scispace - formally typeset
T

Tanja Seibold

Researcher at University of Ulm

Publications -  6
Citations -  31

Tanja Seibold is an academic researcher from University of Ulm. The author has contributed to research in topics: Chemistry & Microvesicles. The author has an hindex of 1, co-authored 4 publications receiving 2 citations.

Papers
More filters
Journal ArticleDOI

Small Extracellular Vesicles and Metastasis-Blame the Messenger.

TL;DR: In this paper, a review discusses how tumor cells facilitate progression through the metastatic cascade by employing extracellular vesicles (sEVs, exosomes) based communication and evaluates their role as biomarkers and vehicles for drug delivery.
Journal ArticleDOI

Pancreatic Cancer Small Extracellular Vesicles (Exosomes): A Tale of Short- and Long-Distance Communication

TL;DR: In this article, small extracellular vesicles (sEVs, exosomes) were used as biomarkers for diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC).
Journal ArticleDOI

Concerted regulation of actin polymerization during constitutive secretion by Cortactin and PKD2

TL;DR: Additional functions for PKD2 (also known as PRKD2) and cortactin are reported in the regulation of actin polymerization during the fission of transport carriers from the TGN by modulating WIP-dependent sequestration of N-WASP.
Journal ArticleDOI

Small Extracellular Vesicles Propagate the Inflammatory Response After Trauma.

TL;DR: In this article, it was shown that different in vivo traumata, such as TxT or an in vitro polytrauma cytokine cocktail trigger secretion of small extracellular nanoveicles (sEVs) from endothelial cells with pro-inflammatory cargo.
Journal ArticleDOI

Comparative Panel Sequencing of DNA Variants in cf-, ev- and tumorDNA for Pancreatic Ductal Adenocarcinoma Patients

TL;DR: A combination of ev- and cfDNA was clearly superior for SNV detection, as compared to either single analyte, thus potentially improving actionable variant prediction upon further optimization, and Stringent bioinformatic processing revealed a significant advantage of evDNA with respect to cfDNA concerning detection performance for SNVs and a numerical increase for indels.