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Different sensor types using chemical and biochemical principles are described. The former are mainly gas sensors, the latter are applied especially to liquids. Those label-free direct detection methods are compared with applications where assays take advantage of labeled receptors.
Furthermore, selected applications in the area of gas sensors are discussed, and sensors for process control, point-of-care diagnostics, environmental analytics, and food analytics are reviewed. In addition, multiplexing approaches used in microplates and microarrays are described.
On account of the huge number of sensor types and the wide range of possible applications, only the most important ones are selected here.
Newly developed active pharmaceutical ingredients (APIs) are often poorly soluble in water. As a result the bioavailability of the API in the human body is reduced. One approach to overcome this restriction is the formulation of amorphous solid dispersions (ASDs), e.g., by hot-melt extrusion (HME). Thus, the poorly soluble crystalline form of the API is transferred into a more soluble amorphous form. To reach this aim in HME, the APIs are embedded in a polymer matrix. The resulting amorphous solid dispersions may contain small amounts of residual crystallinity and have the tendency to recrystallize. For the controlled release of the API in the final drug product the amount of crystallinity has to be known. This review assesses the available analytical methods that have been recently used for the characterization of ASDs
and the quantification of crystalline API content. Well established techniques like near- and mid-infrared spectroscopy (NIR and MIR, respectively), Raman spectroscopy, and emerging ones like UV/VIS, terahertz, and ultrasonic spectroscopy are considered in detail. Furthermore, their advantages and limitations are discussed with regard to general practical applicability as process analytical technology (PAT) tools in industrial manufacturing. The review focuses on spectroscopic methods which have been proven as most suitable for in-line and on-line process analytics. Further aspects are spectroscopic techniques that have been or could be integrated into an extruder.
This paper presents an approach for label-free brain tumor tissue typing. For this application, our dual modality microspectroscopy system combines inelastic Raman scattering spectroscopy and Mie elastic light scattering spectroscopy. The system enables marker-free biomedical diagnostics and records both the chemical and morphologic changes of tissues on a cellular and subcellular level. The system setup is described and the suitability for measuring morphologic features is investigated.
Current techniques for chromosome analysis need to be improved for rapid, economical identification of complex chromosomal defects by sensitive and selective visualisation. In this paper, we present a straightforward method for characterising unstained human metaphase chromosomes. Backscatter imaging in a dark-field setup combined with visible and short near-infrared spectroscopy is used to monitor morphological differences in the distribution of the chromosomal fine structure in human metaphase chromosomes. The reasons for the scattering centres in the fine structure are explained. Changes in the scattering centres during preparation of the metaphases are discussed. FDTD simulations are presented to substantiate the experimental findings. We show that local scattering features consisting of underlying spectral modulations of higher frequencies associated with a high variety of densely packed chromatin can be represented by their scatter profiles even on a sub-microscopic level. The result is independent of the chromosome preparation and structure size. This analytical method constitutes a rapid, costeffective and label-free cytogenetic technique which can be used in a standard light microscope.
We report on the reflectance, transmittance and fluorescence spectra (λ=200–1200nm) of four types of chicken eggshells (white, brown, light green, dark green) measured in situ without pretreatment and after ablation of 20–100 μm of the outer shell regions. The color pigment protoporphyrin IX (PPIX) is embedded in the protein phase of all four shell types as highly fluorescent monomers, in the white and light green shells additionally as non-fluorescent dimers, and in the brown and dark green shells mainly as non-fluorescent poly-aggregates. The green shell colors are formed from an approximately equimolar mixture of PPIX and biliverdin. The axial distribution of protein and color pigments were evaluated from the combined reflectances of both the outer and inner shell surfaces, as well as from the transmittances. For the data generation we used the radiative transfer model in the random walk and Kubelka-Munk approaches.
Different types of raw cotton were investigated by a commercial ultraviolet-visible/near infrared (UV-Vis/NIR) spectrometer (210–2200 nm) as well as on a home-built setup for NIR hyperspectral imaging (NIR-HSI) in the range 1100–2200 nm. UV-Vis/NIR reflection spectroscopy reveals the dominant role proteins, hydrocarbons and hydroxyl groups play in the structure of cotton. NIR-HSI shows a similar result. Experimentally obtained data in combination with principal component analysis (PCA) provides a general differentiation of different cotton types. For UV-Vis/NIR spectroscopy, the first two principal components (PC) represent 82 % and 78 % of the total data variance for the UV-Vis and NIR regions, respectively. Whereas, for NIR-HSI, due to the large amount of data acquired, two methodologies for data processing were applied in low and high lateral resolution. In the first method, the average of the spectra from one sample was calculated and in the second method the spectra of each pixel were used. Both methods are able to explain ≥90 % of total variance by the first two PCs. The results show that it is possible to distinguish between different cotton types based on a few selected wavelength ranges. The combination of HSI and multivariate data analysis has a strong potential in industrial applications due to its short acquisition time and low-cost development. This study opens a novel possibility for a further development of this technique towards real large-scale processes.
Characterization of brain tumours requires neuropathological expertise and is generally performed by histological evaluation and molecular analysis. One emerging technique to assist pathologists in future tumour diagnostics is multimodal optical spectroscopy. In the current clinical routine, tissue preprocessing with formalin is widely established and suitable for spectroscopic investigations since degradation processes impede the measurement of native tissue. However, formalin fixation results in alterations of the tissue chemistry and morphology for example by protein cross-linking. As optical spectroscopy is sensitive to these variations, we evaluate the effects of formalin fixation on multimodal brain tumour data in this proof-of-concept study. Nonfixed and formalin-fixed cross sections of different common human brain tumours were subjected to analysis of chemical variations using ultraviolet and Fourier-transform infrared microspectroscopy. Morphological changes were assessed by elastic light scattering microspectroscopy in the visible wavelength range. Data were analysed with multivariate data analysis and compared with histopathology. Tissue type classifications deduced by optical spectroscopy are highly comparable and independent from the preparation and the fixation protocol. However, formalin fixation leads to slightly better classification models due to improved stability of the tissue. As a consequence, spectroscopic methods represent an appropriate additional contrast for chemical and morphological information in neuropathological diagnosis and should be investigated to a greater extent. Furthermore, they can be included in the clinical workflow even after formalin fixation.
Auf jeder Stufe der Lebensmittelkette muss von der Herstellung bis zum Inverkehrbringen eine Rückverfolgung der Produkte möglich sein. Erzeuger, Verarbeiter, Transportunternehmen und Händler stehen vor der Herausforderung, Systeme zur Rückverfolgbarkeit effizient in ihre Unternehmensprozesse zu integrieren und gegenseitig zu vernetzen. Für die betriebliche Umsetzung werden die rechtlichen Anforderungen skizziert und die Grundlagen eines Rückverfolgbarkeitssystems vorgestellt.
The article analyzes experimentally and theoretically the influence of microscope parameters on the pinhole-assisted Raman depth profiles in uniform and composite refractive media. The main objective is the reliable mapping of deep sample regions. The easiest to interpret results are found with low magnification, low aperture, and small pinholes. Here, the intensities and shapes of the Raman signals are independent of the location of the emitter relative to the sample surface. Theoretically, the results can be well described with a simple analytical equation containing the axial depth resolution of the microscope and the position of the emitter. The lower determinable object size is limited to 2–4 μm. If sub-micrometer resolution is desired, high magnification, mostly combined with high aperture, becomes necessary. The signal intensities and shapes depend now in refractive media on the position relative to the sample surface. This aspect is investigated on a number of uniform and stacked polymer layers, 2–160 μm thick, with the best available transparency. The experimental depth profiles are numerically fitted with excellent accuracy by inserting a Gaussian excitation beam of variable waist and fill fraction through the focusing lens area, and by treating the Raman emission with geometric optics as spontaneous isotropic process through the lens and the variable pinhole, respectively. The intersectional area of these two solid angles yields the leading factor in understanding confocal (pinhole-assisted) Raman depth profiles.