Raman spectroscopy--a prospective tool in the life sciences

Development of a cost-effective confocal Raman microscopy with high sensitivity

Confocal Raman microscopy is a powerful technique for identifying materials and molecular species; however, the signal from Raman scattering is extremely weak. Typically, handheld Raman instruments are cost-effective but less sensitive, while high-end scientific-grade Raman instruments are highly sensitive but extremely expensive. This limits the widespread use of Raman technique in our daily life. To bridge this gap, we explored and developed a cost-effective yet highly sensitive confocal Raman microscopy system. The key components of the system include an excitation laser based on readily available laser diode, a lens-grating-lens type spectrometer with high throughput and image quality, and a sensitive detector based on a linear charge-coupled device (CCD) that can be cooled down to -30 °C. The developed compact Raman instrument can provide high-quality Raman spectra with good spectral resolution. The 3rd order 1450 cm-1 peak of Si (111) wafer shows a signal-to-noise ratio (SNR) better than 10:1, demonstrating high sensitivity comparable to high-end scientific-grade Raman instruments. We also tested a wide range of different samples (organic molecules, minerals and polymers) to demonstrate its universal application capability.

Application of deep UV resonance Raman spectroscopy to column liquid chromatography: Development of a low-flow method for the identification of active pharmaceutical ingredients

In this study, deep UV resonance Raman spectroscopy (DUV-RRS) was coupled with high performance liquid chromatography (HPLC) to be applied in the field of pharmaceutical analysis. Naproxen, Metformin and Epirubicin were employed as active pharmaceutical ingredients (APIs) covering different areas of the pharmacological spectrum. Raman signals were successfully generated and attributed to the test substances, even in the presence of the dominant solvent bands of the mobile phase. To increase sensitivity, a low-flow method was developed to extend the exposure time of the sample. This approach enabled the use of a deep UV pulse laser with a low average power of 0.5 mW. Compared to previous studies, where energy-intensive argon ion lasers were commonly used, we were able to achieve similar detection limits with our setup. Using affordable lasers with low operating costs may facilitate the transfer of the results of this study into practical applications.

Raman cell sorting for single-cell research

Cells constitute the fundamental units of living organisms. Investigating individual differences at the single-cell level facilitates an understanding of cell differentiation, development, gene expression, and cellular characteristics, unveiling the underlying laws governing life activities in depth. In recent years, the integration of single-cell manipulation and recognition technologies into detection and sorting systems has emerged as a powerful tool for advancing single-cell research. Raman cell sorting technology has garnered attention owing to its non-labeling, non-destructive detection features and the capability to analyze samples containing water. In addition, this technology can provide live cells for subsequent genomics analysis and gene sequencing. This paper emphasizes the importance of single-cell research, describes the single-cell research methods that currently exist, including single-cell manipulation and single-cell identification techniques, and highlights the advantages of Raman spectroscopy in the field of single-cell analysis by comparing it with the fluorescence-activated cell sorting (FACS) technique. It describes various existing Raman cell sorting techniques and introduces their respective advantages and disadvantages. The above techniques were compared and analyzed, considering a variety of factors. The current bottlenecks include weak single-cell spontaneous Raman signals and the requirement for a prolonged total cell exposure time, significantly constraining Raman cell sorting technology's detection speed, efficiency, and throughput. This paper provides an overview of current methods for enhancing weak spontaneous Raman signals and their associated advantages and disadvantages. Finally, the paper outlines the detailed information related to the Raman cell sorting technology mentioned in this paper and discusses the development trends and direction of Raman cell sorting.

A Visual Raman Nano-Delivery System Based on Thiophene Polymer for Microtumor Detection

A visual Raman nano-delivery system (NS) is a widely used technique for the visualization and diagnosis of tumors and various biological processes. Thiophene-based organic polymers exhibit excellent biocompatibility, making them promising candidates for development as a visual Raman NS. However, materials based on thiophene face limitations due to their absorption spectra not matching with NIR (near-infrared) excitation light, which makes it difficult to achieve enhanced Raman properties and also introduces potential fluorescence interference. In this study, we introduce a donor-acceptor (D-A)-structured thiophene-based polymer, PBDB-T. Due to the D-A molecular modulation, PBDB-T exhibits a narrow bandgap of Eg = 2.63 eV and a red-shifted absorption spectrum, with the absorption edge extending into the NIR region. Upon optimal excitation with 785 nm light, it achieves ultra-strong pre-resonant Raman enhancement while avoiding fluorescence interference. As an intrinsically sensitive visual Raman NS for in vivo imaging, the PBDB-T NS enables the diagnosis of microtumor regions with dimensions of 0.5 mm × 0.9 mm, and also successfully diagnoses deeper tumor tissues, with an in vivo circulation half-life of 14.5 h. This research unveils the potential application of PBDB-T as a NIR excited visual Raman NS for microtumor diagnosis, introducing a new platform for the advancement of "Visualized Drug Delivery Systems". Moreover, the aforementioned platform enables the development of a more diverse range of targeted visual drug delivery methods, which can be tailored to specific regions.

Real-Time Quantitative Evaluation of a Drug during Liposome Preparation Using a Probe-Type Raman Spectrometer

During the manufacturing process of liposome formulations, it is considered difficult to evaluate their physicochemical properties and biological profiles due to the complexity of their structure and manufacturing process. Conventional quality evaluation is labor-intensive and time-consuming; therefore, there was a need to introduce a method that could perform in-line, real-time evaluation during the manufacturing process. In this study, Raman spectroscopy was used to monitor in real time the encapsulation of drugs into liposomes and the drug release, which are particularly important quality evaluation items. Furthermore, Raman spectroscopy combined with partial least-squares (PLS) analysis was used for quantitative drug evaluation to assess consistency with results from UV-visible spectrophotometry (UV), a common quantification method. The prepared various ciprofloxacin (CPFX) liposomes were placed in cellulose tubes, and a probe-type Raman spectrophotometer was used to monitor drug encapsulation, the removal of unencapsulated drug, and drug release characteristics in real time using a dialysis method. In the Raman spectra of the liposomes prepared by remote loading, the intensities of the CPFX-derived peaks increased upon drug encapsulation and showed a slight decrease upon removal of the unencapsulated drug. Furthermore, the peak intensity decreased more gradually during the drug release. In all Raman monitoring experiments, the discrepancy between quantified values of CPFX concentration in liposomes, as measured by Raman spectroscopy combined with partial least-squares (PLS) analysis, and those obtained through ultraviolet (UV) spectrophotometry was within 6.7%. The results revealed that the quantitative evaluation of drugs using a combination of Raman spectroscopy and PLS analysis was as accurate as the evaluation using UV spectrophotometry, which was used for comparison. These results indicate the promising potential of Raman spectroscopy as an innovative method for the quality evaluation of liposomal formulations.

Intelligent Rapid Detection Techniques for Low-Content Components in Fruits and Vegetables: A Comprehensive Review

Fruits and vegetables are an important part of our daily diet and contain low-content components that are crucial for our health. Detecting these components accurately is of paramount significance. However, traditional detection methods face challenges such as complex sample processing, slow detection speed, and the need for highly skilled operators. These limitations fail to meet the growing demand for intelligent and rapid detection of low-content components in fruits and vegetables. In recent years, significant progress has been made in intelligent rapid detection technology, particularly in detecting high-content components in fruits and vegetables. However, the accurate detection of low-content components remains a challenge and has gained considerable attention in current research. This review paper aims to explore and analyze several intelligent rapid detection techniques that have been extensively studied for this purpose. These techniques include near-infrared spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy, and terahertz spectroscopy, among others. This paper provides detailed reports and analyses of the application of these methods in detecting low-content components. Furthermore, it offers a prospective exploration of their future development in this field. The goal is to contribute to the enhancement and widespread adoption of technology for detecting low-content components in fruits and vegetables. It is expected that this review will serve as a valuable reference for researchers and practitioners in this area.

Optical sensors (optodes) for multiparameter chemical imaging: classification, challenges, and prospects

Chemical gradients and uneven distribution of analytes are common in natural and artificial systems. As a result, the ability to visualize chemical distributions in two or more dimensions has gained significant importance in recent years. This has led to the integration of chemical imaging techniques into all domains of analytical chemistry. In this review, we focus on the use of optical sensors, so-called optodes, to obtain real-time and multidimensional images of two or more parameters simultaneously. It is important to emphasize that multiparameter imaging in this context is not confined solely to multiple chemical parameters (analytes) but also encompasses physical (e.g., temperature or flow) or biological (e.g., metabolic activity) parameters. First, we discuss the technological milestones that have paved the way for chemical imaging using optodes. Later, we delve into various strategies that can be taken to enable multiparameter imaging. The latter spans from developing novel receptors that enable the recognition of multiple parameters to chemometrics and machine learning-based techniques for data analysis. We also explore ongoing trends, challenges, and prospects for future developments in this field. Optode-based multiparameter imaging is a rapidly expanding field that is being fueled by cutting-edge technologies. Chemical imaging possesses the potential to provide novel insights into complex samples, bridging not only across various scientific disciplines but also between research and society.

A beaker method for determination of microplastic concentration by micro-Raman spectroscopy

Fourier-transform infrared (FT-IR) spectroscopy method for measuring small microplastic (SMP) concentration in marine environment is time-consuming and labor-intensive due to sample pre-treatment. In contrast, Raman spectroscopy is less influenced by water and can directly measure SMP samples in water, making it a more efficient method to measure SMP concentration. Therefore, a method that can directly estimate the concentration of SMPs in water was developed, and the relationship between SMP concentration and experimental Raman spectra were established by testing with standard polyethylene (PE) samples. It was found that average spectra acquired in water solution could reflect characteristic peaks of the plastic after baseline correction. Further investigation found that there is a significant functional relationship between correlation coefficient of sample spectra and the concentration of PE particles, and such relationship can be modelled by Langmuir model. The empirical functional relationships can be used to estimate SMP concentrations by measuring average Raman spectra. The developed methodology is helpful for developing rapid SMP identification and monitoring methods in a more complex manner.•A method of directly measuring MP concentration in water is proposed.•Experimental procedures are provided.•Data analysis methods are outlined.

MEMS-based portable confocal Raman spectroscopy rapid imaging system

Aiming at the miniaturization and rapid imaging requirements of a portable confocal Raman system, a MEMS-based portable confocal Raman spectroscopy rapid imaging method is proposed in this study. This method combines the dual 2D MEMS mirror scanning method and the grid-by-grid scanning method. The dual 2D MEMS mirror scanning method is used for the miniaturization design of the system, and the grid-by-grid scanning method is used for rapid imaging of Raman spectroscopy. Finally, the rapid imaging and miniaturization design of a portable confocal Raman spectroscopy system are realized. Based on this method, a portable confocal Raman spectroscopy rapid imaging system with an optical probe size of just 98m m×70m m×40m m is constructed. The experimental results show that the imaging speed of the system is 45 times higher than that of the traditional point-scan confocal Raman system, and the imaging speed can be further improved according to the requirements. In addition, the system is used to swiftly identify agate ore, and the material composition distribution image over a 126µm 2×126µm 2 region is obtained in just 16 min. This method provides a new solution for the rapid imaging and miniaturization design of the confocal Raman system, as well as a new technical means for rapid detection in deep space exploration, geological exploration, and field detection.

A structural and functional comparison between two recombinant human lubricin proteins: Recombinant human proteoglycan-4 (rhPRG4) vs ECF843

Proteoglycan 4 (PRG4, lubricin) is a mucin-like glycoprotein present on the ocular surface that has both boundary lubricating and anti-inflammatory properties. Full-length recombinant human PRG4 (rhPRG4) has been shown to be clinically effective in improving signs and symptoms of dry eye disease (DED). In vitro, rhPRG4 has been shown to reduce inflammation-induced cytokine production and NFκB activity in corneal epithelial cells, as well as to bind to and inhibit MMP-9 activity. A different form of recombinant human lubricin (ECF843), produced from the same cell line as rhPRG4 but manufactured using a different process, was recently assessed in a DED clinical trial. However, ECF843 did not significantly improve signs or symptoms of DED compared to vehicle. Initial published characterization of ECF843 showed it had a smaller hydrodynamic diameter and was less negatively charged than native PRG4. Further examination of the structural and functional properties of ECF843 and rhPRG4 could contribute to the understanding of what led to their disparate clinical efficacy. Therefore, the objective of this study was to characterize and compare rhPRG4 and ECF843 in vitro, both biophysically and functionally. Hydrodynamic diameter and charge were measured by dynamic light scattering (DLS) and zeta potential, respectively. Size and molecular weight was determined for individual species by size exclusion chromatography (SEC) with in-line DLS and multi-angle light scattering (MALS). Bond structure was measured by Raman spectroscopy, and sedimentation properties were measured by analytical ultracentrifugation (AUC). Functionally, MMP-9 inhibition was measured using a commercial MMP-9 activity kit, coefficient of friction was measured using an established boundary lubrication test at a latex-glass interface, and collagen 1-binding ability was measured by quart crystal microbalance with dissipation (QCMD). Additionally, the ability of rhPRG4 and ECF843 to inhibit urate acid crystal formation and cell adhesion was assessed. ECF843 had a significantly smaller hydrodynamic diameter and was less negatively charged than rhPRG4, as assessed by DLS and zeta potential. Size was further explored with SEC-DLS-MALS, which indicated that while rhPRG4 had 3 main peaks, corresponding to monomer, dimer, and multimer as expected, ECF843 had 2 peaks that were similar in size and molecular weight compared to rhPRG4's monomer peak and a third peak that was significantly smaller in both size and molar mass than the corresponding peak of rhPRG4. Raman spectroscopy demonstrated that ECF843 had significantly more disulfide bonds, which are functionally determinant structures, relative to the carbon-carbon backbone compared to rhPRG4, and AUC indicated that ECF843 was more compact than rhPRG4. Functionally, ECF843 was significantly less effective at inhibiting MMP-9 activity and functioning as a boundary lubricant compared to rhPRG4, as well as being slower to bind to collagen 1. Additionally, ECF843 was significantly less effective at inhibiting urate acid crystal formation and at preventing cell adhesion. Collectively, these data demonstrate ECF843 and rhPRG4 are significantly different in both structure and function. Given that a protein's structure sets the foundation for its interactions with other molecules and tissues in vivo, which ultimately determine its function, these differences most likely contributed to the disparate DED clinical trial results.

Molecular in situ monitoring of the pH-triggered response in adaptive polymers by two-dimensional Raman micro-correlation-spectroscopy

Stimuli-responsive polymers can switch specific physical properties in response to a change of the environmental conditions. This behavior offers unique advantages in applications where adaptive materials are needed. To tune the properties of stimuli-responsive polymers, a detailed understanding of the relationship between the applied stimulus and changes in molecular structure as well as the relationship between the latter and macroscopic properties is required, which until now has required laborious methods. Here, we present a straightforward way to investigate the progressing trigger, the change of the chemical composition of the polymer and the macroscopic properties simultaneously. Thereby, the response behavior of the reversible polymer is studied in situ with molecular sensitivity and spatial as well as temporal resolution utilizing Raman micro-spectroscopy. Combined with two-dimensional correlation analysis (2DCOS), this method reveals the stimuli-response on a molecular level and determines the sequence of changes and the diffusion rate inside the polymer. Due to the label-free and non-invasive approach, it is furthermore possible to combine this method with the investigation of macroscopic properties revealing the response of the polymer to the external stimulus on both the molecular and the macroscopic level.

Chemical-imaging-guided optical manipulation of biomolecules

Chemical imaging via advanced optical microscopy technologies has revealed remarkable details of biomolecules in living specimens. However, the ways to control chemical processes in biological samples remain preliminary. The lack of appropriate methods to spatially regulate chemical reactions in live cells in real-time prevents investigation of site-specific molecular behaviors and biological functions. Chemical- and site-specific control of biomolecules requires the detection of chemicals with high specificity and spatially precise modulation of chemical reactions. Laser-scanning optical microscopes offer great platforms for high-speed chemical detection. A closed-loop feedback control system, when paired with a laser scanning microscope, allows real-time precision opto-control (RPOC) of chemical processes for dynamic molecular targets in live cells. In this perspective, we briefly review recent advancements in chemical imaging based on laser scanning microscopy, summarize methods developed for precise optical manipulation, and highlight a recently developed RPOC technology. Furthermore, we discuss future directions of precision opto-control of biomolecules.

Recent advances of Raman spectroscopy for the analysis of bacteria

Rapid and sensitive bacteria detection and identification are becoming increasingly important for a wide range of areas including the control of food safety, the prevention of infectious diseases, and environmental monitoring. Raman spectroscopy is an emerging technology which provides comprehensive information for the analysis of bacteria in a short time and with high sensitivity. Raman spectroscopy offers many advantages including relatively simple operation, non-destructive analysis, and information on molecular differences between bacteria species and strains. A variety of biochemical properties can be measured in a single spectrum. This short review covers the recent advancements and applications of Raman spectroscopy for bacteria analysis with specific focuses on bacteria detection, bacteria identification and discrimination, as well as bacteria antibiotic susceptibility testing in 2022. The development of novel substrates, the combination with other techniques, and the utilization of advanced data processing tools for the improvement of Raman spectroscopy and future directions are discussed.

Raman Spectroscopy as a Tool to Study the Pathophysiology of Brain Diseases

The Raman phenomenon is based on the spontaneous inelastic scattering of light, which depends on the molecular characteristics of the dispersant. Therefore, Raman spectroscopy and imaging allow us to obtain direct information, in a label-free manner, from the chemical composition of the sample. Since it is well established that the development of many brain diseases is associated with biochemical alterations of the affected tissue, Raman spectroscopy and imaging have emerged as promising tools for the diagnosis of ailments. A combination of Raman spectroscopy and/or imaging with tagged molecules could also help in drug delivery and tracing for treatment of brain diseases. In this review, we first describe the basics of the Raman phenomenon and spectroscopy. Then, we delve into the Raman spectroscopy and imaging modes and the Raman-compatible tags. Finally, we center on the application of Raman in the study, diagnosis, and treatment of brain diseases, by focusing on traumatic brain injury and ischemia, neurodegenerative disorders, and brain cancer.

Good vibrations: Raman spectroscopy enables insights into plant biochemical composition

Non-invasive techniques are needed to enable an integrated understanding of plant metabolic responses to environmental stresses. Raman spectroscopy is one such technique, allowing non-destructive chemical characterisation of samples in situ and in vivo and resolving the chemical composition of plant material at scales from microns to metres. Here, we review Raman band assignments of pigments, structural and non-structural carbohydrates, lipids, proteins and secondary metabolites in plant material and consider opportunities this technology raises for studies in vascular plant physiology.

Petri-plate, bacteria, and laser optical scattering sensor

Classical microbiology has paved the path forward for the development of modern biotechnology and microbial biosensing platforms. Microbial culturing and isolation using the Petri plate revolutionized the field of microbiology. In 1887, Julius Richard Petri invented possibly the most important tool in microbiology, the Petri plate, which continues to have a profound impact not only on reliably isolating, identifying, and studying microorganisms but also manipulating a microbe to study gene expression, virulence properties, antibiotic resistance, and production of drugs, enzymes, and foods. Before the recent advances in gene sequencing, microbial identification for diagnosis relied upon the hierarchal testing of a pure culture isolate. Direct detection and identification of isolated bacterial colonies on a Petri plate with a sensing device has the potential for revolutionizing further development in microbiology including gene sequencing, pathogenicity study, antibiotic susceptibility testing , and for characterizing industrially beneficial traits. An optical scattering sensor designated BARDOT (bacterial rapid detection using optical scattering technology) that uses a red-diode laser, developed at the beginning of the 21^st century at Purdue University, some 220 years after the Petri-plate discovery can identify and study bacteria directly on the plate as a diagnostic tool akin to Raman scattering and hyperspectral imaging systems for application in clinical and food microbiology laboratories.

Recent advancements in Janus nanoparticle-based biosensing platforms

Nanoparticles have aided in the development of nano-based sensors for diagnostic applications. However, use of nanoparticles in the development of sensing devices for multiple analyte detection is constrained due to their inability to detect several analytes with a single type of nanoparticle. The term "Janus particle" refers to micro or nanoscale particles that have been divided into sections or compartments, each of which has a distinct set of chemical or physical properties, producing multifunctional particles endowed with distinctive qualities. Furthermore, Janus particles have the ability to perform multiple functions within a single particle at the same time, with no interference from adjacent sections. This review focuses on the use of Janus particles in the fabrication of biosensors as well as in the investigation of various properties endowed by these Janus particles for their use as biosensors. It also discusses the various types of Janus particle-based biosensors that are currently available. Finally, the limitations of Janus particles in sensor technologies and their future scope have been discussed.

Graphical abstract

Recent Advances in Raman Spectral Imaging in Cell Diagnosis and Gene Expression Prediction

Normal and tumor regions within cancer tissue can be distinguished using various methods, such as histological analysis, tumor marker testing, X-ray imaging, or magnetic resonance imaging. Recently, new discrimination methods utilizing the Raman spectra of tissues have been developed and put into practical use. Because Raman spectral microscopy is a non-destructive and non-labeling method, it is potentially compatible for use in the operating room. In this review, we focus on the basics of Raman spectroscopy and Raman imaging in live cells and cell type discrimination, as these form the bases for current Raman scattering-based cancer diagnosis. We also review recent attempts to estimate the gene expression profile from the Raman spectrum of living cells using simple machine learning. Considering recent advances in machine learning techniques, we speculate that cancer type discrimination using Raman spectroscopy will be possible in the near future.

Review of Recent Modern Analytical Technology Combined with Chemometrics Approach Researches on Mushroom Discrimination and Evaluation

Mushroom is a macrofungus with precious fruiting body, as a food, a tonic, and a medicine, human have discovered and used mushrooms for thousands of years. Nowadays, mushroom is also a "super food" recommended by the World Health Organization (WHO) and Food and Agriculture Organization (FAO), and favored by consumers. Discrimination of mushroom including species, geographic origin, storage time, etc., is an important prerequisite to ensure their edible safety and commodity quality. Moreover, the effective evaluation of its chemical composition can help us better understand the nutritional properties of mushrooms. Modern analytical technologies such as chromatography, spectroscopy and mass spectrometry, etc., are widely used in the discrimination and evaluation researches of mushrooms, and chemometrics is an effective means of scientifically processing the multidimensional information hidden in these analytical technologies. This review will outline the latest applications of modern analytical technology combined with chemometrics in qualitative and quantitative analysis and quality control of mushrooms in recent years. Briefly describe the basic principles of these technologies, and the analytical processes of common chemometrics in mushroom researches will be summarized. Finally, the limitations and application prospects of chromatography, spectroscopy and mass spectrometry technology are discussed in mushroom quality control and evaluation.

Label-Free Sensing with Metal Nanostructure-Based Surface-Enhanced Raman Spectroscopy for Cancer Diagnosis

Surface-Enhanced Raman Spectroscopy (SERS) is a powerful analytical technique for the detection of small analytes with great potential for medical diagnostic applications. Its high sensitivity and excellent molecular specificity, which stems from the unique fingerprint of molecular species, have been applied toward the detection of different types of cancer. The noninvasive and rapid detection offered by SERS highlights its applicability for point-of-care (PoC) deployment for cancer diagnosis, screening, and staging, as well as for predicting tumor recurrence and treatment monitoring. This review provides an overview of the progress in label-free (direct) SERS-based chemical detection for cancer diagnosis with the main focus on the advances in the design and preparation of SERS substrates on the basis of metal nanoparticle structures formed via bottom-up strategies. It begins by introducing a synopsis of the working principles of SERS, including key chemometric approaches for spectroscopic data analysis. Then it introduces the advances of label-free sensing with SERS in cancer diagnosis using biofluids (blood, urine, saliva, sweat) and breath as the detection media. In the end, an outlook of the advances and challenges in cancer diagnosis via SERS is provided.

Biofouling of reverse osmosis membranes: assessment by surface-enhanced Raman spectroscopy and microscopic imaging

The decline in the performance of spiral-wound reverse osmosis (SWRO) membranes is frequently due to biofouling. This study focus on qualitative and quantitative diagnosis of SWRO membrane biofouling. Bacterial counts on the different surfaces of the fouled membranes were carried out. Surface enhanced Raman spectroscopy (SERS) was performed to highlight clogging materials as well as their natures and identity. The topography of the fouled membranes and the structures of biofilms were visualized by fluorescence microscopy (FM) and scanning electron microscopy (SEM). The results indicated the presence of bacteria in the different SWRO membrane areas. Those strongly adhered were significantly higher than those weakly. It varied between 26 × 10⁵ and 262 × 10⁵ CFU m^-2. However, SERS mapping showed different fouling levels and the thickness of the fouling layer was 5 µm. Microscopic imaging revealed biotic and abiotic deposits. These data can together allow better management of the seawater desalination process.

Statistical Classification for Raman Spectra of Tumoral Genomic DNA

We exploit Surface-Enhanced Raman Scattering (SERS) to investigate aqueous droplets of genomic DNA deposited onto silver-coated silicon nanowires, and we show that it is possible to efficiently discriminate between spectra of tumoral and healthy cells. To assess the robustness of the proposed technique, we develop two different statistical approaches, one based on the Principal Components Analysis of spectral data and one based on the computation of the ℓ2 distance between spectra. Both methods prove to be highly efficient, and we test their accuracy via the Cohen's κ statistics. We show that the synergistic combination of the SERS spectroscopy and the statistical analysis methods leads to efficient and fast cancer diagnostic applications allowing rapid and unexpansive discrimination between healthy and tumoral genomic DNA alternative to the more complex and expensive DNA sequencing.

In Situ Identification of Unknown Crystals in Acute Kidney Injury Using Raman Spectroscopy

Raman spectroscopy is a well-established and powerful tool for in situ biomolecular evaluation. Type 2 crystal nephropathies are characterized by the deposition of crystalline materials in the tubular lumen, resulting in rapid onset of acute kidney injury without specific symptoms. Timely crystal identification is essential for its diagnosis, mechanism exploration and therapy, but remains challenging. This study aims to develop a Raman spectroscopy-based method to assist pathological diagnosis of type 2 crystal nephropathies. Unknown crystals in renal tissue slides from a victim suffered extensive burn injury were detected by Raman spectroscopy, and the inclusion of crystals was determined by comparing Raman data with established database. Multiple crystals were scanned to verify the reproducibility of crystal in situ. Raman data of 20 random crystals were obtained, and the distribution and uniformity of substances in crystals were investigated by Raman imaging. A mouse model was established to mimic the crystal nephropathy to verify the availability of Raman spectroscopy in frozen biopsy. All crystals on the human slides were identified to be calcium oxalate dihydrate, and the distribution and content of calcium oxalate dihydrate on a single crystal were uneven. Raman spectroscopy was further validated to be available in identification of calcium oxalate dihydrate crystals in the biopsy specimens. Here, a Raman spectroscopy-based method for in situ identification of unknown crystals in both paraffin-embedded tissues and biopsy specimens was established, providing an effective and promising method to analyze unknown crystals in tissues and assist the precise pathological diagnosis in both clinical and forensic medicine.

Enhanced Chemical Sensing with Multiorder Coherent Raman Scattering Spectroscopic Dephasing

Molecular vibrational spectroscopy is widely used in various sensing and imaging applications, providing intrinsic information at the molecular level. Nonlinear optical interactions using ultrashort laser pulses facilitate the selective coherent excitation of molecular vibrational modes by focusing energy into specific molecular bonds, boosting the signal level for multiple orders of magnitude. The dephasing of such coherence, which is susceptible to the local molecular environment, however, is often neglected. The unique capability of vibrational dephasing dynamics to serve as a unique probe for complex molecular interactions and the effect of local nano- and microenvironments are beyond the reach of conventional, intensity-based spectroscopy. Here, we developed a novel multiorder coherent Raman spectroscopy platform with a special focus on the temporal evolution of molecular vibrational dephasing, termed as time-resolved coherent Raman scattering (T-CRS) spectroscopy. By utilizing a high dynamic range detection, molecular vibrational dynamics and the environmental effects are demonstrated with multidimensional spectroscopic sensing, which promises a new range of applications in biology, materials, and chemical sciences.

Temozolomide: an Overview of Biological Properties, Drug Delivery Nanosystems, and Analytical Methods

Temozolomide (TMZ) is an imidazotetrazine prodrug used to treat glioblastoma multiforme. Its physicochemical prop-erties and small size confer the ability to cross the blood-brain barrier. The antitumor activity depends on pH-dependent hydrolysis of the methyldiazonium cation, which is capable of methylating purine bases (O6-guanine; N7-guanine, and N3-adenine) and causing DNA damage and cell death. TMZ is more stable in acidic media (pH ≤ 5.0) than in basic media (pH ≥ 7.0) due to the protonated form that minimizes the catalytic process. Because of this, TMZ has high oral bioavailability, but it has a half-life of 1.8 h and low brain distribution (17.8%), requiring a repeated dos-ing regimen that limits its efficacy and increases adverse events. Drug delivery Nanosystems (DDNs) improve the phys-icochemical properties of TMZ and may provide controlled and targeted delivery. Therefore, DDNs can increase the efficacy and safety of TMZ. In this context, to ensure the efficiency of DDNs, analytical methods are used to evaluate TMZ pharmacokinetic parameters, encapsulation efficiency, and the release profile of DDNs. Among the methods, high-performance liquid chromatography is the most used due to its detection sensitivity in complex matrices such as tissues and plasma. Micellar electrokinetic chromatography features fast analysis and no sample pretreatment. Spec-trophotometric methods are still used to determine encapsulation efficiency due to their low cost, despite their low sen-sitivity. This review summarizes the physicochemical and pharmacological properties of free TMZ and TMZ-loaded DDNs. In addition, this review addresses the main analytical methods employed to characterize TMZ in different ma-trices.

Phenotypic Differentiation of Autotrophic and Heterotrophic Bacterial Cells Using Raman-D2O Labeling

Carbon cycling is one of the major biogeochemical processes driven by bacteria. Autotrophic bacteria convert carbon dioxide (CO₂) into organic compounds that are used by heterotrophs. Mixotrophic bacteria can employ both autotrophy and heterotrophy for growth. The characterization of the lifestyle of individual cells is essential to understand the microbial activity and thus reveal the implication of bacteria in the carbon flux. In this study, we used groundwater bacteria to investigate the potential of Raman-D₂O labeling in combination with chemometrics to identify the carbon assimilation strategies of bacteria. Classification models were built using principal component analysis (PCA) followed by linear discriminant analysis (LDA). Autotrophs assimilated a significantly higher amount (mean C-D ratio between 16.63 and 21.69%) of deuterium than heterotrophs. The C-D signal only provides information about the activity since it appears in the Raman-silent region, where no interference with the taxonomic information is expected. The classification between autotrophs and heterotrophs achieved an overall accuracy of 96.3%. In the validation step with an independent dataset containing species not included in the model, the PCA-LDA model achieved 100% accuracy. This demonstrated that the C-D signal contributed to the identification of autotrophic and heterotrophic bacterial cells. This work reports a robust, rapid, and nondestructive approach for the identification of single cells based on their carbon acquisition strategies. The present study foresees the potential of Raman-D₂O labeling as a promising method for automated discrimination of in situ functional activities of bacteria in environmental systems.

Investigation of mammalian cells expressing SARS-CoV-2 proteins by surface-enhanced Raman scattering and multivariate analysis

COVID-19 has caused millions of cases and deaths all over the world since late 2019. Rapid detection of the virus is crucial for controlling its spread through a population. COVID-19 is currently detected by nucleic acid-based tests and serological tests. However, these methods have limitations such as the requirement of high-cost reagents, false negative results and being time consuming. Surface-enhanced Raman scattering (SERS), which is a powerful technique that enhances the Raman signals of molecules using plasmonic nanostructures, can overcome these disadvantages. In this study, we developed a virus-infected cell model and analyzed this model by SERS combined with Principal Component Analysis (PCA). HEK293 cells were transfected with plasmids encoding the nucleocapsid (N), membrane (M) and envelope (E) proteins of SARS-CoV-2 via polyethyleneimine (PEI). Non-plasmid transfected HEK293 cells were used as the control group. Cellular uptake was optimized with green fluorescence protein (GFP) plasmids and evaluated by fluorescence microscopy and flow cytometry. The transfection efficiency was found to be around 60%. The expression of M, N, and E proteins was demonstrated by western blotting. The SERS spectra of the total proteins of transfected cells were obtained using a gold nanoparticle-based SERS substrate. Proteins of the transfected cells have peak positions at 646, 680, 713, 768, 780, 953, 1014, 1046, 1213, 1243, 1424, 2102, and 2124 cm^-1. To reveal spectral differences between plasmid transfected cells and non-transfected control cells, PCA was applied to the spectra. The results demonstrated that SERS coupled with PCA might be a favorable and reliable way to develop a rapid, low-cost, and promising technique for the detection of COVID-19.

Molecular Regulation of Polymeric Raman Probes for Ultrasensitive Microtumor Diagnosis and Noninvasive Microvessle Imaging

Raman imaging is a powerful tool for the diagnosis of cancers and visualization of various biological processes. Polymers possessing excellent biocompatibility are promising probes for Raman imaging. However, few polymers are reported to serve as Raman probes for in vivo imaging, mainly due to the intrinsic weak Raman signal intensity and fluorescence interference of these polymers. Herein, a poly(indacenodithiophene-benzothiadiazole) (IDT-BT) polymer is presented, which emits unprecedentedly strong Raman signals under the near-infrared wavelength (785 nm) excitation, thus functioning as a Raman probe for ultrasensitive in vivo Raman imaging. Further mechanistic studies unveil that the unique Raman feature of the IDT-BT polymer relies on molecularly regulating its absorbance edge adjacent to the desired excitation wavelength, thus avoiding fluorescence interference and simultaneously emitting strong Raman scattering under preresonant excitation. Taking advantage of this discipline, the IDT-BT polymeric probe successfully realizes intraoperative Raman imaging of micrometastasis as small as 0.3 mm × 0.3 mm, comparable to the most sensitive Raman probes currently reported. Impressively, the IDT-BT enables noninvasive microvascular imaging, which is not achieved using other Raman probes. This work opens a new avenue toward the development of polymeric Raman probes for in vivo Raman imaging.

Low-Resolution Raman Spectroscopy for the detection of contaminant species in algal bioreactors

Fouling of aquatic systems by harmful microalgal and cyanobacterial species is an environmental and public health concern. Microalgal bioreactors are engineered ecosystems for the cultivation of algal biomass to meet the increasing demand for alternative protein sources and algae-derived products. Such bioreactors are often open or semi-open ponds or raceways that are prone to contamination by contaminant photosynthetic microorganisms, including harmful cyanobacterial species (HCBs). HCBs affect the quality of products through the accumulation of off-flavours, reducing their acceptance by consumers, and through the production of several different toxins collectively known as cyanotoxins. The density of cultured species within the bioreactor environment creates difficulty in detecting low concentrations of contaminant cells, and there is currently no technology enabling rapid monitoring of contaminations. The present study demonstrates the potential of Low-Resolution Raman Spectroscopy (LRRS) as a tool for rapid detection of low concentrations of HCBs within dense populations of the spirulina (Arthrospira platensis) cultures. An LRRS system adapted for the direct measurement of raw biomass samples was used to assemble a database of Raman spectral signatures, from eight algal and cyanobacterial strains. This dataset was used to develop both quantitative and discriminative chemometric models. The results obtained from the chemometric analyses demonstrate the ability of the LRRS to detect and quantify algal and cyanobacterial species at concentrations as low as 10³ cells/mL and to robustly discriminate between species at concentrations of 10⁴ cells/mL. The LRRS and chemometric analyses were further able to detect the presence of low concentrations (10³cells/mL) of contaminating species, including the toxic cyanobacterium Microcystis aeruginosa, within dense (>10⁷ cells/mL) spirulina cultures. The results presented provide a first demonstration of the potential of LRRS technology for real-time detection of contaminant species within microalgal bioreactors, and possibly for early detection of developing harmful algal blooms in other aquatic ecosystems.

Bio-physical and Computational Studies on Serum Albumin / Target Protein Binding of a Potential Anti-Cancer Agent

The successful evolution of an effective drug depends on its pharmacokinetics, efficiency and safety and these in turn depend on the drug-target/drug-carrier protein binding. This work, deals with the interaction of a pyridine derivative, 2-hydroxy-5-(4-methoxyphenyl)-6-phenylpyridine 3-carbonitrile (HDN) with serum albumins at physiological conditions utilizing the steady state and time-resolved fluorescence techniques by probing the emission behavior of Trp in BSA and HSA. In-silico studies revealed a combined static and dynamic quenching mechanism for the interactions. The binding studies suggests a spontaneous binding between HDN and the albumins with a moderate binding affinity (Kb ∼ 10-5 M-1) with a single class of binding site. The FRET mediated emission from HDN indicates preferential binding of HDN in subdomain IIA of the albumins with Trp residue in close proximity. Circular dichroism results indicate HDN induced conformational changes for BSA and HSA, but the α-helical secondary structure was well preserved even up to a concentration of 10 µM HDN. Moderate binding affinity of HDN with BSA and HSA and the unaltered secondary structure of proteins on binding propose the potential application of HDN as an efficient drug. The application of docking method on the affinity of HDN towards the proposed target/receptor is discussed.

Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review

Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.

Spatiotemporal distribution of chemical signatures exhibited by Myxococcus xanthus in response to metabolic conditions

Myxococcus xanthus is a common soil bacterium with a complex life cycle, which is known for production of secondary metabolites. However, little is known about the effects of nutrient availability on M. xanthus metabolite production. In this study, we utilize confocal Raman microscopy (CRM) to examine the spatiotemporal distribution of chemical signatures secreted by M. xanthus and their response to varied nutrient availability. Ten distinct spectral features are observed by CRM from M. xanthus grown on nutrient-rich medium. However, when M. xanthus is constrained to grow under nutrient-limited conditions, by starving it of casitone, it develops fruiting bodies, and the accompanying Raman microspectra are dramatically altered. The reduced metabolic state engendered by the absence of casitone in the medium is associated with reduced, or completely eliminated, features at 1140 cm^-1, 1560 cm^-1, and 1648 cm^-1. In their place, a feature at 1537 cm^-1 is observed, this feature being tentatively assigned to a transitional phase important for cellular adaptation to varying environmental conditions. In addition, correlating principal component analysis heat maps with optical images illustrates how fruiting bodies in the center co-exist with motile cells at the colony edge. While the metabolites responsible for these Raman features are not completely identified, three M. xanthus peaks at 1004, 1151, and 1510 cm^-1 are consistent with the production of lycopene. Thus, a combination of CRM imaging and PCA enables the spatial mapping of spectral signatures of secreted factors from M. xanthus and their correlation with metabolic conditions.

Visualizing and quantifying antimicrobial drug distribution in tissue

The biodistribution and pharmacokinetics of drugs are vital to the mechanistic understanding of their efficacy. Measuring antimicrobial drug efficacy has been challenging as plasma drug concentration is used as a surrogate for tissue drug concentration, yet typically does not reflect that at the intended site(s) of action. Utilizing an image-guided approach, it is feasible to accurately quantify the biodistribution and pharmacokinetics within the desired site(s) of action. We outline imaging modalities used in visualizing drug distribution with examples ranging from in vitro cellular drug uptake to clinical treatment of microbial infections. The imaging modalities of interest are: radio-labeling, magnetic resonance, mass spectrometry imaging, computed tomography, fluorescence, and Raman spectroscopy. We outline the progress, limitations, and future outlook for each methodology. Further advances in these optical approaches would benefit patients and researchers alike, as non-invasive imaging could yield more profound insights with a lower clinical burden than invasive measurement approaches used today.

Live Cell Poration by Au Nanostars to Probe Intracellular Molecular Composition with SERS

A new type of flat substrate has been used to visualize structures inside living cells by surface-enhanced Raman scattering (SERS) and to study biochemical processes within cells. The SERS substrate is formed by stabilized aggregates of gold nanostars on a glass microscope slide coated with a layer of poly (4-vinyl pyridine) polymer. This type of SERS substrate provides good cell adhesion and viability. Au nanostars' long tips can penetrate the cell membrane, allowing it to receive the SERS signal from biomolecules inside a living cell. The proposed nanostructured surfaces were tested to study, label-free, the distribution of various biomolecules in cell compartments.

Coherent anti-Stokes Raman scattering microspectroscopy: an emerging technique for non-invasive optical assessment of a local bio-nano-environment

Raman spectroscopy provides a non-invasive, chemically-specific optical imaging of biological objects without relying on endogenous labels. Nonlinear Raman spectroscopy allows non-invasive imaging at much faster speed with an improved spatial resolution and axial sectioning capability. In this report we propose a novel use of nonlinear Raman spectroscopy as a sensor of local nano-environment. Time-resolved coherent anti-Stokes Raman spectrograms are found to be sensitive to small variations of local structural changes, which are not normally observed using conventional Raman spectroscopy.

A Portable Ultrawideband Confocal Raman Spectroscopy System with a Handheld Probe for Skin Studies

Confocal Raman spectroscopy (CRS) has shown potential in non-invasive skin analysis. However, current CRS systems have various limitations including a narrow detection band, large size, non-flexibility, slowness, and complexity, which hinder their clinical applications. Herein, we developed a portable ultrawideband CRS system with a fiber-based handheld probe to acquire the Raman spectra in both fingerprint and high wavenumber regions in a fast and quasi-simultaneous way. Dual-wavelength excitation with a dual-passband laser cleaning filter and high-speed fiber array multiplexer was adopted instead of a specialized grating and detector to achieve instant switching between the detection regions and improve system robustness. Preliminary in vivo results demonstrated its depth profiling capability in an ultrawide detection range for stratum corneum thickness, natural moisturizing factor, and water content quantification, indicating its great potential in a wide range of clinical and cosmeceutical applications.

Highly Sensitive Low-Frequency Time-Domain Raman Spectroscopy via Fluorescence Encoding

Fluorescence-encoded vibrational spectroscopy has become increasingly more popular by virtue of its high chemical specificity and sensitivity. However, current fluorescence-encoded vibrational spectroscopy methods lack sensitivity in the low-frequency region, which if addressed could further enhance their capabilities. Here, we present a method for highly sensitive low-frequency fluorescence-encoded vibrational spectroscopy, termed fluorescence-encoded time-domain coherent Raman spectroscopy (FLETCHERS). By first exciting molecules into vibrationally excited states and then promoting the vibrating molecules to electronic states at varying times, the molecular vibrations can be encoded onto the emitted time-domain fluorescence intensity. We demonstrate the sensitive low-frequency detection capability of FLETCHERS by measuring vibrational spectra in the lower fingerprint region of rhodamine 800 solutions as dilute as 250 nM, which is ∼1000 times more sensitive than conventional vibrational spectroscopy. These results, along with further improvement of the method, open up the prospect of performing single-molecule vibrational spectroscopy in the low-frequency region.

Detection and quantification of toxicants in food and water using Ag-Au core-shell fractal SERS nanostructures and multivariate analysis

Here we demonstrate a facile, two step formation of silver core - gold shell (Ag-Au) nanostructures using microelectrodes and assess their performance as surface-enhanced Raman scattering (SERS) substrates to detect and quantify toxicants. Ag nanostructures, serving as the scaffolds for the bimetallic structures, were grown first by using electrochemical deposition on the edges of microelectrodes functionalized with the alkanethiol, 11-mercaptoundecanoic acid. Subsequently, different concentrations of HAuCl₄ were used to perform a galvanic reaction on the surfaces of the Ag nanostructures with aqueous droplets being placed on the microelectrodes for 10 min before the substrate was rinsed and dried. Lower HAuCl₄ concentrations were found to better preserve the fractal morphology of the formed Ag-Au nanostructures, while higher concentrations resulted in Ag-Au fragments. The SERS enhancement factor for the Ag-Au nanostructures was estimated to have a max value of 6.51 x 10⁵. Combining a data reduction technique with a linear classifier, both identification and quantification were demonstrated with 100% success. The toxicants thiram, thiabendazole, malachite green and biphenyl-4-thiol were all detected and identified at 1 ppm. Lastly, as a proof of concept, the Ag-Au nanostructures were transferred to a PDMS film resulting in a flexible SERS substrate capable of direct detection of thiram on an apple peel without any additional sample pre-treatment.

Raman Spectroscopy Can Distinguish Glyphosate-Susceptible and -Resistant Palmer Amaranth (Amaranthus palmeri)

The non-judicious use of herbicides has led to a widespread evolution of herbicide resistance in various weed species including Palmer amaranth, one of the most aggressive and troublesome weeds in the United States. Early detection of herbicide resistance in weed populations may help growers devise alternative management strategies before resistance spreads throughout the field. In this study, Raman spectroscopy was utilized as a rapid, non-destructive diagnostic tool to distinguish between three different glyphosate-resistant and four -susceptible Palmer amaranth populations. The glyphosate-resistant populations used in this study were 11-, 32-, and 36-fold more resistant compared to the susceptible standard. The 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) gene copy number for these resistant populations ranged from 86 to 116. We found that Raman spectroscopy could be used to differentiate herbicide-treated and non-treated susceptible populations based on changes in the intensity of vibrational bands at 1156, 1186, and 1525 cm-1 that originate from carotenoids. The partial least squares discriminant analysis (PLS-DA) model indicated that within 1 day of glyphosate treatment (D1), the average accuracy of detecting herbicide-treated and non-treated susceptible populations was 90 and 73.3%, respectively. We also found that glyphosate-resistant and -susceptible populations of Palmer amaranth can be easily detected with an accuracy of 84.7 and 71.9%, respectively, as early as D1. There were relative differences in the concentration of carotenoids in plants with different resistance levels, but these changes were not significant. The results of the study illustrate the utility of Raman spectra for evaluation of herbicide resistance and stress response in plants under field conditions.

Design of a Multimodal Imaging System and Its First Application to Distinguish Grey and White Matter of Brain Tissue. A Proof-of-Concept-Study

Multimodal imaging gains increasing popularity for biomedical applications. This article presents the design of a novel multimodal imaging system. The centerpiece is a light microscope operating in the incident and transmitted light mode. Additionally, Raman spectroscopy and VIS/NIR reflectance spectroscopy are adapted. The proof-of-concept is realized to distinguish between grey matter (GM) and white matter (WM) of normal mouse brain tissue. Besides Raman and VIS/NIR spectroscopy, the following optical microscopy techniques are applied in the incident light mode: brightfield, darkfield, and polarization microscopy. To complement the study, brightfield images of a hematoxylin and eosin (H&E) stained cryosection in the transmitted light mode are recorded using the same imaging system. Data acquisition based on polarization microscopy and Raman spectroscopy gives the best results regarding the tissue differentiation of the unstained section. In addition to the discrimination of GM and WM, both modalities are suited to highlight differences in the density of myelinated axons. For Raman spectroscopy, this is achieved by calculating the sum of two intensity peak ratios (I2857 + I2888)/I2930 in the high-wavenumber region. For an optimum combination of the modalities, it is recommended to apply the molecule-specific but time-consuming Raman spectroscopy to smaller regions of interest, which have previously been identified by the microscopic modes.

Detecting Minerals and Organics Relevant to Planetary Exploration Using a Compact Portable Remote Raman System at 122 Meters

Raman spectroscopy is a technique that can detect and characterize a range of molecular compounds such as water, water ice, water-bearing minerals, and organics of particular interest to planetary science. The detection and characterization of these molecular compounds, which are indications of habitability on planetary bodies, have become an important goal for planetary exploration missions spanning the solar system. Using a compact portable remote Raman system consisting of a 532 nm neodymium-doped yttrium aluminum garnet- (Nd:YAG-) pulsed laser, a 3-in. (7.62 cm) diameter mirror lens and a compact spectrograph with a miniature intensified charge coupled device (mini-ICCD), we were able to detect water (H₂O), water ice (H₂O-ice), CO₂-ice, hydrous minerals, organics, nitrates, and an amino acid from a remote distance of 122 m in natural lighting conditions. To the best of our knowledge, this is the longest remote Raman detection using a compact system. The development of this uniquely compact portable remote Raman system is applicable to a range of solar system exploration missions including stationary landers for ocean worlds and lunar exploration, as they provide unambiguous detection of compounds indicative of life as well as resources necessary for further human exploration.

Multivariate analysis of mean Raman spectra of erythrocytes for a fast analysis of the biochemical signature of ageing

Ageing of red blood cells (RBC) is a physiological process, fundamental to ensure a proper blood homeostasis that, in vivo, balances the production of new cells and the removal of senescent erythrocytes. A detailed characterization at the cellular level of the progression of the ageing phenomenon can reveal biological, biophysical and biochemical fingerprints for diseases related to misbalances of the cell turnover and for blood pathologies. We applied Principal Components Analysis (PCA) to mean Raman spectra of single cells at different ageing times to rapidly highlight subtle spectral differences associated with conformational and biochemical modifications. Our results demonstrate a two-step ageing process characterized by a first phase in which proteins plays a relevant role, followed by a further cellular evolution driven by alterations in the membrane lipid contribution. Moreover, we used the same approach to directly analyse relevant spectral effects associated to reduction in Haemoglobin oxygenation level and membrane fluidity induced by the ageing. The method is robust and effective, allowing to classify easily the studied cells based on their age and morphology, and consequently to evaluate the biological quality of a blood sample.

Plasmonic-based impedance microspectroscopy of optically heterogeneous samples

A robust impedance microscopy technique is presented. This optical tool enables high resolution imaging of electrical properties with promising biophysical applications. The underlying principle is that surface plasmon resonance (SPR) sensors are able to measure perturbations of surface charge density and therefore can be used to compute the impedance of surface-adhered cells. However, the ability to perform reliable quantitative impedance imaging is affected by the optical heterogeneity of the cell-sensor interface. To address this issue, a novel method for quantitative time-resolved resonance angle tracking is developed and applied to correct for the effect of the optical properties. To demonstrate the capability of this technique, impedance microspectroscopy of bovine serum albumin (BSA) patterns was performed enabling measurements of capacitance with submicroscopic resolution. The work presented offers an impedance microspectroscopy method that will create new avenues in studying the electrical properties of single cells and biomolecules as well as bio-electrical currents.

Hydrocracking: A Perspective towards Digitalization

In a world of fast technological advancements, it is increasingly important to see how hydrocracking applications can benefit from and adapt to digitalization. A review of hydrocracking processes from the perspective of modeling and characterization methods is presented next to an investigation on digitalization trends. Both physics-based and data-based models are discussed according to their scope of use, needs, and capabilities based on open literature. Discrete and continuous lumping, structure-oriented lumping, and single event micro-kinetic models are reported as well as artificial neural networks, convolutional neural networks, and surrogate models. Infrared, near-infrared, ultra-violet and Raman spectroscopic methods are given with their examples for the characterization of feed or product streams of hydrocracking processes regarding boiling point curve, API, SARA, sulfur, nitrogen and metal content. The critical points to consider while modeling the system and the soft sensor are reported as well as the problems to be addressed. Optimization, control, and diagnostics applications are presented together with suggested future directions of interdisciplinary studies. The links required between the models, soft sensors, optimization, control, and diagnostics are suggested to achieve the automation goals and, therefore, a sustainable operation.