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1.
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Highlights
  • •Highly parallelizable 4D feature detection in ion mobility enhanced shotgun proteomics.
  • •Multidimensional non-linear mass, retention time and ion mobility recalibration.
  • •Collision cross section aware matching between runs.
  • •Label-free quantification of ion mobility MS data.
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2.
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Highlights
  • •Human spermatozoa possess cells of poor morphology that lack nuclear integrity.
  • •These cells can be isolated by density separation.
  • •Mass spectrometry reveals their nuclei contain excess protein.
  • •TOP2A is a promising marker of this poor nuclear development.
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3.
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Highlights
  • •Automated statistical approach for detecting uninformative features and outliers.
  • •Improved performance on relative protein quantification.
  • •An option in the open-source R-based software MSstats.
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4.
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Highlights
  • •DEqMS is a method for statistical analysis of quantitative MS-data.
  • •Variance estimates based on the actual MS-data structure.
  • •Improved statistical power and accuracy in protein differential analysis.
  • •DEqMS is available as a user-friendly R package in Bioconductor.
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5.
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Highlights
  • •N-glycan patterns are distinct in pediatric and adult urine.
  • •Sex differences of N-glycans are much larger in adults.
  • •Pediatric urine has almost no sex differences in N-glycan levels.
  • •In adults, the majority of N-glycans were more abundant in males.
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6.
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Highlights
  • •Rapid DIA-only library building with gas-phase fractionation.
  • •Recommended DIA acquisition strategies with staggered windows and forbidden zones.
  • •Optimized DIA instrument settings for several Thermo Orbitrap instruments.
  • •Data analysis tutorial using open source DIA software.
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7.
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Highlights
  • •Integrated phosphoproteomics and analyses of newly synthesized proteins in neurons.
  • •Resource of temporal mGluR-induced signaling pathways upon DHPG stimulation.
  • •Validation of PKC, MAPK1, CAMKIIa, and CDK2 in mGluR-activation and signaling.
  • •Validation of Intersectin-1 in DHPG-induced AMPAR internalization.
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8.
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Highlights
  • •PRMT5 glutathionylation is increased in aged mice or under oxidative stress.
  • •Deglutathionylation of PRMT5 is catalyzed by glutaredoxin-1.
  • •PRMT5 glutathionylation decreases its methyltransferase activity.
  • •PRMT5 glutathionylation results in G2/M arrest and inhibits cell proliferation.
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9.
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Highlights
  • •Label-free and dimethyl labeling MS analysis of 6 RBPs from Drosophila ovaries.
  • •Functionally related RBPs show overlapping proteomes.
  • •Selective co-purification of splicing factors and translational regulators.
  • •Validation of 26 novel interactions by co-immunoprecipitation.
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10.
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Highlights
  • P. aeruginosa grown with exosiderophores and analyzed by proteomic and RT-qPCR.
  • •Catechol-type exosiderophores strongly induce the expression of their transporters.
  • •Repression of the endogenous iron uptake pathways.
  • •Complex phenotypic plasticity in the expression of the various iron-uptake pathways.
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11.
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Highlights
  • •CD73 is one of the most upregulated proteins in the radioresistant cells.
  • •CD73 upregulation confers radioresistance and irradiation-induced apoptosis.
  • •CD73 confers radioresistance potentially through inactivating protein BAD.
  • •Elevated CD73 is required for maintaining the resistant cells in a mesenchymal state.
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12.
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Highlights
  • •Urinary peptide profiling of youths with type 1 diabetes before clinical injury.
  • •Internal validation of uromodulin peptides by parallel reaction monitoring.
  • •Discovery of novel bioactivity of uromodulin peptides in vitro.
  • In silico prediction of proteases involved in uromodulin processing.
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13.
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Highlights
  • •Future proteomic analyses for longitudinal studies and P4 medicine arguably require ≥1M samples/day.
  • •Proteome depth/coverage is commonly the focus whereas analytical speed is typically neglected.
  • •A compromise between analytical depth and speed is needed for future large-scale studies.
  • •Ultrahigh-speed ‘omic’ analyses require tools that are intrinsically fast such as laser-based MS.
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14.
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Highlights
  • •Quantitative mass spectrometric method to monitor PTM stability.
  • •Pulse labeling reveals dehydroxylation of several asparagine hydroxylation sites.
  • •Reversal of TNKS2, TRPV3 and HIF1a asparagine hydroxylation sites.
  • •Protein dehydroxylation is an additional level of control for cellular signaling networks.
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15.
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Highlights
  • •Cecal Ligation Puncture (CLP) mouse model to study sepsis-induced kidney disease.
  • •Quantitative global proteome and phosphoproteome profiling of mouse kidneys.
  • •Highly significant candidate markers for onset and progression of AKI to CKD.
  • •Mechanistic insights into sepsis-associated kidney injuries.
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16.
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Highlights
  • •MSFragger now supports raw timsTOF PASEF data.
  • •IonQuant performs fast and accurate feature detection and quantification.
  • •MSFragger and IonQuant provide excellent performance for timsTOF PASEF data.
  • •Flexibility allows for complex analyses, such as semi-enzymatic and open search.
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17.
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Highlights
  • •In depth performance assessment of leading tools for differential protein abundance.
  • •Novel fast modular framework MSqRobSum for robust protein summarization and inference.
  • •MsqRobSum outperforms leading protein summarization-based tools.
  • •MSqRobSum is on par with top-performing peptide based tool MSqRob.
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18.
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Highlights
  • •Comprehensive sialiomics of isolated rat synaptosomes.
  • •Site-specific modulation of sialic acids on surface glycoproteins after brief depolarization.
  • •Sialylation as dynamic modification important for synaptic depolarization-dependent processes.
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19.
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Highlights
  • •Used affinity-enrichable, isotopically coded, and MS-cleavable crosslinker.
  • •Targeted acquisition strategy based on isotopic-coding described and evaluated.
  • •Novel data analysis pipeline developed provides improved crosslink identification.
  • •Large dataset reveals hundreds of mitochondrial protein-protein interactions.
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20.
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Highlights
  • •Two molecular groups in anal squamous carcinoma according proteomic profile.
  • •Differences in possible targeted processes such as metabolism or immune response.
  • •Different percentage of tumor lymphocyte infiltration.
  • •Difference in the frequency of ATM variants, related to PPAR inhibitors.
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