Add BrightSurf on Google Email

Max Delbrück Center for Molecular Medicine in the Helmholtz Association


Avatars to help tailor glioblastoma therapies

Researchers have developed a novel zebrafish xenograft platform to screen for novel treatments for glioblastoma, an aggressive brain tumor. The platform uses zebrafish avatars to model glioblastoma cells from individual patients, allowing researchers to identify patient-specific targets and potential treatments.

SourceMax Delbrück Center for Molecular Medicine in the Helmholtz Association·JournalEMBO Molecular Medicine·TypeExperimental study·DateOct 4, 2023

New technology to study virus infections

Scientists at Max Delbrück Center have developed a tool to screen drugs that can help treat viral diseases like COVID-19 by analyzing the immune response of lung epithelial cells. The technology uses synthetic locus control region (sLCR) DNA sequences that glow red when triggered, enabling researchers to identify potential treatments.

Nasal vaccine to prevent COVID-19 passes first tests

A new live attenuated SARS-CoV-2 vaccine administered through the nose has shown better immunity than injected vaccines in hamster models, reducing transmissibility. The vaccine stimulates local immunity by activating antibody immunoglobulin A and memory T cells, providing early protection against COVID-19.

SourceMax Delbrück Center for Molecular Medicine in the Helmholtz Association·JournalNature Microbiology·TypeExperimental study·DateApr 3, 2023

Salt cuts off the energy supply to immune regulators

A new study found that excessive salt intake disrupts the energy metabolism of regulatory T cells, leading to dysfunction. This may have implications for autoimmune and cardiovascular diseases. The research suggests that sodium can alter gene expression and trigger malfunctions in mitochondrial energy generation.

SourceMax Delbrück Center for Molecular Medicine in the Helmholtz Association·JournalCell Metabolism·TypeExperimental study·DateFeb 9, 2023

AI identifies cancer cells

A new machine learning algorithm called 'ikarus' has found a gene signature characteristic of tumors, distinguishing between healthy and tumor cells in various types of cancer. The algorithm was trained on single-cell sequencing data sets and demonstrated an extraordinarily high success rate in distinguishing between different cell types.

SourceMax Delbrück Center for Molecular Medicine in the Helmholtz Association·JournalGenome Biology·TypeData/statistical analysis·DateJun 10, 2022