Search Results
Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy
2020, Stiebing, Clara, Jahn, Izabella J., Schmitt, Michael, Keijzer, Nanda, Kleemann, Robert, Kiliaan, Amanda J., Drexler, Wolfgang, Leitgeb, Rainer A., Popp, Jürgen
The presence of biomarkers characteristic for Alzheimer's disease in the retina is a controversial topic. Raman spectroscopy offers information on the biochemical composition of tissues. Thus, it could give valuable insight into the diagnostic value of retinal analysis. Within the present study, retinas of a double transgenic mouse model, that expresses a chimeric mouse/human amyloid precursor protein and a mutant form of human presenilin 1, and corresponding control group were subjected to ex vivo Raman imaging. The Raman data recorded on cross sections of whole eyes highlight the layered structure of the retina in a label-free manner. Based on the Raman information obtained from en face mounted retina samples, a discrimination between healthy and Alzheimer's disease retinal tissue can be done with an accuracy of 85.9%. For this a partial least squares-linear discriminant analysis was applied. Therefore, although no macromolecular changes in form of, i.e., amyloid beta plaques, can be noticed based on Raman spectroscopy, subtle biochemical changes happening in the retina could lead to Alzheimer's disease identification. ©
Discrimination between pathogenic and non-pathogenic E. coli strains by means of Raman microspectroscopy
2020, Lorenz B., Ali N., Bocklitz T., Rösch P., Popp J.
Bacteria can be harmless commensals, beneficial probiotics, or harmful pathogens. Therefore, mankind is challenged to detect and identify bacteria in order to prevent or treat bacterial infections. Examples are identification of species for treatment of infection in clinics and E. coli cell counting for water quality monitoring. Finally, in some instances, the pathogenicity of a species is of interest. The main strategies to investigate pathogenicity are detection of target genes which encode virulence factors. Another strategy could be based on phenotypic identification. Raman spectroscopy is a promising phenotypic method, which offers high sensitivities and specificities for the identification of bacteria species. In this study, we evaluated whether Raman microspectroscopy could be used to determine the pathogenicity of E. coli strains. We used Raman spectra of seven non-pathogenic and seven pathogenic E. coli strains to train a PCA-SVM model. Then, the obtained model was tested by identifying the pathogenicity of three additional E. coli strains. The pathogenicity of these three strains could be correctly identified with a mean sensitivity of 77%, which is suitable for a fast screening of pathogenicity of single bacterial cells. [Figure not available: see fulltext.]. © 2020, The Author(s).
Spectrometer‐free Optical Hydrogen Sensing Based on Fano‐like Spatial Distribution of Transmission in a Metal−Insulator−Metal Plasmonic Doppler Grating
2021, Chen, Yi‐Ju, Lin, Fan‐Cheng, Singh, Ankit Kumar, Ouyang, Lei, Huang, Jer‐Shing
Optical nanosensors are promising for hydrogen sensing because they are small, free from spark generation, and feasible for remote optical readout. Conventional optical nanosensors require broadband excitation and spectrometers, rendering the devices bulky and complex. An alternative is spatial intensity-based optical sensing, which only requires an imaging system and a smartly designed platform to report the spatial distribution of analytical optical signals. Here, a spatial intensity-based hydrogen sensing platform is presented based on Fano-like spatial distribution of the transmission in a Pd-Al2O3-Au metal-insulator-metal plasmonic Doppler grating (MIM-PDG). The MIM-PDG manifests the Fano resonance as an asymmetric spatial transmission intensity profile. The absorption of hydrogen changes the spatial Fano-like transmission profiles, which can be analyzed with a “spatial” Fano resonance model and the extracted Fano resonance parameters can be used to establish analytical calibration lines. While gratings sensitive to hydrogen absorption are suitable for hydrogen sensing, hydrogen insensitive gratings are also found, which provide an unperturbed reference signal and may find applications in nanophotonic devices that require a stable optical response under fluctuating hydrogen atmosphere. The MIM-PDG platform is a spectrometer-free and intensity-based optical sensor that requires only an imaging system, making it promising for cellphone-based optical sensing applications. © 2021 The Authors. Advanced Optical Materials published by Wiley-VCH GmbH.
Towards Bacteria Counting in DI Water of Several Microliters or Growing Suspension Using Impedance Biochips
2020, Kiani, Mahdi, Tannert, Astrid, Du, Nan, Hübner, Uwe, Skorupa, Ilona, Bürger, Danilo, Zhao, Xianyue, Blaschke, Daniel, Rebohle, Lars, Cherkouk, Charaf, Neugebauer, Ute, Schmidt, Oliver G., Schmidt, Heidemarie
We counted bacterial cells of E. coli strain K12 in several-microliter DI water or in several-microliter PBS in the low optical density (OD) range (OD = 0.05–1.08) in contact with the surface of Si-based impedance biochips with ring electrodes by impedance measurements. The multiparameter fit of the impedance data allowed calibration of the impedance data with the concentration cb of the E. coli cells in the range of cb = 0.06 to 1.26 × 109 cells/mL. The results showed that for E. coli in DI water and in PBS, the modelled impedance parameters depend linearly on the concentration of cells in the range of cb = 0.06 to 1.26 × 109 cells/mL, whereas the OD, which was independently measured with a spectrophotometer, was only linearly dependent on the concentration of the E. coli cells in the range of cb = 0.06 to 0.50 × 109 cells/mL.
Present and future of surface-enhanced Raman scattering
2020, Langer, Judith, de Aberasturi, Dorleta Jimenez, Aizpurua, Javier, Alvarez-Puebla, Ramon A., Auguié, Baptiste, Baumberg, Jeremy J., Bazan, Guillermo C., Bell, Steven E.J., Boisen, Anja, Brolo, Alexandre G., Choo, Jaebum, Cialla-May, Dana, Deckert, Volker, Fabris, Laura, Faulds, Karen, de Abajo, F. Javier García, Goodacre, Royston, Graham, Duncan, Haes, Amanda J., Haynes, Christy L., Huck, Christian, Itoh, Tamitake, Käll, Mikael, Kneipp, Janina, Kotov, Nicholas A., Kuang, Hua, Le Ru, Eric C., Lee, Hiang Kwee, Li, Jian-Feng, Ling, Xing Yi, Maier, Stefan A., Mayerhöfer, Thomas, Moskovits, Martin, Murakoshi, Kei, Nam, Jwa-Min, Nie, Shuming, Ozaki, Yukihiro, Pastoriza-Santos, Isabel, Perez-Juste, Jorge, Popp, Juergen, Pucci, Annemarie, Reich, Stephanie, Ren, Bin, Schatz, George C., Shegai, Timur, Schlücker, Sebastian, Tay, Li-Lin, Thomas, K. George, Tian, Zhong-Qun, Van Duyne, Richard P., Vo-Dinh, Tuan, Wang, Yue, Willets, Katherine A., Xu, Chuanlai, Xu, Hongxing, Xu, Yikai, Yamamoto, Yuko S., Zhao, Bing, Liz-Marzán, Luis M.
The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.
Plasmon induced deprotonation of 2-mercaptopyridine
2020, Singh P., Deckert-Gaudig T., Zhang Z., Deckert V.
Surface plasmons can provide a novel route to induce and simultaneously monitor selective bond formation and breakage. Here pH-induced protonation, followed by plasmon-induced deprotonation of 2-mercaptopyridine was investigated using surface- and tip-enhanced Raman scattering (SERS and TERS). A large difference in the deprotonation rate between SERS and TERS will be demonstrated and discussed with respect to hot-spot distribution. © 2020 The Royal Society of Chemistry.
Surface-Enhanced Raman Spectroscopy to Characterize Different Fractions of Extracellular Vesicles from Control and Prostate Cancer Patients
2021, Osei, Eric Boateng, Paniushkina, Liliia, Wilhelm, Konrad, Popp, Jürgen, Nazarenko, Irina, Krafft, Christoph
Extracellular vesicles (EVs) are membrane-enclosed structures ranging in size from about 60 to 800 nm that are released by the cells into the extracellular space; they have attracted interest as easily available biomarkers for cancer diagnostics. In this study, EVs from plasma of control and prostate cancer patients were fractionated by differential centrifugation at 5000× g, 12,000× g and 120,000× g. The remaining supernatants were purified by ultrafiltration to produce EV-depleted free-circulating (fc) fractions. Spontaneous Raman and surface-enhanced Raman spectroscopy (SERS) at 785 nm excitation using silver nanoparticles (AgNPs) were employed as label-free techniques to collect fingerprint spectra and identify the fractions that best discriminate between control and cancer patients. SERS spectra from 10 µL droplets showed an enhanced Raman signature of EV-enriched fractions that were much more intense for cancer patients than controls. The Raman spectra of dehydrated pellets of EV-enriched fractions without AgNPs were dominated by spectral contributions of proteins and showed variations in S-S stretch, tryptophan and protein secondary structure bands between control and cancer fractions. We conclude that the AgNPs-mediated SERS effect strongly enhances Raman bands in EV-enriched fractions, and the fractions, EV12 and EV120 provide the best separation of cancer and control patients by Raman and SERS spectra.
Rapid detection of the aspergillosis biomarker triacetylfusarinine C using interference-enhanced Raman spectroscopy
2020, Pahlow S., Orasch T., Žukovskaja O., Bocklitz T., Haas H., Weber K.
Triacetylfusarinine C (TAFC) is a siderophore produced by certain fungal species and might serve as a highly useful biomarker for the fast diagnosis of invasive aspergillosis. Due to its renal elimination, the biomarker is found in urine samples of patients suffering from Aspergillus infections. Accordingly, non-invasive diagnosis from this easily obtainable body fluid is possible. Within our contribution, we demonstrate how Raman microspectroscopy enables a sensitive and specific detection of TAFC. We characterized the TAFC iron complex and its iron-free form using conventional and interference-enhanced Raman spectroscopy (IERS) and compared the spectra with the related compound ferrioxamine B, which is produced by bacterial species. Even though IERS only offers a moderate enhancement of the Raman signal, the employment of respective substrates allowed lowering the detection limit to reach the clinically relevant range. The achieved limit of detection using IERS was 0.5 ng of TAFC, which is already well within the clinically relevant range. By using an extraction protocol, we were able to detect 1.4 μg/mL TAFC via IERS from urine within less than 3 h including sample preparation and data analysis. We could further show that TAFC and ferrioxamine B can be clearly distinguished by means of their Raman spectra even in very low concentrations. © 2020, The Author(s).
Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study
2020, Guo S., Beleites C., Neugebauer U., Abalde-Cela S., Afseth N.K., Alsamad F., Anand S., Araujo-Andrade C., Aškrabić S., Avci E., Baia M., Baranska M., Baria E., Batista De Carvalho L.A.E., De Bettignies P., Bonifacio A., Bonnier F., Brauchle E.M., Byrne H.J., Chourpa I., Cicchi R., Cuisinier F., Culha M., Dahms M., David C., Duponchel L., Duraipandian S., El-Mashtoly S.F., Ellis D.I., Eppe G., Falgayrac G., Gamulin O., Gardner B., Gardner P., Gerwert K., Giamarellos-Bourboulis E.J., Gizurarson S., Gnyba M., Goodacre R., Grysan P., Guntinas-Lichius O., Helgadottir H., Grošev V.M., Kendall C., Kiselev R., Kölbach M., Krafft C., Krishnamoorthy S., Kubryck P., Lendl B., Loza-Alvarez P., Lyng F.M., Machill S., Malherbe C., Marro M., Marques M.P.M., Matuszyk E., Morasso C.F., Moreau M., Muhamadali H., Mussi V., Notingher I., Pacia M.Z., Pavone F.S., Penel G., Petersen D., Piot O., Rau J.V., Richter M., Rybarczyk M.K., Salehi H., Schenke-Layland K., Schlücker S., Schosserer M., Schütze K., Sergo V., Sinjab F., Smulko J., Sockalingum G.D., Stiebing C., Stone N., Untereiner V., Vanna R., Wieland K., Popp J., Bocklitz T.
The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies. © 2020 American Chemical Society.
Fiber-based SORS-SERDS system and chemometrics for the diagnostics and therapy monitoring of psoriasis inflammatory disease in vivo
2021-1-28, Schleusener, Johannes, Guo, Shuxia, Darvin, Maxim E., Thiede, Gisela, Chernavskaia, Olga, Knorr, Florian, Lademann, Jürgen, Popp, Jürgen, Bocklitz, Thomas W.
Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.