Rapid detection of viable microbes with 5-cyano-2,3-di-(p-tolyl)tetrazolium chloride and 5(6)-carboxyfluorescein diacetate using a fibre fluorescence spectroscopy system.

AIMS: To assess the efficacy of two commercially available viability dyes, 5-cyano-2,3-di-(p-tolyl)tetrazolium chloride (CTC) and 5(6)-carboxyfluorescein diacetate (CFDA), in reporting on viable cell concentration and species using an all-fibre fluorometer. METHODS AND RESULTS: Four bacterial species (two Gram-positive and two Gram-negative) commonly associated with food poisoning or food spoilage (Escherichia coli, Salmonella enterica, Staphylococcus aureus, and Bacillus cereus) were stained with CTC or CFDA and the fibre fluorometer was used to collect full fluorescence emission spectra. A good correlation between concentration and fluorescence intensity was found for Gram-negative bacteria between 107 and 108 colony-forming units (CFU) ml-1. There was no correlation with concentration for Gram-positive bacteria; however, the information in the CTC and CFDA spectra shows the potential to distinguish Gram-negative cells from Gram-positive cells, although it may simply reflect the overall bacterial metabolic activity under staining conditions from this study. CONCLUSIONS: The limit of detection (LoD) is too high in the dip-probe approach for analysis; however, the development of an approach measuring the fluorescence of single cells may improve this limitation. The development of new bacteria-specific fluorogenic dyes may also address this limitation. The ability to differentiate bacteria using these dyes may add value to measurements made to enumerate bacteria using CTC and CFDA.

Support vector regression for prediction of stable isotopes and trace elements using hyperspectral imaging on coffee for origin verification.

The potential of using rapid and non-destructive near-infrared - hyperspectral imaging (HSI-NIR) for the prediction of an integrated stable isotope and multi-element dataset was explored for the first time with the help of support vector regression. Speciality green coffee beans sourced from three continents, eight countries, and 22 regions were analysed using a push-broom HSI-NIR (700-1700 nm), together with five isotope ratios (δ13C, δ15N, δ18O, δ2H, and δ34S) and 41 trace elements. Support vector regression with the radial basis function kernel was conducted using X as the HSI-NIR data and Y as the geochemistry markers. Model performance was evaluated using root mean squared error, coefficient of determination, and mean absolute error. Three isotope ratios (δ18O, δ2H, and δ34S) and eight elements (Zn, Mn, Ni, Mo, Cs, Co, Cd, and La) had an R2predicted 0.70 - 0.99 across all origin scales (continent, country, region). All five isotope ratios were well predicted at the country and regional levels. The wavelength regions contributing the most towards each prediction model were highlighted, including a discussion of the correlations across all geochemical parameters. This study demonstrates the feasibility of using HSI-NIR as a rapid and non-destructive method to estimate traditional geochemistry parameters, some of which are origin-discriminating variables related to altitude, temperature, and rainfall differences across origins.

Continuous separation of bacterial cells from large debris using a spiral microfluidic device.

With the global increase in food exchange, rapid identification and enumeration of bacteria has become crucial for protecting consumers from bacterial contamination. Efficient analysis requires the separation of target particles (e.g., bacterial cells) from food and/or sampling matrices to prevent matrix interference with the detection and analysis of target cells. However, studies on the separation of bacteria-sized particles and defined particles, such as bacterial cells, from heterogeneous debris, such as meat swab suspensions, are limited. In this study, we explore the use of passive-based inertial microfluidics to separate bacterial cells from debris, such as fascia, muscle tissues, and cotton fibers, extracted from ground meat and meat swabs-a novel approach demonstrated for the first time. Our objective is to evaluate the recovery efficiency of bacterial cells from large debris obtained from ground meat and meat swab suspensions using a spiral microfluidic device. In this study, we establish the optimal flow rates and Dean number for continuous bacterial cell and debris separation and a methodology to determine the percentage of debris removed from the sample suspension. Our findings demonstrate an average recovery efficiency of ∼80% for bacterial cells separated from debris in meat swab suspensions, while the average recovery efficiency from ground beef suspensions was ∼70%. Furthermore, approximately 50% of the debris in the ground meat suspension were separated from bacterial cells.

Near-infrared reflectance spectroscopy accurately predicted isotope and elemental compositions for origin traceability of coffee.

Stable isotope ratios and trace elements are well-established tools that act as signatures of the product's environmental conditions and agricultural processes; but they involve time, money, and environmentally destructive chemicals. In this study, we tested for the first time the potential of near-infrared reflectance spectroscopy (NIR) to estimate/predict isotope and elemental compositions for the origin verification of coffee. Green coffee samples from two continents, 4 countries, and 10 regions were analysed for five isotope ratios (δ13C, δ15N, δ18O, δ2H, and δ34S) and 41 trace elements. NIR (1100-2400 nm) calibrations were developed using pre-processing with extended multiplicative scatter correction (EMSC) and mean centering and partial-least squares regression (PLS-R). Five elements (Mn, Mo, Rb, B, La) and three isotope ratios (δ13C, δ18O, δ2H) were moderately to well predicted by NIR (R2: 0.69 to 0.93). NIR indirectly measured these parameters by association with organic compounds in coffee. These parameters were related to altitude, temperature and rainfall differences across countries and regions and were previously found to be origin discriminators for coffee.

Stable isotope and trace element analyses with non-linear machine-learning data analysis improved coffee origin classification and marker selection.

BACKGROUND: This study investigated the geographical origin classification of green coffee beans from continental to country and regional levels. An innovative approach combined stable isotope and trace element analyses with non-linear machine learning data analysis to improve coffee origin classification and marker selection. Specialty green coffee beans sourced from three continents, eight countries, and 22 regions were analyzed by measuring five isotope ratios (δ13 C, δ15 N, δ18 O, δ2 H, and δ34 S) and 41 trace elements. Partial least squares discriminant analysis (PLS-DA) was applied to the integrated dataset for origin classification. RESULTS: Origins were predicted well at the country level and showed promise at the regional level, with discriminating marker selection at all levels. However, PLS-DA predicted origin poorly at the continental and Central American regional levels. Non-linear machine learning techniques improved predictions and enabled the identification of a higher number of origin markers, and those that were identified were more relevant. The best predictive accuracy was found using ensemble decision trees, random forest and extreme gradient boost, with accuracies of up to 0.94 and 0.89 for continental and Central American regional models, respectively. CONCLUSION: The potential for advanced machine learning models to improve origin classification and the identification of relevant origin markers was demonstrated. The decision-tree-based models were superior with their embedded variable identification features and visual interpretation. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Rapid Detection of Escherichia coli Antibiotic Susceptibility Using Live/Dead Spectrometry for Lytic Agents.

Antibiotic resistance is a serious threat to public health. The empiric use of the wrong antibiotic occurs due to urgency in treatment combined with slow, culture-based diagnostic techniques. Inappropriate antibiotic choice can promote the development of antibiotic resistance. We investigated live/dead spectrometry using a fluorimeter (Optrode) as a rapid alternative to culture-based techniques through application of the LIVE/DEAD® BacLightTM Bacterial Viability Kit. Killing was detected by the Optrode in near real-time when Escherichia coli was treated with lytic antibiotics-ampicillin and polymyxin B-and stained with SYTO 9 and/or propidium iodide. Antibiotic concentration, bacterial growth phase, and treatment time used affected the efficacy of this detection method. Quantification methods of the lethal action and inhibitory action of the non-lytic antibiotics, ciprofloxacin and chloramphenicol, respectively, remain to be elucidated.

A novel optical biosensor for in situ and small-scale monitoring of bacterial transport in saturated columns.

In situ monitoring techniques can provide new insight into bacterial transport after inoculating exogenous bacteria into contaminated soils for bioremediation. A real-time and non-destructive optical sensor (the optrode) was employed to monitor in situ transport of two fluorescently labelled bacteria - Green Fluorescent Protein (Gfp)-labelled, hydrophilic Pseudomonas putida and Tomato Fluorescent Protein (td)-labelled, hydrophobic Rhodococcus erythropolis, in a saturated sand column with and without rhamnolipid surfactant. In situ measurements were made at three sampling ports in the column with the optrode in two sets of column experiments. In Experiment 1, liquid samples were extracted for ex situ analyses (plate counts and fluorescence), while in Experiment 2 no liquid samples were extracted. Extracting liquid samples for ex situ analyses in Experiment 1 disturbed in situ measurements; in situ measured bacterial concentrations were lower, or a significant lag in breakthrough occurred relative to ex situ measurements. In Experiment 2, the optrode worked well in monitoring bacterial transport, which gave consistent transport parameters at each sampling port. Moreover, the optrode enabled the impact of bacterial hydrophobicity and rhamnolipid surfactant on bacterial transport to be observed. Specifically, hydrophilic P. putida was transported faster through the column than hydrophobic R. erythropolis; we infer from this result that fewer P. putida cells adsorb to sand particles than do R. erythropolis cells. The rhamnolipid surfactant enhanced the transport of both hydrophilic and hydrophobic bacteria. These two observations are consistent with Lifshitz-van der Waals forces and acid-base interactions between bacteria and sand.

Potential of Raman spectroscopy in facilitating pharmaceutical formulations development - An AI perspective.

Drug development is time-consuming and inherently possesses a high failure rate. Pharmaceutical formulation development is the bridge that links a new chemical entity (NCE) to pre-clinical and clinical trials, and has a high impact on the efficacy and safety of the final drug product. Further, the time required for this process is escalating as formulation techniques are becoming more complicated due to the rising demands for drug products with better efficacy and patient compliance, as well as the inherent difficulties of addressing the unfavorable properties of NCEs such as low water solubility. The advent of artificial intelligence (AI) provides possibilities to accelerate the drug development process. In this review, we first examine applications of AI methods in different types of pharmaceutical formulations and formulation techniques. Moreover, as availability of data is the engine for the advancement of AI, we then suggest a potential way (i.e. applying Raman spectroscopy) for faster high-quality data gathering from formulations. Raman techniques have the capability of analyzing the composition and distribution of components and the physicochemical properties thereof within formulations, which are prominent factors governing drug dissolution profiles and subsequently bioavailability. Thus, useful information can be obtained bridging formulation development to the final product quality.

Species Dependence of SYTO 9 Staining of Bacteria.

SYTO 9 is a fluorescent nucleic acid stain that is widely used in microbiology, particularly for fluorescence microscopy and flow cytometry analyzes. Fluorimetry-based analysis, i.e., analysis of fluorescence intensity from a bulk sample measurement, is more cost effective, rapid and accessible than microscopy or flow cytometry but requires application-specific calibration. Here we show the relevance of SYTO 9 for food safety analysis. We stained four bacterial species of relevance to food safety (Bacillus cereus, Escherichia coli, Salmonella enterica subspecies enterica ser. Typhimurium, Staphylococcus aureus) with different concentrations of SYTO 9, with and without the presence of ethylenediaminetetraacetic acid (EDTA), for varying amounts of time, to investigate the effect of these treatment parameters on fluorescence intensity. The addition of EDTA and an increased staining duration did not significantly affect fluorescence intensity, and over the bacterial cell concentration range investigated (∼105-108 CFU/ml) there was no significant difference in using 0.5 or 1 µM SYTO 9. The effect of bacterial cell concentration on fluorescence intensity was species specific. At different bacterial cell concentrations, the effect of species on fluorescence intensity is different. This interaction complicates the development of a general fluorimetry-based protocol for the determination of bacterial cell concentration in a mixed bacterial suspension, as would be expected from samples taken from food safety settings.

Asia-Pacific Optical Sensors Conference: focus issue introduction.

This feature issue of Optics Express contains 17 articles expanding on recent advances in optical sensors presented at the eighth Asia-Pacific Optical Sensors Conference (APOS 2019) held in Auckland, New Zealand, from November 19 to 22, 2019. These articles span sensing for real-time positioning, refractive indices, strain, gas, and temperature using a variety of methods including photoacoustic computed tomography, coherent optical frequency-modulated continuous-wave interferometry, enhanced Bragg gratings, and phase-sensitive optical frequency-domain reflectometry.

Rapid and cost-effective evaluation of bacterial viability using fluorescence spectroscopy.

A rapid and easy method that takes advantage of an inexpensive and portable fibre-based spectroscopic system (optrode) to determine the ratio of live to dead bacteria is proposed. Mixtures of live and dead Escherichia coli with proportions of live:dead cells varying from 0 to 100% were stained using SYTO 9 and propidium iodide (PI) and measured using the optrode. We demonstrated several approaches to obtaining the proportions of live:dead E. coli in a mixture of both live and dead, from analyses of the fluorescence spectra collected by the optrode. To find a suitable technique for predicting the percentage of live bacteria in a sample, four analysis methods were assessed and compared: SYTO 9:PI fluorescence intensity ratio, an adjusted fluorescence intensity ratio, single-spectrum support vector regression (SVR) and multi-spectra SVR. Of the four analysis methods, multi-spectra SVR obtained the most reliable results and was able to predict the percentage of live bacteria in 108 bacteria/mL samples between c. 7 and 100% live, and in 107 bacteria/mL samples between c. 7 and 73% live. By demonstrating the use of multi-spectra SVR and the optrode to monitor E. coli viability, we raise points of consideration for spectroscopic analysis of SYTO 9 and PI and aim to lay the foundation for future work that uses similar methods for different bacterial species.

Bead-Based Flow-Cytometric Cell Counting of Live and Dead Bacteria.

Flow cytometry (FCM) is based on the detection of scattered light and fluorescence to identify cells with characteristics of interest. Many flow cytometers cannot precisely control the flow through its interrogation point and hence the volume and concentration of the sample cannot be immediately obtained. Here we describe the optimization and evaluation of a bead-based method for absolute cell counting applicable to basic flow cytometers without specialized counting features. Prior to the application of this method to an unknown concentration of a species of bacteria, a calibration experiment should be completed to characterize limits of detection and range of linearity with respect to the plate count method. To demonstrate the calibration process, mixtures of Escherichia coli or Staphylococcus aureus with proportions of live and dead cells ranging from 0% to 100% were prepared. These samples were stained using nucleic acid-binding dyes, and 6 µm reference beads were added (LIVE/DEAD® BacLight kit). The calibration samples were analyzed using bead-based FCM as well as the agar plate count method, and the results from both methods were compared.

Optimisation of the Protocol for the LIVE/DEAD® BacLightTM Bacterial Viability Kit for Rapid Determination of Bacterial Load.

Rapid antimicrobial susceptibility testing is needed to reduce prescription of inappropriate antibiotics. A rapid alternative to standard culture-based testing is to determine reductions in cell viability using the LIVE/DEAD® BacLightTM Bacterial Viability Kit. We optimised the kit protocol for this application, focusing on simplifying the process by minimising the steps involved and on determining the optimal analytical parameters for fluorescence measurements from the dyes SYTO 9 and propidium iodide (PI). We demonstrate that for our experimental system, the intensity of emissions should be integrated from 505-515 nm for SYTO 9 and 600-610 nm for PI, and the proportion of live cells calculated from a new dye ratio formula, termed the adjusted dye ratio. We show that the pre-staining washing step is not necessary if a non-fluorescent growth media is used; however, staining must be done for each sampling as prolonged exposure to the dyes negatively impacts cell viability. The optimised methodology was able to reproducibly detect reductions in culture viability when the proportion of live cells in a sample of 1 × 108 cells/ml fell below ∼50% live in a media that supports the growth required for detecting antibiotic killing. Finally, we show that the interaction of fluorescence emission spectra from SYTO 9 and PI stained Escherichia coli cells is influenced by the proportion of dead cells in a sample. The excitation of PI by SYTO 9 was found to occur in populations containing sufficient numbers of dead cells (>25%), whereas in populations with low numbers of dead cells the dye interaction was additive in regard to red emissions, indicating that these dye interactions may offer another dimension to live/dead analysis. Fluorescence measurements from samples established according to the optimised protocol can be taken using a flow cytometer, spectrofluorometer, microplate reader, and the Optrode, a fibre-based spectroscopic system developed at the University of Auckland.

Near real-time enumeration of live and dead bacteria using a fibre-based spectroscopic device.

A rapid, cost-effective and easy method that allows on-site determination of the concentration of live and dead bacterial cells using a fibre-based spectroscopic device (the optrode system) is proposed and demonstrated. Identification of live and dead bacteria was achieved by using the commercially available dyes SYTO 9 and propidium iodide, and fluorescence spectra were measured by the optrode. Three spectral processing methods were evaluated for their effectiveness in predicting the original bacterial concentration in the samples: principal components regression (PCR), partial least squares regression (PLSR) and support vector regression (SVR). Without any sample pre-concentration, PCR achieved the most reliable results. It was able to quantify live bacteria from 108 down to 106.2 bacteria/mL and showed the potential to detect as low as 105.7 bacteria/mL. Meanwhile, enumeration of dead bacteria using PCR was achieved between 108 and 107 bacteria/mL. The general procedures described in this article can be applied or modified for the enumeration of bacteria within populations stained with fluorescent dyes. The optrode is a promising device for the enumeration of live and dead bacterial populations particularly where rapid, on-site measurement and analysis is required.

Dry powder inhaler formulations of poorly water-soluble itraconazole: A balance between in-vitro dissolution and in-vivo distribution is necessary.

Formulating poorly water-soluble drug, itraconazole (ITZ), as dry powder inhaler (DPI) may be more effective for the treatment of invasive pulmonary Aspergillosis than intravenous injection and oral administration. It is necessary to improve the dissolution of ITZ because the alveolar lining fluid is limited and thus the dissolution of ITZ in the lung may be slow and incomplete. However, too fast dissolution may result in over-absorption into the circulation and thus insufficient distribution in the lung. The purpose of this study is to understand the relationship between in-vitro dissolution and in-vivo distribution of ITZ from DPI formulations. Two DPI formulations (F1 and F2) with identical compositions and similar aerodynamic behaviors were fabricated by hot melt extrusion and thus jet-milling. ITZ was formulated with mannitol as fine solid crystal suspension system to effectively improve its dissolution. In-vitro dissolution tests and in-vivo pharmacokinetic studies indicated that F1 released faster than F2 under both sink and non-sink conditions, but exhibited a lower lung retention and higher plasma absorption than F2. These results suggested that although dissolution enhancement of poorly water-soluble drugs in pulmonary delivery may be necessary to overcome problems such as local irritation and quick elimination by macrophages, it may have an impact on the distribution of the drug between the lung and the plasma. A balance between airway dissolution and systemic absorption should be taken into consideration when developing DPI formulations of poorly water-soluble ITZ.

A rapid and low-cost estimation of bacteria counts in solution using fluorescence spectroscopy.

The fluorescence spectrum of bacterially bound acridine orange (AO) was investigated to evaluate its use for the rapid enumeration of bacteria. Escherichia coli ATCC 25922 samples were stained with 2 × 10-2, 2 × 10-3 or 2 × 10-4% w/v AO, followed by 3, 2 or 0 washing cycles, respectively, and fluorescence spectra were recorded using a fibre-based spectroscopic system. Independent component analysis was used to analyse the spectral datasets for each staining method. Bacterial concentration order of magnitude classification models were calculated using independent component weights. The relationship between fluorescence intensity of bound AO and bacterial concentration was not linear. However, the spectral signals collected for AO stain concentration-bacterial concentration pairs were reproducible and unique enough to enable classification of samples. When above 105 CFU ml-1, it was possible to rapidly determine what the order of magnitude of bacterial concentration of a sample was using a combination of two of the sample preparation methods. A relatively inexpensive (around US$10 per test) rapid method (within 25 min of sampling) for enumeration of bacteria by order of magnitude will reduce the time and cost of microbiological tests requiring gross concentration information. Graphical Abstract Fluorescence spectra of bacterially bound acridine orange (AO) were used for the rapid enumeration of bacteria. Order of magnitude bacterial concentration classification models were calculated using independent components analysis of these fluorescence spectra. When above 105 CFU ml-1, it was possible to rapidly determine the order of magnitude of bacterial concentration of a sample using a combination of two sample preparation methods.

Screening for Adulterants in Liquid Milk Using a Portable Raman Miniature Spectrometer with Immersion Probe.

A portable Raman system with an immersion fiber optic probe was assessed for point-of-collection screening for the presence of adulterants in liquid milk. N-rich adulterants and sucrose were measured in this proof-of-concept demonstration. Reproducibility, limit of detection range and other figures of merit such as specificity, sensitivity, ratio of predicted to standard deviation, standard error of prediction and root mean squared error for cross validation were determined from partial least squares (PLS) and partial least squares with discriminant analysis (PLS-DA) calibrations of milk mixtures containing 50-1000 ppm (parts per million) of melamine, ammonium sulphate, Dicyandiamide, urea and sucrose. The spectra were recorded by immersing the fiber optic probe directly in the milk solutions. Despite the high scattering background which was easily and reliably estimated and subtracted, the reproducibility for four N-rich compounds averaged to 11% residual standard deviation (RSD) and to 5% RSD for sucrose. PLS calibration models predicted the concentrations of separate validation sets with standard errors of prediction of between 44 and 76 ppm for the four N-rich compounds and 0.17% for sucrose. The sensitivity and specificity of the PLS-DA calibration were 92% and 89%, respectively. The study shows promise for use of portable mini Raman systems for routine rapid point-of-collection screening of liquid milk for the presence of adulterants, without the need for sample preparation or addition of chemicals.

Near infrared spectroscopic assessment of developing engineered tissues: correlations with compositional and mechanical properties.

Articular cartilage degeneration causes pain and reduces the mobility of millions of people annually. Regeneration of cartilage is challenging, due in part to its avascular nature, and thus tissue engineering approaches for cartilage repair have been studied extensively. Current techniques to assess the composition and integrity of engineered tissues, including histology, biochemical evaluation, and mechanical testing, are destructive, which limits real-time monitoring of engineered cartilage tissue development in vitro and in vivo. Near infrared spectroscopy (NIRS) has been proposed as a non-destructive technique to characterize cartilage. In the current study, we describe a non-destructive NIRS approach for assessment of engineered cartilage during development, and demonstrate correlation of these data to gold standard mid infrared spectroscopic measurements, and to mechanical properties of constructs. Cartilage constructs were generated using bovine chondrocyte culture on polyglycolic acid (PGA) scaffolds for six weeks. BMP-4 growth factor and ultrasound mechanical stimulation were used to provide a greater dynamic range of tissue properties and outcome variables. NIR spectra were collected daily using an infrared fiber optic probe in diffuse reflectance mode. Constructs were harvested after three and six weeks of culture and evaluated by the correlative modalities of mid infrared (MIR) spectroscopy, histology, and mechanical testing (equilibrium and dynamic stiffness). We found that specific NIR spectral absorbances correlated with MIR measurements of chemical composition, including relative amount of PGA (R = 0.86, p = 0.02), collagen (R = 0.88, p = 0.03), and proteoglycan (R = 0.83, p = 0.01). In addition, NIR-derived water content correlated with MIR-derived proteoglycan content (R = 0.76, p = 0.04). Both equilibrium and dynamic mechanical properties generally improved with cartilage growth from three to six weeks. In addition, significant correlations between NIRS-derived parameters and mechanical properties were found for constructs that were not treated with ultrasound (PGA (R = 0.71, p = 0.01), water (R = 0.74, p = 0.02), collagen (R = 0.69, p = 0.04), and proteoglycan (R = 0.62, p = 0.05)). These results lay the groundwork for extension to arthroscopic engineered cartilage assessment in clinical studies.

Near infrared spectroscopic imaging assessment of cartilage composition: Validation with mid infrared imaging spectroscopy.

Disease or injury to articular cartilage results in loss of extracellular matrix components which can lead to the development of osteoarthritis (OA). To better understand the process of disease development, there is a need for evaluation of changes in cartilage composition without the requirement of extensive sample preparation. Near infrared (NIR) spectroscopy is a chemical investigative technique based on molecular vibrations that is increasingly used as an assessment tool for studying cartilage composition. However, the assignment of specific molecular vibrations to absorbance bands in the NIR spectrum of cartilage, which arise from overtones and combinations of primary absorbances in the mid infrared (MIR) spectral region, has been challenging. In contrast, MIR spectroscopic assessment of cartilage is well-established, with many studies validating the assignment of specific bands present in MIR spectra to specific molecular vibrations. In the current study, NIR imaging spectroscopic data were obtained for compositional analysis of tissues that served as an in vitro model of OA. MIR spectroscopic data obtained from the identical tissue regions were used as the gold-standard for collagen and proteoglycan (PG) content. MIR spectroscopy in transmittance mode typically requires a much shorter pathlength through the sample (≤10 microns thick) compared to NIR spectroscopy (millimeters). Thus, this study first addressed the linearity of small absorbance bands in the MIR region with increasing tissue thickness, suitable for obtaining a signal in both the MIR and NIR regions. It was found that the linearity of specific, small MIR absorbance bands attributable to the collagen and PG components of cartilage (at 1336 and 856 cm(-1), respectively) are maintained through a thickness of 60 µm, which was also suitable for NIR data collection. MIR and NIR spectral data were then collected from 60 µm thick samples of cartilage degraded with chondroitinase ABC as a model of OA. Partial least squares (PLS) regression using NIR spectra as input predicted the MIR-determined compositional parameters of PG/collagen within 6% of actual values. These results indicate that NIR spectral data can be used to assess molecular changes that occur with cartilage degradation, and further, the data provide a foundation for future clinical studies where NIR fiber optic probes can be used to assess the progression of cartilage degradation.

Nondestructive Assessment of Engineered Cartilage Composition by Near Infrared Spectroscopy.

Tissue engineering presents a strategy to overcome the limitations of current tissue healing methods. Scaffolds, cells, external growth factors and mechanical input are combined in an effort to obtain constructs with properties that mimic native tissues. However, engineered constructs developed using similar culture environments can have very different matrix composition and biomechanical properties. Accordingly, a nondestructive technique to assess constructs during development such that appropriate compositional endpoints can be defined is desirable. Near infrared spectroscopy (NIRS) analysis is a modality being investigated to address the challenges associated with current evaluation techniques, which includes nondestructive compositional assessment. In the present study, cartilage tissue constructs were grown using chondrocytes seeded onto polyglycolic acid (PGA) scaffolds in similar environments in three separate tissue culture experiments and monitored using NIRS. Multivariate partial least squares (PLS) analysis models of NIR spectra were calculated and used to predict tissue composition, with biochemical assay information used as the reference data. Results showed that for combined data from all tissue culture experiments, PLS models were able to assess composition with significant correlations to reference values, including engineered cartilage water (at 5200 cm(-1), R = 0.68, p = 0.03), proteoglycan (at 4310 cm(-1), R = 0.82, p = 0.007), and collagen (at 4610 cm(-1), R = 0.84, p = 0.005). In addition, degradation of PGA was monitored using specific NIRS frequencies. These results demonstrate that NIR spectroscopy combined with multivariate analysis provides a nondestructive modality to assess engineered cartilage, which could provide information to determine the optimal time for tissue harvest for clinical applications.