High-Throughput and High-Sensitivity Biomarker Monitoring in Body Fluid by Fast LC SureQuant IS-Targeted Quantitation.

Targeted proteomics methods have been greatly improved and refined over the last decade and are becoming increasingly the method of choice in protein and peptide quantitative assays. Despite the tremendous progress, targeted proteomics assays still suffer from inadequate sensitivity for lower abundant proteins and throughput, especially in complex biological samples. These attributes are essential for establishing targeted proteomics methods at the forefront of clinical use.

A proinflammatory stem cell niche drives myelofibrosis through a targetable galectin-1 axis.

Myeloproliferative neoplasms are stem cell-driven cancers associated with a large burden of morbidity and mortality. Most patients present with early-stage disease, but a substantial proportion progress to myelofibrosis or secondary leukemia, advanced cancers with a poor prognosis and high symptom burden. Currently, it remains difficult to predict progression, and therapies that reliably prevent or reverse fibrosis are lacking.

Lipid levels correlate with neuronal and dopaminergic markers during the differentiation of SH-SY5Y cells.

Parkinson's Disease (PD) is characterised by the loss of dopaminergic neurons and the deposition of protein inclusions called Lewy Bodies (LBs). LBs are heterogeneous structures composed of protein and lipid molecules and their main constituent is the presynaptic protein α-synuclein. SH-SY5Y cells are neuroblastoma cells commonly used to model PD because they express dopaminergic markers and α-synuclein and they can be differentiated into neuronal cells using established protocols.

CLIPPER 2.0: Peptide-Level Annotation and Data Analysis for Positional Proteomics.

Positional proteomics methodologies have transformed protease research, and have brought mass spectrometry (MS)-based degradomics studies to the forefront of protease characterization and system-wide interrogation of protease signaling. Considerable advancements in both sensitivity and throughput of liquid chromatography (LC)-MS/MS instrumentation enable the generation of enormous positional proteomics datasets of natural and protein termini and neo-termini of cleaved protease substrates. However, concomitant progress has not been observed to the same extent in data analysis and post-processing steps, arguably constituting the largest bottleneck in positional proteomics workflows.