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- ItemFusion of MALDI Spectrometric Imaging and Raman Spectroscopic Data for the Analysis of Biological Samples(Lausanne : Frontiers Media, 2018) Ryabchykov, Oleg; Popp, Jürgen; Bocklitz, Thomas W.Despite of a large number of imaging techniques for the characterization of biological samples, no universal one has been reported yet. In this work, a data fusion approach was investigated for combining Raman spectroscopic data with matrix-assisted laser desorption/ionization (MALDI) mass spectrometric data. It betters the image analysis of biological samples because Raman and MALDI information can be complementary to each other. While MALDI spectrometry yields detailed information regarding the lipid content, Raman spectroscopy provides valuable information about the overall chemical composition of the sample. The combination of Raman spectroscopic and MALDI spectrometric imaging data helps distinguishing different regions within the sample with a higher precision than would be possible by using either technique. We demonstrate that a data weighting step within the data fusion is necessary to reveal additional spectral features. The selected weighting approach was evaluated by examining the proportions of variance within the data explained by the first principal components of a principal component analysis (PCA) and visualizing the PCA results for each data type and combined data. In summary, the presented data fusion approach provides a concrete guideline on how to combine Raman spectroscopic and MALDI spectrometric imaging data for biological analysis.
- ItemDisturbing-free determination of yeast concentration in DI water and in glucose using impedance biochips(Basel : MDPI AG, 2020) Kiani, M.; Du, N.; Vogel, M.; Raff, J.; Hübner, U.; Skorupa, I.; Bürger, D.; Schulz, S.E.; Schmidt, O.G.; Blaschke, D.; Schmidt, H.Deionized water and glucose without yeast and with yeast (Saccharomyces cerevisiae) of optical density OD600 that ranges from 4 to 16 has been put in the ring electrode region of six different types of impedance biochips and impedance has been measured in dependence on the added volume (20, 21, 22, 23, 24, 25 µL). The measured impedance of two out of the six types of biochips is strongly sensitive to the addition of both liquid without yeast and liquid with yeast and modelled impedance reveals a linear relationship between the impedance model parameters and yeast concentration. The presented biochips allow for continuous impedance measurements without interrupting the cultivation of the yeast. A multiparameter fit of the impedance model parameters allows for determining the concentration of yeast (cy) in the range from cy = 3.3 × 107 to cy = 17 × 107 cells/mL. This work shows that independent on the liquid, i.e., DI water or glucose, the impedance model parameters of the two most sensitive types of biochips with liquid without yeast and with liquid with yeast are clearly distinguishable for the two most sensitive types of biochips.
- ItemcellSTORM - Cost-effective Super-Resolution on a Cellphone using dSTORM(San Francisco : Public Library of Science, 2019) Diederich, Benedict; Then, Patrick; Jügler, Alexander; Förster, Ronny; Heintzmann, RainerHigh optical resolution in microscopy usually goes along with costly hardware components, such as lenses, mechanical setups and cameras. Several studies proved that Single Molecular Localization Microscopy can be made affordable, relying on off-the-shelf optical components and industry grade CMOS cameras. Recent technological advantages have yielded consumer-grade camera devices with surprisingly good performance. The camera sensors of smartphones have benefited of this development. Combined with computing power smartphones provide a fantastic opportunity for “imaging on a budget”. Here we show that a consumer cellphone is capable of optical super-resolution imaging by (direct) Stochastic Optical Reconstruction Microscopy (dSTORM), achieving optical resolution better than 80 nm. In addition to the use of standard reconstruction algorithms, we used a trained image-to-image generative adversarial network (GAN) to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance directly on the smartphone. We believe that “cellSTORM” paves the way to make super-resolution microscopy not only affordable but available due to the ubiquity of cellphone cameras.High optical resolution in microscopy usually goes along with costly hardware components, such as lenses, mechanical setups and cameras. Several studies proved that Single Molecular Localization Microscopy can be made affordable, relying on off-the-shelf optical components and industry grade CMOS cameras. Recent technological advantages have yielded consumer-grade camera devices with surprisingly good performance. The camera sensors of smartphones have benefited of this development. Combined with computing power smartphones provide a fantastic opportunity for “imaging on a budget”. Here we show that a consumer cellphone is capable of optical super-resolution imaging by (direct) Stochastic Optical Reconstruction Microscopy (dSTORM), achieving optical resolution better than 80 nm. In addition to the use of standard reconstruction algorithms, we used a trained image-to-image generative adversarial network (GAN) to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance directly on the smartphone. We believe that “cellSTORM” paves the way to make super-resolution microscopy not only affordable but available due to the ubiquity of cellphone cameras.
- ItemAluminum-Doped Zinc Oxide Improved by Silver Nanowires for Flexible, Semitransparent and Conductive Electrodes on Textile with High Temperature Stability(Basel : MDPI, 2023) Hupfer, Maximilian Lutz; Gawlik, Annett; Dellith, Jan; Plentz, JonathanIn order to facilitate the design freedom for the implementation of textile-integrated electronics, we seek flexible transparent conductive electrodes (TCEs) that can withstand not only the mechanical stresses encountered during use but also the thermal stresses of post-treatment. The transparent conductive oxides (TCO) typically used for this purpose are rigid in comparison to the fibers or textiles they are intended to coat. In this paper, a TCO, specifically aluminum-doped zinc oxide (Al:ZnO), is combined with an underlying layer of silver nanowires (Ag-NW). This combination brings together the advantages of a closed, conductive Al:ZnO layer and a flexible Ag-NW layer, forming a TCE. The result is a transparency of 20–25% (within the 400–800 nm range) and a sheet resistance of 10 Ω/sq that remains almost unchanged, even after post-treatment at 180 °C.
- ItemShape-Dependent Catalytic Activity of Gold and Bimetallic Nanoparticles in the Reduction of Methylene Blue by Sodium Borohydride(Basel : MDPI, 2021) Stolle, Heike Lisa Kerstin Stephanie; Kluitmann, Jonas Jakobus; Csáki, Andrea; Köhler, Johann Michael; Fritzsche, WolfgangIn this study the catalytic activity of different gold and bimetallic nanoparticle solutions towards the reduction of methylene blue by sodium borohydride as a model reaction is investigated. By utilizing differently shaped gold nanoparticles, i.e., spheres, cubes, prisms and rods as well as bimetallic gold–palladium and gold–platinum core-shell nanorods, we evaluate the effect of the catalyst surface area as available gold surface area, the shape of the nanoparticles and the impact of added secondary metals in case of bimetallic nanorods. We track the reaction by UV/Vis measurements in the range of 190–850 nm every 60 s. It is assumed that the gold nanoparticles do not only act as a unit transferring electrons from sodium borohydride towards methylene blue but can promote the electron transfer upon plasmonic excitation. By testing different particle shapes, we could indeed demonstrate an effect of the particle shape by excluding the impact of surface area and/or surface ligands. All nanoparticle solutions showed a higher methylene blue turnover than their reference, whereby gold nanoprisms exhibited 100% turnover as no further methylene blue absorption peak was detected. The reaction rate constant k was also determined and revealed overall quicker reactions when gold or bimetallic nanoparticles were added as a catalyst, and again these were highest for nanoprisms. Furthermore, when comparing gold and bimetallic nanorods, it could be shown that through the addition of the catalytically active second metal platinum or palladium, the dye turnover was accelerated and degradation rate constants were higher compared to those of pure gold nanorods. The results explore the catalytic activity of nanoparticles, and assist in exploring further catalytic applications.
- ItemComputational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning(Washington, DC : OSA, 2021) Pradhan, Pranita; Meyer, Tobias; Vieth, Michael; Stallmach, Andreas; Waldner, Maximilian; Schmitt, Michael; Popp, Juergen; Bocklitz, ThomasHematoxylin and Eosin (H&E) staining is the 'gold-standard' method in histopathology. However, standard H&E staining of high-quality tissue sections requires long sample preparation times including sample embedding, which restricts its application for 'real-time' disease diagnosis. Due to this reason, a label-free alternative technique like non-linear multimodal (NLM) imaging, which is the combination of three non-linear optical modalities including coherent anti-Stokes Raman scattering, two-photon excitation fluorescence and second-harmonic generation, is proposed in this work. To correlate the information of the NLM images with H&E images, this work proposes computational staining of NLM images using deep learning models in a supervised and an unsupervised approach. In the supervised and the unsupervised approach, conditional generative adversarial networks (CGANs) and cycle conditional generative adversarial networks (cycle CGANs) are used, respectively. Both CGAN and cycle CGAN models generate pseudo H&E images, which are quantitatively analyzed based on mean squared error, structure similarity index and color shading similarity index. The mean of the three metrics calculated for the computationally generated H&E images indicate significant performance. Thus, utilizing CGAN and cycle CGAN models for computational staining is beneficial for diagnostic applications without performing a laboratory-based staining procedure. To the author's best knowledge, it is the first time that NLM images are computationally stained to H&E images using GANs in an unsupervised manner.
- ItemUsing machine-learning to optimize phase contrast in a low-cost cellphone microscope(San Francisco, CA : Public Library of Science, 2018) Diederich, Benedict; Wartmann, Rolf; Schadwinkel, Harald; Heintzmann, RainerCellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computational and imaging resources to perform medical diagnosis in developing countries at a very low cost. Many relevant samples, like biological cells or waterborn parasites, are almost fully transparent. As they do not exhibit absorption, but alter the light’s phase only, they are almost invisible in brightfield microscopy. Expensive equipment and procedures for microscopic contrasting or sample staining often are not available. Dedicated illumination approaches, tailored to the sample under investigation help to boost the contrast. This is achieved by a programmable illumination source, which also allows to measure the phase gradient using the differential phase contrast (DPC) [1, 2] or even the quantitative phase using the derived qDPC approach [3]. By applying machine-learning techniques, such as a convolutional neural network (CNN), it is possible to learn a relationship between samples to be examined and its optimal light source shapes, in order to increase e.g. phase contrast, from a given dataset to enable real-time applications. For the experimental setup, we developed a 3D-printed smartphone microscope for less than 100 $ using off-the-shelf components only such as a low-cost video projector. The fully automated system assures true Koehler illumination with an LCD as the condenser aperture and a reversed smartphone lens as the microscope objective. We show that the effect of a varied light source shape, using the pre-trained CNN, does not only improve the phase contrast, but also the impression of an improvement in optical resolution without adding any special optics, as demonstrated by measurements.
- ItemClonal Complexes Distribution of Staphylococcus aureus Isolates from Clinical Samples from the Caribbean Islands(Basel : MDPI, 2023) Monecke, Stefan; Akpaka, Patrick Eberechi; Smith, Margaret R.; Unakal, Chandrashekhar G.; Thoms Rodriguez, Camille-Ann; Ashraph, Khalil; Müller, Elke; Braun, Sascha D.; Diezel, Celia; Reinicke, Martin; Ehricht, RalfThe aim of this study was to comprehensively characterise S. aureus from the Caribbean Islands of Trinidad and Tobago, and Jamaica. A total of 101 S. aureus/argenteus isolates were collected in 2020, mainly from patients with skin and soft tissue infections. They were characterised by DNA microarray allowing the detection of ca. 170 target genes and assignment to clonal complexes (CC)s and strains. In addition, the in vitro production of Panton–Valentine leukocidin (PVL) was examined by an experimental lateral flow assay. Two isolates were identified as S. argenteus, CC2596. The remaining S. aureus isolates were assigned to 21 CCs. The PVL rate among methicillin-susceptible S. aureus (MSSA) isolates was high (38/101), and 37 of the 38 genotypically positive isolates also yielded positive lateral flow results. The isolate that did not produce PVL was genome-sequenced, and it was shown to have a frameshift mutation in agrC. The high rate of PVL genes can be attributed to the presence of a known local CC8–MSSA clone in Trinidad and Tobago (n = 12) and to CC152–MSSA (n = 15). In contrast to earlier surveys, the USA300 clone was not found, although one MSSA isolate carried the ACME element, probably being a mecA-deficient derivative of this strain. Ten isolates, all from Trinidad and Tobago, were identified as MRSA. The pandemic ST239–MRSA–III strain was still common (n = 7), but five isolates showed a composite SCCmec element not observed elsewhere. Three isolates were sequenced. That showed a group of genes (among others, speG, crzC, and ccrA/B-4) to be linked to its SCC element, as previously found in some CC5– and CC8–MRSA, as well as in S. epidermidis. The other three MRSA belonged to CC22, CC72, and CC88, indicating epidemiological connections to Africa and the Middle East.
- ItemSignal and noise analysis for chiral structured illumination microscopy(Washington, DC : Optical Society of America, OSA, 2021) Huang, Shiang-Yu; Singh, Ankit Kumar; Huang, Jer-ShingRecently, chiral structured illumination microscopy has been proposed to image fluorescent chiral domains at sub-wavelength resolution. Chiral structured illumination microscopy is based on the combination of structured illumination microscopy, fluorescence-detected circular dichroism, and optical chirality engineering. Since circular dichroism of natural chiral molecules is typically weak, the differential fluorescence is also weak and can be easily buried by the noise, hampering the fidelity of the reconstructed images. In this work, we systematically study the impact of the noise on the quality and resolution of chiral domain images obtained by chiral SIM. We analytically describe the signal-to-noise ratio of the reconstructed chiral SIM image in the Fourier domain and verify our theoretical calculations with numerical demonstrations. Accordingly, we discuss the feasibility of chiral SIM in different experimental scenarios and propose possible strategies to enhance the signal-to-noise ratio for samples with weak circular dichroism.
- 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.