Sparse decomposition enables adaptive and accurate Raman spectral denoising

Enhancing the quality of spectral denoising plays a vital role in Raman spectroscopy. Nevertheless, the intricate nature of the noise, coupled with the existence of impurity peaks, poses significant challenges to achieving high accuracy while accommodating various Raman spectral types. In this study, an innovative adaptive sparse decomposition denoising (ASDD) method is proposed for denoising Raman spectra. This approach features several innovations. Firstly, a dictionary comprising spectral feature peaks is established from the input spectra by applying a chemometric feature extraction method, which better aligns with the original data compared to traditional dictionaries. Secondly, a dynamic Raman spectral dictionary construction technique is introduced to swiftly adapt to new substances, employing a limited amount of additional Raman spectral data. Thirdly, the orthogonal matching pursuit algorithm is utilized to sparsely decompose the Raman spectra onto the constructed dictionaries, effectively eliminating various random and background noises in the Raman spectra. Empirical results confirm that ASDD enhances the accuracy and robustness of denoising Raman spectra. Significantly, ASDD surpasses existing algorithms in processing Raman spectra of pesticide.

Raman spectroscopy online monitoring of biomass production, intracellular metabolites and carbon substrates during submerged fermentation of oleaginous and carotenogenic microorganisms

BACKGROUND

Monitoring and control of both growth media and microbial biomass is extremely important for the development of economical bioprocesses. Unfortunately, process monitoring is still dependent on a limited number of standard parameters (pH, temperature, gasses etc.), while the critical process parameters, such as biomass, product and substrate concentrations, are rarely assessable in-line. Bioprocess optimization and monitoring will greatly benefit from advanced spectroscopy-based sensors that enable real-time monitoring and control. Here, Fourier transform (FT) Raman spectroscopy measurement via flow cell in a recirculatory loop, in combination with predictive data modeling, was assessed as a fast, low-cost, and highly sensitive process analytical technology (PAT) system for online monitoring of critical process parameters. To show the general applicability of the method, submerged fermentation was monitored using two different oleaginous and carotenogenic microorganisms grown on two different carbon substrates: glucose fermentation by yeast Rhodotorula toruloides and glycerol fermentation by marine thraustochytrid Schizochytrium sp. Additionally, the online FT-Raman spectroscopy approach was compared with two at-line spectroscopic methods, namely FT-Raman and FT-infrared spectroscopies in high throughput screening (HTS) setups.

RESULTS

The system can provide real-time concentration data on carbon substrate (glucose and glycerol) utilization, and production of biomass, carotenoid pigments, and lipids (triglycerides and free fatty acids). Robust multivariate regression models were developed and showed high level of correlation between the online FT-Raman spectral data and reference measurements, with coefficients of determination (R2) in the 0.94-0.99 and 0.89-0.99 range for all concentration parameters of Rhodotorula and Schizochytrium fermentation, respectively. The online FT-Raman spectroscopy approach was superior to the at-line methods since the obtained information was more comprehensive, timely and provided more precise concentration profiles.

CONCLUSIONS

The FT-Raman spectroscopy system with a flow measurement cell in a recirculatory loop, in combination with prediction models, can simultaneously provide real-time concentration data on carbon substrate utilization, and production of biomass, carotenoid pigments, and lipids. This data enables monitoring of dynamic behaviour of oleaginous and carotenogenic microorganisms, and thus can provide critical process parameters for process optimization and control. Overall, this study demonstrated the feasibility of using FT-Raman spectroscopy for online monitoring of fermentation processes.

Terbium Removal from Aqueous Solutions Using a In2O3 Nanoadsorbent and Arthrospira platensis Biomass

Terbium is a rare-earth element with critical importance for industry. Two adsorbents of different origin, In2O3 nanoparticles and the biological sorbent Arthrospira platensis, were applied for terbium removal from aqueous solutions. Several analytical techniques, including X-ray diffraction, Fourier-transform infrared spectroscopy, and scanning electron microscopy, were employed to characterize the adsorbents. The effect of time, pH, and terbium concentration on the adsorption efficiency was evaluated. For both adsorbents, adsorption efficiency was shown to be dependent on the time of interaction and the pH of the solution. Maximum removal of terbium by Arthrospira platensis was attained at pH 3.0 and by In2O3 at pH 4.0-7.0, both after 3 min of interaction. Several equilibrium (Langmuir, Freundlich, and Temkin) and kinetics (pseudo-first order, pseudo-second order, and Elovich) models were applied to describe the adsorption. The maximum adsorption capacity was calculated from the Langmuir model as 212 mg/g for Arthrospira platensis and 94.7 mg/g for the In2O3 nanoadsorbent. The studied adsorbents can be regarded as potential candidates for terbium recovery from wastewater.

Rosehip Extract-Loaded Liposomes for Potential Skin Application: Physicochemical Properties of Non- and UV-Irradiated Liposomes

In the present study, rosehip (Rosa canina L.) extract was successfully encapsulated in phospholipid liposomes using a single-step procedure named the proliposome method. Part of the obtained liposomes was subjected to UV irradiation and non-treated (native) and UV-irradiated liposomes were further characterized in terms of encapsulation efficiency, chemical composition (HPLC analysis), antioxidant capacity, particle size, PDI, zeta potential, conductivity, mobility, and antioxidant capacity. Raman spectroscopy as well as DSC analysis were applied to evaluate the influence of UV irradiation on the physicochemical properties of liposomes. The encapsulation efficiency of extract-loaded liposomes was higher than 90%; the average size was 251.5 nm; the zeta potential was -22.4 mV; and the conductivity was found to be 0.007 mS/cm. UV irradiation did not cause a change in the mentioned parameters. In addition, irradiation did not affect the antioxidant potential of the liposome-extract system. Raman spectroscopy indicated that the extract was completely covered by the lipid membrane during liposome entrapment, and the peroxidation process was minimized by the presence of rosehip extract in liposomes. These results may guide the potential application of rosehip extract-loaded liposomes in the food, pharmaceutical, or cosmetic industries, particularly when liposomal sterilization is needed.

Probing the impact of sustainable emerging sonication and DBD plasma technologies on the quality of wheat sprouts juice

Sonication and dielectric barrier discharge (DBD) plasma are sustainable emerging food processing technologies. The study investigates the impact of sonication, DBD-plasma, and thermal treatment (TT) on wheat sprout juice. The obtained results indicated a significant (p < 0.05) increase in chlorophyll, total phenolics, flavonoids, DPPH assay, and ORAC assay after DBD-plasma (40 V) and sonication (30 mins) treatment as compared to TT and untreated samples. Both emerging technologies significantly (p < 0.05) reduce the polyphenol oxidase and peroxidase activities, but the TT sample had the highest reduction. Moreover, the synergistic application of both technologies significantly reduced the E. coli/Coliform, aerobics, yeast and mold up to the 2 log reduction, but the TT sample had a complete reduction. DBD-plasma and sonication processing significantly decreased (p < 0.05) the particle size, reducing apparent viscosity (η) and consistency index (K); while increasing the flow behavior (n), leading to higher stability of wheat sprout juice. To assess the impact of emerging techniques on nutrient concentration, we used surface-enhance Raman spectroscopy (SERS) as an emerging method. Silver-coated gold nano-substrates were used to compare the nutritional concentration of wheat sprout juice treated with sonication, DBD-plasma, and TT-treated samples. Results showed sharp peaks for samples treated with DBD-plasma followed by sonication, untreated, and TT. The obtained results, improved quality of wheat sprout juice, and lower microbial and enzymatic loads were confirmed, showing the suitability of these sustainable processing techniques for food processing and further research.

Recent Advances in Nanomaterial-Based Sensing for Food Safety Analysis

The increasing public attention on unceasing food safety incidents prompts the requirements of analytical techniques with high sensitivity, reliability, and reproducibility to timely prevent food safety incidents occurring. Food analysis is critically important for the health of both animals and human beings. Due to their unique physical and chemical properties, nanomaterials provide more opportunities for food quality and safety control. To date, nanomaterials have been widely used in the construction of sensors and biosensors to achieve more accurate, fast, and selective food safety detection. Here, various nanomaterial-based sensors for food analysis are outlined, including optical and electrochemical sensors. The discussion mainly involves the basic sensing principles, current strategies, and novel designs. Additionally, given the trend towards portable devices, various smartphone sensor-based point-of-care (POC) devices for home care testing are discussed.

Quantification of glycated hemoglobin and glucose in vivo using Raman spectroscopy and artificial neural networks

Undiagnosed type 2 diabetes (T2D) remains a major public health concern. The global estimation of undiagnosed diabetes is about 46%, being this situation more critical in developing countries. Therefore, we proposed a non-invasive method to quantify glycated hemoglobin (HbA1c) and glucose in vivo. We developed a technique based on Raman spectroscopy, RReliefF as a feature selection method, and regression based on feed-forward artificial neural networks (FFNN). The spectra were obtained from the forearm, wrist, and index finger of 46 individuals. The use of FFNN allowed us to achieve an error in the predictive model of 0.69% for HbA1c and 30.12 mg/dL for glucose. Patients were classified according to HbA1c values into three categories: healthy, prediabetes, and T2D. The proposed method obtained a specificity and sensitivity of 87.50% and 80.77%, respectively. This work demonstrates the benefit of using artificial neural networks and feature selection techniques to enhance Raman spectra processing to determine glycated hemoglobin and glucose in patients with undiagnosed T2D.

Raman Method in Identification of Species and Varieties, Assessment of Plant Maturity and Crop Quality—A Review

The present review covers reports discussing potential applications of the specificity of Raman techniques in the advancement of digital farming, in line with an assumption of yield maximisation with minimum environmental impact of agriculture. Raman is an optical spectroscopy method which can be used to perform immediate, label-free detection and quantification of key compounds without destroying the sample. The authors particularly focused on the reports discussing the use of Raman spectroscopy in monitoring the physiological status of plants, assessing crop maturity and quality, plant pathology and ripening, and identifying plant species and their varieties. In recent years, research reports have presented evidence confirming the effectiveness of Raman spectroscopy in identifying biotic and abiotic stresses in plants as well as in phenotyping and digital selection of plants in farming. Raman techniques used in precision agriculture can significantly improve capacities for farming management, crop quality assessment, as well as biological and chemical contaminant detection, thereby contributing to food safety as well as the productivity and profitability of agriculture. This review aims to increase the awareness of the growing potential of Raman spectroscopy in agriculture among plant breeders, geneticists, farmers and engineers.

Structural characterization of a homopolysaccharide produced by Weissella cibaria FMy 2-21-1 and its potential application as a green corrosion inhibiting film

Steel corrosion is a global issue that affects safety and the economy. Currently, the homopolysaccharide (HoPS) structure of a novel lactic acid bacterium (LAB) is under study, as well as its application as a green corrosion inhibitor. Weissella cibaria FMy 2-21-1 is a LAB strain capable of producing HoPS in sucrose enriched media. The isolated and purified HoPS was characterized by different spectroscopic analyses as a linear α-1,6 dextran adopting a random coil conformation, with high molecular weight and extended size in water. The polysaccharide showed a semi-crystalline organization, which is a requirement for film formation. Its biocoating showed a grainy network structure, with a slightly lesser hydrophobic role in the aqueous environment than in the ionic one. The electrochemical measurements of the steel-HoPS coating showed that the biopolymer layer acts as an anodic-type corrosion inhibitor, with high resistance to corrosion by water and with chloride ions which prevent pitting, a corrosion process typical of bare steel. Few reports have cited the application of LAB HoPS as corrosive coating inhibitors. This work is the first to explore the influence of a structurally characterized dextran from Weissella cibaria strain as a potential steel corrosion inhibitor in ionic environments.

Tuning the drug multimodal release through a co-assembly strategy based on magnetic gels

Self-assembled short peptide-based gels are highly promising drug delivery systems. However, implementing a stimulus often requires screening different structures to obtain gels with suitable properties, and drugs might not be well encapsulated and/or cause undesirable effects on the gel's properties. To overcome this challenge, a new design approach is presented to modulate the release of doxorubicin as a model chemotherapeutic drug through the interplay of (di)phenylalanine-coated magnetic nanoparticles, PEGylated liposomes and doxorubicin co-assembly in dehydropeptide-based gels. The composites enable an enhancement of the gelation kinetics in a concentration-dependent manner, mainly through the use of PEGylated liposomes. The effect of the co-assembly of phenylalanine-coated nanoparticles with the hydrogel displays a concentration and size dependence. Finally, the integration of liposomes as doxorubicin storage units and of nanoparticles as composites that co-assemble with the gel matrix enables the tuneability of both passive and active doxorubicin release through a thermal, and a low-frequency alternating magnetic field-based trigger. In addition to the modulation of the gel properties, the functionalization with (di)phenylalanine improves the cytocompatibility of the nanoparticles. Hereby, this work paves a way for the development of peptide-based supramolecular systems for on-demand and controlled release of drugs.

Fano resonance line shapes in the Raman spectra of tubulin and microtubules reveal quantum effects

Microtubules are self-assembling biological nanotubes made of the protein tubulin that are essential for cell motility, cell architecture, cell division, and intracellular trafficking. They demonstrate unique mechanical properties of high resilience and stiffness due to their quasi-crystalline helical structure. It has been theorized that this hollow molecular nanostructure may function like a quantum wire where optical transitions can take place, and photoinduced changes in microtubule architecture may be mediated via changes in disulfide or peptide bonds or stimulated by photoexcitation of tryptophan, tyrosine, or phenylalanine groups, resulting in subtle protein structural changes owing to alterations in aromatic flexibility. Here, we measured the Raman spectra of a microtubule and its constituent protein tubulin both in dry powdered form and in aqueous solution to determine if molecular bond vibrations show potential Fano resonances, which are indicative of quantum coupling between discrete phonon vibrational states and continuous excitonic many-body spectra. The key findings of this work are that we observed the Raman spectra of tubulin and microtubules and found line shapes characteristic of Fano resonances attributed to aromatic amino acids and disulfide bonds.

Distinguishing cotton seed genotypes by means of vibrational spectroscopic methods (NIR and Raman) and chemometrics

The use of vibrational spectroscopy, such as near infrared (NIR) and Raman, combined with multivariate analysis methods to analyze agricultural products are promising for investigating genetically modified organisms (GMO). In Brazil, cotton is grown under humid tropical conditions and is highly affected by pests and diseases, requiring the use of large amounts of phytosanitary chemicals. To avoid the use of those pesticides, genetic improvement can be carried out to produce species tolerant to herbicides, resistant to fungi and insects, or even to provide greater productivity and better quality. Even with these advantages, it is necessary to manage and limit the contact of transgenic species with native ones, avoiding possible contamination or even extinction of conventional species. The identification of the presence of GMOs is based on complex DNA-based analysis, which is usually laborious, expensive, time-consuming, destructive, and generally unavailable. In the present study, a new methodology to identify GMOs using partial least squares discriminant analysis (PLS-DA) on NIR and Raman data is proposed to distinguish conventional and transgenic cotton seed genotypes, providing classification errors for prediction set of 2.23% for NIR and 0.0% for Raman.

Biochemical changes in the cytoplasm of bovine oocytes during the in vitro maturation process: a Raman microscopy study

The sequence and chronology of the main biochemical changes occurring in the cytoplasm of bovine oocytes during the in vitro maturation process were tracked by Raman microscopy applied to cells previously subjected to enzymatic digestion of the zona pellucida. Specific spectral markers for proteins, lipids and carbohydrates were used to evaluate the developmental status of the ooplasm at four different times. Spectral changes revealed that lipid accumulation was dominant during the first six hours of culture while protein content reached the average levels characteristic of mature oocytes within the last four hours of the maturation process. A time-dependent decrease in carbohydrates was also observed. Finally, the carbohydrate-to-protein (P₁₀₃₇/P₁₀₀₂) ratio proved to be sensitive enough to determine the cytoplasmic maturation state of bovine oocytes and promises to be useful in future research aimed at optimizing culture conditions through the promotion of protein accumulation in the ooplasm.

The Potential of Spectroscopic Techniques in Coffee Analysis—A Review

This review provides an overview of recent studies on the potential of spectroscopy techniques (mid-infrared, near infrared, Raman, and fluorescence spectroscopy) used in coffee analysis. It specifically covers their applications in coffee roasting supervision, adulterants and defective beans detection, prediction of specialty coffee quality and coffees’ sensory attributes, discrimination of coffee based on variety, species, and geographical origin, and prediction of coffees chemical composition. These are important aspects that significantly affect the overall quality of coffee and consequently its market price and finally quality of the brew. From the reviewed literature, spectroscopic methods could be used to evaluate coffee for different parameters along the production process as evidenced by reported robust prediction models. Nevertheless, some techniques have received little attention including Raman and fluorescence spectroscopy, which should be further studied considering their great potential in providing important information. There is more focus on the use of near infrared spectroscopy; however, few multivariate analysis techniques have been explored. With the growing demand for fast, robust, and accurate analytical methods for coffee quality assessment and its authentication, there are other areas to be studied and the field of coffee spectroscopy provides a vast opportunity for scientific investigation.

Interaction of borohydride stabilized silver nanoparticles with sulfur-containing organophosphates

Understanding the interactions between nanoparticles and organophosphates is the key to developing cost-effective colorimetric pesticide detection. We have studied the interaction between three different organophosphates containing the P[double bond, length as m-dash]S group and borohydride stabilized silver nanoparticles. Three different organophosphates, namely phorate, chlorpyrifos, and malathion, have been used. The colorimetric changes are corroborated with UV-visible absorption studies along with the change in particle size and zeta potential. This effect persists in the presence of NaCl solution also. The chlorpyrifos and malathion do not show significant interactions with uncapped nanoparticles over time, while phorate undergoes degradation due to the scission of the S-CH2 linkage. A reaction mechanism, wherein a silver and sulfur (Ag→S) complex is formed, which is in agreement with Raman spectroscopic studies is proposed. The orientations of phorate near Ag nanoparticles are discussed from the adsorption energy calculation using density functional theory.

Multiwell Raman plate reader for high-throughput biochemical screening

Although Raman spectroscopy has been used for the quantitative analysis of samples in many fields, including material science, biomedical, and pharmaceutical research, its low sensitivity hindered the application of the analytical capability for high-throughput screening. Here, we developed a high-throughput Raman screening system that can analyze hundreds of specimens in a multiwell plate simultaneously. Multiple high numerical aperture (NA) lenses are assembled under each well in the multiwell plate to detect Raman scattering simultaneously with high sensitivity. The Raman spectrum of 192 samples loaded on a standard 384-well plate can be analyzed simultaneously. With the developed system, the throughput of Raman measurement was significantly improved (about 100 times) compared to conventional Raman instruments based on a single-point measurement. By using the developed system, we demonstrated high-throughput Raman screening to investigate drug polymorphism and identify a small-molecule binding site in a protein. Furthermore, the same system was used to demonstrate high-speed chemical mapping of a centimeter-sized pork slice.

Study the impact of ultra-sonication and pulsed electric field on the quality of wheat plantlet juice through FTIR and SERS

Pulsed electric field (PEF) and Ultrasound (US) are commonly used in food processing. We investigated the combined impact of pulsed electric field (PEF) and ultrasound (US) on the wheat plantlet juice. When compared with the individual treatments, the highest values of total phenolics, total flavonoids, chlorophyll, ORAC assay, and DPPH activities were obtained using the combined (US + PEF) methods. The US + PEF significantly decreased the peroxidase and polyphenol oxidase activities from 0.87 to 0.27 Abs min-1 and 0.031-0.016 Abs min-1. Also, the synergistic application significantly lowered the yeast and mold (3.92 to 2.11 log CFU/mL), E. coli/Coliform (1.95 to 0.96 log CFU/mL), and aerobics (4.41 to 2.01 log CFU/mL). Furthermore, Fourier Transform Infrared (FT-IR) and surface-enhanced Raman spectroscopy (SERS) was used to analyzing juice quality. Gold nanoparticles (AuNPs) were used as the SERS substrates, which provided stronger Raman peaks for the samples treated with US + PEF methods. The FT-IR analysis showed significant enhancement of the nutritional molecules. The enhanced quality of wheat plantlet juice combined with lower yeast and mold suggests the suitability of integrated methods for further research and applications.

Raman Spectroscopy Technique: A Non-Invasive Tool in Celiac Disease Diagnosis

Celiac disease (CD) is diagnosed by a combination of specific serology and typical duodenal lesions. The histological confirmation of CD, mandatory in the majority of patients with suspected CD, is based on invasive and poorly tolerated procedures, such as upper gastrointestinal endoscopy. In this study we propose an alternative and non-invasive methodology able to confirm the diagnosis of CD based on the analysis of serum samples using the Raman spectroscopy technique. Three different bands centered at 1650, 1450 and 1003 cm^-1 have been considered and the A₁₄₅₀/A₁₀₀₃ and A₁₆₅₀/A₁₀₀₃ ratios have been computed to discriminate between CD and non-CD subjects. The reliability of the methodology was validated by statistical analysis using receiver operating characteristic (ROC) curves. The Youden index was also determined to obtain optimal cut-off points. The obtained results highlighted that the proposed methodology was able to distinguish between CD and non-CD subjects with 98% accuracy. The optimal cut-off points revealed, for both the A₁₄₅₀/A₁₀₀₃ and A₁₆₅₀/A₁₀₀₃ ratios, high values of sensitivity and specificity (>95.0% and >92.0% respectively), confirming that Raman spectroscopy may be considered a valid alternative to duodenal biopsy and demonstrates spectral changes in the secondary structures of the protein network.

Ultrasensitive and Selective Impedimetric Determination of Prostate Specific Membrane Antigen Based on Di-Succinimide Functionalized Polythiophene Covered Cost-Effective Indium Tin Oxide

A new and ultrasensitive impedimetric biosensor fabricated by using conjugated di-succinimide substituted polythiophene (P(ThidiSuc)) polymer modified indium tin oxide electrode is developed for the first time to detect the prostate specific membrane antigen (PSMA). The polymer P(Thi-diSuc) is synthesized by using a simple way and used in the fabrication of the proposed biosensor. The synthesized polymer contains di-succinimide groups, which offers covalent immobilization of PSMA specific antibodies. The developed strategy shortens the biosensor fabrication steps, because these active groups bind covalently to the amino ends of PSMA specific antibodies and this reaction does not require any crosslinking agent. Various characterization studies like impedimetric and voltammetric measurements, and morphological analyses are utilized to confirm the successful development of the biosensor. Under optimum conditions, the biosensing ability of the PSMA determination has a wide linear determination range from 0.015 to 14.4 pg mL^-1 , as well as a low limit of detection of 6.4 fg mL^-1 and a high sensitivity of 1.36 kohm pg^-1 mL cm^-2 . Furthermore, the proposed biosensor is able to measure the PSMA antigen in real human serums, which offers that it is a simple, low-cost, and sensitive tool with excellent potential for application in the quantification of PSMA.

Assessment of Biotechnologically Important Filamentous Fungal Biomass by Fourier Transform Raman Spectroscopy

Oleaginous filamentous fungi can accumulate large amount of cellular lipids and biopolymers and pigments and potentially serve as a major source of biochemicals for food, feed, chemical, pharmaceutical, and transport industries. We assessed suitability of Fourier transform (FT) Raman spectroscopy for screening and process monitoring of filamentous fungi in biotechnology. Six Mucoromycota strains were cultivated in microbioreactors under six growth conditions (three phosphate concentrations in the presence and absence of calcium). FT-Raman and FT-infrared (FTIR) spectroscopic data was assessed in respect to reference analyses of lipids, phosphorus, and carotenoids by using principal component analysis (PCA), multiblock or consensus PCA, partial least square regression (PLSR), and analysis of spectral variation due to different design factors by an ANOVA model. All main chemical biomass constituents were detected by FT-Raman spectroscopy, including lipids, proteins, cell wall carbohydrates, and polyphosphates, and carotenoids. FT-Raman spectra clearly show the effect of growth conditions on fungal biomass. PLSR models with high coefficients of determination (0.83-0.94) and low error (approximately 8%) for quantitative determination of total lipids, phosphates, and carotenoids were established. FT-Raman spectroscopy showed great potential for chemical analysis of biomass of oleaginous filamentous fungi. The study demonstrates that FT-Raman and FTIR spectroscopies provide complementary information on main fungal biomass constituents.

Rapid characterization of hypanthium and seed in wild and cultivated rosehip: application of Raman microscopy combined with multivariate analysis

Rosehip (pseudo-fruit) of dog rose (Rosa canina L.) is highly valued, and owing to nutritional and sensory properties it has a significant place in the food industry. This work represents an innovative report focusing on the evaluation of the phytochemical composition of rosehips (hypanthium and seed) grown in different locations in Serbia, using Raman microspectroscopy combined with multivariate data analysis. Some significant differences arose between the analysed rosehip samples with regard to the chemical profile of both hypanthium parenchyma cells and seed, although no evident discrimination was recorded between the samples of wild and cultivated rosehip. The differences between the hypanthium samples compared were mainly determined by the content of carotenoids, phenolic compounds and polysaccharides, whereas phenolics, polysaccharides (pectin, cellulose and hemicellulose) and lipids (to a lower extent) contributed to the seed sample discrimination. The differences observed between the rosehip samples may be attributed to abiotic factors (growing, ripening and storage conditions), which had a significant impact on the carotenoid and polyphenols biosynthesis.

Comparison of the Effects of Statins on A549 Nonsmall-Cell Lung Cancer Cell Line Lipids Using Fourier Transform Infrared Spectroscopy: Rosuvastatin Stands Out

Statins are commonly prescribed antilipidemic and anticholesterol class of drugs. In addition to their major role, they have been found to have anticancer effects on in vitro, animal and clinical studies. The aim of this study was to investigate the effects of six different statins (rosuvastatin, pravastatin, simvastatin, lovastatin, fluvastatin, and atorvastatin) on A549 cancer cells lipids by Fourier transform infrared (FTIR) spectroscopy. Proliferation tests were carried out to detect the half-maximal inhibitory concentrations (IC₅₀ ) of each statin on A549 cells. The IC₅₀ values were 50 μM for simvastatin, 150 μM for atorvastatin and pravastatin, and 170 μM for fluvastatin, 200 μM for rosuvastatin and lovastatin on A549 cells. No correlation was found between the antiproliferative effects of the statins and lipid-lowering effect. The cells were treated with IC₅ , IC₁₀ , and IC₅₀ values of each statins concentration and lipid extracts were compared using FTIR spectroscopy. The results indicated that different statins had different effects on the lipid content of A549 cells. The FTIR spectra of the lipid exctracts of statin-treated A549 cells indicated that the value of hydrocarbon chain length, unsaturation index, oxidative stress level, and phospholipid containing lipids increased except for rosuvastatin-treated A549 cells. In addition, rosuvastatin significantly lowered cholesterol ester levels. In conclusion, the contrasting effects of rosuvastatin should be further investigated.

Characterization of glycated hemoglobin based on Raman spectroscopy and artificial neural networks

The World Health Organization has declared the glycated hemoglobin (HbA1c) as a gold standard biomarker for diabetes diagnosis; this has led to relevant research on the spectral behavior and characterization of HbA1c. This paper presents an analysis of Raman peaks of commercial lyophilized HbA1c, diluted in distilled water, using concentrations of 4.76% and 9.09%, as well as pure powder (100% concentration). Vibrational Raman peak positions of HbA1c powder were found at 1578, 1571, 1536, 1436, 1311, 1308, 1230, 1222, 1114, 1106, 969, 799 and 665 cm^-1; these values are consistent with results reported in other works. Besides, a nonlinear regression model based on a Feed-Forward Neural Network (FFNN) was built to quantify percentages of HbA1c for unknown concentrations. Using the Raman spectra as independent variables, the regression provided a Root Mean Square Error in Cross-Validation (RMSECV) of 0.08% ± 0.04. We also include a detailed molecular assignment of the average spectra of lyophilized powder of HbA1c.

A Four-Level Maturity Index for Hot Peppers (Capsicum annum) Using Non-Invasive Automated Mobile Raman Spectroscopy for On-Site Testing

A handheld Raman spectrometer was used to determine the ripeness of peppers. Raman spectra were recorded non-invasively on the fruit surface. The spectroscopic data were transformed into a classification scheme referred to as the maturity index which allowed for attribution of the fruit stadium to four levels from immature to fully mature. Hot pepper and tomato ripening includes pectic polysaccharide depolymerization, chlorophyll degradation and carotenoid formation, among others. The latter were followed non-invasively by Raman spectroscopy. Two portable systems and one benchtop system were compared for their applicability and robustness to establish a suitable maturity index. Spectral acquisition, data treatment and multivariate data analysis were automated using a Matlab script on a laptop computer. The automated workflow provided a graphic visualization of the relevant parameters and results on-site in real time. In terms of reliability and applicability, the chemometric model to determine the maturity of fruits was compared to a univariate procedure based on the average intensity and ratio of three characteristic signals. Portable Raman spectrometers in combination with the maturity index or a chemometric model should be suitable to assess the stage of maturing for carotenoid-containing fruits and thus to determine ripeness on-site or during a sorting process in an automated manner.

Optical Screening Methods for Pesticide Residue Detection in Food Matrices: Advances and Emerging Analytical Trends

Pesticides have been extensively used in agriculture to protect crops and enhance their yields, indicating the need to monitor for their toxic residues in foodstuff. To achieve that, chromatographic methods coupled to mass spectrometry is the common analytical approach, combining low limits of detection, wide linear ranges, and high accuracy. However, these methods are also quite expensive, time-consuming, and require highly skilled personnel, indicating the need to seek for alternatives providing simple, low-cost, rapid, and on-site results. In this study, we critically review the available screening methods for pesticide residues on the basis of optical detection during the period 2016-2020. Optical biosensors are commonly miniaturized analytical platforms introducing the point-of-care (POC) era in the field. Various optical detection principles have been utilized, namely, colorimetry, fluorescence (FL), surface plasmon resonance (SPR), and surface enhanced Raman spectroscopy (SERS). Nanomaterials can significantly enhance optical detection performance and handheld platforms, for example, handheld SERS devices can revolutionize testing. The hyphenation of optical assays to smartphones is also underlined as it enables unprecedented features such as one-click results using smartphone apps or online result communication. All in all, despite being in an early stage facing several challenges, i.e., long sample preparation protocols or interphone variation results, such POC diagnostics pave a new road into the food safety field in which analysis cost will be reduced and a more intensive testing will be achieved.

Application of Raman Spectroscopy for the Evaluation of Metabolomic Dynamic Analysis in Athletic Horses

Raman spectroscopy is a rapid qualitative and quantitative technique that allows the simultaneous determination of several components, both biomolecules both chemical compounds, in the biological fluids to assess the metabolic status. In this study, the serum composition was evaluated in regularly trained athletic horses using Raman spectroscopy to identify biomarkers of sports performance. Five clinically healthy and regularly trained Italian Saddle horses were subjected to a standardized obstacle course (350 m/minute; eleven 1.25 high jumps) preceded by a warm-up. On the collected sera, at rest, immediately after exercise, 30 minutes, and 1 hour after the end of the exercise Raman measurements were performed using a diode laser with the excitation wavelength of 785 nm. The analysis of the obtained spectra allowed the identification of peaks and bands different in position and intensity among the experimental conditions. The acquired spectra, obtained from horse sera collected during the experimental protocol, were visually similar, except for the large band detected in the 1,250-1,800 cm^-1 range. The spectral intensity of the Raman spectrum decreased after training and 30 minutes after the end of exercise respect to the before exercise value, to come to the basal value after 60 minutes the end of the exercise. In conclusion, we can claim the ability of Raman spectroscopy to reveal the metabolic status of horses after physical exercise.

Rapid discrimination of intact beef, venison and lamb meat using Raman spectroscopy

With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies. Results obtained using linear and non-linear kernel SVM models yielded sensitivities of over 87 and 90 % respectively, with the corresponding specificities above 88 % on validation against a test set. The PLSDA model yielded over 80 % accuracy in classifying each of the meat specie. PLSDA and SVM classification models in combination with Raman spectroscopy posit an effective technique for red meat discrimination.

Raman Spectroscopy as Noninvasive Method of Diagnosis of Pediatric Onset Inflammatory Bowel Disease

We propose here a spectroscopic method to diagnose and differentiate inflammatory bowel diseases (IBD), such as ulcerative colitis (UC) and Crohn’s disease (CD) with pediatric onset, in a complete noninvasive way without performing any duodenal biopsy. In particular, the Raman technique was applied to proteic extract from fecal samples in order to achieve information about molecular vibrations that can potentially furnish spectral signatures of cellular modifications occurring as a consequence of specific pathologic conditions. The attention was focused on the investigation of the amide I region, quantitatively accounting the spectral changes in the secondary structures by applying deconvolution and curve-fitting. Inflammation is found to give rise to a significant increasing of the nonreducible (trivalent)/reducible (divalent) cross-linking ratio R of the protein network. This parameter revealed an excellent marker in order to distinguish IBD subjects from non-IBD ones, and, among IBD patients, to differentiate between UC and CD. The proposed methodology was validated by statistical analysis using the receiver operating characteristic (ROC) curve.

Discrimination of milk species using Raman spectroscopy coupled with partial least squares discriminant analysis in raw and pasteurized milk

BACKGROUND

Heat treatment is the most common practice for the microbiological safety of milk; hence, determination of the heat treatment of milk is essential. Also, mislabeling or adulteration of expensive milk samples, like ewe or goat milk, with cow's milk is a growing problem in the dairy market. Thus, the determination of the authenticity of milk samples has crucial importance for both producers and consumers. The aim of this study was to discriminate milk samples using Raman spectroscopy with partial least squares discriminant analysis (PLS-DA), first with regard to whether the milk was heat-treated or not, and second with regard to species (cow, goat, ewe, mixture (adulterated)) in both raw and pasteurized milk.

RESULTS

First, discrimination of milk samples as raw or pasteurized was achieved using PLS-DA. Both in calibration and prediction models, high sensitivity and specificity values were obtained for raw and pasteurized milk samples. Second, the proposed method also discriminated milk samples according to their species (cow, goat, ewe, and mixture) for both raw and pasteurized milk. In both calibration and prediction models, the sensitivity and specificity values were above 0.857 and 0.897 respectively. Also, the accuracy values were above 0.915. The results obtained denote satisfactory accurate classification of the samples.

CONCLUSION

The results suggest that Raman spectroscopy coupled with PLS-DA can be successfully used to discriminate milk samples according to heat treatment (raw/pasteurized) and their species within 20 s per sample. It was seen that Raman spectra provide valuable information to be used especially for discrimination of milk samples according to their origin. © 2020 Society of Chemical Industry.

Assessment of milkweed floss as a natural hollow oleophilic fibrous sorbent for oil spill cleanup

Natural oil sorbent materials with a high oil sorption capacity have recently received remarkable attention for oil spill cleanup from seawater. This study reports on the development of a superhydrophobic hollow cellulosic fiber that could serve as an oil spill cleanup material. As oil sorption is based on the physical and chemical characteristics of the sorbent, FTIR, SEM, XRD, and surface contact angle of the fibers were determined. A series of tests were then carried out to analyze the sorption capacity, dynamic oil retention, and reusability. Subsequently, the effect of the fibers' weight on the amount of oil absorption and absorption time was investigated. The wettability analyses showed that the milkweed floss fiber possessed a superhydrophobic characteristic (with the water contact angle of 140°). The empty channel of the fiber was more than 90% of its total volume. The hydrophobicity and capillary properties helped the fibers to absorb up to 100 g/g of oil, which was higher than that obtained by many natural cellulosic fibers.

Protein Quantification and Imaging by Surface-Enhanced Raman Spectroscopy and Similarity Analysis

Protein quantification techniques such as immunoassays have been improved considerably, but they have several limitations, including time-consuming procedures, low sensitivity, and extrinsic detection. Because direct surface-enhanced Raman spectroscopy (SERS) can detect intrinsic signals of proteins, it can be used as an effective detection method. However, owing to the complexity and reliability of SERS signals, SERS is rarely adopted for quantification without a purified target protein. This study reports an efficient and effective direct SERS-based immunoassay (SERSIA) technique for protein quantification and imaging. SERSIA relies on the uniform coating of gold nanoparticles (GNPs) on a target-protein-immobilized substrate by simple centrifugation. As centrifugation induces close contact between the GNPs and target proteins, the intrinsic signals of the target protein can be detected. For quantification, the protein levels in a cell lysate are estimated using similarity analysis between antibody-only and protein-conjugated samples. This method reliably estimates the protein level at a sub-picomolar detection limit. Furthermore, this method enables quantitative imaging of immobilized protein at a micrometer range. Because this technique is fast, sensitive, and requires only one type of antibody, this approach can be a useful method to detect proteins in biological samples.