A critical evaluation of Raman spectroscopy for the analysis of lipids: fatty acid methyl esters

Scrutinized lipid utilization disrupts Amphotericin-B responsiveness in clinical isolates of Leishmania donovani

The management of Leishmania donovani (LD), responsible for fatal visceral leishmaniasis (VL), faces increasing challenges due to rising drug unresponsiveness, leading to increasing treatment failures. While hypolipidemia characterizes VL, LD, a cholesterol auxotroph, relies on host lipid scavenging for its intracellular survival. The aggressive pathology, in terms of increased organ parasite load, observed in hosts infected with antimony-unresponsive-LD (LD-R) as compared to their sensitive counterparts (LD-S), highlights LD-R's heightened reliance on host lipids. Here, we report that LD-R-infection in mice promotes fluid-phase endocytosis in the host macrophages, selectively accumulating neutral lipids while excluding oxidized-low-density lipoprotein (LDL). LD-R enhances the fusion of endocytosed LDL-vesicles with its phagolysosomal membrane and inhibits cholesterol mobilization from these vesicles by suppressing NPC-1. This provides LD-R amastigotes with excess lipids, supporting their rapid proliferation and membrane synthesis. This excess LDL-influx leads to an eventual accumulation of neutral lipid droplets around LD-R amastigotes, thereby increasing their unresponsiveness toward Amphotericin-B, a second-line amphiphilic antileishmanial. Notably, VL patients showing relapse with Amphotericin-B treatment exhibited significantly lower serum LDL and cholesterol than cured cases. Treatment with Aspirin, a lipid droplet blocker, reduced lipid droplets around LD-R amastigotes, restoring Amphotericin-B responsiveness.

Gold Nanoparticle Incorporated Graphene Oxide as a SERS Platform for Ultratrace Antibody Free Sensing of the Cancer Biomarker CEA

A simple, fast, low-cost, and efficient method is designed for the synthesis of graphene oxide (GO) (20 nm) from graphite using a strong oxidant Ce(IV). GO is further modified with gold nanoparticles (AuNPs) (5-8 nm) to generate a AuGO nanocomposite (25 nm). Raman spectral analyses confirm that the synthesized AuGO has a potential selective sensing ability for the cancer biomarker carcinoembryonic antigen (CEA) in serum. Sensing assays are also carried out in the presence of high concentrations of glucose, cholesterol, and insulin using this method, which become significantly elevated in conditions of different pathophysiological disorders. Ultratrace antibody free sensing of CEA in serum is achieved using surface-enhanced Raman spectroscopy with an amazing LOD of 12.5 fg/mL. The interaction between CEA and AuGO is further established using Raman, fluorescence, circular dichroism spectroscopy, and theoretical studies. The specificity of sensing is tested by checking the response in the presence of other cancer biomarkers, such as CA 19-9, CA 125, and PSA, which do not show any signal enhancement with AuGO in Raman spectroscopy.

Machine Learning-Based SERS Chemical Space for Two-Way Prediction of Structures and Spectra of Untrained Molecules

Identifying unknown molecules beyond existing databases remains challenging in surface-enhanced Raman scattering (SERS) spectroscopy. Conventional SERS analysis relies on matching experimental and cataloged spectra, limiting identification to known molecules in databases. With a vast chemical space of >1060 molecules, it is impractical to obtain the spectra of every molecule and rely solely on in silico techniques for spectral predictions. Here, we showcase an ML-based SERS chemical space that leverages key spectra-structure correlations to achieve two-way spectra-to-structure and structure-to-spectra predictions for untrained molecules with a >90% average accuracy. Using a SERS chemical space comprising 38 linear molecules from four classes (alcohols, aldehydes, amines, and carboxylic acids), our experimental and in silico studies reveal underlying spectral features that enable the prediction of untrained molecules represented by two molecular descriptors (functional group and carbon chain length). For forward spectra-to-structure predictions, we devise a two-step "classification and regression" ML framework to sequentially predict the functional group and carbon chain length of untrained molecules with 100% accuracy and ≤1 carbon difference, respectively. In addition, using an eXtreme Gradient Boosting (XGBoost) regressor trained on the two molecular descriptors, we attain inverse structure-to-spectra prediction with a high average cosine similarity of 90.4% between the predicted and experimental spectra. Our ML-based SERS chemical space represents a shift in molecular identification from traditional spectral matching to predictive modeling of spectra-structure relationships. These insights could motivate the expansion of SERS chemical spaces and realize demands for present and future SERS technologiesfor accurate unknown identification across diverse fields.

Urineprint of high-altitude: Insights from analyses of urinary biomarkers and bio-physical-chemical features of extracellular vesicles

Humans exposed to altitude hypoxia experience dysfunctions of the urinary system. As a non-invasive, easily manageable and informative biological sample, urine represents a relevant matrix for detecting clinical impairments of urinary system, as well as alterations of other systems and extracellular vesicles (EVs) biology during high-altitude expeditions. Nevertheless, gaps exist in the comprehensive assessment of dysfunction, molecular burden and EVs biology due to high-altitude acute exposure. This study aimed to find a biophysical and biochemical signature of urinary EVs for hypoxia-induced changes in urinary function, putatively accompanied by an oxinflammatory burden. Urine samples of 15 participants were sampled at low and high-altitude during an Alpine project (7 women and 8 men, aged 24-to-63 years and with BMI 17.93-to-30.76 kg/m2) and analysed for: creatinin and albumin, lipid peroxidation, IL6, NO derivatives; atomic force microscopy and Raman spectroscopy were carried out after urinary EVs were isolated through sucrose-gradient ultracentrifugation. Albumin-to-creatinin ratio increased at high altitude, as did IL6 and 8-isoprostane. AFM showed a globular and flattened shape of EVs, although several samples were characterized by a lot of contaminants and EVs lost their prototypal spherical shape; EVs comprehensively maintained their morphology at high altitude. Raman spectroscopy revealed some typical phospholipidic-like pattern, often masked by contaminants of spectra that most often refer to high-altitude samples. Collectively, short-term exposure to altitude hypoxia increased renal concentrating ability, produced non-pathological impairment or renal function, and triggered an oxyinflammatory burden with heterogeneous response of NO system. The combination of AFM and Raman spectroscopy revealed that EVs collected at high altitude more likely are fused together and incorporated into a sediment matrix, and contain contaminants peaks that make the purification process less efficient. The combination of analytical procedures as in the present study offers novel possibilities to detect the biological and clinical effects of high altitude on renal system.

In vivo assessment of topically applied silver nanoparticles on entire cornea: comprehensive FTIR study

Silver nanoparticles (AgNPs) have gained attention in medicine for their potent antibacterial, antiviral, and anti-inflammatory properties. The use of silver nanoparticles in ophthalmic solutions raises concerns regarding potential toxicity of nanoparticles to ocular tissues, such as the cornea, conjunctiva, and retina, which necessitates further toxicity assessments aiding in the development of safer ophthalmic solutions. This study investigates the impact of AgNPs on corneal tissue using ophthalmic investigations, Fourier transform infrared (FTIR) spectroscopy, and chemometric analyses. Three concentrations of AgNPs (0.48 µg/mL, 7.2 µg/mL, and 15.5 µg/mL) were topically applied twice daily for 10 days, synthesized biologically by reducing silver nitrate with almond kernels water extract. Corneas, obtained by cutting 2-3 mm below the ora serrata, were analyzed with FTIR spectroscopy and subjected to chemometric analyses. Results reveal AgNPs' influence on constituents with OH and NH groups, affecting corneal lipids and reducing the lipid saturation index. AgNPs alter both bulk and interfacial water, leading to changes in corneal hydration thus modifying corneal physico-chemical properties. The influence extends to the water environment around proteins and lipids, releasing bound water from phospholipids and disrupting hydrogen bonding networks around proteins. In conclusion, the applied AgNPs concentrations can be linked to dry eye onset.

New insights into lipid and fatty acid metabolism from Raman spectroscopy

One of the challenges facing biology is to understand metabolic events at a single cellular level. While approaches to examine dynamics of protein distribution or report on spatiotemporal location of signalling molecules are well-established, tools for the dissection of metabolism in single living cells are less common. Advances in Raman spectroscopy, such as stimulated Raman scattering (SRS), are beginning to offer new insights into metabolic events in a range of experimental systems, including model organisms and clinical samples, and across a range of disciplines. Despite the power of Raman imaging, it remains a relatively under-used technique to approach biological problems, in part because of the specialised nature of the analysis. To raise the profile of this method, here we consider some key studies which illustrate how Raman spectroscopy has revealed new insights into fatty acid and lipid metabolism across a range of cellular systems. The powerful and non-invasive nature of this approach offers a new suite of tools for biomolecular scientists to address how metabolic events within cells informs on or underpins biological function. We illustrate potential biological applications, discuss some recent advances, and offer a direction of travel for metabolic research in this area.

Ripening process in exocarps of scarlet eggplant (Solanum aethiopicum) and banana (Musa spp.) investigated by Raman spectroscopy

In this work, we used Raman spectroscopy to identify compounds present at different maturation stages of the exocarp of scarlet eggplant and two banana cultivars, 'prata' and 'nanica'. Raman spectral analyses of both fruits showed bands attributed to phenolic acids, flavonoids, carotenoids, and fatty acids. During the scarlet eggplant's maturation process, Raman spectral profile changes are mainly observed in the carotenoid content rather than flavonoids. Furthermore, it is suggested that naringenin chalcone together with β-carotene determines the orange-red color of the ripe stage. Variations in chemical composition among the maturation stages of bananas were observed predominantly in 'prata' when compared to 'nanica'. In contrast to scarlet eggplant changes in the spectral profile were more evident in the content of the flavonoid/phenolic acids. The in situ analysis was demonstrated to be useful as a guide in selecting bioactive compounds on demand from low-cost horticultural waste.

In situ single-droplet analysis of emulsified fat using confocal Raman microscopy: insights into crystal network formation within spatial resolution

Fat crystallization is one of the predominant factors influencing the structure and properties of fat-containing emulsions. In the present study, the role of emulsifiers on fat crystallization dynamics within droplet multiphase systems was evaluated via single-droplet analysis, taking advantage of the non-destructive properties of confocal Raman microscopy. Palm oil droplets dispersed in water were used as a model system, due to palm oil's well-known crystallization properties. Emulsion droplets of the same size were generated using two different emulsifiers (Whey Protein Isolate and Tween 60), at various concentrations. Fast and slow cooling treatments were applied to affect fat crystallisation and network formation as well as droplet morphology, and crystallization dynamics. Raman imaging analysis demonstrated that the chemical structure and concentration of the emulsifier significantly influenced both crystal nucleation within the droplets, as well as the spatial distribution and morphology of the fat crystal network. Additionally, analysis of the spectra of the crystallized phase provided essential information regarding the impact of the emulsifiers on the microstructure, degree of structural order, and structural arrangements of the fat crystal networks. Furthermore, by performing single droplet analysis during cooling it was possible to observe shape distortions in Tween 60 stabilized droplets, as a consequence of the formation of a three-dimensional network of fat crystals that strongly interacted with the interface. On the other hand, the droplets retained their shape when whey proteins were absorbed at the interface. Confocal Raman microscopy, in combination with polarized light microscopy, is, therefore, a well-suited tool for in situ, single-droplet analysis of emulsified oil systems, providing essential information about emulsified fat crystallization dynamics, contributing to better understanding and designing products with enhanced structure and function.

Mesoscopic Structure of Lipid Nanoparticle Formulations for mRNA Drug Delivery: Comirnaty and Drug-Free Dispersions

Lipid nanoparticles (LNPs) produced by antisolvent precipitation (ASP) are used in formulations for mRNA drug delivery. The mesoscopic structure of such complex multicomponent and polydisperse nanoparticulate systems is most relevant for their drug delivery properties, medical efficiency, shelf life, and possible side effects. However, the knowledge on the structural details of such formulations is very limited. Essentially no such information is publicly available for pharmaceutical dispersions approved by numerous medicine agencies for the use in humans and loaded with mRNA encoding a mimic of the spike protein of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) as, e.g., the Comirnaty formulation (BioNTech/Pfizer). Here, we present a simple preparation method to mimic the Comirnaty drug-free LNPs including a comparison of their structural properties with those of Comirnaty. Strong evidence for the liquid state of the LNPs in both systems is found in contrast to the designation of the LNPs as solid lipid nanoparticles by BioNTech. An exceptionally detailed and reliable structural model for the LNPs i.a. revealing their unexpected narrow size distribution will be presented based on a combined small-angle X-ray scattering and photon correlation spectroscopy (SAXS/PCS) evaluation method. The results from this experimental approach are supported by light microscopy, 1H NMR spectroscopy, Raman spectroscopy, cryogenic electron microscopy (cryoTEM), and simultaneous SAXS/SANS studies. The presented results do not provide direct insights on particle formation or dispersion stability but should contribute significantly to better understanding the LNP drug delivery process, enhancing their medical benefit, and reducing side effects.

Comprehensive spectroscopic, metabolomic, and proteomic liquid biopsy in the diagnostics of hepatocellular carcinoma

Liquid biopsy is a very topical issue in clinical diagnostics research nowadays. In this study, we explored and compared various analytical approaches to blood plasma analysis. Finally, we proposed a comprehensive procedure, which, thanks to the utilization of multiple analytical techniques, allowed the targeting of various biomolecules in blood plasma reflecting diverse biological processes underlying disease development. The potential of such an approach, combining proteomics, metabolomics, and vibrational spectroscopy along with preceding blood plasma fractionation, was demonstrated on blood plasma samples of patients suffering from hepatocellular carcinoma in cirrhotic terrain (n = 20) and control subjects with liver cirrhosis (n = 20) as well as healthy subjects (n = 20). Most of the applied methods allowed the classification of the samples with an accuracy exceeding 80.0 % and therefore have the potential to be used as a stand-alone method in clinical diagnostics. Moreover, a final panel of 48 variables obtained by a combination of the utilized analytical methods enabled the discrimination of the hepatocellular carcinoma samples from cirrhosis with 94.3 % cross-validated accuracy. Thus, this study, although limited by the cohort size, clearly demonstrated the benefit of the multimethod approach in clinical diagnosis.

Colossal Barocaloric Effect of Binary Fatty Acid Methyl Esters under Low Pressures near Room Temperature

Refrigeration technology based on the caloric effect is one of the more environmentally friendly alternatives to gas compression refrigeration. The barocaloric effect utilizes pressure to induce phase transition and results in a large entropy change. In this work, a colossal barocaloric effect in the liquid-solid transition (L-S-T) of binary fatty acid methyl esters (BFAMEs) was discovered. At 295 K, an isothermal entropy change as high as 591 J kg-1 K-1 and a reversible entropy change of 356 J kg-1 K-1 at a hydrostatic pressure of 80 MPa were obtained by mixing methyl palmitate and methyl stearate with a specific ratio to synthesize a BFAME. The value of the isothermal entropy change of the BFAME is comparable to that of a commercial gas compression refrigerant, R134a. This work will provide a new L-S-T candidate material to replace commercial refrigerants for the potential application of caloric effect refrigeration technology.

Thermal Effects on the Quality Parameters of Extra Virgin Olive Oil Using Fluorescence Spectroscopy

Extra virgin olive oil is one of the superlative due to its health benefits. In this work, the Fluorescence spectra of extra virgin olive oil (EVOO) from different olive growing regions of Pakistan and Al-Jouf region from the Kingdom of Saudi Arabia (KSA) were obtained. The emission bands depicted relative intensity variations in all non-heated and heated EVOO samples. Prominent emission bands at 385, 400, 435 and 470 nm represent oxidized products of fatty acids, bands at 520 and 673 nm has been assigned to beta carotene and chlorophyll isomers respectively. All EVOO samples collected from Al-Jouf region, KSA and from Pakistan (Loralai Baluchistan, Barani Agricultural Research Institute, Chakwal and Morgha Biodiversity Park, Rawalpindi) regions showed thermal stability. Other EVOO samples from Chaman Baluchistan and one sample from wild specie (Baluchistan) bought directly from farmers showed denatured spectra even without heating. Chemical characteristics of all EVOO samples changed significantly at 200 °C. Relatively, EVOO samples from Al-Jouf showed more thermal stability which might be due to geographical distribution, environmental effects, genetic background and processing or storage conditions. These results demonstrated fluorescence spectroscopy as a quick, cost-effective and reliable approach to assess the quality and thermal stability of EVOO. These characteristics of fluorescence spectroscopy may lead to the development of portable device for the onsite monitoring of EVOO.

Evaluation of IR and Raman spectroscopic markers of human collagens: Insides for indicating colorectal carcinogenesis

Vibrational spectroscopic methods are widely used in the molecular diagnostics of carcinogenesis. Collagen, a component of connective tissue, plays a special role as a biochemical marker of pathological changes in tissues. The vibrational bands of collagens are very promising to distinguish between normal colon tissue, benign and malignant colon polyps. Differences in these bands indicate changes in the amount, structure, conformation and the ratio between the individual structural forms (subtypes) of this protein. The screening of specific collagen markers of colorectal carcinogenesis was carried out based on the FTIR and Raman (λ_ex 785 nm) spectra of colon tissue samples and purified human collagens. It was found that individual types of human collagens showed significant differences in their vibrational spectra, and specific spectral markers were found for them. These collagen bands were assigned to specific vibrations in the polypeptide backbone, amino acid side chains and carbohydrate moieties. The corresponding spectral regions for colon tissues and colon polyps were investigated for the contribution of collagen vibrations. Mentioned spectral differences in collagen spectroscopic markers could be of interest for early ex vivo diagnosis of colorectal carcinoma if combine vibrational spectroscopy and colonoscopy.

Spectroscopic signature of ZnO NP-induced cell death modalities assessed by non-negative PCA

Selective cytotoxicity of ZnO nanoparticles among different cell types and cancer and non-cancerous cells has been demonstrated earlier. In the view of anticancer potential of ZnO nanoparticles and their presence in numerous industrial products, it is of great importance to carefully evaluate their effects and mechanisms of action in both cancerous and healthy cells. In this paper, the effects of ZnO nanoparticles on cancerous HeLa and non-cancerous MRC-5 cells are investigated by studying the changes in the vibrational properties of the cells using Raman spectroscopy. Both types of cells were incubated with ZnO nanoparticles of average size 40 nm in the doses from the range 10-40 µg/ml for the period of 48 h, after which Raman spectra were collected. Raman modes' intensity ratios I₁₆₅₉/I₁₄₄₄, I₂₈₅₅/I₂₉₃₃ and I₁₃₃₇/I₁₃₀₅ were determined as spectral markers of the cytotoxic effect of ZnO in both cell types. Non-negative principal component analysis was used instead of standard one for analysis and detection of spectral features characteristic for nanoparticle-treated cells. The first several non-negative loading vectors obtained in this analysis coincided remarkably well with the Raman spectra of particular biomolecules, showing increase of lipid and decrease of nucleic acids and protein content. Our study pointed out that Raman spectral markers of lipid unsaturation, especially I₁₂₇₀/I₁₃₀₀, are relevant for tracing the cytotoxic effect of ZnO nanoparticles on both cancerous and non-cancerous cells. The change of these spectral markers is correlated to the dose of applied nanoparticles and to the degree of cellular damage. Furthermore, great similarity of spectral features of increasing lipids to spectral features of phosphatidylserine, one of the main apoptotic markers, was recognized in treated cells. Finally, the results strongly indicated that the degree of lipid saturation, presented in the cells, plays an important role in the interaction of cells with nanoparticles.

Exposing intracellular molecular changes during the differentiation of human-induced pluripotent stem cells into erythropoietin-producing cells using Raman spectroscopy and imaging

The objective of this study was to explore intracellular molecular changes during the differentiation of human-induced pluripotent stem cells (iPSCs) into erythropoietin (EPO)-producing cells using Raman spectroscopy and imaging. Raman imaging data of fixed cells at four stages of cell differentiation were analyzed by a partial least squares (PLS) regression model, and the variations in the intracellular molecular compositions with cell differentiation were investigated. As a result, three biomarkers characterizing the cell phases were identified: dimethyl sulfoxide (DMSO), fatty acids with a low grade of unsaturation, and glycoproteins. The uptake of DMSO by EPO-producing cells, which was added into a culture medium as an inducer for cell differentiation, was detected, and the increase in unsaturated fatty acid concentrations was revealed that lipid metabolism changed over the course of cell differentiation. The decrease in the glycoprotein concentration after the cell phase during which iPSCs differentiated into EPO-producing cells was also made clear. Raman imaging successfully visualized chemical images of these three biomarkers in two dimensions, where the biomarker concentrations independently varied during cell differentiation. These results demonstrated the application potential of the proposed method to regenerative medicine for monitoring cell differentiation and discriminating cell maturation in situ at the molecular level.

Rapid identification of flaxseed oil based on portable fiber optic Raman spectroscopy combined with an oil microscopy method

To explore a fast, simple, and accurate method to identify adulteration in flaxseed oil, the Raman spectral data of 130 samples containing flaxseed, canola, cottonseed, and adulterated oils were obtained using a portable fiber optic Raman spectrometer. The Raman spectral results showed that the Raman spectra of the flaxseed and canola oils had noticeable peak shifts, whereas the peak positions of the flaxseed and cottonseed oils were relatively similar. Clear peak intensity differences were observed in the flaxseed, cottonseed, and canola oils, mainly at 868 cm^-1 , 1022 cm^-1 , 1265 cm^-1 , and 1655 cm^-1 , with Raman shift intensities in the following order: I_{flaxseed oil}  > I_{cottonseed oil}  > I_{canola oil} . Similarly, the peak intensity of the flaxseed and adulterated oils also exhibited certain differences (at 868 cm^-1 , 1022 cm^-1 , 1265 cm^-1 , and 1655 cm^-1 ), and the Raman shift intensity tended to decrease gradually with the increasing content of canola and cottonseed oils in the flaxseed oil. Additionally, the results of Raman spectroscopy combined with the "oil microscopy" method exhibited large variations in the radar patterns of the flaxseed, canola, and cottonseed oils, whereas the radar patterns of the flaxseed and adulterated oils closely resembled each other. The results indicated that Raman spectroscopy in combination with oil microscopy more effectively revealed the subtle differences in the Raman shift intensity, serving as a more visual and comprehensive approach for differentiating the quality variations between pure flaxseed oil and other oil species and adulterated oil. PRACTICAL APPLICATION: This study analyzed the Raman spectra of flaxseed, canola, cottonseed, and adulterated oils using fiber optic Raman spectroscopy. Combined with the oil microscopy method for comprehensive evaluation and analysis, it is feasible to effectively identify the quality differences among flaxseed, canola, cottonseed, and adulterated oils.

Raman Microspectroscopy Identifies Biochemical Activation Fingerprints in THP-1- and PBMC-Derived Macrophages

(1) The monocytic leukemia cell line THP-1 and primary monocyte-derived macrophages (MDMs) are popular in vitro model systems to study human innate immunity, wound healing, and tissue regeneration. However, both cell types differ significantly in their origin and response to activation stimuli. (2) Resting THP-1 and MDMs were stimulated with lipopolysaccharide (LPS) and interferon γ (IFNγ) and analyzed by Raman microspectroscopy (RM) before and 48 h after activation. Raman data were subsequently analyzed using principal component analysis. (3) We were able to resolve and analyze the spatial distribution and molecular composition of proteins, nucleic acids, and lipids in resting and activated THP-1 and MDMs. Our findings reveal that proinflammatory activation-induced significant spectral alterations at protein and phospholipid levels in THP-1. In MDMs, we identified that nucleic acid and non-membrane-associated intracellular lipid composition were also affected. (4) Our results show that it is crucial to carefully choose the right cell type for an in vitro model as the nature of the cells itself may impact immune cell polarization or activation results. Moreover, we demonstrated that RM is a sensitive tool for investigating cell-specific responses to activation stimuli and monitoring molecular changes in subcellular structures.

Raman Microscopy Techniques to Study Lipid Droplet Composition in Cancer Cells

Raman spectroscopy using feature selection schemes has considerable advantages over gas chromatography for the analysis of fatty acids' composition changes. Here, we introduce an educational methodology to demonstrate the potential of micro-Raman spectroscopy to determine with high accuracy the unsaturation or saturation degrees and composition changes of the fatty acids found in the lipid droplets of the LNCaP prostate cancer cells that were treated with various fatty acids. The methodology uses highly discriminatory wavenumbers among fatty acids present in the sample selected by using the Support Vector Machine algorithm.

Classification and Identification of Archaea Using Single-Cell Raman Ejection and Artificial Intelligence: Implications for Investigating Uncultivated Microorganisms

Archaea can produce special cellular components such as polyhydroxyalkanoates, carotenoids, rhodopsin, and ether lipids, which have valuable applications in medicine and green energy production. Most of the archaeal species are uncultivated, posing challenges to investigating their biomarker components and biochemical properties. In this study, we applied Raman spectroscopy to examine the biological characteristics of nine archaeal isolates, including halophilic archaea (Haloferax larsenii, Haloarcula argentinensis, Haloferax mediterranei, Halomicrobium mukohataei, Halomicrobium salinus, Halorussus sp., Natrinema gari), thermophilic archaea (Sulfolobus acidocaldarius), and marine group I (MGI) archaea (Nitrosopumilus maritimus). Linear discriminant analysis of the Raman spectra allowed visualization of significant separations among the nine archaeal isolates. Machine-learning classification models based on support vector machine achieved accuracies of 88-100% when classifying the nine archaeal species. The predicted results were validated by DNA sequencing analysis of cells isolated from the mixture by Raman-activated cell sorting. Raman spectra of uncultured archaea (MGII) were also obtained based on Raman spectroscopy and fluorescence in situ hybridization. The results combining multiple Raman-based techniques indicated that MGII may have the ability to produce lipids distinct from other archaeal species. Our study provides a valuable approach for investigating and classifying archaea, especially uncultured species, at the single-cell level.

Lipidome profiling with Raman microspectroscopy identifies macrophage response to surface topographies of implant materials

Biomaterial characteristics such as surface topographies have been shown to modulate macrophage phenotypes. The standard methodologies to measure macrophage response to biomaterials are marker-based and invasive. Raman microspectroscopy (RM) is a marker-independent, noninvasive technology that allows the analysis of living cells without the need for staining or processing. In the present study, we analyzed human monocyte-derived macrophages (MDMs) using RM, revealing that macrophage activation by lipopolysaccharides (LPS), interferons (IFN), or cytokines can be identified by lipid composition, which significantly differs in M0 (resting), M1 (IFN-γ/LPS), M2a (IL-4/IL-13), and M2c (IL-10) MDMs. To identify the impact of a biomaterial on MDM phenotype and polarization, we cultured macrophages on titanium disks with varying surface topographies and analyzed the adherent MDMs with RM. We detected surface topography-induced changes in MDM biochemistry and lipid composition that were not shown by less sensitive standard methods such as cytokine expression or surface antigen analysis. Our data suggest that RM may enable a more precise classification of macrophage activation and biomaterial-macrophage interaction.

Ex Vivo Vibration Spectroscopic Analysis of Colorectal Polyps for the Early Diagnosis of Colorectal Carcinoma

Colorectal cancer is one of the most common and often fatal cancers in humans, but it has the highest chance of a cure if detected at an early precancerous stage. Carcinogenesis in the colon begins as an uncontrolled growth forming polyps. Some of these polyps can finally be converted to colon cancer. Early diagnosis of adenomatous polyps is the main approach for screening and preventing colorectal cancer, and vibration spectroscopy can be used for this purpose. This work is focused on evaluating FTIR and Raman spectroscopy as a tool in the ex vivo analysis of colorectal polyps, which could be important for the early diagnosis of colorectal carcinoma. Multivariate analyses (PCA and LDA) were used to assist the spectroscopic discrimination of normal colon tissue, as well as benign and malignant colon polyps. The spectra demonstrated evident differences in the characteristic bands of the main tissue constituents, i.e., proteins, nucleic acids, lipids, polysaccharides, etc. Suitable models for discriminating the three mentioned diagnostic groups were proposed based on multivariate analyses of the spectroscopic data. LDA classification was especially successful in the case of a combined set of 55 variables from the FTIR, FT Raman and dispersion Raman spectra. This model can be proposed for ex vivo colorectal cancer diagnostics in combination with the colonoscopic extraction of colon polyps for further testing. This pilot study is a precursor for the further evaluation of the diagnostic potential for the simultaneous in vivo application of colonoscopic Raman probes.

Comparative spectroscopic analysis, performance and emissions evaluation of Madhuca longifolia and Jatropha curcas produced biodiesel

In order to fulfil the growing need to replace fossil fuels, investigations exploring the production of biodiesel from agricultural biomass have gained attention. In this study, biodiesels were produced from Madhuca longifolia and Jatropha curcas by means of pre-treatment followed by a two-step acid-base homogeneous catalyst method. These biodiesels were blended with diesel at different percentages. The efficacy of the process was examined using various characterization methods while the efficiency of the produced biodiesels was examined by their engine performance and emission tests. Both Madhuca and Jatropha-based biodiesels exhibited physiochemical properties like that of diesel. Biodiesels were produced by pre-treating with orthophosphoric acid and toluene. The second step involves acid esterification, followed by base transesterification. Raman spectra exhibited C=O stretching at 1725 cm^-1 indicating conversion of Madhuca and Jatropha oil into biodiesel. Fourier transform infrared spectroscopy showed a strong presence of fatty acid profile and triglyceride ester linkage at 1744 cm^-1_. Ultraviolet-visible (UV) spectra confirmed the presence of conjugated dienes in the extracted biodiesels. UV absorbance at 320 nm decreased linearly with blend percentage. ¹H and ¹³C nuclear magnetic resonance (NMR) confirmed the presence of methyl ester moiety at 3.6 δ (ppm) and methoxy carbon at 51.2 δ in biodiesel, distinguishing it from diesel. In the engine performance tests, the variations of brake specific fuel consumption, exhaust gas temperature and brake thermal efficiency versus brake power were studied. The emission tests of different blends were done in terms of carbon monoxide, nitrous oxide and unburnt hydrocarbon. The Jatropha biodiesel exhibited lower mean brake specific fuel consumption, exhaust gas temperature, emitted less carbon monoxide and unburnt hydrocarbon than Madhuca biodiesel. The average decrease in brake thermal efficiency was more in Jatropha biodiesel than Madhuca biodiesel. The present work uses for the first time treatment of ortho phosphoric acid and toluene to produce biodiesel followed by a two-step homogeneous acid-base catalyst method, drastically reducing free fatty acid value.

Lipid profiling using Raman and a modified support vector machine algorithm

Lipid droplets are dynamic organelles that play important cellular roles. They are composed of a phospholipid membrane and a core of triglycerides and sterol esters. Fatty acids have important roles in phospholipid membrane formation, signaling, and synthesis of triglycerides as energy storage. Better non-invasive tools for profiling and measuring cellular lipids are needed. Here we demonstrate the potential of Raman spectroscopy to determine with high accuracy the composition changes of the fatty acids and cholesterol found in the lipid droplets of prostate cancer cells treated with various fatty acids. The methodology uses a modified least squares fitting (LSF) routine that uses highly discriminatory wavenumbers between the fatty acids present in the sample using a support vector machine algorithm. Using this new LSF routine, Raman micro-spectroscopy can become a better non-invasive tool for profiling and measuring fatty acids and cholesterol for cancer biology.

Quantifying Conformational Isomerism in Chain Molecules by Linear Raman Spectroscopy: The Case of Methyl Esters

The conformational preferences of the ester group have the potential to facilitate the large amplitude folding of long alkyl chains in the gas phase. They are monitored by Raman spectroscopy in supersonic jet expansions for the model system methyl butanoate, after establishing a quantitative relationship with quantum-chemical predictions for methyl methanoate. This requires a careful analysis of experimental details, and a simulation of the rovibrational contours for near-symmetric top molecules. The technique is shown to be complementary to microwave spectroscopy in quantifying coexisting conformations. It confirms that a C-O-C(=O)-C-C chain segment can be collapsed into a single all-trans conformation by collisional cooling, whereas alkyl chain isomerism beyond this five-membered chain largely survives the jet expansion. This sets the stage for the investigation of linear alkyl alkanoates in terms of dispersion-induced stretched-chain to hairpin transitions by Raman spectroscopy.

Exploration of Principal Component Analysis: Deriving Principal Component Analysis Visually Using Spectra

Spectroscopy rapidly captures a large amount of data that is not directly interpretable. Principal component analysis is widely used to simplify complex spectral datasets into comprehensible information by identifying recurring patterns in the data with minimal loss of information. The linear algebra underpinning principal component analysis is not well understood by many applied analytical scientists and spectroscopists who use principal component analysis. The meaning of features identified through principal component analysis is often unclear. This manuscript traces the journey of the spectra themselves through the operations behind principal component analysis, with each step illustrated by simulated spectra. Principal component analysis relies solely on the information within the spectra, consequently the mathematical model is dependent on the nature of the data itself. The direct links between model and spectra allow concrete spectroscopic explanation of principal component analysis , such as the scores representing "concentration" or "weights". The principal components (loadings) are by definition hidden, repeated and uncorrelated spectral shapes that linearly combine to generate the observed spectra. They can be visualized as subtraction spectra between extreme differences within the dataset. Each PC is shown to be a successive refinement of the estimated spectra, improving the fit between PC reconstructed data and the original data. Understanding the data-led development of a principal component analysis model shows how to interpret application specific chemical meaning of the principal component analysis loadings and how to analyze scores. A critical benefit of principal component analysis is its simplicity and the succinctness of its description of a dataset, making it powerful and flexible.

Label-free screening of biochemical changes in macrophage-like cells following MoS2 exposure using Raman micro-spectroscopy

The emergence of large scale production techniques for 2D particulate materials has dramatically increased their applications potential. Understanding the interactions of biological cells with such particulate material is therefore of paramount importance, both for toxicological assessment and potential biomedical applications. Conventional in-vitro cytological assays commonly record only a single colorimetric end-point, and do not provide an in-depth analysis of how such materials are uptaken and processed within cells. To demonstrate its potential as an alternative, label free approach, confocal Raman micro-spectroscopy has been used to profile the cellular response of macrophage-like immune cells as a result of exposure to a sub-lethal dose of particulate MoS₂, as an example novel 2D material. Particles were seen to be uptaken and trafficked in sub-cellular vesicles, and this sensitive technique allows differences in the biochemical composition of the vesicles to be assessed and monitored as a function of time. Untreated macrophage-like cells contain lipidic vesicles which are found to be relatively rich in the membrane lipid sphingomyelin, key to the process of cell membrane regeneration. After exposure to MoS₂, the particulate material is seen to be invaginated in similar vesicles, the most prominent of which now, however, have spectroscopic signatures which are dominated by those of phosphatidyl family lipids, consistent with the phagocytotic pathway. The lipidic content of cells is seen to increase at all time-points (4, 24 and 72 h). although vesicles composed of sphingomyelin become more prominent again following a prolonged incubation of 72 h to a sub-lethal dose of MoS₂, as the immune cell has processed the particulate material and initiates recovery to a normal/untreated state. This study reveals Raman micro-spectroscopy is an effective method for monitoring cellular responses and evolution of organelle compositions in response to MoS₂ exposure. The additional benefit of using this technique is that cells can be monitored as a function of time, while it can also be used for screening other micro/nano materials for toxicology and/or establishing cell responses.

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.

Microstructure and molecular vibration of mannosylerythritol lipids from Pseudozyma yeast strains

This work highlights microstructure and molecular vibration of mannosylerythritol lipids (MELs) from Pseudozyma aphidis B1 and Pseudozyma hubeiensis TS18 strains collected from brown algae and mangrove sediments. The scanning electron microscopy (SEM) shows the elongated structures with polar budding in the cells of B1 and TS18 yeast strains. The high-resolution transmission electron microscopy (HRTEM) identifies large lipid bodies that contain MELs confirmed by the anthrone test and thin layer chromatography. The HRTEM also reveals unknown electron dense inclusions. The surface-enhanced Raman scattering (SERS) was used to analysis molecular vibrations of cells, MEL mixtures, and purified MELs (A, B, and C) extracted from the B1 and TS18 cells. The peak analysis of Raman spectra suggests a higher level of saturation per fatty acid chain in MEL-B in both B1 and TS18 cells. This work demonstrates that the out-of-plane bending vibrations of the CH bonds in the range of 840-940 cm^-1 can serve an efficient indicator for detecting MEL-A, -B, and -C.

Raman spectroscopy: A rapid method to assess the effects of pasture feeding on the nutritional quality of butter

The animal diet is a critical variable affecting the composition and functionality of dairy products. As "Grass-Fed" labeling becomes more prominent on the market, rapid and label-free methods for verification of feeding systems are required. This work proposes the use of Raman spectroscopy to study the effects of 3 different experimental cow feeding systems-perennial ryegrass pasture, perennial ryegrass with white clover pasture, and an indoor total mixed ration diet (TMR)-on the nutritional quality of sweet cream butter. The results demonstrate that Raman spectroscopy coupled with multivariate analysis is a promising approach to distinguish butter derived from pasture or conventional TMR feeding systems. A Pearson correlation analysis confirmed high positive correlations between the spectral bin at 1,657 cm^-1, ascribed to the stretching vibrations of C=C bonds, and concentrations of α-linolenic acid and conjugated linolenic acid (CLA) in butter, and in general with the concentration of n-3 and n-3+CLA fatty acids and polyunsaturated fatty acids in the samples. The yellow color indicative of the presence of carotenoids in butter, which has previously been suggested as a biomarker of pasture or "Grass-Fed" feeding, was also positively correlated with the data obtained from the Raman spectra. Raman spectroscopy could also be used to accurately predict indicators of the nutritional quality of butter, such as the thrombogenic index, which showed a strong negative correlation with the spectral bin at 3,023 cm^-1.

Investigation of the Applicability of Raman Spectroscopy as Online Process Control during Consumer Milk Production

Online detection of product defects using fast spectroscopic measurements is beneficial for producers in the dairy industry since it allows readjustment of product characteristics or redirection of product streams during production. Raman spectroscopy has great potential for such application due to the fast and simple measurement. Its suitability as online sensor for process control was investigated at typical control points in consumer milk production being raw milk storage, standardization, and heat treatment. Additionally, the appropriateness of Raman spectroscopy to act as indicator for product application parameters was investigated using the example of barista foam. To assess the suitability of a pure online system, the merit of Raman spectra was evaluated by a principal component analysis (PCA). Thereby, proteolytic spoilage due to the presence of extracellular enzymes of Pseudomonas sp. was detected and samples based on the applied heat treatment (extended shelf life (ESL) and ultra-high temperature (UHT)) could be separated. A correlation of the content of free fatty acids and foam stability with spectra of the respective milk samples was found, allowing a prediction of the technofunctional quality criterion “Barista” suitability of a UHT milk. The results underlined the suitability of Raman spectroscopy for the detection of deviations from a defined product standard of consumer milk.

Chemical characterization of mountain forest soils: impact of long-term atmospheric deposition loadings (Czech-Polish-German border region)

The composition of lipids in soil offers clues to soil degradation processes due their persistency and selectivity in soil, and close relation to long-term processes in the ecosystem, thanks to their role in cell membranes of organisms. Organic solvent-extractable compounds were recovered from soils collected at two sites differing in the degree of forest damage. Gas chromatography/mass spectroscopy and Fourier transform infrared spectroscopy were applied in order to characterize solvent-extractable lipids. Raman spectroscopy was also applied as it provides distinct advantages for determining the structural order of carbonaceous materials. The organic matter measurement techniques were combined with an established simultaneous multi-element measurement technique. Variations in individual soil horizons from the sites were reflected in the crystallinity of epicuticular waxes, presence of long-chain aliphatic hydrocarbons, concentrations of n-alkanes, saturated and unsaturated fatty acids, dicarboxylic acids, and in the content of aromatic structures, hydroxyl, ester, and carboxylic acid groups. The results are explained by differently transformed organic matter. The concentrations of elements in the soils were also affected by atmospheric depositions, including higher accumulations of arsenic and antimony, and lower contents of natural nutrients. These data have potential to be used as sensitive biogenic indicators of ecosystem damage by long-term atmospheric depositions.

Confined synthesis of carbon dots with tunable long-wavelength emission in a 2-dimensional layered double hydroxide matrix

Fluorescent carbon dots (CDs) have drawn significant attention due to their variable species and intriguing optical properties; however, spectrally tuning the fluorescence color of CDs, especially in a long-wavelength region, is still a challenge. In this study, CDs were synthesized through the hydrothermal reaction of 2,5-diaminobenzenesulfonate (DBS) and dodecyl sulfate (DS) in the confined interlayer space of layered double hydroxides (LDHs). Particularly, the emission color of the obtained CD/LDH phosphors could be spectrally tuned from greenish-yellow (λ_em = 537 nm) to red (λ_em = 597 nm) by simply changing the molar ratio of the intercalated DBS and DS. Through the detailed characterization of different interlayer CDs by Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, elemental analysis, and X-ray photoelectron spectroscopy (XPS), a new route of modulating the absorption and emission wavelengths of CDs by regulating the content of graphitic nitrogen during heteroatom doping is presented. In addition, the stabilities of the solid-state luminescence against UV bleaching and temperature variation were improved by the rigid 2-dimensional (2D) LDH matrix, and prospective applications of the proposed CD/LDH phosphors were demonstrated in multicolour displays and in the fabrication of white light-emitting diodes (WLEDs).

Characterization of desi ghee obtained from different extraction methods using Raman spectroscopy

In this study, the potential of Raman spectroscopy has been utilized to characterize the methods direct cream (DC), milk butter (MB) and milk skin (MS) used for the extraction of desi ghee from buffalo and cow milk. Raman spectra from six types of ghee samples extracted by above methods were acquired using two laser wavelengths of 532 and 785 nm. The Raman spectra of cow ghee revealed that it contains three bands of beta-carotene at 1005, 1156 and 1520 cm^-1 which differentiated it from buffalo ghee. To highlight small spectral differences, statistical analysis through principal component analysis (PCA) has been performed on the Raman spectra of ghee samples to reach subsequent conclusion. Based on the variations in molecular composition of cow ghee samples, it has been found that DC method retain relatively higher concentration of beta-carotene and MB method contain higher concentration of conjugated linoleic acid (CLA) and fatty acids than MS method. Similarly, DC & MS methods were found best for retaining relatively higher concentration of CLA and fatty acids in buffalo ghee as compared to MB method which retains relatively higher concentration of fatty acids.

Preliminary investigation into the use of Raman spectroscopy for the verification of Australian grass and grain fed beef

Australian grass and grain-fed beef products attract premium prices at sale and several beef processors market beef underwritten by production system claims. This preliminary investigation assessed the feasibility of using Raman spectroscopy to detect differences in the chemical composition of subcutaneous fat from cattle raised in extensive and intensive production systems. Raman spectra, fatty acid composition, β-carotene composition and objective colour measurements were measured on 150 grass and 150 grain-fed cattle. Spectral differences at peaks including 1069 cm^-1, 1127 cm^-1, 1301 cm^-1 and 1445 cm^-1 suggest that Raman spectra is able to detect differences in saturated fatty acids, which were significantly higher in carcases from grain-fed cattle. Differences in spectra at 1658 cm^-1 were observed, however further research is required to investigate the cause of this spectral feature. Overall, this study indicated that Raman spectroscopy is a potential tool for the authentication of beef carcases from grass and grain-fed production systems.

Rapid Identification of Rainbow Trout Adulteration in Atlantic Salmon by Raman Spectroscopy Combined with Machine Learning

This study intends to evaluate the utilization potential of the combined Raman spectroscopy and machine learning approach to quickly identify the rainbow trout adulteration in Atlantic salmon. The adulterated samples contained various concentrations (0-100% w/w at 10% intervals) of rainbow trout mixed into Atlantic salmon. Spectral preprocessing methods, such as first derivative, second derivative, multiple scattering correction (MSC), and standard normal variate, were employed. Unsupervised algorithms, such as recursive feature elimination, genetic algorithm (GA), and simulated annealing, and supervised K-means clustering (KM) algorithm were used for selecting important spectral bands to reduce the spectral complexity and improve the model stability. Finally, the performances of various machine learning models, including linear regression, nonlinear regression, regression tree, and rule-based models, were verified and compared. The results denoted that the developed GA-KM-Cubist machine learning model achieved satisfactory results based on MSC preprocessing. The determination coefficient (R2) and root mean square error of prediction sets (RMSEP) in the test sets were 0.87 and 10.93, respectively. These results indicate that Raman spectroscopy can be used as an effective Atlantic salmon adulteration identification method; further, the developed model can be used for quantitatively analyzing the rainbow trout adulteration in Atlantic salmon.

Visualizing wax ester fermentation in single Euglena gracilis cells by Raman microspectroscopy and multivariate curve resolution analysis

BACKGROUND

Global demand for energy is on the rise at a time when limited natural resources are fast depleting. To address this issue, microalgal biofuels are being recommended as a renewable and eco-friendly substitute for fossil fuels. Euglena gracilis is one such candidate that has received special interest due to their ability to synthesize wax esters that serve as precursors for production of drop-in jet fuel. However, to realize economic viability and achieve industrial-scale production, development of novel methods to characterize algal cells, evaluate its culture conditions, and construct appropriate genetically modified strains is necessary. Here, we report a Raman microspectroscopy-based method to visualize important metabolites such as paramylon and ester during wax ester fermentation in single Euglena gracilis cells in a label-free manner.

RESULTS

We measured Raman spectra to obtain intracellular biomolecular information in Euglena under anaerobic condition. First, by univariate approach, we identified Raman markers corresponding to paramylon/esters and constructed their time-lapse chemical images. However, univariate analysis is severely limited in its ability to obtain detailed information as several molecules can contribute to a Raman band. Therefore, we further employed multivariate curve resolution analysis to obtain chain length-specific information and their abundance images of the produced esters. Accumulated esters in Euglena were particularly identified to be myristyl myristate (C28), a wax ester candidate suitable to prepare drop-in jet fuel. Interestingly, we found accumulation of two different forms of myristyl myristate for the first time in Euglena through our exploratory multivariate analysis.

CONCLUSIONS

We succeeded in visualizing molecular-specific information in Euglena during wax ester fermentation by Raman microspectroscopy. It is obvious from our results that simple univariate approach is insufficient and that multivariate curve resolution analysis is crucial to extract hidden information from Raman spectra. Even though we have not measured any mutants in this study, our approach is directly applicable to other systems and is expected to deepen the knowledge on lipid metabolism in microalgae, which eventually leads to new strategies that will help to enhance biofuel production efficiency in the future.

On the Molecular Interactions in Lipid Bilayer-Water Assemblies of Different Curvatures

This work concerns the importance of intermolecular interactions present in aqueous lipid assembly systems depending on the type of aggregates they form. We have studied aqueous mixtures of diglycerol monooleate, Capmul glycerol monoleate (GMO-50) and polyoxyethylene (20) sorbitan monooleate (Polysorbate 80, P80) using small-angle X-ray scattering (SAXS) measurements to reveal the structure of liquid crystalline phases. On the basis of the SAXS data, a phase diagram was constructed. We discuss the effect of curvature changes of the lipid-aqueous interface obtained by changing the water content and the temperature. The results are related to the intermolecular interactions, as revealed by Raman spectroscopy, with a focus on the bilayer type of system of different curvature and bilayer flexibility, namely, the lamellar phase, bicontinuous cubic phase, and sponge phase. All phases show large similarities in their chain conformation and head group interactions as revealed by the Raman spectra, arising from the fact that all three structures are formed by lipid bilayers. However, subtle differences in the molecular organization of the sponge phase were revealed by employing Raman difference spectroscopy and by analysis of key spectroscopic indicators, which show a less dense hydrocarbon chain packing compared to the inverse bicontinuous cubic or lamellar phase.

Oculohypotensive effects of various acetozolamide nanopreparations for topical treatment of animal model-induced glaucoma and their impact on optic nerve

Acetozolamide-ACZ, carbonic anhydrase inhibitor- is still the most effective systemic drug for glaucoma treatment. Due to its limited ocular bioavailability, topical formulations are not available yet. This study introduces within the framework of nanotechnology three nanopreparations of acetozolamide for topical application, one of them is liposomal phospholipid vehicle and the other two preparations are propolis and Punica granatum (pomegranate). The hypotensive effect of these different nanopreparations in lowering the increased intraocular pressure that was induced in experimental rabbits is monitored for 130 hrs. Structural characteristics of the optic nerve dissected from all involved groups were studied by Fourier transfrom infrared spectroscopy. The obtained results indicate the impact of the topically applied acetozolamide nanopreparations in lowering the intraocular pressure to its normotensive control value. On the other hand, the optic nerve characteristics were found to be dependent on the way acetozolamide introduced. Glaucoma affects structural components that contain OH group and increases β-turns of the protein secondary structure while, reducing the content of both α-helix and Turns. In the same context, liposomal-acetozolamide and propolis nanopreparations protecting the optic nerve protein secondary structure from these changes associated with glaucoma.

Chemical Property Changes and Thermal Analysis during the Carbonizing Process of the Pollen Grains of Typha

Carbonized pollen grains of Typha (CPT) were widely used in clinical for antithrombosis, wound and bleeding in China. In order to ensure the role of drugs, it is very important to control the quality of drugs. However, there is a lack of monitoring methods in the process of charcoal preparation. To characterize the process of CPT, we used thermal analysis, scanning electron microscope (SEM), color measurement, Fourier transform infrared spectrometry (FTIR) and HPLC. In this study, 7 min was the optimal processing time and the heating process condition should be controlled under 272.35 ± 7.23 °C. This comprehensive strategy to depict the whole carbonizing process would provide new ideas for researches on quality control of Traditional Chinese Medicine (TCM) and processing theory of charcoal medicine.

Ratiometric analysis using Raman spectroscopy as a powerful predictor of structural properties of fatty acids

Raman spectroscopy has been used extensively for the analysis of biological samples in vitro, ex vivo and in vivo. While important progress has been made towards using this analytical technique in clinical applications, there is a limit to how much chemically specific information can be extracted from a spectrum of a biological sample, which consists of multiple overlapping peaks from a large number of species in any particular sample. In an attempt to elucidate more specific information regarding individual biochemical species, as opposed to very broad assignments by species class, we propose a bottom-up approach beginning with a detailed analysis of pure biochemical components. Here, we demonstrate a simple ratiometric approach applied to fatty acids, a subsection of the lipid class, to allow the key structural features, in particular degree of saturation and chain length, to be predicted. This is proposed as a starting point for allowing more chemically and species-specific information to be elucidated from the highly multiplexed spectrum of multiple overlapping signals found in a real biological sample. The power of simple ratiometric analysis is also demonstrated by comparing the prediction of degree of unsaturation in food oil samples using ratiometric and multivariate analysis techniques which could be used for food oil authentication.

Detection of Saturated Fatty Acids Associated with a Self-Healing Synthetic Biological Membrane Using Fiber-Enhanced Surface Enhanced Raman Scattering

The Synthetic Biological Membrane (SBM) project at NASA Ames developed a portable, self-repairing wastewater purification system. The self-repair process relies upon secreted fatty acids from a genetically engineered organism. However, solubilized fatty acids are difficult to detect using conventional methods. Surface-enhanced Raman scattering (SERS) was used to successfully detect solubilized fatty acids with the following limits of detection: 10^-9, 10^-8, 10^-9, and 10^-6 M for decanoic acid, myristic acid, palmitic acid, and stearic acid, respectively. Additionally, hollow core photonic crystal fiber (HCPCF) was applied as the sampling device together with SERS to develop in situ surveillance of the production of fatty acids. Using SERS + HCPCF yielded an 18-fold enhancement in SERS signal for the CH₂ twist peak at 1295 cm^-1 as compared to SERS alone. The results will help the SBM project to integrate a self-healing wastewater purification membrane into future water recycling systems.

Detection of olive oil adulteration with waste cooking oil via Raman spectroscopy combined with iPLS and SiPLS

Olive oil adulteration with waste cooking oil was detected and quantified by combining optical Raman scattering spectroscopy and chemometrics. Spectra of 96 olive oil samples with waste cooking oil (2.5%, 5%, 10%, 20%, 30% and 50%) were collected by the portable Raman spectroscopy system. iPLS and SiPLS quantitative analysis models were established. The results revealed that spectral data after SNV processing are the best for synergy interval partial least square (SiPLS) modeling and forecast. The root mean squared error of calibration (RMSEC) is 0.0503 and the root mean squared error of validation (RMSEV) is 0.0485. The lower limit of application (LLA) of the proposed method is c[WCO]=0.5%. According to linear regression calculation, the theoretical limit of detection (LOD) of the proposed method is about c[WCO]=0.475%. The established model could make effective quantitative analysis on adulteration of waste cooking oil. It provides a quick accurate method for adulteration detection of waste cooking oil in olive oil.

Development of a classification model for non-alcoholic steatohepatitis (NASH) using confocal Raman micro-spectroscopy

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder in developed countries [1]. A subset of individuals with NAFLD progress to non-alcoholic steatohepatitis (NASH), an advanced form of NAFLD which predisposes individuals to cirrhosis, liver failure and hepatocellular carcinoma. The current gold standard for NASH diagnosis and staging is based on histological evaluation, which is largely semi-quantitative and subjective. To address the need for an automated and objective approach to NASH detection, we combined Raman micro-spectroscopy and machine learning techniques to develop a classification model based on a well-established NASH mouse model, using spectrum pre-processing, biochemical component analysis (BCA) and logistic regression. By employing a selected pool of biochemical components, we identified biochemical changes specific to NASH and show that the classification model is capable of accurately detecting NASH (AUC=0.85-0.87) in mice. The unique biochemical fingerprint generated in this study may serve as a useful criterion to be leveraged for further validation in clinical samples.

Continuous gradient temperature Raman spectroscopy from -100 to 40°C yields new molecular models of arachidonic acid and 2-Arachidonoyl-1-stearoyl-sn-glycero-3-phosphocholine

Despite its biochemical importance, a complete Raman analysis of arachidonic acid (AA, 20:4n-6) has never been reported. Gradient temperature Raman spectroscopy (GTRS) applies the temperature gradients utilized in differential scanning calorimetry (DSC) to Raman spectroscopy, providing a straightforward technique to identify molecular rearrangements that occur near and at phase transitions. Herein we utilize the GTRS technique for AA and 1-18:0, 2-20:4n-6 phosphatidyl choline (AAPC) from cryogenic to mammalian body temperatures. 20Mb three-dimensional data arrays with 0.2°C increments and first/second derivatives allowed complete assignment of solid, liquid and transition state vibrational modes. The AA DSC shows a large exothermic peak at -60°C indicating crystallization or a similar major structural change. No exothermic peak of this magnitude was observed in six other unsaturated lipids (DHA, n-3DPA, n-6DPA, LA, ALA, OA). Melting in AA occurs over a large range: (-60 to -35°C): very large frequency offsets and intensity changes correlate with premelting initiating circa -60°C, followed by melting (-37°C). Novel, unique 3D structures for both molecules reveal that AA is not symmetric as a free fatty acid, and it changes significantly when in the sn-2 phospholipid position. Further, different CH and CH₂ sites are unequally elastic and nonequivalent.