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- ItemFLIM data analysis based on Laguerre polynomial decomposition and machine-learning(Bellingham, Wash. : SPIE, 2021) Guo, Shuxia; Silge, Anja; Bae, Hyeonsoo; Tolstik, Tatiana; Meyer, Tobias; Matziolis, Georg; Schmitt, Michael; Popp, Jürgen; Bocklitz, ThomasSignificance: The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis. Aim: We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML). Approach: The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker. Results: The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.
- ItemFuture heat stress to reduce people’s purchasing power(San Francisco, Ca. : PLOS, 2021) Kuhla, Kilian; Willner, Sven Norman; Otto, Christian; Wenz, Leonie; Levermann, AndersWith increasing carbon emissions rising temperatures are likely to impact our economies and societies profoundly. In particular, it has been shown that heat stress can strongly reduce labor productivity. The resulting economic perturbations can propagate along the global supply network. Here we show, using numerical simulations, that output losses due to heat stress alone are expected to increase by about 24% within the next 20 years, if no additional adaptation measures are taken. The subsequent market response with rising prices and supply shortages strongly reduces the consumers’ purchasing power in almost all countries including the US and Europe with particularly strong effects in India, Brazil, and Indonesia. As a consequence, the producing sectors in many regions temporarily benefit from higher selling prices while decreasing their production in quantity, whereas other countries suffer losses within their entire national economy. Our results stress that, even though climate shocks may stimulate economic activity in some regions and some sectors, their unpredictability exerts increasing pressure on people’s livelihood.
- ItemThree step flow focusing enables image-based discrimination and sorting of late stage 1 Haematococcus pluvialis cells(San Francisco, Ca. : PLOS, 2021) Kraus, Daniel; Kleiber, Andreas; Ehrhardt, Enrico; Leifheit, Matthias; Horbert, Peter; Urban, Matthias; Gleichmann, Nils; Mayer, Guenter; Popp, Juergen; Henkel, ThomasLabel-free and gentle separation of cell stages with desired target properties from mixed stage populations are a major research task in modern biotechnological cultivation process and optimization of micro algae. The reported microfluidic sorter system (MSS) allows the subsequent investigation of separated subpopulations. The implementation of a viability preserving MSS is shown for separation of late stage 1 Haematococcus pluvialis (HP) cells form a mixed stage population. The MSS combines a three-step flow focusing unit for aligning the cells in single file transportation mode at the center of the microfluidic channel with a pure hydrodynamic sorter structure for cell sorting. Lateral displacement of the cells into one of the two outlet channels is generated by piezo-actuated pump chambers. In-line decision making for sorting is based on a user-definable set of image features and properties. The reported MSS significantly increased the purity of target cells in the sorted population (94%) in comparison to the initial mixed stage population (19%).
- ItemIn vivo detection of changes in cutaneous carotenoids after chemotherapy using shifted excitation resonance Raman difference and fluorescence spectroscopy(Oxford [u.a.] : Wiley-Blackwell, 2020) Jung, Sora; Darvin, Maxim E.; Schleusener, Johannes; Thiede, Gisela; Lademann, Juergen; Braune, Marcel; Elban, Felia; Fuss, HaraldBackground: Various cutaneous toxicities under chemotherapy indicate a local effect of chemotherapy by secretion after systemic application. Here, changes in the fluorescence and Raman spectral properties of the stratum corneum subsequent to intravenous chemotherapy were assessed. Methods: Twenty healthy subjects and 20 cancer patients undergoing chemotherapy were included. Measurement time points in cancer patients were before the first cycle of chemotherapy (Tbase) and immediately after intravenous application of the chemotherapy (T1). Healthy subjects were measured once without any further intervention. Measurements were conducted using an individually manufactured system consisting of a handheld probe and a wavelength-tunable diode laser-based 488 nm SHG light source. Hereby, changes in both skin fluorescence and shifted excitation resonance Raman difference spectroscopy (SERRDS) carotenoid signals were assessed. Results: Healthy subjects showed significantly (P <.001) higher mean concentrations of carotenoids compared to cancer subjects at Tbase. An increase in fluorescence intensity was detected in almost all patients after chemotherapy, especially after doxorubicin infusion. Furthermore, a decrease in the carotenoid concentration in the skin after chemotherapy was found. Conclusion: The SERRDS based noninvasive detection can be used as an indirect quantitative assessment of fluorescent chemotherapeutics. The lower carotenoid SERRDS intensities at Tbase might be due to cancerous diseases and co-medication. © 2020 The Authors. Skin Research and Technology Published by John Wiley & Sons Ltd.
- ItemBroad consent under the GDPR : an optimistic perspective on a bright future(Berlin ; Heidelberg [u.a.] : Springer Open, 2020) Hallinan, DaraBroad consent-the act of gaining one consent for multiple potential future research projects-sits at the core of much current genomic research practice. Since the 25th May 2018, the General Data Protection Regulation (GDPR) has applied as valid law concerning genomic research in the EU and now occupies a dominant position in the legal landscape. Yet, the position of the GDPR concerning broad consent has recently been cause for concern in the genomic research community. Whilst the text of the GDPR apparently supports the practice, recent jurisprudence contains language which is decidedly less positive. This article takes an in-depth look at the situation concerning broad consent under the GDPR and-despite the understandable concern flowing from recent jurisprudence-offers a positive outlook. This positive outlook is argued from three perspectives, each of which is significant in defining the current, and ongoing, legitimacy and utility of broad consent under the GDPR: The principled, the legal technical, and the practical. © 2020 The Author(s).
- ItemCorrecting systematic errors by hybrid 2D correlation loss functions in nonlinear inverse modelling(San Francisco, California, US : PLOS, 2023) Mayerhöfer, Thomas G.; Noda, Isao; Pahlow, Susanne; Heintzmann, Rainer; Popp, JürgenRecently a new family of loss functions called smart error sums has been suggested. These loss functions account for correlations within experimental data and force modeled data to obey these correlations. As a result, multiplicative systematic errors of experimental data can be revealed and corrected. The smart error sums are based on 2D correlation analysis which is a comparably recent methodology for analyzing spectroscopic data that has found broad application. In this contribution we mathematically generalize and break down this methodology and the smart error sums to uncover the mathematic roots and simplify it to craft a general tool beyond spectroscopic modelling. This reduction also allows a simplified discussion about limits and prospects of this new method including one of its potential future uses as a sophisticated loss function in deep learning. To support its deployment, the work includes computer code to allow reproduction of the basic results.