Spectroscopic data often contain artifacts or noise related to the sample characteristics, instrumental variations, or experimental design flaws. Therefore, classifying the raw data is not recommended and might lead to biased results. Nevertheless, most issues may be addressed through appropriate data pre-processing. Effective pre-processing is particularly crucial in critical applications like liquid biopsy for disease detection, where even minor performance improvements may impact patient outcomes. Unfortunately, there is no consensus regarding optimal pre-processing, complicating cross-study comparisons. This study presents a comprehensive evaluation of various pre-processing methods and their combinations to assess their influence on classification results. The goal was to identify whether some pre-processing methods are associated with higher classification outcomes and find an optimal strategy for the given data. Data from Raman optical activity and infrared and Raman spectroscopy were processed, applying tens of thousands of possible pre-processing pipelines. The resulting data were classified using three algorithms to distinguish between subjects with liver cirrhosis and those who had developed hepatocellular carcinoma. Results highlighted that some specific pre-processing methods often ranked among the best classification results, such as the Rolling Ball for correcting the baseline of Raman spectra or the Doubly Reweighted Penalized Least Squares and Mixture model in the case of Raman optical activity. On the other hand, the selection of filtering and/or normalization approach usually did not have a significant impact. Nonetheless, the pre-processing of top-scoring pipelines also depended on the classifier utilized. The best pipelines yielded an AUROC of 0.775-0.823, varying with the evaluated spectroscopic data and classifier.

• Klíčová slova
• Chiroptical spectroscopy, Classification, Data pre-processing, Diagnostics, Liquid biopsy, Machine learning, Vibrational spectroscopy,
• MeSH
• algoritmy MeSH
• hepatocelulární karcinom * diagnóza   patologie   MeSH
• jaterní cirhóza diagnóza   patologie   MeSH
• lidé MeSH
• metoda nejmenších čtverců MeSH
• nádory jater * diagnóza   patologie   MeSH
• Ramanova spektroskopie * metody   MeSH
• spektrofotometrie infračervená metody   MeSH
• tekutá biopsie metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Vibrational spectroscopy is a nondestructive analysis technique that depends on the periodic variations in dipole moments and polarizabilities resulting from the molecular vibrations of molecules/atoms. These methods have important advantages over conventional analytical techniques, including (a) their simplicity in terms of implementation and operation, (b) their adaptability to on-line and on-farm applications, (c) making measurement in a few minutes, and (d) the absence of dangerous solvents throughout sample preparation or measurement. Food safety is a concept that requires the assurance that food is free from any physical, chemical, or biological hazards at all stages, from farm to fork. Continuous monitoring should be provided in order to guarantee the safety of the food. Regarding their advantages, vibrational spectroscopic methods, such as Fourier-transform infrared (FTIR), near-infrared (NIR), and Raman spectroscopy, are considered reliable and rapid techniques to track food safety- and food authenticity-related issues throughout the food chain. Furthermore, coupling spectral data with chemometric approaches also enables the discrimination of samples with different kinds of food safety-related hazards. This review deals with the recent application of vibrational spectroscopic techniques to monitor various hazards related to various foods, including crops, fruits, vegetables, milk, dairy products, meat, seafood, and poultry, throughout harvesting, transportation, processing, distribution, and storage.

• Klíčová slova
• Food safety, Fourier transform infrared spectroscopy, Infrared spectroscopy, Nondestructive methods, Raman spectroscopy, Value chain, Vibrational Spectroscopy,
• MeSH
• analýza potravin * metody   MeSH
• bezpečnost potravin * metody   MeSH
• farmy MeSH
• Ramanova spektroskopie * metody   MeSH
• spektrální analýza * metody   MeSH
• spektroskopie infračervená s Fourierovou transformací metody   MeSH
• vibrace MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

In this study, we employed stimulated Raman scattering (SRS) microscopy, augmented with sum frequency generation, to characterize complex solid-state mixtures, containing many solid-state forms of the same compound, for the first time. Five crystalline forms and one amorphous form of lactose were characterized and resolved, including two more recently defined anhydrous solid-state forms. Additionally, the complex solid-state character of several commercially available pharmaceutical tableting and inhalation grades of lactose was profiled. The advanced multimodal label-free microscopy method enabled visualization of the distribution of the solid-state forms with submicron spatial resolution, including the detection of trace levels. In addition, quantitative solid-state compositions of the lactose products were estimated. Overall SRS microscopy allows sensitive and specific spatially resolved solid-state characterization of complex mixtures, beyond what is possible with established (nonspatially resolved) characterization methods.

• MeSH
• laktosa * chemie   analýza   MeSH
• léčivé přípravky chemie   MeSH
• mikroskopie MeSH
• nelineární optická mikroskopie * metody   MeSH
• Ramanova spektroskopie * metody   MeSH
• tablety chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• laktosa * MeSH
• léčivé přípravky MeSH
• tablety MeSH

MicroRNAs (miRNAs) are small non-coding RNAs (18-22 nucleotides) that regulate gene expression and are associated with various diseases, including Laryngeal Cancer (LCa), which has a high mortality rate due to late diagnosis. Traditional methods for miRNA detection present several drawbacks (time-consuming steps, high cost and high false positive rate). Early-stage diagnosis and selective detection of miRNAs remain challenging. This study proposes a 3D flexible biosensor that combines nanofibers (NFs), gold nanoparticles (AuNPs), and an inverse molecular sentinel (iMS) for enzyme-free, SERS-based detection of miRNA-223-3p, evaluated as a potential LCa biomarker. The electrospun flexible nanofibers decorated with AuNPs enhance Raman signal. Selective detection of miRNA-223-3p is achieved by immobilizing an iMS-DNA probe labeled with a Raman reporter (Cyanine 3) on the AuNPs. The iMS distinctive stem-and-loop structure undergoes a conformational change upon interaction with the miRNA-223-3p, producing an "on to off" SERS signal. The proposed sensor demonstrated a linear detection range from 10 to 250 fM, with a limit of detection (LOD) of 19.50 ± 0.05 fM. The sensor selectivity was confirmed by analyzing the SERS signal behaviour in the presence of both Non-complementary miRNA and miRNA with three mismatched base pairs. This easily fabricable sensor requires no amplification and offers key advantages, including sensitivity, flexibility, and cost-effectiveness.

• Klíčová slova
• Flexible sensors, Laryngeal Cancer, Nanofiber, SERS, miRNA-223-3p,
• MeSH
• biosenzitivní techniky * metody   MeSH
• časná detekce nádoru * metody   MeSH
• kovové nanočástice chemie   MeSH
• lidé MeSH
• limita detekce MeSH
• mikro RNA * analýza   genetika   MeSH
• nádory hrtanu * diagnóza   genetika   MeSH
• nanovlákna * chemie   MeSH
• Ramanova spektroskopie * metody   MeSH
• zlato chemie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• mikro RNA * MeSH
• MIRN223 microRNA, human MeSH Prohlížeč
• zlato MeSH

An important issue in the context of both potenial toxicity of iron oxide nanoparticles (IONP) and their medical applications is tracking of the internalization process of these nanomaterials into living cells, as well as their localization and fate within them. The typical methods used for this purpose are transmission electron microscopy, confocal fluorescence microscopy as well as light-scattering techniques including dark-field microscopy and flow cytometry. All the techniques mentioned have their advantages and disadvantages. Among the problems it is necessary to mention complicated sample preparation, difficult interpretation of experimental data requiring qualified and experienced personnel, different behavior of fluorescently labeled IONP comparing to those label-free or finally the lack of possibility of chemical composition characteristics of nanomaterials. The purpose of the present investigation was the assessment of the usefulness of Raman microscopy for the tracking of the internalization of IONP into cells, as well as the optimization of this process. Moreover, the study focused on identification of the potential differences in the cellular fate of superparamagnetic nanoparticles having magnetite and maghemite core. The Raman spectra of U87MG cells which internalized IONP presented additional bands which position depended on the used laser wavelength. They occurred at the wavenumber range 1700-2400 cm-1 for laser 488 nm and below the wavenumber of 800 cm-1 in case of laser 532 nm. The intensity of the mentioned Raman bands was higher for the green laser (532 nm) and their position, was independent and not characteristic on the primary core material of IONP (magnetite, maghemite). The obtained results showed that Raman microscopy is an excellent, non-destructive and objective technique that allows monitoring the process of internalization of IONP into cells and visualizing such nanoparticles and/or their metabolism products within them at low exposure levels. What is more, the process of tracking IONP using the technique may be further improved by using appropriate wavelength and power of the laser source.

• Klíčová slova
• Internalization into cells, Iron oxide nanoparticles, Magnetite and maghemite core, Multivariate methods, Raman spectroscopy and imaging,
• MeSH
• lidé MeSH
• magnetické nanočástice oxidů železa * chemie   MeSH
• mikroskopie metody   MeSH
• nádorové buněčné linie MeSH
• Ramanova spektroskopie * metody   MeSH
• železité sloučeniny chemie   analýza   metabolismus   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• železité sloučeniny MeSH

Quadruplexes formed by guanine derivatives or guanine-rich nucleic acids are involved in metabolism and genetic storage of many living organisms, they are used in DNA nanotechnologies or as biosensors. Since many quadruplex geometries are possible the determination of their structures in aqueous solutions is difficult. Raman optical activity (ROA) can make it easier: For guanosine monophosphate (GMP), we observed a distinct change of the spectra upon its condensation and quadruplex formation. The vibrational bands become more numerous, stronger, and narrower. In particular, a huge ROA signal appears below 200 cm-1. The aggregation can be induced by high concentration, low temperature, or by a metal ion. We focused on well-defined quadruplexes stabilized by potassium, where using molecular dynamics and density functional theory the spectra and particular features related to GMP geometric parameters could be understood. The simulations explain the main experimental trends and confirm that the ROA spectroscopy is sensitive to fine structural details, including guanine base twist in the quadruplex helix.

• Klíčová slova
• Density functional theory, Guanine quadruplexes, Molecular dynamics, Raman optical activity,
• MeSH
• DNA chemie   MeSH
• draslík chemie   MeSH
• G-kvadruplexy * MeSH
• guanin * chemie   MeSH
• kvantová teorie MeSH
• kyselina 5'-guanylová chemie   MeSH
• Ramanova spektroskopie * metody   MeSH
• simulace molekulární dynamiky MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• DNA MeSH
• draslík MeSH
• guanin * MeSH
• kyselina 5'-guanylová MeSH

Lung carcinoma remains the leading cause of cancer death worldwide. The tactic to change this unfortunate rate may be a timely and rapid diagnostic, which may in many cases improve patient prognosis. In our study, we focus on the comparison of two novel methods of rapid lung carcinoma diagnostics, label-free in vivo and ex vivo Raman spectroscopy of the epithelial tissue, and assess their feasibility in clinical practice. As these techniques are sensitive not only to the basic molecular composition of the analyzed sample but also to the secondary structure of large biomolecules, such as tissue proteins, they represent suitable candidate methods for epithelial cancer diagnostics. During routine bronchoscopy, we collected 78 in vivo Raman spectra of normal and cancerous lung tissue and 37 samples of endobronchial pathologies, which were subsequently analyzed ex vivo. Using machine learning techniques, namely principal component analysis (PCA) and support vector machines (SVM), we were able to reach 87.2% (95% CI, 79.8-94.6%) and 100.0% (95% CI, 92.1-100.0%) of diagnostic accuracy for in vivo and ex vivo setup, respectively. Although the ex vivo approach provided superior results, the rapidity of in vivo Raman spectroscopy might become unmatchable in the acceleration of the diagnostic process.

• Klíčová slova
• Endoscopy, Ex vivo diagnostics, In vivo diagnostics, Lung cancer, Machine learning, Optical biopsy, Raman spectroscopy,
• MeSH
• analýza hlavních komponent * MeSH
• lidé středního věku MeSH
• lidé MeSH
• nádory plic * diagnóza   patologie   MeSH
• Ramanova spektroskopie * metody   MeSH
• senioři MeSH
• support vector machine MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Antibiotic resistance stands as a critical medical concern, notably evident in commonly prescribed beta-lactam antibiotics. The imperative need for expeditious and precise early detection methods underscores their role in facilitating timely intervention, curbing the propagation of antibiotic resistance, and enhancing patient outcomes. RESULTS: This study introduces the utilization of surface-enhanced Raman spectroscopy (SERS) in tandem with machine learning (ML) for the sensitive detection of characteristic gene fragments responsible for antibiotic resistance appearance and spreading. To make the detection procedure close to the real case, we used bacterial plasmids as starting biological objects, containing or not the characteristic gene fragment (up to 1:10 ratio), encoding beta-lactam antibiotics resistance. The plasmids were subjected to enzymatic digestion and without preliminary purification or isolation the created fragments were captured by functional SERS substrates. Based on subsequent SERS measurements, a database was created for the training and validation of ML. Method validation was performed using separately measured spectra, which did not overlap with the database used for ML training. To check the efficiency of recognising the target fragment, control experiments involved bacterial plasmids containing different resistance genes, the use of inappropriate enzymes, or the absence of plasmid. SIGNIFICANCE: SERS-ML allowed express detection of bacterial plasmids containing a characteristic gene fragment up to the 10-7 concentration of the initial plasmid, despite the complex composition of the biological sample, including the presence of interfering plasmids. Our approach offers a promising alternative to existing methods for monitoring antibiotic-resistant bacteria, characterized by its simplicity, low detection limit, and the potential for rapid and straightforward analysis.

• Klíčová slova
• Bacterial plasmid, Beta-lactam antibiotics resistance, Detection, Logistic regression, Machine learning, SERS,
• MeSH
• antibakteriální látky farmakologie   MeSH
• beta-laktamová antibiotika MeSH
• beta-laktamová rezistence genetika   MeSH
• beta-laktamy farmakologie   MeSH
• Escherichia coli genetika   účinky léků   izolace a purifikace   MeSH
• plazmidy * genetika   MeSH
• povrchové vlastnosti MeSH
• Ramanova spektroskopie * metody   MeSH
• strojové učení * MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• antibakteriální látky MeSH
• beta-laktamová antibiotika MeSH
• beta-laktamy MeSH

Phosphorylated peptides are instrumental in studying protein phosphorylation events. In the present study, Raman optical activity (ROA) is employed to elucidate the structure of a dipeptide, L-alanyl-L-glutamine (L-Ala-L-Gln) and its two differently alkylated N-phosphorylated derivatives. Theoretical simulations were conducted to aid the interpretation of peptide conformation variations upon phosphorylation, and of the measured Raman and ROA spectra. Induced circularly polarized luminescence (CPL) was also recorded in solution, in the presence of a simple europium aqua ion. As the spectra are peptide specific, this type of stereochemical analysis is expected to aid identification of the phosphorylation sites also in other peptides and possibly proteins.

• Klíčová slova
• Biomolecular spectroscopy, Circularly polarized luminescence, Molecular dynamics, Peptide phosphorylation, Raman optical activity,
• MeSH
• dipeptidy * chemie   MeSH
• fosforylace MeSH
• molekulární modely MeSH
• Ramanova spektroskopie * metody   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• alanylglutamine MeSH Prohlížeč
• dipeptidy * MeSH

Understanding the function of a biomolecule hinges on its 3D conformation or secondary structure. Chirally sensitive, optically active techniques based on the differential absorption of UV-vis circularly polarized light excel at rapid characterisation of secondary structures. However, Raman spectroscopy, a powerful method for determining the structure of simple molecules, has limited capacity for structural analysis of biomolecules because of intrinsically weak optical activity, necessitating millimolar (mM) sample quantities. A breakthrough is presented for utilising Raman spectroscopy in ultrasensitive biomolecular conformation detection, surpassing conventional Raman optical activity by 15 orders of magnitude. This strategy combines chiral plasmonic metasurfaces with achiral molecular Raman reporters and enables the detection of different conformations (α-helix and random coil) of a model peptide (poly-L/D-lysine) at the ≤attomole level (monolayer). This exceptional sensitivity stems from the ability to detect local, molecular-scale changes in the electromagnetic (EM) environment of a chiral nanocavity induced by the presence of biomolecules using molecular Raman reporters. Further signal enhancement is achieved by incorporating achiral Au nanoparticles. The introduction of the nanoparticles creates highly localized regions of extreme optical chirality. This approach, which exploits Raman, a generic phenomenon, paves the way for next-generation technologies for the ultrasensitive detection of diverse biomolecular structures.

• Klíčová slova
• Plasmonics, SERS, chirality, enantiomer, super chirality optical chirality,
• MeSH
• kovové nanočástice chemie   MeSH
• molekulární konformace MeSH
• nanotechnologie metody   MeSH
• peptidy chemie   MeSH
• Ramanova spektroskopie * metody   MeSH
• zlato chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• peptidy MeSH
• zlato MeSH