23 research outputs found
An orifice shape-based reduced order model of patient-specific mitral valve regurgitation
Mitral valve regurgitation (MR) is one of the most prevalent valvular heart diseases. Its quantitative assessment is challenging but crucial for treatment decisions. Using computational fluid dynamics (CFD), we developed a reduced order model (ROM) describing the relationship between MR flow rates, transvalvular pressure differences, and the size and shape of the regurgitant valve orifice. Due to its low computational cost, this ROM could easily be implemented into clinical workflows to support the assessment of MR. We reconstructed mitral valves of 43 patients from 3D transesophageal echocardiographic images and estimated the 3D anatomic regurgitant orifice areas using a shrink-wrap algorithm. The orifice shapes were quantified with three dimensionless shape parameters. Steady-state CFD simulations in the reconstructed mitral valves were performed to analyse the relationship between the regurgitant orifice geometry and the regurgitant hemodynamics. Based on the results, three ROMs with increasing complexity were defined, all of which revealed very good agreement with CFD results with a mean bias below 3% for the MR flow rate. Classifying orifices into two shape groups and assigning group-specific flow coefficients in the ROM reduced the limit of agreement predicting regurgitant volumes from 9.0 ml to 5.7 ml at a mean regurgitant volume of 57 ml
CD3 aptamers promote expansion and persistence of tumor-reactive T cells for adoptive T cell therapy in cancer
Instituto Salud Carlos III financed with Feder Funds PI20-01132 (“A way to make Europe”) for F.P. This project has received funding from the European Union Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Action grant agreement no. 721358 and under the H2020-FETOPEN “DESTINATION” grant agreement no. 899833
Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty
This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings
Strategies for the site-specific decoration of DNA origami nanostructures with functionally intact proteins
DNA origami structures provide flexible scaffolds for the organization of single biomolecules with nanometer precision. While they find increasing use for a variety of biological applications, the functionalization with proteins at defined stoichiometry, high yield, and under preservation of protein function remains challenging. In this study, we applied single molecule fluorescence microscopy in combination with a cell biological functional assay to systematically evaluate different strategies for the site-specific decoration of DNA origami structures, focusing on efficiency, stoichiometry, and protein functionality. Using an activating ligand of the T-cell receptor (TCR) as the protein of interest, we found that two commonly used methodologies underperformed with regard to stoichiometry and protein functionality. While strategies employing tetravalent wildtype streptavidin for coupling of a biotinylated TCR-ligand yielded mixed populations of DNA origami structures featuring up to three proteins, the use of divalent (dSAv) or DNA-conjugated monovalent streptavidin (mSAv) allowed for site-specific attachment of a single biotinylated TCR-ligand. The most straightforward decoration strategy, via covalent DNA conjugation, resulted in a 3-fold decrease in ligand potency, likely due to charge-mediated impairment of protein function. Replacing DNA with charge-neutral peptide nucleic acid (PNA) in a ligand conjugate emerged as the coupling strategy with the best overall performance in our study, as it produced the highest yield with no multivalent DNA origami structures and fully retained protein functionality. With our study we aim to provide guidelines for the stoichiometrically defined, site-specific functionalization of DNA origami structures with proteins of choice serving a wide range of biological applications
Monomeric agonist peptide/MHCII complexes activate T-cells in an autonomous fashion
Molecular crowding of agonist peptide/MHC class II complexes (pMHCIIs) with structurally similar, yet per se non-stimulatory endogenous pMHCIIs is postulated to sensitize T-cells for the recognition of single antigens on the surface of dendritic cells and B-cells. When testing this premise with the use of advanced live cell microscopy, we observe pMHCIIs as monomeric, randomly distributed entities diffusing rapidly after entering the APC surface. Synaptic TCR engagement of highly abundant endogenous pMHCIIs is low or non-existent and affects neither TCR engagement of rare agonist pMHCII in early and advanced synapses nor agonist-induced TCR-proximal signaling. Our findings highlight the capacity of single freely diffusing agonist pMHCIIs to elicit the full T-cell response in an autonomous and peptide-specific fashion with consequences for adaptive immunity and immunotherapeutic approaches
An orifice shape-based reduced order model of patient-specific mitral valve regurgitation
Mitral valve regurgitation (MR) is one of the most prevalent valvular heart diseases. Its quantitative assessment is challenging but crucial for treatment decisions. Using computational fluid dynamics (CFD), we developed a reduced order model (ROM) describing the relationship between MR flow rates, transvalvular pressure differences, and the size and shape of the regurgitant valve orifice. Due to its low computational cost, this ROM could easily be implemented into clinical workflows to support the assessment of MR. We reconstructed mitral valves of 43 patients from 3D transesophageal echocardiographic images and estimated the 3D anatomic regurgitant orifice areas using a shrink-wrap algorithm. The orifice shapes were quantified with three dimensionless shape parameters. Steady-state CFD simulations in the reconstructed mitral valves were performed to analyse the relationship between the regurgitant orifice geometry and the regurgitant hemodynamics. Based on the results, three ROMs with increasing complexity were defined, all of which revealed very good agreement with CFD results with a mean bias below 3% for the MR flow rate. Classifying orifices into two shape groups and assigning group-specific flow coefficients in the ROM reduced the limit of agreement predicting regurgitant volumes from 9.0 ml to 5.7 ml at a mean regurgitant volume of 57 ml