Raman Spectroscopy for Pharmaceutical Quantitative Analysis by Low-Rank Estimation

Methods for Rapid Evaluation of Microbial Antibiotics Resistance

Antibiotic resistance is a major challenge for public health systems worldwide. Rapid and effective identification of bacterial strains is critical for reducing the use of antibiotics and restricting the spread of antibiotic-resistant microorganisms. Various approaches have been developed in recent years for rapid bacterial identification and antibiotic susceptibility testing (AST), such as Raman spectroscopy, single cell image analysis, microfluidic techniques, mass spectrometry analysis, use of high-sensitive luminescent and fluorescent tags, impedance-based detection, and others. This review describes the methods developed for rapid bacterial identification and assessment of their antibiotic susceptibility, including general principles, specific problems, and future prospects.

Iterative Regression of Corrective Baselines (IRCB): A New Model for Quantitative Spectroscopy

In this work, a new model with broad utility for quantitative spectroscopy development is reported. A primary objective of this work is to create a novel modeling procedure that may allow for higher automation of the model development process. The fundamental concept is simple yet powerful even for complex spectra and is employed with no additional preprocessing. This approach is applicable for several types of spectroscopic data to develop regression models that have similar or greater quality than the current methods. The key modeling steps are a matrix transformation and subsequent feature selection process that are collectively referred to as iterative regression of corrective baselines (IRCB). The transformed matrix (Xtransform) is a linearized form of the original X data set. Features from Xtransform that are predictive of Y can be ranked and selected by ordinary least-squares regression. The best features (rows of Xtransform) are linear depictions of Y that can be utilized to develop regression models with several machine learning models. The IRCB workflow is first detailed by using a case study of Fourier transform infrared (FTIR) spectroscopy for prepared solutions of a three-component mixture. Next, IRCB is applied and compared to benchmark results for the 2006 "Chimiométrie" near-infrared spectroscopy (NIR) soil composition challenge and Raman measurements of a simulated nuclear waste slurry.

Evaluation of Ilex guayusa and Piper marginatum Extract Cytotoxicity on Human Dental Pulp Mesenchymal Stem Cells

BACKGROUND

Amelogenesis imperfecta is a hereditary disorder affecting dental enamel. Among its phenotypes, hypocalcified AI is characterized by mineral deficiency, leading to tissue wear and, consequently, dental sensitivity. Excessive fluoride intake (through drinking water, fluoride supplements, toothpaste, or by ingesting products such as pesticides or insecticides) can lead to a condition known as dental fluorosis, which manifests as stains and teeth discoloration affecting their structure. Our recent studies have shown that extracts from Colombian native plants, Ilex guayusa and Piper marginatum, deposit mineral ions such as phosphate and orthophosphate into the dental enamel structure; however, it is unknown whether these extracts produce toxic effects on the dental pulp.

OBJECTIVE

To assess cytotoxicity effects on human dental pulp stem cells (hDPSCs) exposed to extracts isolated from I. guayusa and P. marginatum and, hence, their safety for clinical use.

METHODS

Raman spectroscopy, fluorescence microscopy, and flow cytometry techniques were employed. For Raman spectroscopy, hDPSCs were seeded onto nanobiochips designed to provide surface-enhanced Raman spectroscopy (SERS effect), which enhances their Raman signal by several orders of magnitude. After eight days in culture, I. guayusa and P. marginatum extracts at different concentrations (10, 50, and 100 ppm) were added. Raman measurements were performed at 0, 12, and 24 h following extract application. Fluorescence microscopy was conducted using an OLIMPUS fv1000 microscope, a live-dead assay was performed using a kit employing a BD FACS Canto TM II flow cytometer, and data analysis was determined using a FlowJo program.

RESULTS

The Raman spectroscopy results showed spectra consistent with viable cells. These findings were corroborated using fluorescence microscopy and flow cytometry techniques, confirming high cellular viability.

CONCLUSIONS

The analyzed extracts exhibited low cytotoxicity, suggesting that they could be safely applied on enamel for remineralization purposes. The use of nanobiochips for SERS effect improved the cell viability assessment.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Modular Micro Raman Reader Instrument for Fast SERS-Based Detection of Biomarkers

Sensitive detection of biomarkers is very critical in the diagnosis, management, and monitoring of diseases. Recent efforts have suggested that bioassays using surface-enhanced Raman scattering as a signal read-out strategy possess certain unique beneficial features in terms of sensitivity and low limits of detection which set this method apart from its counterparts such as fluorescence, phosphorescence, and radiolabeling. Surface-enhanced Raman scattering (SERS) has also emerged as an ideal choice for the development of multiplexed bioassays. Such promising features have prompted the need for the development of SERS-based tools suitable for point-of-care applications. These tools must be easy to use, portable, and automated for the screening of many samples in clinical settings if diagnostic applications are considered. The availability of such tools will result in faster and more reliable detection of disease biomarkers, improving the accessibility of point-of-care diagnostics. In this paper, we describe a modular Raman reader instrument designed to create such a portable device suitable for screening a large number of samples with minimal operator assistance. The device's hardware is mostly built with commercially available components using our unique design. Dedicated software was created to automatically run sample screening and analyze the data measured. The mRR is an imaging system specifically created to automate measurements, eliminating human bias while enhancing the rate of data collection and analysis ~2000 times. This paper presents both the design and capabilities of the custom-built modular Raman reader system (mRR) capable of automated and fast measurements of sandwich immunoassay samples on gold substrates using modified gold nanoparticles as Raman tags. The limit of detection (LOD) of the tested MUC4-specific iSERS assay was measured to be 0.41 µg/mL.

Raman Mapping-Based Reverse Engineering Facilitates Development of Sustained-Release Nifedipine Tablet

The development of generic preparations that are bioequivalent to a reference listed drug (RLD) is faced with challenges because some critical attributes of RLDs are commonly unknown to developers. In order to determine these attributes, Raman mapping-based reverse engineering in this study to analyze a model sustained-release tablet of nifedipine. The Raman mapping results indicate that the size and size distribution of nifedipine are critical to its release pattern and bioavailability. The tablets with a particle size of nifedipine comparable to that of a commercial product, Adalat^®-L, showed similar in vitro release profiles to the RLD. Moreover, a pharmacokinetic study in human volunteers proved the bioequivalence of the two preparations. In conclusion, Raman mapping-based reverse engineering has the potential to facilitate the development of generic preparations.

A Spatial-Temporal Analysis of Cellular Biopolymers on Leaf Blight-Infected Tea Plants Using Confocal Raman Microspectroscopy

The objective of the present study was to characterize the temporal and spatial variation of biopolymers in cells infected by the tea leaf blight using confocal Raman microspectroscopy. We investigated the biopolymers on serial sections of the infection part, and four sections corresponding to different stages of infection were obtained for analysis. Raman spectra extracted from four selected regions (circumscribing the vascular bundle) were analyzed in detail to enable a semi-quantitative comparison of biopolymers on a micron-scale. As the infection progressed, lignin and other phenolic compounds decreased in the vascular bundle, while they increased in both the walls of the bundle sheath cells as well as their intracellular components. The amount of cellulose and other polysaccharides increased in all parts as the infection developed. The variations in the content of lignin and cellulose in different tissues of an individual plant may be part of the reason for the plant's disease resistance. Through wavelet-based data mining, two-dimensional chemical images of lignin, cellulose and all biopolymers were quantified by integrating the characteristic spectral bands ranging from 1,589 to 1,607 cm^-1, 1,087 to 1,100 cm^-1, and 2,980 to 2,995 cm^-1, respectively. The chemical images were consistent with the results of the semi-quantitative analysis, which indicated that the distribution of lignin in vascular bundle became irregular in sections with severe infection, and a substantial quantity of lignin was detected in the cell wall and inside the bundle sheath cell. In serious infected sections, cellulose was accumulated in vascular bundles and distributed within bundle sheath cells. In addition, the distribution of all biopolymers showed that there was a tylose substance produced within the vascular bundles to prevent the further development of pathogens. Therefore, confocal Raman microspectroscopy can be used as a powerful approach for investigating the temporal and spatial variation of biopolymers within cells. Through this method, we can gain knowledge about a plant's defense mechanisms against fungal pathogens.

A spectral recovery method for Raman spectroscopy utilizing prior datasets

Spectral-based method has been widely used for the qualitative and quantitative analysis of different substances in various fields. The spectral recovery method is a crucial role in the spectral-based method, which can save the measurement cost and computation time in measuring. In this paper, we introduce a simple and reliable spectral recovery method base on prior datasets, which can tolerate substantial spectral noise. The method has been successfully applied in the quantitative analysis of the pharmaceutical mixture. The SNR of the recovery spectra can be increased by ~100 times.