [-1] in given external samples (GSE69822)</p> <p>18) vlog_trans.csv: Variant stabilized log-transformed expression values in given external samples (GSE69822)</p> <p>19) path_rtk_ras_pi3k_genes.txt: File with the list of ERK/RAS/PI3K pathway genes used in the analysis. </p> <p>20) path_myc_genes.txt: File with the list of Myc pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>21) path_ras_genes.txt: File with the list of RAS pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>22) path_cell_cycle_genes.txt: File with the list of cell cycle pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>23) path_wnt_genes.txt: File with the list of WNT pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>24) GSE94937_rpkm_kras.csv: Expression values in given external samples (GSE94937)</p> <p>25) GSE94937_kras_sign.txt: File with values assigned for KRAS Mutant [1] or WT [-1] in given external samples (GSE94937)</p>
The sodium/proton exchanger NHA2 regulates blood pressure through a WNK4-NCC dependent pathway in the kidney
<p>NHA2 is sodium/hydrogen exchanger that was associated with arterial hypertension in humans, but the role of NHA2 in kidney function and blood pressure homeostasis is currently unknown. Here we show that NHA2 localizes almost exclusively to distal convoluted tubules in the kidney. NHA2 knock-out mice displayed reduced blood pressure, normocalcemic hypocalciuria and an attenuated response to the thiazide diuretic hydrochlorothiazide. Phosphorylation of the thiazide-sensitive sodium/chloride cotransporter NCC and its upstream activating kinase Ste20/SPS1-related proline/alaninerich kinase (SPAK), as well as the abundance of with no lysine [K] kinase 4 (WNK4), were significantly reduced in kidneys of NHA2 knock-out mice. In vitro experiments recapitulated these findings and revealed increased WNK4 ubiquitylation and enhanced proteasomal WNK4 degradation upon loss of NHA2. The effect of NHA2 on WNK4 stability was Kelch-like 3 (KLHL3)-dependent. More specifically, loss of NHA2 selectively attenuated KLHL3 phosphorylation and the physiologically important PKAand PKC-mediated decrease of WNK4 degradation was blunted upon loss of NHA2. Phenotype analysis of NHA2/NCC double knock-out mice supported the notion that NHA2 affects blood pressure homeostasis by an intrarenal and NCC-dependent mechanism. In summary, our data reveal NHA2 as a critical component of the WNK4-NCC pathway and hence as a novel regulator of blood pressure homeostasis in the kidney.</p>
Alternative pathways to diversity across ecologically distinct lizard radiations
Aim: Lizard assemblages vary greatly in taxonomic, ecological and phenotypic diversity, yet the mechanisms that generate and maintain these patterns at a macroecological scale are not well understood. We aimed to characterize the ecological and environmental drivers of species richness patterns in the context of macroecological theory for ten independent lizard radiations. Location: Global Time Period: Present-day Major taxa: Lizards Methods: We analyzed patterns of species and ecological trait diversity in ten ecologically distinct and widely distributed clades encompassing nearly all known lizard species. Using recently published spatial, phylogenetic, and ecological trait datasets, we built spatially explicit structural equation models to ask whether species diversity was directly or indirectly related to functional divergence or convergence within communities, and with features of the environment, including measures of productivity, complexity, and harshness. Results: Our results show that high species diversity is achieved via different pathways in different lizard clades, with both functionally divergent and convergent assemblages harboring high diversity in different clades. More generally, we also find common, positive effects of temperature, productivity, and topography on species richness within lizard clades. Main Conclusions: Thermal constraints, topographic complexity, and spatial structuring of functional diversity help explain the presence of highly diverse lizard assemblages, suggesting the importance of environmental filters in shaping present-day diversity and assemblage structure. Our results show how different pathways to high richness in different clades have contributed to the overall global pattern of species richness in reptiles.
The Immp2l mutation causes ovarian aging through ROS-wnt/β-catenin-estrogen (cyp19a1) pathway: preventive effect of melatonin
<p>Mitochondria play important roles in ovarian follicle development. Mitochondrial dysfunction, including mitochondrial gene deficiency, impairs the ovarian development. Here, we explored the role and mechanism of mitochondrial inner membrane gene <i>Immp2l</i> in ovarian follicle growth and development. Our results revealed that the female Immp2l<sup>-/-</sup> mice were infertile, while the Immp2l<sup>+/- </sup>mice were normal. Body and ovarian weights were reduced in the female Immp2l<sup>-/- </sup>mice, ovarian follicle growth and development were stunted in the secondary follicle stage. Although a few ovarian follicles were ovulated, the oocytes were not fertilized due to mitochondrial dysfunction. Increased oxidative stress, decreased estrogen levels, and altered genes expression of Wnt/β-catenin and steroid hormone synthesis pathways were observed in 28-day-old Immp2l<sup>-/-</sup> mice. The Immp2l mutation accelerated ovarian aging process, as no ovarian follicles were detected in age of 5 months in Immp2l<sup>-/- </sup>mice. All the aforementioned changes in the Immp2l<sup>-/- </sup>mice were reversed by administration of antioxidant melatonin to the Immp2l<sup>-/-</sup> mice. Furthermore, our in vitro study using Immp2l knockdown granulosa cells confirmed that the Immp2l downregulation induced granulosa cell aging by enhancing ROS levels, suppressing <i>Wnt16</i>, increasing β-catenin and decreasing steroid hormone synthesis gene <i>cyp19a1</i> and estrogen levels, accompanied by an increase in the aging phenotype of granulosa cells. Melatonin treatment delayed granulosa cell aging progression. Taken together, Immp2l causes ovarian aging through the ROS-Wnt/β-catenin-estrogen (cyp19a1) pathway, which can be reversed by melatonin treatment.Mitochondria play important roles in ovarian follicle development. Mitochondrial dysfunction, including mitochondrial gene deficiency, impairs the ovarian development. Here, we explored the role and mechanism of mitochondrial inner membrane gene <i>Immp2l</i> in ovarian follicle growth and development. Our results revealed that the female Immp2l<sup>-/-</sup> mice were infertile, while the Immp2l<sup>+/- </sup>mice were normal. Body and ovarian weights were reduced in the female Immp2l<sup>-/- </sup>mice, ovarian follicle growth and development were stunted in the secondary follicle stage. Although a few ovarian follicles were ovulated, the oocytes were not fertilized due to mitochondrial dysfunction. Increased oxidative stress, decreased estrogen levels, and altered genes expression of Wnt/β-catenin and steroid hormone synthesis pathways were observed in 28-day-old Immp2l<sup>-/-</sup> mice. The Immp2l mutation accelerated ovarian aging process, as no ovarian follicles were detected in age of 5 months in Immp2l<sup>-/- </sup>mice. All the aforementioned changes in the Immp2l<sup>-/- </sup>mice were reversed by administration of antioxidant melatonin to the Immp2l<sup>-/-</sup> mice. Furthermore, our in vitro study using Immp2l knockdown granulosa cells confirmed that the Immp2l downregulation induced granulosa cell aging by enhancing ROS levels, suppressing <i>Wnt16</i>, increasing β-catenin and decreasing steroid hormone synthesis gene <i>cyp19a1</i> and estrogen levels, accompanied by an increase in the aging phenotype of granulosa cells. Melatonin treatment delayed granulosa cell aging progression. Taken together, Immp2l causes ovarian aging through the ROS-Wnt/β-catenin-estrogen (cyp19a1) pathway, which can be reversed by melatonin treatment.</p>
Data from: A proteomics approach for the identification of cullin-9 (CUL9) related signaling pathways in induced pluripotent stem cell models
<p>CUL9 is a non-canonical and poorly characterized member of the largest family of E3 ubiquitin ligases known as the Cullin RING ligases (CRLs). Most CRLs play a critical role in developmental processes, however, the role of CUL9 in neuronal development remains elusive. We determined that deletion or depletion of CUL9 protein causes aberrant formation of neural rosettes, an in vitro model of early neuralization. In this study, we applied mass spectrometric approaches in human pluripotent stem cells (hPSCs) and neural progenitor cells (hNPCs) to identify CUL9 related signaling pathways that may contribute to this phenotype. Through LC-MS/MS analysis of immunoprecipitated endogenous CUL9, we identified several subunits of the APC/C, a major cell cycle regulator, as potential CUL9 interacting proteins. Knockdown of the APC/C adapter protein FZR1 resulted in a significant increase in CUL9 protein levels, however, CUL9 does not appear to affect protein abundance of APC/C subunits and adapters or alter cell cycle progression. Quantitative proteomic analysis of CUL9 KO hPSCs and hNPCs identified protein networks related to metabolic, ubiquitin degradation, and transcriptional regulation pathways that are disrupted by CUL9 deletion in both hPSCs and hNPCs. The results of our study build on current evidence that CUL9 may have unique functions in different cell types potentially contributing to the difficulty of identifying CUL9 substrates.</p> <p><strong>Information on data/files</strong>:</p> <p><em>Please first unzip Figure_4_CUL9-IP-LCMSMS-data.zip and Figure_7_iTRAQ-data.zip, then follow the description below.</em></p> <p>CUL9 immunoprecipitation from whole lysates collected for hPSCs were analyzed using LC/MS-MS. IgG was used as a control to determine proteins specifically enriched in the CUL9 IP. This data correlates to Figure 4 of the associated manuscript.</p> <p>Initial CUL9 immunoprecipitation was performed by VG and analyzed by LC-MS/MS at UNC.</p> <p>Fig4-LCMSMS_IPCUL9_Replicate1_UNC</p> <p>Two more immunoprecipitations were performed by VG and analyzed by LC-MS/MS at Vanderbilt University MSRC Proteomics Core. The first run (replicate 1) was used to produce the STRING figure in the associated manuscript, as well as the volcano plot in Supplemental Figure 8.</p> <p>Two Scaffold files contain raw data and our analysis parameters:</p> <ul> <li>Fig4-LCMSMS_IPCUL9_Replicate2_Vanderbilt</li> <li>Fig4-LCMSMS_LCMSMS_IPCUL9_Replicate3_Vanderbilt</li> </ul> <p>Excel files exported from the above Scaffold files contain the raw data in excel format including spectral counts, peptide counts, protein probability, and detailed raw data as it pertains to each identified protein. See these data sets in the folders below:</p> <ul> <li>Fig4-LCMSMS_IPCUL9_Run2_Vanderbilt_CompleteDataSet</li> <li>Fig4-LCMSMS_IPCUL9_Run3_Vanderbilt_CompleteDataSet</li> </ul> <p>CUL9 KO clones were used to identify proteins increased or decreased compared to parental wild-type cell lines using iTRAQ. This data correlates to Figure 8 of the associated manuscript. Two iTRAQ experiments were performed to identify proteins altered in CUL9 KO iPSCs, neural stem cells (NSCs), and NPCs. Each set of experiments was duplicated – each in a different isogenic CUL9 KO clone (Clone 20 or Clone B)</p> <p><strong>iTRAQ labeling of experiment one is as follows:</strong></p> <ol> <li>Label 115: Parental WT NSCs</li> <li>Label 117: CUL9 KO Clone 20 or B NSCs</li> <li>Label 114: Parental WT NPCs</li> <li>Label 116: CUL9 KO Clone 20 or B NPCs</li> </ol> <p>Files containing raw and analyzed data of experiment one are labeled as follows:</p> <ul> <li>Fig7_Experiment1_Clone 002_compared-to-NSC-WT</li> <li>Fig7_Experiment1_Clone001-compared-to-NSC-WT</li> <li>Fig7_Experiment1_Clone001iPSC_compared-to-iPSCWT</li> <li>Fig7_Experiment1_Clone002_compared-to-iPSCWT</li> </ul> <p><strong>iTRAQ labeling of experiment two is as follows:</strong></p> <p>For Clone 20:</p> <ol> <li>Label 115: Parental WT NSCs</li> <li>Label 117: CUL9 KO Clone 20 or B NSCs</li> <li>Label 114: Parental WT iPSCs</li> <li>Label 116: CUL9 KO Clone 20 or B iPSCs</li> </ol> <p>Files containing raw and analyzed data of experiment two are labeled as follows:</p> <ul> <li>Fig7_Experiment2_Clone001NPC_Compared-to-NPC-WT</li> <li>Fig7_Experiment2_Clone001NPC_Compared-to-NSC-WT</li> <li>Fig7_Experiment2_Clone002NPC_Compared-to-NPC-WT</li> <li>Fig7_Experiment2_Clone002NPC_Compared-to-NSC-WT</li> </ul> <p>Please note that the first tab of each excel document contains the full raw data set before analysis. All other tabs contain analyzed data comparing the proteins identified in two cell lines. Analyzed tabs are labeled to indicate which cell lines are being compared. Please note that the CUL9 isogenic clones Clone 20=Clone#1 and Clone B=Clone#2 as referenced in the associated manuscript.</p> <p>Detailed information about the protocols used for collection and analysis of this data can be found in the supplemental information within the associated manuscript.</p>
Supplemental data: Interfering Peptides Targeting Protein-Protein Interactions in the Ethylene Plant Hormone Signaling Pathway as Tools to Delay Plant Senescence
<p>This dataset supplements the chapter "Interfering Peptides Targeting Protein-Protein Interactions in the Ethylene Plant Hormone Signaling Pathway as Tools to Delay Plant Senescence" published in Methods in Molecular Biology. It includes sample files that illustrate data collection and processing outlined in the article.</p>
Supplementary material 1 from: McGrannachan CM, Pagad S, McGeoch MA (2021) A multiregional assessment of transnational pathways of introduction. NeoBiota 64: 43-67. https://doi.org/10.3897/neobiota.64.60642
Figure S1. Cumulative introduction events between 1800 and 2017 for a) interconnected waterways and natural dispersal pathway subcategories and b) unknown pathway subcategories
Supplementary material 2 from: McGrannachan CM, Pagad S, McGeoch MA (2021) A multiregional assessment of transnational pathways of introduction. NeoBiota 64: 43-67. https://doi.org/10.3897/neobiota.64.60642
Appendix S1. Guidelines for the recording of dates of introduction/ first record and conversion of dates to whole numbers
Appendix 3 to "The Status of Biological Invasions and their Management in South Africa in 2019"—Data on the status of pathways
<p>For more details see: http://iasreport.sanbi.org.za</p> <p>SANBI and CIB 2020. Appendix 3 to "The Status of Biological Invasions and their Management in South Africa in 2019"—Data on the status of pathways. South African National Biodiversity Institute, Kirstenbosch and DSI-NRF Centre of Excellence for Invasion Biology, Stellenbosch. http://dx.doi.org/10.5281/zenodo.3947666</p>
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.