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Biology subjects

Merillat, S.

Publications and source records attributed to Merillat, S..

2 recordsLinked to original sources

Protein design to broadly reprogram engineered T cell function

The efficacy of engineered T cell therapies in solid tumors remains limited by T cell dysfunction, driven by complex processes that cannot be easily manipulated via genetic knockouts or overexpression of individual genes. Protein design can create new biological functions that can rewire these consequential cell fate decisions. Here, we introduce OUTLAST Regulators, designed proteins that reprogram critical T cell signaling pathways to enhance functional persistence. These proteins are capable of regulating diverse groups of proteins such as the NR4A family of pro-exhaustion transcription factors, E3 ligases Cbl-b and c-Cbl, and SOCS family proteins. Our designs markedly improve CAR-T and TCR-T performance in vitro and in vivo in stringent solid tumor preclinical models. OUTLAST Regulators are implemented as compact genetic modules compatible with standard viral vectors and cell therapy manufacturing processes, creating a powerful platform for programming new functions into enhanced cell and gene therapies.

synthetic biology↗

Validation and comparison of three freely available methods for extracting white matter hyperintensities: FreeSurfer, UBO Detector and BIANCA

White matter hyperintensities (WMH) of presumed vascular origin are frequently found in MRIs of healthy older adults. WMH are also associated with aging and cognitive decline. Here, we compared and validated three freely available algorithms for WMH extraction: FreeSurfer, UBO Detector, and BIANCA (Brain Intensity AbNormality Classification Algorithm) using a longitudinal dataset comprising MRI data of cognitively healthy older adults (baseline N = 231, age range 64-87 years). As reference we manually segmented WMH in T1w, 3D FLAIR, 2D FLAIR images. These manual segmentations were then used to assess the segmentation accuracy of the different automated algorithms. Further, we assessed the relationships of WMH volume estimates provided by the algorithms with Fazekas scores and age. FreeSurfer underestimated the WMH volumes and scored worst in Dice Similarity Coefficient (DSC = 0.434) but its WMH volumes strongly correlated with the Fazekas scores (rs = 0.73). BIANCA accomplished the highest DCS (0.602) with 3D FLAIR images. However, the relations with the Fazekas scores were only moderate, especially in the 2D FLAIR images (rs = 0.41), and many outlier WMH volumes were detected when exploring within-person trajectories (2D FLAIR: ~30%). UBO Detector performed similarly to BIANCA in DSC with both modalities and reached the best DSC in 2D FLAIR (0.531) without requiring a tailored training dataset. In addition, it achieved very high associations with the Fazekas scores (2D FLAIR: rs = 0.80). In summary, our results emphasize the importance of carefully contemplating the choice of the WMH segmentation algorithm and MR-modality.

neuroscience↗