Detecting fentanyl using point-of-care drug checking technologies: A validation study.

OBJECTIVES: Point-of-care drug checking services, wherein individuals can check the content and purity of their drugs, have emerged as a public health intervention to address the fentanyl crisis; however, there have been no rigorous evaluations of the technologies against reference standard laboratory techniques. METHODS: Two point-of-care technologies, fentanyl immunoassay strips and Fourier-Transform Infrared (FTIR) spectroscopy, were implemented at two supervised injection sites in Vancouver, Canada. We calculated sensitivity, specificity, and false negative rate for both testing methods as compared to a laboratory reference standard. RESULTS: Between October 2017 and 2018, 331 samples were sent for confirmatory testing. Immunoassay strips had a sensitivity of 87.5% and specificity of 95.2%, with a false negative rate of 12.5%. FTIR spectroscopy had a sensitivity of 72.1% and specificity of 99.0%, with a false negative rate of 27.9%. CONCLUSION: As expected, while FTIR spectroscopy can quantify concentrations on a wide array of compounds, it can only do so above the detection limit. Using FTIR spectroscopy and immunoassay strips in combination has the potential to offset the limitations of each technology when used alone.

Standardization of complex biologically derived spectrochemical datasets.

Spectroscopic techniques such as Fourier-transform infrared (FTIR) spectroscopy are used to study interactions of light with biological materials. This interaction forms the basis of many analytical assays used in disease screening/diagnosis, microbiological studies, and forensic/environmental investigations. Advantages of spectrochemical analysis are its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, an urgent need exists for repetition and validation of these methods in large-scale studies and across different research groups, which would bring the method closer to clinical and/or industrial implementation. For this to succeed, it is important to understand and reduce the effect of random spectral alterations caused by inter-individual, inter-instrument and/or inter-laboratory variations, such as variations in air humidity and CO2 levels, and aging of instrument parts. Thus, it is evident that spectral standardization is critical to the widespread adoption of these spectrochemical technologies. By using calibration transfer procedures, in which the spectral response of a secondary instrument is standardized to resemble the spectral response of a primary instrument, different sources of variation can be normalized into a single model using computational-based methods, such as direct standardization (DS) and piecewise direct standardization (PDS); therefore, measurements performed under different conditions can generate the same result, eliminating the need for a full recalibration. Here, we have constructed a protocol for model standardization using different transfer technologies described for FTIR spectrochemical applications. This is a critical step toward the construction of a practical spectrochemical analysis model for daily routine analysis, where uncertain and random variations are present.

Strategies for noise reduction and standardization of milk mid-infrared spectra from dairy cattle.

The use of Fourier-transform mid-infrared (FTIR) spectroscopy is of interest to the dairy industry worldwide for predicting milk composition and other novel traits that are difficult or expensive to measure directly. Although there are many valuable applications for FTIR spectra, noise from differences in spectral responses between instruments is problematic because it reduces prediction accuracy if ignored. The purpose of this study was to develop strategies to reduce the impact of noise and to compare methods for standardizing FTIR spectra in order to reduce between-instrument variability in multiple-instrument networks. Noise levels in bands of the infrared spectrum caused by the water content of milk were characterized, and a method for identifying and removing outliers was developed. Two standardization methods were assessed and compared: piecewise direct standardization (PDS), which related spectra on a primary instrument to spectra on 5 other (secondary) instruments using identical milk-based reference samples (n = 918) analyzed across the 6 instruments; and retroactive percentile standardization (RPS), whereby percentiles of observed spectra from routine milk test samples (n = 2,044,094) were used to map and exploit primary- and secondary-instrument relationships. Different applications of each method were studied to determine the optimal way to implement each method across time. Industry-standard predictions of milk components from 2,044,094 spectra records were regressed against predictions from spectra before and after standardization using PDS or RPS. The PDS approach resulted in an overall decrease in root mean square error between industry-standard predictions and predictions from spectra from 0.190 to 0.071 g/100 mL for fat, from 0.129 to 0.055 g/100 mL for protein, and from 0.143 to 0.088 g/100 mL for lactose. Reductions in prediction error for RPS were similar but less consistent than those for PDS across time, but similar reductions were achieved when PDS coefficients were updated monthly and separate primary instruments were assigned for the North and South Islands of New Zealand. We demonstrated that the PDS approach is the most consistent method to reduce prediction errors across time. We also showed that the RPS approach is sensitive to shifts in milk composition but can be used to reduce prediction errors, provided that secondary-instrument spectra are standardized to a primary instrument with samples of broadly equivalent milk composition. Appropriate implementation of either of these approaches will improve the quality of predictions based on FTIR spectra for various downstream applications.

Chemometric assisted Fourier Transform Infrared (FTIR) Spectroscopic analysis of fruit wine samples: Optimizing the initialization and convergence criteria in the non-negative factor analysis algorithm for developing a robust classification model.

The present work proposes certain optimization in the non-negative factor analysis (NNFA) algorithm to ensure an efficient analysis of the Fourier transformation infrared (FTIR) spectral data sets of the fruit wine samples. The first optimization deals with initialization of the variables in a controlled fashion that would ensure a reasonably good quality initial estimate to implement NNFA algorithm. It prevents NNFA algorithm from itinerating with random numbers that essentially have no chemical relevance. The second implemented optimization involves eliminating the alternate least square of convergence and allowing the algorithm to iterate until the iteration limit is reached. This criterion avoids the algorithm to have premature convergence and ensures that model provide the solutions which corresponds to the global minima. The application of NNFA with suggested optimizations are found to capture the subtle differences in the spectral profiles and classify the fruit wine samples that are essentially complex mixtures of several chemicals in unknown proportions. The proposed approach is also found to perform better than principal component analysis on practical grounds. In summary, the current work provides a simple, sensitive and cost-effective approach using optimized NNFA and FTIR spectroscopy for classifying the fruit wine samples.

Reference samples guide variable selection for correlation of wine sensory and volatile profiling data.

The relationship between wine flavour and wine volatile composition is well recognised, however with thousands of compounds in wine the exact nature of individual contributions may be hard to determine due to synergistic and masking effects. Untargeted chemical analyses coupled with descriptive sensory and partial least squares regression modelling can help unravel interactions to identify groups of compounds that contribute to sensory properties. Variable selection is often applied prior to modelling to eliminate irrelevant variables. In this study, sensory references used to train the sensory panel were chemically analysed and employed to reduce the number of variables used to construct the models. This novel variable selection approach was compared against the inclusion of all variables and the most commonly applied variable selection method - analysis of variance. Models constructed from variables present in sensory references performed similarly to other models and identified interesting groups of compounds to investigate further.

Evaluation of ATR-FTIR for analysis of bacterial cellulose impurities.

This research evaluated the utility of using the large amount of spectral data obtained during attenuated total reflection Fourier-transform infrared spectrophotometry (ATR-FTIR) analysis of dried biocellulose (BC) to estimate the type and concentration of potential bacterial cells impurities present in the BC. Pre-cleaned BC was contaminated with known concentrations of representative nucleic acid, lipid, and protein impurities, as well as whole bacterial cells. These impurity standards were then subjected to ATR-FTIR analysis, and the resulting spectral data were used to develop models to estimate the concentrations of impurities in differentially processed BC. Results indicated that ATR-FTIR is a useful tool for estimating impurities in BC, and may also be applicable for measurement of levels of non-cellulose biomolecules added to BC for various purposes.

Identification, isolation, and synthesis of seven novel impurities of anti-diabetic drug Repaglinide.

Seven unknown impurities in Repaglinide bulk drug batches at below 0.1% (ranging from 0.05 to 0.10%) were detected by an ultra-performance liquid chromatographic (UPLC) method. These impurities were isolated from the crude sample of Repaglinide using preparative high performance liquid chromatography (prep-HPLC). Based on liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI/MS) study, the chemical structures of seven new impurities (8, 9, 10, 11, 13, 14, and 16) were presumed and characterized as 4-(cyanomethyl)-2-ethoxybenzoic acid (8), 4-(cyanomethyl)-2-ethoxy-N-(3-methyl-1-(2-(piperidin-1-yl)phenyl)butyl)benzamide (9), 4-(2-amino-2-oxoethyl)-2-ethoxy-N-(3-methyl-1-(2-(piperidin-1-yl)phenyl)butyl) benzamide (10) and 2-(3-ethoxy-4-((3-methyl-1-(2-(piperidin-1-yl)phenyl)butyl) carbamoyl) phenyl) acetic acid (11) and 4-(cyanomethyl)-N-cyclohexyl-2-ethoxybenzamide (13), 2-(4-(cyclohexylcarbamoyl)-3-ethoxyphenyl) acetic acid (14) and N-cyclohexyl-4-(2-(cyclohexylamino)-2-oxoethyl)-2-ethoxybenzamide (16). The complete spectral analysis, proton nuclear magnetic resonance (1 H NMR), 13 C NMR, MS, and infrared (IR) confirmed the proposed chemical structures of impurities. Identification, structural characterization, formation, and their synthesis was first reported in this study. The impurity 11 was crystallized and structure was solved by single crystal X-ray diffraction. Copyright © 2017 John Wiley & Sons, Ltd.

Reversible Data Hiding in FTIR Microspectroscopy Images with Tamper Indication and Payload Error Correction.

Fourier transform infrared (FTIR) microspectroscopy images contain information from the whole infrared spectrum used for microspectroscopic analyses. In combination with the FTIR image, visible light images are used to depict the area from which the FTIR spectral image was sampled. These two images are traditionally acquired as separate files. This paper proposes a histogram shifting-based data hiding technique to embed visible light images in FTIR spectral images producing single entities. The primary objective is to improve data management efficiency. Secondary objectives are confidentiality, availability, and reliability. Since the integrity of biomedical data is vital, the proposed method applies reversible data hiding. After extraction of the embedded data, the FTIR image is reversed to its original state. Furthermore, the proposed method applies authentication tags generated with keyed Hash-Based Message Authentication Codes (HMAC) to detect tampered or corrupted areas of FTIR images. The experimental results show that the FTIR spectral images carrying the payload maintain good perceptual fidelity and the payload can be reliably recovered even after bit flipping or cropping attacks. It has been also shown that extraction successfully removes all modifications caused by the payload. Finally, authentication tags successfully indicated tampered FTIR image areas.

Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models.

An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows' physiological status. In this context, and to take advantage of these existing models, the purpose of this work was to evaluate whether a spectral standardization method can enable the use of multiple equations within a network of different FT-MIR spectrometers. The piecewise direct standardization method was used, matching "slave" instruments to a common reference, the "master." The effect of standardization on network reproducibility was assessed on 66 instruments from 3 different brands by comparing the spectral variability of the slaves and the master with and without standardization. With standardization, the global Mahalanobis distance from the slave spectra to the master spectra was reduced on average from 2,655.9 to 14.3, representing a significant reduction of noninformative spectral variability. The transfer of models from instrument to instrument was tested using 3 FT-MIR models predicting (1) the quantity of daily methane emitted by dairy cows, (2) the concentration of polyunsaturated fatty acids in milk, and (3) the fresh cheese yield. The differences, in terms of root mean squared error, between master predictions and slave predictions were reduced after standardization on average from 103 to 17 g/d, from 0.0315 to 0.0045 g/100 mL of milk, and from 2.55 to 0.49 g of curd/100 g of milk, respectively. For all the models, standard deviations of predictions among all the instruments were also reduced by 5.11 times for methane, 5.01 times for polyunsaturated fatty acids, and 7.05 times for fresh cheese yield, showing an improvement of prediction reproducibility within the network. Regarding the results obtained, spectral standardization allows the transfer and use of multiple models on all instruments as well as the improvement of spectral and prediction reproducibility within the network. The method makes the models universal, thereby offering opportunities for data exchange and the creation and use of common robust models at an international level to provide more information to the dairy sector from direct analysis of milk.

Quantitative analysis of anti-inflammatory drugs using FTIR-ATR spectrometry.

Four simple, accurate, sensitive and economic Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopic (ATR-FTIR) methods have been developed for the quantitative estimation of some non-steroidal anti-inflammatory drugs. The first method involves the determination of Etodolac by direct measurement of the absorbance at 1716cm-1. In the second method, the second derivative of the IR spectra of Tolfenamic acid and its reported degradation product (2-chlorobenzoic acid) was used and the amplitudes were measured at 1084.27cm-1 and 1056.02cm-1 for Tolfenamic acid and 2-chlorobenzoic acid, respectively. The third method used the first derivative of the IR spectra of Bumadizone and its reported degradation product, N,N-diphenylhydrazine and the amplitudes were measured at 2874.98cm-1 and 2160.32cm-1 for Bumadizone and N,N-diphenylhydrazine, respectively. The fourth method depends on measuring the amplitude of Diacerein at 1059.18cm-1 and of rhein, its reported degradation product, at 1079.32cm-1 in their first derivative spectra. The four methods were successfully applied on the pharmaceutical formulations by extracting the active constituent in chloroform and the extract was directly measured in liquid phase mode using a specific cell. Moreover, validation of these methods was carried out following International Conference of Harmonisation (ICH) guidelines.

The Studies of Archaeological Pottery with the Use of Selected Analytical Techniques.

Modern analytical methods play an important role in archaeological objects, including ceramics. This review focuses on the use of analytical methods such as: gas chromatography coupled mass spectrometry, Fourier transform infrared spectroscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS), powder X-ray diffraction with thermal analysis to study the chemical and mineralogical composition of archaeological samples and organic residues preserved inside. In this paper, special attention was paid to the ToF-SIMS method, which allows the determination of characteristic ions on the surface of ceramic samples.

Use of ATR-FTIR spectroscopy coupled with chemometrics for the authentication of avocado oil in ternary mixtures with sunflower and soybean oils.

Avocado oil is a high-value and nutraceutical oil whose authentication is very important since the addition of low-cost oils could lower its beneficial properties. Mid-FTIR spectroscopy combined with chemometrics was used to detect and quantify adulteration of avocado oil with sunflower and soybean oils in a ternary mixture. Thirty-seven laboratory-prepared adulterated samples and 20 pure avocado oil samples were evaluated. The adulterated oil amount ranged from 2% to 50% (w/w) in avocado oil. A soft independent modelling class analogy (SIMCA) model was developed to discriminate between pure and adulterated samples. The model showed recognition and rejection rate of 100% and proper classification in external validation. A partial least square (PLS) algorithm was used to estimate the percentage of adulteration. The PLS model showed values of R(2) > 0.9961, standard errors of calibration (SEC) in the range of 0.3963-0.7881, standard errors of prediction (SEP estimated) between 0.6483 and 0.9707, and good prediction performances in external validation. The results showed that mid-FTIR spectroscopy could be an accurate and reliable technique for qualitative and quantitative analysis of avocado oil in ternary mixtures.

Biofluid infrared spectro-diagnostics: pre-analytical considerations for clinical applications.

Several proof-of-concept studies on the vibrational spectroscopy of biofluids have demonstrated that the methodology has promising potential as a clinical diagnostic tool. However, these studies also show that there is a lack of a standardised protocol in sample handling and preparation prior to spectroscopic analysis. One of the most important sources of analytical errors is the pre-analytical phase. For the technique to be translated into clinics, it is clear that a very strict protocol needs to be established for such biological samples. This study focuses on some of the aspects of the pre-analytical phase in the development of the high-throughput Fourier Transform Infrared (FTIR) spectroscopy of some of the most common biofluids such as serum, plasma and bile. Pre-analytical considerations that can impact either the samples (solvents, anti-coagulants, freeze-thaw cycles…) and/or spectroscopic analysis (sample preparation such as drying, deposit methods, volumes, substrates, operators dependence…) and consequently the quality and the reproducibility of spectral data will be discussed in this report.

[Influence of spectral interferences on the results of quartz determination by infrared spectrometry]. / Wplyw interferencji spektralnych na wyniki oznaczen kwarcu metoda spektrometrii w podczerwieni.

BACKGROUND: Determination of quartz by Fourier transform infrared spectrometry (FTIR) is not specific: the obtained results are influenced by matrix components, some of which cause spectral interference. The aim of the study was to evaluate the effect of dust components responsible for spectral interference with quartz on the results of its determinations, and to develop methods to minimize the effects of interferences. MATERIAL AND METHODS: Investigation of interferent effects were conducted using respirable dusts: quartz SRM 1878a, cristobalite SRM 1879a, synthetic amorphous silica (Zeosil) and feldspar, albite and kaolinite. For the study 17 mixtures with quartz and interferents at concentrations from 10 to 90% were prepared. Determinations of quartz were carried out by the KBr disc method. RESULTS: In mixtures of quartz with interferents, the results based on bands 798-779 cm-1 were overestimated by 10-55%, while those based on band 695 cm-1 were closer to the true content of quartz. It was found that the best methods able to decrease the impact of spectral interference are: scaled subtraction of IR spectra of feldspar or kaolinite analysed in nonashed samples, correction curve for kaolinite also investigated in nonashed samples with quartz-content calculation based on band 695 cm-1 in mixtures with cristobalite, amorphous silica or kaolinite in ashed samples. CONCLUSIONS: The study indicates the need to identify spectral interferences in dust when determining crystalline silica by FT-IR and to take actions to minimize their impact on the obtained results.

Standardization of milk mid-infrared spectra from a European dairy network.

The goal of this study was to find a procedure to standardize dairy milk mid-infrared spectra from different Fourier transform mid-infrared spectrophotometers (different brands or models) inside a European dairy network to create new farm-management indicators (e.g., fertility, health, feed, environmental impact) based on milk infrared spectra. This step is necessary to create common spectral databases, allowing the building of statistical tools, to be used by all instruments of the network. The method used was piecewise direct standardization (PDS), which matches slave-instrument spectra on master-instrument spectra. To evaluate the possibility of using common equations on different instruments, the PDS method was tested on a set of milk samples measured on each machine, and an equation predicting fat content of milk is applied on all. Regressions were performed between master and slaves fat predictions, before and after PDS. Bias and root mean square error between predictions were decreased after PDS, respectively, from 0.3781 to 0.0000 and from 0.4609 to 0.0156 (g of fat/100mL of milk). The stability over time of these results was confirmed by an application of the coefficients created by PDS 1 mo later on the slave spectra. These preliminary results showed that the PDS method permits a reduction of the inherent spectral variability between instruments, allowing the merging of Fourier transform mid-infrared milk spectra from different instruments into a common database, the creation of new types of dairy farm management indicators, and the use of these common calibrations for all Fourier transform mid-infrared instruments of the European dairy network.

Characterization of the initial level and migration of silicone oil lubricant in empty prefilled syringes for biologics using infrared spectroscopy.

Glass prefillable syringes are lubricated with silicone oil to ensure functionality and a consistent injection for the end user. If excessive silicone is applied, droplets could potentially result in aggregation of sensitive biopharmaceuticals or clouding of the solution. Therefore, monitoring and optimization of the applied silicone layer is critical for prefilled syringe development. The hydrophobic properties of silicone oil, the potential for assay interference, and the very small quantities applied to prefilled syringes present a challenge for the development of a suitable assay. In this work we present a rapid and simple Fourier transform infrared (FTIR) spectroscopy method for quantitation of total silicone levels applied to prefilled syringes. Level-dependent silicone oil migration occurred over time for empty prefilled syringes stored tip-up. However, migration from all prefilled syringes with between 0.25 and 0.8 mg of initial silicone oil resulted in a stable limiting minimum level of between 0.15 and 0.26 mg of silicone in the syringe reached after 1 to 4 years of empty tip-up storage. The results of the FTIR assay correlated well with non-destructive reflectometry characterization of the syringes. This assay can provide valuable data for selection of a robust initial silicone oil target and quality control of prefilled syringes intended for biopharmaceuticals. LAY ABSTRACT: Glass prefillable syringes are lubricated with silicone oil to ensure functionality and a consistent injection for the end user. If excessive silicone is applied, droplets could potentially result in aggregation of sensitive biopharmaceuticals or clouding of the solution. Therefore, monitoring and optimization of the applied silicone layer is critical for prefilled syringe development. The hydrophobic properties of silicone oil, the potential for assay interference, and the very small quantities applied to prefilled syringes present a challenge for the development of a suitable assay. In this work we present a rapid and simple Fourier transform infrared (FTIR) spectroscopy method for quantitation of total silicone levels applied to prefilled syringes. Level-dependent silicone oil migration occurred over time for empty prefilled syringes stored tip-up. However, migration from all prefilled syringes with between 0.25 and 0.8 mg of initial silicone oil resulted in a stable limiting minimum level of between 0.15 and 0.26 mg of silicone in the syringe reached after 1 to 4 years of empty tip-up storage. The results of the FTIR assay correlated well with non-destructive reflectometry characterization of the syringes. This assay can provide valuable data for selection of a robust initial silicone oil target and quality control of prefilled syringes intended for biopharmaceuticals.

Automated acid and base number determination of mineral-based lubricants by fourier transform infrared spectroscopy: commercial laboratory evaluation.

The Fluid Life Corporation assessed and implemented Fourier transform infrared spectroscopy (FTIR)-based methods using American Society for Testing and Materials (ASTM)-like stoichiometric reactions for determination of acid and base number for in-service mineral-based oils. The basic protocols, quality control procedures, calibration, validation, and performance of these new quantitative methods are assessed. ASTM correspondence is attained using a mixed-mode calibration, using primary reference standards to anchor the calibration, supplemented by representative sample lubricants analyzed by ASTM procedures. A partial least squares calibration is devised by combining primary acid/base reference standards and representative samples, focusing on the main spectral stoichiometric response with chemometrics assisting in accounting for matrix variability. FTIR(AN/BN) methodology is precise, accurate, and free of most interference that affects ASTM D664 and D4739 results. Extensive side-by-side operational runs produced normally distributed differences with mean differences close to zero and standard deviations of 0.18 and 0.26 mg KOH/g, respectively. Statistically, the FTIR methods are a direct match to the ASTM methods, with superior performance in terms of analytical throughput, preparation time, and solvent use. FTIR(AN/BN) analysis is a viable, significant advance for in-service lubricant analysis, providing an economic means of trending samples instead of tedious and expensive conventional ASTM(AN/BN) procedures.

[The effect of Tween-80 on the differentiation of Trichophyton mentagrophytes and Trichophyton rubrum strains with FT-IR spectroscopy]. / Trichophyton mentagrophytes ve Trichophyton rubrum kökenlerinin FT-IR spektroskopi ile ayriminda Tween-80 etkisi.

Trichophyton mentagrophytes and Trichophyton rubrum, are two of the frequently identified dermatophyte species in routine microbiology laboratories. Although newer technologies may assist in species-level identification, direct application of these methods usually require improvement in order to obtain reliable identification of these species. Earlier data have shown that dermatophytes may be identified with FT-IR spectroscopy although there are some limitations. In particular, the organic bond ranges in FT-IR spectra showed more irregularity because of the eucaryotic complexity of the molds. In this study, Tween-80 which is an inorganic molecule, was added to the dermatophyte growth medium in order to investigate its effect on FT-IR spectroscopy analysis of dermatophytes. Nine reference dermatophyte strains [5 T.mentagrophytes complex (T.asteroides CBS 424.63, T.erinacei CBS 344.79, CBS 511.73, CBS 677.86, T.mentagrophytes CBS 110.65) and 4 T.rubrum complex strains with different morphotypes (T.fluviomuniense CBS 592.68, T.kuryangei CBS 422.67, T.raubitschekii CBS 102856, T.rubrum CBS 392.58)] were included in the study. All strains were cultured on Sabouraud glucose agar either with or without 1% Tween-80 for three weeks. After the incubation period, superficial scrapings from each dermatophyte colony were analyzed using FT-IR spectroscopy. All measurements were performed in transmission mode between 4400 and 400 cm-1. Numerous spectral window data were analyzed by principal component analysis and hierarchical clustering was performed. The second derivations of spectral ranges revealed clear grouping of T.mentagrophytes complex and T.rubrum complex in association over five separate spectral ranges. The findings also showed that while all of the T.mentagrophytes strains contained lipid compounds in their mold structure after Tween-80 incubation (p< 0.025), T.rubrum strains did not. Based on these results, it was concluded that culture medium containing Tween-80 was sufficient to enable differentiation of T.mentagrophytes complex from T.rubrum complex by FT-IR spectroscopy. This effect might be attributed to the possible transfer of lipid compounds from culture to cell structure during growth. Further studies with the use of large number of reference strains and clinical isolates exposed to different environmental factors, such as antifungal agents and inorganic ions, are needed to support these data indicating favorable effect of Tween-80 on the differentiation of T.mentagrophytes and T.rubrum complexes by FT-IR spectroscopy.

Rapid measurement of human milk macronutrients in the neonatal intensive care unit: accuracy and precision of fourier transform mid-infrared spectroscopy.

BACKGROUND: Although it is well established that human milk varies widely in macronutrient content, it remains common for human milk fortification for premature infants to be based on historic mean values. As a result, those caring for premature infants often underestimate protein intake. Rapid precise measurement of human milk protein, fat, and lactose to allow individualized fortification has been proposed for decades but remains elusive due to technical challenges. OBJECTIVE: This study aimed to evaluate the accuracy and precision of a Fourier transform (FT) mid-infrared (IR) spectroscope in the neonatal intensive care unit to measure human milk fat, total protein, lactose, and calculated energy compared with standard chemical analyses. METHODS: One hundred sixteen breast milk samples across lactation stages from women who delivered at term (n = 69) and preterm (n = 5) were analyzed with the FT mid-IR spectroscope and with standard chemical methods. Ten of the samples were tested in replicate using the FT mid-IR spectroscope to determine repeatability. RESULTS: The agreement between the FT mid-IR spectroscope analysis and reference methods was high for protein and fat and moderate for lactose and energy. The intra-assay coefficients of variation for all outcomes were less than 3%. CONCLUSION: The FT mid-IR spectroscope demonstrated high accuracy in measurement of total protein and fat of preterm and term milk with high precision.