Fourier Transform Infrared Fingerprint Research Articles

Identification of Orthosiphon stamineus from different phytogeographical zones in Indonesia by FTIR-fingerprinting and chemometrics

Orthosiphon stamineus (OS) or cat’s whiskers (Lamiaceae) is one of the herbs broadly used as raw materials for functional food and traditional remedies, for it contains phenolic acids and flavonoids. OS grows well in tropical and subtropical regions of Asia and Africa. Phytogeographical characteristics are among many variables that greatly control plant growth and phytochemical content. This research was conducted to analyze and classify 14 samples of OS leaves from different regions in Indonesia according to phytogeographic profiles using a combination of Fourier-transform infrared (FTIR) fingerprinting and chemometrics, i.e., principal component analysis (PCA) and cluster analysis (CA). The first two PCs were used to show the grouping of 14 samples with a cumulative variance at 91%. Results showed that all samples had comparable FTIR spectra showing the stretching frequencies of O-H, C-H, and C=C bonds. Further discrimination with PCA and CA was able to classify them into four groups of different phytogeographical origins: group 1 comprised OS samples from Tawangmangu, Mojokerto, Batu, Sampang, Madiun, South Jakarta, Jombang, Surabaya, Kediri, and Ngawi, group 2 from Lampung and Gresik, group 3 from Badung, and group 4 from Kotabaru. Thus, it can be inferred that FTIR fingerprinting combined with chemometrics can distinguish between OS crude drugs from different locations. Introducing a wider variety of OS analytical methods is believed to positively influence the flexibility and ease of quality control of herbal ingredients, ultimately ensuring the safety and efficacy of herbal medicinal products.

Fourier transform infrared (FTIR) spectroscopy approach combined with discriminant analysis and prediction model for crude palm oil authentication of different geographical and temporal origins

The traceability of palm oil to determine its geographical origins within the palm oil supply chains is of importance to ensure quality and sustainable production. The current traceability systems are insufficient, thus requiring a more viable and effective approach to improve the traceability framework of the palm oil supply chain. In this study, the feasibility of Fourier transform infrared (FTIR) and chemometric methods for the traceability of crude palm oil (CPO) samples in Malaysia was investigated. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was used to examine the FTIR spectral data of 354 CPO samples collected from four different mills in Malaysia from February until July 2019. The optimal OPLS-DA models were achieved with standard normal variate (SNV) preprocessing and Pareto (Par) scaling to discriminate the CPO according to its geographical provenance and time of sampling. OPLS-DA models using CPO fingerprints successfully discriminated CPO samples according to their geographical origin and production month, with a total accuracy of correct classification for the blind samples (test set) in the prediction models greater than 90% and with the area under the receiver operating characteristic (ROC) curve values exceeding 0.9. The OPLS-DA loading plot indicated that spectral regions associated with free fatty acid (FFA), iodine value (IV) as well as the saturated and unsaturated fatty acid content were responsible for the discrimination patterns and can be potentially used as spectral markers to differentiate CPO samples. Overall, the study shows that combination of FTIR fingerprinting and chemometric methods could serve as an effective tool to trace and discriminating CPO samples according to their geographical origins and production times. The approaches used in the study present an innovative strategy for monitoring quality of palm oil, and moving forward will also facilitate efforts at successful tracking of palm oil across supply chains, especially when combined with additional analytical techniques.

Comparison of FTIR fingerprint, phenolic content, antioxidant and anti-glucosidase activities among Phaseolus vulgaris L., Arachis hypogaea L. and Plukenetia volubilis L.

BackgroundInhibition of starch-hydrolysing enzymes is one of the major methods to reduce the risk of type−2 diabetes mellitus. Nowadays, there are no reports involving oil-rich and oil-low seeds of different botanical origins. The current study intended to extract Phaseolus vulgaris L. and Arachis hypogaea L. including Plukenetia volubilis L. using ethanol and water solvents, and to analyse Fourier-transform infrared (FTIR) fingerprint, total phenolic content, antioxidant and anti-glucosidase activities of the extracts by principal component analysis (PCA) and cluster analysis. ResultsThe result showed that the ethanol extracts of P. vulgaris L., A. hypogaea L., and P. volubilis L. showed total phenolic content higher than those of the aqueous extracts. The result also demonstrated that the aqueous and ethanol extracts from P. volubilis L. seed showed the highest antioxidant and anti-glucosidase activities, respectively. In comparison with the efficacy of the aqueous extracts of beans, A. hypogaea L. showed the highest antioxidant activity and anti-glucosidase activity. For the ethanol extract of beans, P. vulgaris L. (red kidney bean) showed the highest antioxidant activity, while P. vulgaris L. (white kidney beans) showed the highest anti-glucosidase activity. Moreover, significantly positive correlations between total phenolic content and anti-glucosidase activity (r = 0.41, P-value = 0.018), and between total phenolic content and FTIR data (r = 0.66, P-value = 0.000) were found. ConclusionsFTIR of the extracts showed functional groups corresponding with phenolic compounds. Moreover, the PCA and cluster analysis from FTIR data, phenolic content and biological activity could separate solvent types used for extraction.How to cite: Thummajitsakul S, Piyaphan P, Khamthong S, et al. Comparison of FTIR fingerprint, phenolic content, antioxidant and anti-glucosidase activities among Phaseolus vulgaris L., Arachis hypogaea L. and Plukenetia volubilis L. Electron J Biotechnol 2023;61. https://doi.org/10.1016/j.ejbt.2022.10.003.

Evaluating quality consistency of cigarette by 3 kinds of quantum fingerprints

Cigarette has a history of more than 40 years and once sold well all over the country. The purpose of this paper is to evaluate the quality consistency of 30 batches of cigarettes. Differential scanning calorimetry (DSC) curves, Fourier Transform Infrared (FT-IR) spectra and terahertz time-domain spectra of 30 batches of cigarettes were collected. In this paper, a new quality evaluation method was explored, the obtained fingerprints were quantized, the t-test was used to analyze the correlation between the original fingerprint and the quantum fingerprint. The quantized fingerprints were evaluated by the systematically quantitative fingerprint method (SQFM), the macro qualitative similarity and the macro quantitative similarity were used to reflect the internal differences of the samples. Finally, the antioxidant activities of 30 batches of samples were investigated, and the correlation between quantum fingerprints and IC50 values were analyzed by Pearson correlation coefficient (r).The result shows that there was no significant difference between the quantum fingerprint and the original fingerprint; SQFM can effectively calculate the similarity of sample curves and classify samples into different grades; the FT-IR fingerprints had a good correlation with the IC50 value. 30 samples performed a good quality consistency within an acceptable grades range. In addition, quantum fingerprints have broad application prospects in spectral analysis.

Fourier-transform infrared (FTIR) fingerprinting for quality assessment of protein hydrolysates

Enzymatic protein hydrolysis can be used industrially for refining peptides from poultry by-products. The aim is to introduce these peptides for human consumption, but today the majority is used for feed or pet food. One main barrier for entering the human market is unknown and unstable peptide product qualities. Reliable analytical methods for characterising the peptide fraction is therefore vital for optimizing and controlling the product quality.In this work, we investigate the potential of using a large database of dry-film Fourier-transform Infrared (FTIR) fingerprints to gain new insight in quality variations of peptide products. The database cover >1300 samples from laboratory experiments performed over several years. We found that the FTIR fingerprints contain patterns that are stable across experiments and time, and that variations in the fingerprint can be related to raw material composition and processing factors.We also show that the database can be used for evaluating industrial samples. By comparing the FTIR fingerprints of industrial samples with those in the database, we could see systematic changes in product quality over time and make hypotheses about the underlying causes for change. These results lay the foundation for using dry-film FTIR spectroscopy as an industrial tool for product and process optimisation and control.

FTIR fingerprints discriminate ionic liquids’ antibacterial activity

Ionic liquids (ILs) are those organic salts which exist in liquid form below 100 ​°C. ILs have drawn attention of scientific community due to their increased industrial applications in variety of sectors. In the present study Fourier transform infrared (FTIR) spectroscopy has been utilized to discriminate the antibacterial activities of ILs having different cations and anions against various microorganisms found in the environment. Imidazolium, Pyridinium, Quaternary ammonium and Tetraalkylphosphonium were used as cations in the study whereas, Bromide, Methane sulphonate, Bis(trifluoromethanesulfonyl)imide, Dichloroacetate, Tetrafluoroborate and Hydrogen sulphate were used as anionic parts. High and low ILs relative to antibacterial activity is obtained through m-clust clustering. Mostly ILs formed with Octyl methyl imidazolium (OMIm) and butyl methyl imidazolium (BMIm) show high antibacterial activity against the considered microbes. Spectral base line is corrected through modified polynomial fitting (MPF) with smoothing parameter λ ​= ​1. For discrimination of ILs i.e. high and low antibacterial groups through FTIR spectral data sparse partial least squares discriminant analysis (sPLS-LDA) and jackknife partial least squares logistic regression (jPLS-LR) are used. Spectral wavenumbers selection and model parameters are optimized by maximizing the crossvalidation accuracy. Based on 100 Monte Carlo simulation runs, sPLS-LDA best discriminate ILs groups with 90% validated accuracy. Influential wavelength extracted by sPLS-LDA are used to identify the influential functional compounds i.e. C–Br, C = N, C = CH2, C = CH, C–O and O–H, which discriminate the ILs groups. The results indicated that FTIR fingerprints could be used as a rapid method to discriminate antibacterial activities of ionic liquids.

Fourier-transform infrared spectroscopy for monitoring proteolytic reactions using dry-films treated with trifluoroacetic acid

In this study we explore the potential of using Fourier-transform infrared (FTIR) spectra of trifluoroacetate-protein and peptide complexes for monitoring proteolytic reactions. The idea of treating dry-films of protein hydrolysates with trifluoroacetic acid (TFA) prior to FTIR analysis is based on the unique properties of TFA. By adding a large excess of TFA to protein hydrolysate samples, the possible protonation sites of the proteins and peptides will be saturated. In addition, TFA has a low boiling point when protonated as well as complex-forming abilities. When forming TFA-treated dry-films of protein hydrolysates, the excess TFA will evaporate and the deprotonated acid (CF3COO−) will interact as a counter ion with the positive charges on the sample materials. In the study, spectral changes in TFA-treated dry-films of protein hydrolysates from a pure protein and poultry by-products, were compared to the FTIR fingerprints of untreated dry-films. The results show that time-dependent information related to proteolytic reactions and, consequently, on the characteristics of the protein hydrolysates can be obtained. With additional developments, FTIR on dry-films treated with TFA may be regarded as a potential future tool for the analysis of all types of proteolytic reactions in the laboratory as well as in industry.

Characterization of α-glucosidase inhibitory activity of Tetracera scandens leaves by Fourier transform infrared spectroscopy-based metabolomics

Tetracera scandens is a medicinal shrub that belongs to Dilleniaceae. The leaves of the plant have been traditionally used in the treatment of diabetes mellitus in Malaysia. The conventional quality control analysis of medicinal plants that relies on the quantification of few major metabolites is considered time-consuming since it requires extensive sample preparation and neglects the possible impacts that the minor metabolites could have on the activity. This study was aimed to investigate the α-glucosidase inhibitory (AGI) potential of different hydromethanolic extracts of T. scandens leaves and to establish a predictive multivariate model that could be used for the quality evaluation of T. scandens leaf based on the Fourier transform infrared (FT-IR) spectra of its extracts. Different solvent ratios (0%, 20%, 40%, 60%, 80% and 100% methanol in water) were used to prepare a total of 36 extracts. The AGI potential and the FT-IR fingerprint spectrum were acquired for each extract. A four components orthogonal partial least squares (OPLS) model (1 + 3 + 0) with R2Y of 0.951 and Q2Y of 0.916 was established to describe the correlation between the fingerprint FT-IR spectra of different T. scandens extracts and their corresponding AGI activities. The carbon-halide, carbon–oxygen single bonds, as well as the hydroxyl and carbonyl groups were identified to be positively correlated with the AGI activity. To sum up, an OPLS model was successfully developed as a rapid quality evaluation method to predict the AGI activity of T. scandens.

Average molecular weight, degree of hydrolysis and dry-film FTIR fingerprint of milk protein hydrolysates: Intercorrelation and application in process monitoring

Fourier-transform infrared (FTIR) spectroscopy was applied to predict the degree of hydrolysis (DH%) and weight-average molecular weight (Mw) in milk protein hydrolysates. Both DH% and Mw are important quality parameters of protein hydrolysates. Measuring these parameters and following their development during proteolytic reactions is therefore essential for process control and optimization in industry. In the present study the intercorrelation and the complimentary nature of these parameters were investigated and a partial least squares regression (PLSR) model was developed for the prediction of DH% from molecular weight distributions. Finally, we developed PLSR models based on dry-film FTIR spectroscopy for the prediction of both DH% and Mw. Here spectral changes in the amide region were found to be important for the two calibration models, underlining the advantage of dry-film FTIR measurement. This shows that dry-film infrared spectroscopy is a promising tool for dual prediction of DH% and Mw.

Application of FTIR fingerprints coupled with chemometric for comparison of stingless bee propolis from different extraction methods

Propolis is a mixture of resin collected by the bees to build their hive. These mixtures contain natural remedy and used to treat variety of health-related problems. Unlike honeybee propolis, the study of stingless bee propolis still lacking. The important part of propolis study is the optimization of extraction procedures. The aim for this study is to employ chemometrics on FTIR data in order to discriminate the chemical fingerprinting of Malaysian stingless bee, Heterotrigona itama propolis yielded from different extraction methods, which were maceration, sonication and soxhlet. The chemical fingerprinting was obtained through Fourier Transform Infrared (FTIR). Principle component analysis (PCA) and hierarchical cluster analysis (HCA) were applied as pattern recognition methods for FTIR spectra. PCA of FTIR data for different extraction methods of stingless bee’s propolis revealed that variability of PC1 and PC2 is 84.76%. PCA’s variation in propolis by different extraction methods was classified based on specific functional groups arisen from the peaks. The FTIR fingerprinting of HCA of stingless bee’s propolis were distributed into three clusters based on percentages of ethanol, intensity of peaks and different fingerprint region. FTIR coupled with chemometric analysis showed classification of different extraction methods of propolis from PCA and HCA based on vibration of functional groups presence in the samples. Taken together, these results showed that different extraction methods play important role in detaining of chemical in propolis of stingless bee.

Comparative in vitro and in silico characterization of anticancer compounds piceatannol, biochanin-A and resveratrol on breast cancer cells

Background: Biochanin-A and Piceatannol are phytochemical constituents extracted from Sophora interrupta. Although both the compounds were isolated from a single plant, these compounds were not compared against anticancer activity. Objective: A systematic comparative analysis of biochanin-A, piceatannol, and resveratrol was performed to investigate cancer cell viability, motility, metabolic changes in Michigan Cancer Foundation-7 breast cancer cells, and structure compound interaction with the vascular endothelial growth factor (VEGF) receptors were studied. Materials and Methods: Cancer cell viability was studied using 3 (4, 5 dimethyl thiazol 2yl) 2, 5 diphenyltetrazo- lium bromide and acridine orange (AO)/ethidium bromide (EtBr) assay. The wound-healing assay was performed by measuring cell migration from the scratch area. Metabolic changes of the compounds in culture conditions were recorded using Fourier-transform infrared (FT-IR) spectroscopy. Molecular docking and dynamic simulations were performed using Schrodinger software. Results: Our results showed that the half-maximal growth inhibitory concentration for biochanin-A is 150 μM/ml and piceatannol and resveratrol showed 150 μM/ml, which is evident from the uptake of AO and EtBr dyes by live/dead cells. Moreover, drug-treated cells were unable to fill the cleared area from the scratch area, which suggests that all compounds effectively inhibit cell motility. FT-IR fingerprint showed a marked difference in the percentage of transition and dynamic structural changes between untreated and treated samples. Strong hydrogen-bond interaction with VEGF receptor-1 (VEGFR1) and VEGFR2 proteins and their interactions were stable throughout the simulation period. Moreover, these compounds inhibited sprouting of a new blood vessel from the chicken aorta and microvessels formation in the in ovo chorioallantoic membrane assay. Conclusion: Taken together, we conclude that anticancer and anti-angiogenic activity, structure-function relationship of biochanin-A is like well-known anticancer compound resveratrol and its metabolic product piceatannol in breast cancer cells.

Fourier-transform infrared and Raman characterization of bilayer membranes of the phospholipid SOPC and its mixtures with cholesterol

One of the primary roles of cholesterol (Chol) in the biological cell is to modulate the physical properties of the bilayer phospholipid membrane. Moreover, the effect of cholesterol on lipid bilayers is strongly dependent on the concentration, hence it can easily adapt to the changes in the cell temperature. Incorporation of cholesterol in membranes induces diverse changes in the bilayer properties, including variation of the bilayer thicknesses and changing the lipid order. Taking into consideration these physical and structural characteristics of the lipid membranes with cholesterol, as well as their optical birefringence, we apply the typical structural methods for studying these complex biological systems. We have used Fourier transform infrared (FTIR) and micro-Raman spectroscopy, aiming on study of the specific physical characteristics of the lipid membrane of the type 1-stearoyl-2-oleoyl-sn-glycerol-3-phosphocoline (SOPC). The analysis of the FTIR and Raman fingerprint spectral range, including band deconvolution, indicated that hydrogen bonds (HBs) exist between the hydroxyl groups of cholesterol and the carbonyl ester groups of the polar–apolar interface of the bilayer membrane. Upon insertion into the bilayer Chol actively participates in H-bonding at the CO sites, facilitates H-bonding of water to the PO2-site and relaxes the “improper H-bonding” of H2O molecules to the choline moiety. We also establish an overall ordering effect of Chol on the lipid bilayer. The interplay of cholesterol and water in realization of HB with the phospholipid moieties, in dependence on the Chol concentration, was analyzed.

Discrimination of citrus fruits using FT-IR fingerprinting by quantitative prediction of bioactive compounds.

High throughput screening of citrus samples containing elevated concentrations of total carotenoids, flavonoids, and phenolic compounds was accomplished using ultraviolet-visible spectroscopy and Fourier transform infrared (FT-IR) spectroscopy, combined with multivariate analysis. Principal component analysis and partial least squares discriminant analysis using FT-IR spectra were able to differentiate seven citrus fruit groups into three distinct clusters corresponding to their taxonomic relationship. Quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds in citrus fruit was established using a partial least squares regression algorithm from the FT-IR spectra. The regression coefficients (R 2) of predicted and estimated values of total carotenoids, flavonoids, and phenolic compounds were all 0.99. The results indicated that accurate quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from citrus fruit FT-IR spectra, and that the resulting quantitative prediction model might be useful as a rapid selection tool for citrus fruits containing elevated carotenoids, flavonoids, and phenolic compounds.

Discrimination of Shirazi thyme from thymus species and antioxidant activity prediction using chemometrics and FT-IR spectroscopy

Local names are not reliable sources for identification of plants, because they differ significantly from one region to another. Apart from confusing nomenclature, the similar appearance and fragrance of Shirazi thyme and Thymus species cause misidentification. In order to prevent the adverse events in relation to the use of improper herbal products, easy-to-use quality control (QC) methodology was developed to classify these culinary plants. Fourier transform infrared (FT-IR) fingerprinting technique was applied for classification of these plants on the basis of their biochemical compositions. Powerful PLS-DA classification model with classification accuracy of 100% was obtained. For the first time in the present study, it was revealed that Shirazi thyme samples have higher antioxidant activity [average IC50 of 37.03 (µg/ml)] compared to different Thymus species [average IC50 of 148.35 (µg/ml)]. FT-IR fingerprint profiles were also used to construct a predictive model for antioxidant activity of the plants based on a reliable PLSR model. The developed PLSR model revealed that IR wavenumbers of 1000–1200, 1700, and 3200–3500 cm−1 are important for antioxidant activity prediction of the analyzed plants. The applied approach has the potential for being used in QC programs not only for fraud mitigation and detection, but also for estimation of antioxidant activity of the culinary plants.

Physicochemical properties of pectin from green jelly leaf (Cyclea barbata Miers)

The water extract of Green Jelly leaves (GJL) obtained by crushing the leaves in water (1:40) was capable of forming a gel at room temperature. The composition of GJL consisted mainly of carbohydrate (∼70w/w), protein (∼13% w/w) and minerals (∼6% w/w). The mineral portion consisted of mainly calcium (∼1.2% w/w), zinc (∼0.12% w/w) and magnesium (∼0.11% w/w). The isolated polysaccharide fraction (∼42.6% w/w) consisted of mainly galacturonic acid (∼35.8% w/w) and neutral sugars (∼6.8% w/w), with a weight-average molecular weight of ∼4.4×105g/mol. The results obtained by Fourier Transform Infra-Red (FTIR) showed that GJL polysaccharide fraction had a fairly similar FTIR fingerprint as the commercial low-methoxyl pectin (LMP). The degree of esterification of the polysaccharide changed drastically (from 97% to 10%) depending on the temperature used during the extraction process. The zeta potential of the extracted polysaccharide showed high negative charged as compared to the commercial LMP but close to sodium alginate. The study showed that the gelation was divalent cation-mediated and probably facilitated by the low degree of esterification which reduced steric hindrance from the methyl ester groups.

Development of FTIR fingerprint for identification of armand clematis stem (Chuanmutong) and related herbs

Armand clematis stem (Clematidis Armandii Caulis, Chuanmutong) is a widely used Chinese herb to disinhibit urine and relieve stranguria. It is difficult to be identified owing to its various macroscopic feature and unknown characteristic compounds. Thus, total of 24 Chuanmutong samples and 7 related herbs including four manshurian aristolochia stem (Aristolochiae Manshuriensis Caulis, Guanmutong) and three akebia stem (Akebiae Caulis, Mutong) samples were collected and analyzed in the range of 4 000 - 400 cm⁻¹ by Fourier Transform Infrared (FTIR) and two-dimensional infrared correlation spectroscopy (2D-FTIR) techniques. The FTIR spectra of 24 Chuanmutong samples are consistent in the spectrum profiles, position and intensity of characteristic peaks. 20 of the 24 Chuanmutong samples were randomly selected as calibration samples to calculate and simulate mean spectrum. This mean spectrum is named as FTIR fingerprint of Chuanmutong with characteristic peaks at 3 412, 2 932, 1 739, 1 639, 1 509, 1 456, 1 426, 1 376, 1 332, 1 261, 1 159, 1 035, 897 ,609 cm⁻¹. Meanwhile, the limited level (Mean-3σ=0.992 6) to identify true or false Chuanmutong by correlation coefficient of FTIR spectra was calculated based on the 20 Chuanmutong calibration samples. Then, the rest 4 Chuanmutong, 4 Guanmutong and 3 Mutong samples were used as validation samples to evaluate the identification efficacy. The result shows that the FTIR spectra of 4 Chuanmutong validation samples were similar to the fingerprint. Their correlation coefficients of FTIR spectra were over the limited level and accepted as Chuanmutong. However, the spectra of Guanmutong and Mutong were significantly different from Chuanmutong fingerprint. The correlation coefficients of Guanmutong (0.902 1-0.940 4, n=4) and Mutong (0.954 9-0.978 9, n=3) FTIR spectra were less than the limited level and rejected from Chuanmutong. Furthermore, the number, position and intensity of auto-peaks on the 2D-FTIR were drastically different among the three herbs. It is concluded that the developed FTIR fingerprinting can be rapidly and accurately identify Chuanmutong and differentiate from related herbs.

Investigation of Growth Rate and Phycocolloid Content from Kappaphycus alvarezii (Rhodophyta, Solieriaceae) under Different Light Conditions Using Vibrational Spectroscopy

<p><em>Kappa</em>-carrageenan (<em>K</em>-carrageenan) is an important phycocolloid which is a major constituent of the cell wall of <em>Kappaphycus alvarezii</em>. The chemical structure of <em>K</em>-carrageenan comprises a linear backbone of D-galactose residues linked with alternating α-(1,3) and β-(1,4) linkages which are substituted by one ester-sulphonic group per di-galactose repeating unit. The spectral qualities of light as well as the ambient carbon dioxide concentration, both play an important role in the photosynthetic pathway in plants and this investigation set forth to establish the effect of different wavelengths of light and carbon dioxide supplementation on the chemical structure of <em>K</em>-carrageenan obtained from <em>K. alvarezii. </em>Specimens were cultivated under a range of monochromatic light spectra and assessed for chemical composition using Fourier Transform Infrared (FTIR) spectroscopy.The <em>K. alvarezii</em> control was irradiated with full light spectrum, treatments were carried out using blue (492-455 nm), green (577-492 nm) and red (780-622 nm)light. One experiment was carried out by supplementation with carbon dioxide. Samples were collected after 14 days. The effect of different wavelengths of light on the growth rates of experimental samples was determined. Red light had the most significant impact on the growth rate of <em>K. alvarezii </em>as compared to those treated with blue light. The FTIR fingerprint of the ground seaweed was found to be identical to that of commercial <em>K</em>-carrageenan (Sigma). Special emphasis was given to the 800-1300 cm<sup>-1 </sup>region, which presents several vibrational modes. All the samples produced similar FTIR spectral profiles, suggesting that genes related to the carrageenan biosynthesis are not affected by different wavelengths of light or CO<sub>2</sub>. The results obtained from FTIR spectroscopy demonstrated that different wavelengths of light and supplementation with CO<sub>2</sub> have no influence to the chemical structure of <em>K</em>-carrageenan in <em>K. alvarezii</em>.</p>

Classification of Gemcitabine resistant Cholangiocarcinoma cell lines using synchrotron FTIR microspectroscopy.

Cholangiocarcinoma (CCA), a cancer of bile duct epithelium, is a major health problem in Thailand especially in the northeast. Overall treatment outcomes have not shown much improvement because the disease is usually detected at an advanced stage and often shows chemotherapeutic resistance. High-throughput Fourier Transform Infrared (FTIR) microspectroscopy can be used for cell classification and has the potential to diagnose cancer and possibly predict chemo-response. This study was aimed to differentiate gemcitabine-sensitive and gemcitabine-resistant induction in two CCA cell lines (KKU-M139 and KKU-M214) and xenograft tissues using synchrotron-FTIR microspectroscopy. Partial Least Squares Discriminant Analysis (PLS-DA) could discriminate between chemo-sensitive and chemo-resistant cells in the FTIR fingerprint spectral region (1800-1000 cm-1 ) with more than 90% sensitivity and specificity. The chemo-resistant and chemo-sensitive phenotypes were different in protein (amide I, amide II), lipids (carbonyl group and CH3 deformation) and phosphodiester from nucleic acids. Additionally, spectra from xenograft tissues showed similar results to the cell line study with marked differences between chemo-resistant and chemo-sensitive CCA tissues, and PLS-DA could discriminate the chemotherapeutic response with 98% sensitivity and specificity. This is the first study to demonstrate the use of FTIR microspectroscopy to assess chemo-response both in vitro and in vivo.

Real time monitoring of bioreactor mAb IgG3 cell culture process dynamics via Fourier transform infrared spectroscopy: Implications for enabling cell culture process analytical technology

Compared to small molecule process analytical technology (PAT) applications, biotechnology product PAT applications have certain unique challenges and opportunities. Understanding process dynamics of bioreactor cell culture process is essential to establish an appropriate process control strategy for biotechnology product PAT applications. Inline spectroscopic techniques for real time monitoring of bioreactor cell culture process have the distinct potential to develop PAT approaches in manufacturing biotechnology drug products. However, the use of inline Fourier transform infrared (FTIR) spectroscopic techniques for bioreactor cell culture process monitoring has not been reported. In this work, real time inline FTIR Spectroscopy was applied to a lab scale bioreactor mAb IgG3 cell culture fluid biomolecular dynamic model. The technical feasibility of using FTIR Spectroscopy for real time tracking and monitoring four key cell culture metabolites (including glucose, glutamine, lactate, and ammonia) and protein yield at increasing levels of complexity (simple binary system, fully formulated media, actual bioreactor cell culture process) was evaluated via a stepwise approach. The FTIR fingerprints of the key metabolites were identified. The multivariate partial least squares (PLS) calibration models were established to correlate the process FTIR spectra with the concentrations of key metabolites and protein yield of in-process samples, either individually for each metabolite and protein or globally for all four metabolites simultaneously. Applying the 2nd derivative pre-processing algorithm to the FTIR spectra helps to reduce the number of PLS latent variables needed significantly and thus simplify the interpretation of the PLS models. The validated PLS models show promise in predicting the concentration profiles of glucose, glutamine, lactate, and ammonia and protein yield over the course of the bioreactor cell culture process. Therefore, this work demonstrated the technical feasibility of real time monitoring of the bioreactor cell culture process via FTIR spectroscopy. Its implications for enabling cell culture PAT were discussed.

Sugar and acid content of Citrus prediction modeling using FT-IR fingerprinting in combination with multivariate statistical analysis

A high-throughput screening system for Citrus lines were established with higher sugar and acid contents using Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. FT-IR spectra confirmed typical spectral differences between the frequency regions of 950–1100cm−1, 1300–1500cm−1, and 1500–1700cm−1. Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate five Citrus lines into three separate clusters corresponding to their taxonomic relationships. The quantitative predictive modeling of sugar and acid contents from Citrus fruits was established using partial least square regression algorithms from FT-IR spectra. The regression coefficients (R2) between predicted values and estimated sugar and acid content values were 0.99. These results demonstrate that by using FT-IR spectra and applying quantitative prediction modeling to Citrus sugar and acid contents, excellent Citrus lines can be early detected with greater accuracy.