Arthur Viode

[Oliver M. Bernhardt 🇺🇦 @OliverMBernhar1]

Dear MS Community For those who did not have the chance to see my ASMS poster about our new search-engine, let me run you through some of the highlights. Roughly a year ago we started looking into improving our capabilities for unspecific searches.

[Kinga Smolen @KingaSmolen]

Predictive gene expression signature diagnoses neonatal sepsis before clinical presentation - eBioMedicine https://t.co/VvkqkbrnOX

[Alexey Nesvizhskii @nesvilab]

New large-scale plasma proteome profiling study, 1100+ samples, 6Tb of data, 2500+ proteins quantified. Analysis using Bruker DDA-PASEF. I actually think DDA MS1 LFQ is a solid strategy and even has some advantages, even in what seems to be the era of DIA. https://t.co/S3HeHERK7a

[Vadim Demichev @DemichevLab]

Want reliable quantities? Brilliant students in my lab @ZiskaKistner @JustusGrossmann figured out how. We present QuantUMS, an ML-based algorithm for step-change better quantitation in proteomics and statistical confidence in individual quantities https://t.co/9AhXScJfhl

QuantUMS is integrated in DIA-NN (beta version referenced in preprint), but we also plan to release it as an open-source tool, for use on various kinds of data, not just DIA.

We further anticipate significant gains to be achieved by integrating the accuracy metric reported by QuantUMS with existing packages for statistical analysis of proteomics data.

Some benchmarks are in the twitter thread below.

[Vincent Albrecht @_VAlbrecht]

Check out our perspective on MS-based body fluid #proteomics in @molcellprot.
We discuss how recent and cutting-edge advances overcome long-standing challenges and bring the field to an exciting turning point.

Great thanks to Jakob Bader and @labs_mann

https://t.co/wElmV9Nj2U

[Judith Steen @ionicwoman]

Meta-analysis of published cerebrospinal fluid proteomics data identifies and validates metabolic enzyme panel as Alzheimer’s disease biomarkers https://t.co/Ll2OeLtJdR

[Molecular Neurodegeneration @MolNeuro]

'Using mass spectrometry to validate mouse models of #tauopathy'

Yan Yan & Casey N. Cook @MayoClinicNeuro #AlzheimersDisease #FrontotemporalDementia

https://t.co/VeOYEI6B50

[Elo Lab @EloLab_fi]

Our new study in @NatureComms evaluates tools to detect longitudinal differential expression in #proteomics data and introduces a robust approach RolDE for longitudinal #biomarkerdiscovery. @BioscienceTurku @UniTurku @SuomenAkatemia @InFLAMES_Health https://t.co/evGv68Kkr4

[Arthur Viode @ArthurViode]

Just introduced a game-changing plasma depletion method for deep and high throughput protein profiling!
@bruker @EvosepBio @ScienceAdvances #proteomics #massspectrometry #innovation #clinicalresearch #COVID19 #HarvardMed
https://t.co/wegG0BDOk7

[Alexey Nesvizhskii @nesvilab]

The Hanno Steen lab at Boston Children's' Hospital optimized #FragPipe for a high-performance computing environment, and applied it to analyze 3348 timsTOF plasma samples (6.4 Tb) from a longitudinal COVID-19 patients study. https://t.co/fP7ZkfbfyP

[Journal of Proteome Research @JProteomeRes]

The @steen_lab presents a Fragpipe-based parallelization strategy for analysis of LC-MS proteomics data. Their strategy reduced run time by 90% & enables them to map the proteomes of 1000s of samples! https://t.co/LP970Uapvr

[Molecular Neurodegeneration @MolNeuro]

'Common mouse models of #tauopathy reflect early but not late human disease'

@steen_lab @ionicwoman @harvardmed #AlzheimersDisease #proteomics

https://t.co/5RDXz5qouk

[Judith Steen @ionicwoman]

Kathrin Wenger and our team asked, Why do drugs for Alzheimer’s Disease work in animal models, but often fail in clinical trials?
https://t.co/qsTShu3QmB
#AlzheimersDisease #tauopathy #proteomics #HarvardMed #neurodegeneration #dementia