arXiv subjects

Klaus Gerwert

Publications and source records attributed to Klaus Gerwert.

4 recordsLinked to original sources

arXiv2026

Infrared photonics for healthcare: A roadmap for proactive and predictive health management

The field of infrared (IR) photonics is currently undergoing remarkable progress, moving rapidly towards practical sensing applications demanded by medical therapy and diagnostics (theranostics). The Developments can be divided into three main categories: (i) novel devices and measurement concepts including advanced updates of classical approaches that push medical sensing into the spotlight; (ii) new demonstrations of photonic integrated circuit (PIC-)based IR devices enabling highly miniaturized sensors for point-of-care application as well as medical and wellness wearables; and (iii) technologically-mature IR demonstrators that enable first medical sensing and treatment applications. This roadmap paper provides a consolidated overview of this highly dynamic and interdisciplinary research field with a focus on the major roadblocks that limit the widespread adoption of IR photonics in large-scale medical diagnostics. Special attention is given to the ambivalence between the molecular-level spectroscopic interpretation and a broader health-state assessment, highlighting the need for a common framework. Additionally, the paper discusses the critical importance of unified measurement standards, calibration protocols, and medical certification processes to ensure the validity of experimental results, reproducibility, and clinical trust, particularly when novel experimental techniques and AI algorithms are involved. Perspectives from major past and current contributors to application-oriented IR photonics will be provided.

physics.app-ph↗

arXiv2025

An immuno-Infrared Sensor detects preclinical Alzheimer's and Parkinson's Disease by misfolding

The immuno-infrared sensor detects target proteins in solution. Exemplary, the initial misfolding of amyloid beta (Abeta) peptides in blood is measured, enabling early risk prediction of Alzheimer's disease in the preclinical stage. Antibodies concentrate the target protein on the functionalized attenuated total reflection crystal surface. A quantum cascade laser is used to measure the amide I band, which indicates the secondary structure distribution of Abeta in blood as a biomarker.

physics.bio-ph↗

arXiv2020

Deep Neural Networks for the Correction of Mie Scattering in Fourier-Transformed Infrared Spectra of Biological Samples

Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of (resonant) Mie scattering, which often overshadows biochemically relevant spectral information by a non-linear, non-additive spectral component in Fourier transformed infrared (FTIR) spectroscopic measurements. Correspondingly, many successful machine learning approaches for FTIR spectra have relied on preprocessing procedures that computationally remove the scattering components from an infrared spectrum. We propose an approach to approximate this complex preprocessing function using deep neural networks. As we demonstrate, the resulting model is not just several orders of magnitudes faster, which is important for real-time clinical applications, but also generalizes strongly across different tissue types. Furthermore, our proposed method overcomes the trade-off between computation time and the corrected spectrum being biased towards an artificial reference spectrum.

cs.LG↗

arXiv2019

Estimation of Protein-Ligand Unbinding Kinetics Using Non-Equilibrium Targeted Molecular Dynamics Simulations

We here report on non-equilibrium targeted Molecular Dynamics simulations as tool for the estimation of protein-ligand unbinding kinetics. Correlating simulations with experimental data from SPR kinetics measurements and X-ray crystallography on two small molecule compound libraries bound to the N-terminal domain of the chaperone Hsp90, we show that the mean non-equilibrium work computed in an ensemble of trajectories of enforced ligand unbinding is a promising predictor for ligand unbinding rates. We furthermore investigate the molecular basis determining unbinding rates within the compound libraries. We propose ligand conformational changes and protein-ligand nonbonded interactions to impact on unbinding rates. Ligands may remain longer at the protein if they exhibit strong electrostatic and/or van der Waals interactions with the target. In the case of ligands with rigid chemical scaffold that exhibit longer residence times however, transient electrostatic interactions with the protein appear to facilitate unbinding. Our results imply that understanding the unbinding pathway and the protein-ligand interactions along this path is crucial for the prediction of small molecule ligands with defined unbinding

q-bio.BM↗