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Find video protocols related to scientific articles indexed in Pubmed.
Effect of netazepide, a gastrin/CCK2 receptor antagonist, on gastric acid secretion and rabeprazole-induced hypergastrinaemia in healthy subjects.
Br J Clin Pharmacol
PUBLISHED: 10-16-2014
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To compare gastric acid suppression by netazepide, a gastrin/CCK2 receptor antagonist, with that by a proton pump inhibitor (PPI), and to determine if netazepide can prevent the trophic effects of PPI-induced hypergastrinaemia.
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Fast and robust discrimination of almonds (Prunus amygdalus) with respect to their bitterness by using near infrared and partial least squares-discriminant analysis.
Food Chem
PUBLISHED: 02-05-2014
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In this study, near-infrared spectroscopy (NIR) coupled to chemometrics is used to develop a fast, simple, non-destructive and robust method for discriminating sweet and bitter almonds (Prunus amygdalus) by the in situ measurement of the kernel surface without any sample pre-treatment. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) models were built to discriminate both types of almonds, obtaining high levels of sensitivity and specificity for both classes, with more than 95% of the samples correctly classified and discriminated. Moreover, the almonds were also analysed by Raman spectroscopy, the reference technique for this type of analysis, to validate and confirm the results obtained by NIR.
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Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms.
J Pharm Sci
PUBLISHED: 01-22-2013
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The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed.
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Quantitatively different, yet qualitatively alike: a meta-analysis of the mouse core gut microbiome with a view towards the human gut microbiome.
PLoS ONE
PUBLISHED: 01-01-2013
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A number of human diseases such as obesity and diabetes are associated with changes or imbalances in the gut microbiota (GM). Laboratory mice are commonly used as experimental models for such disorders. The introduction and dynamic development of next generation sequencing techniques have enabled detailed mapping of the GM of both humans and animal models. Nevertheless there is still a significant knowledge gap regarding the human and mouse common GM core and thus the applicability of the latter as an animal model. The aim of the present study was to identify inter- and intra-individual differences and similarities between the GM composition of particular mouse strains and humans.
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Influence of solvent evaporation rate and formulation factors on solid dispersion physical stability.
Eur J Pharm Sci
PUBLISHED: 07-12-2011
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New chemical entities (NCEs) often show poor water solubility necessitating solid dispersion formulation. The aim of the current study is to employ design of experiments in investigating the influence of one critical process factor (solvent evaporation rate) and two formulation factors (PVP:piroxicam ratio (PVP:PRX) and PVP molecular weight (P(MW))) on the physical stability of PRX solid dispersion prepared by the solvent evaporation method. The results showed the rank order of an increase in factors contributing to a decrease in the extent of PRX nucleation being evaporation rate>PVP:PRX>P(MW). The same rank order was found for the decrease in the extent of PRX crystal growth in PVP matrices from day 0 up to day 12. However, after 12days the rank became PVP:PRX>evaporation rate>P(MW). The effects of an increase in evaporation rate and PVP:PRX ratio in stabilizing PRX were of the same order of magnitude, while the effect from P(MW) was much smaller. The findings were confirmed by XRPD. FT-IR showed that PRX recrystallization in the PVP matrix followed Ostwalds step rule, and an increase in the three factors all led to increased hydrogen bonding interaction between PRX and PVP. The present study showed the applicability of the Quality by Design approach in solid dispersion research, and highlights the need for multifactorial analysis.
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Calibration transfer for excitation-emission fluorescence measurements.
Anal. Chim. Acta
PUBLISHED: 04-05-2011
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The main part of the wide array of different calibration transfer methods found in literature is dedicated to two-way data arrangements (m×n matrices). Less work has been done within the area of calibration transfer for three-way data structures (m×n×l tensors) such as calibrations made for excitation-emission-matrix (EEM) fluorescence spectra. There are two possible ways to attack the problem for EEM transfer. Either the tensors are unfolded to two-way data, whereby the existing methods can be applied, or new methods dedicated to three-way calibration transfer have to be developed. This paper presents and compares both. It was possible to make a local linear pixel-based model that could be used for transfer of EEMs. This new method has a similar performance to the classical methods found in literature, direct- and piecewise direct standardization. The three-way advantages made it possible to use as few as four samples to build useable transfer models. Care has to be taken though when choosing the samples. When subset recalibration of the systems is compared to calibration transfer, better performance is seen for the transferred calibrations. Overall the three-way calibration transfer methods have a slightly better performance than the two-way methods.
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Particle size dependence of polymorphism in spray-dried mannitol.
Eur J Pharm Sci
PUBLISHED: 03-25-2011
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The purpose of this project was to investigate the polymorphic variation of spray-dried mannitol model formulations as a function of particle size. Spray-dried powders with varying mannitol polymorphs were produced by adjusting process parameters, using co-solvent and adding a model protein (lysozyme). The obtained dry powders were dispersed into different size fractions using a Next Generation Pharmaceutical Impactor. The mannitol polymorphs in the different size fractions were analyzed using X-ray powder diffraction (XRPD), Fourier transform near infrared (FT-NIR) and Raman spectroscopy. Chemometrics was applied to interpret the FT-NIR and Raman spectra. Different spray-dried mannitol systems were established in this study, which contain mixtures of ?- and ?-mannitol. The XRPD, FT-NIR and Raman studies showed that the use of ethanol as a co-solvent increased the amount of ?-mannitol in the smaller particles. The addition of low levels of lysozyme resulted in more ?-mannitol in the smaller particles, while an increased content of lysozyme in spray-dried mannitol system resulted in more ?-mannitol in the smaller particle size fraction. In conclusion spray-drying of mannitol based formulations can result in variation in the solid state composition of mannitol as a function of particle size. This finding may be clinically relevant and underlines the need for proper process control of inhalable dry powder produced by spray-drying.
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Initial adhesion of Listeria monocytogenes to solid surfaces under liquid flow.
Int. J. Food Microbiol.
PUBLISHED: 03-22-2011
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Some strains of the food borne pathogen Listeria monocytogenes persist in food processing environments. The exact reason behind this phenomenon is not known, but strain differences in the ability to adhere to solid surfaces could offer an explanation. In the present work, initial adhesion of nine strains of L. monocytogenes was investigated under liquid flow at two levels of shear stress on six different surfaces using a flow chamber set-up with microscopy measurements. The surfaces tested were glass and PVC, and glass coated with beef extract, casein, and homogenised and unhomogenised milk. In addition, the effect of prior environmental stress (5% NaCl, low nutrient availability) on initial adhesion was investigated. The hydrophobicity of the investigated surfaces was determined by contact angle measurements and the surface properties of the investigated L. monocytogenes strains were determined using Microbial Adhesion To Solvents (MATS). All surfaces with the exception of PVC were found to be hydrophilic. Strain differences were found to significantly influence the initial adhesion rate (IAR) of all nine strains to all the surfaces (p<0.05) at both low and high shear stress. Furthermore, there was a significant effect of the surfaces tested (p<0.05) in the adhesion ability of almost all strains. The IAR was affected by flow rate (shear stress) as seen by a decrease in adhesion at high shear stress for most strains. A significant effect of interactions between strain-surface and strain-shear stress (p<0.001) was observed but not of interactions between surface-shear stress. No correlation between surface hydrophobicity and IAR was observed. Addition of 5% NaCl during propagation resulted in a decrease in IAR whilst propagation in low nutrient media caused an increase indicating a general change in surface characteristics under these conditions. Known persisting strains did not display general better adherence.
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Internal and external validation strategies for the evaluation of long-term effects in NIR calibration models.
J. Agric. Food Chem.
PUBLISHED: 02-11-2011
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Some of the practical aspects of long-term calibration-set building are presented in this study. A calibration model able to predict the Kolbach index for brewing malt is defined, and four different validations and resampling schemes were applied to determine its real predictive power. The results obtained demonstrated that one single performance criterion might be not sufficient and can lead to over- or underestimation of the model quality. Comparing a simple leave-one-sample-out cross-validation (CV) with two more challenging CVs with leave-N-samples-out, where the resamplings were repeated 200 times, it is demonstrated that the error of prediction value has an uncertainty, and these values change according to the type and the number of validation samples. Then, two kinds of test-set validations were applied, using data blocks based on the sample collections year, demonstrating that it is necessary to consider long-term effects on NIR calibrations and to be conservative in the number of factors selected. The conclusion is that one should be modest in reporting the prediction error because it changes according to the type of validation used to estimate it and it is necessary to consider the long-term effects.
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Determination of dry matter content in potato tubers by low-field nuclear magnetic resonance (LF-NMR).
J. Agric. Food Chem.
PUBLISHED: 09-22-2010
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The objective of this study was to develop a calibration model between time-domain low-field nuclear magnetic resonance (LF-NMR) measurements and dry matter (DM) content in single potatoes. An extensive sampling procedure was used to collect 210 potatoes from eight cultivars with a wide range in DM content, ranging from 16 to 28%. The exponential NMR relaxation curves were resolved into four mono-exponential components using a number of solution diagnostics. Partial least-squares (PLS) regression between NMR parameters (relaxation time constants T(2,1-4) and magnitudes M(0,1-4)) and DM content resulted in a model with low error (RMSECV, 0.71; RMSEP, 0.60) and high correlation (r(CV), 0.97; r(test), 0.98) between predicted and actual DM content. Correlation between DM content and each of the proton populations revealed that M(0,1) (T(2,1), 3.6 ms; SD, 0.3 ms; r, 0.95) and M(0,4) (T(2,4), 508 ms; SD, 53 ms; r, -0.90) were the major contributors to the PLS regression model.
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Multi-way based calibration transfer between two Raman spectrometers.
Analyst
PUBLISHED: 04-19-2010
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A standardization algorithm based on the application of Tucker3 models on the tensorized measurement signals is proposed to transfer calibration information between two Raman spectrometers. The secondary instrument in this study is a low cost and portable CCD based unit employing an efficient 532 nm green laser. The primary instrument is a high performance Fourier-transform based laboratory instrument using a low efficiency NIR laser at 1064 nm, albeit with very limited sample fluorescence interference. This work is a first investigation of calibration transfer on Raman spectral data which include different values of fluorescent background from one instrument to the other. The spectra of a small set of calibration samples are measured on both spectrometers. Using the ability of Tucker3 to estimate missing values in tensorized data, we reconstruct the spectrum of a new sample on the primary instrument based on its measured response of the secondary instrument without the need for constructing an explicit transfer model. This way spectra of a prediction sample measured on one spectrometer can be successfully transferred to another spectrometer as if it has been measured directly on the latter. Hence, the task of calibration transfer among instruments is posed as a missing data problem. A discrete wavelet transform is performed to improve the predictive ability. Performance criteria for judging the success of the calibration transfer are reported as the standard error of prediction for estimation of samples in a prediction set. By comparison, the proposed Tucker3 based standardization method shows a better performance as compared to piecewise direct standardization. The method is expected to be applicable for performing calibration transfer using data from instruments other than Raman spectrometers.
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Determination of an acceptable level of spectral data compression by discrete wavelet transforms.
Anal. Chim. Acta
PUBLISHED: 01-23-2010
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Today, due to the ever increasing amount of data generated by analytical instruments, good compression methods are desired to keep computation time acceptable. The lower the volume and noise content of data, the easier it becomes to investigate and interpret the modeling results. Discrete Wavelet Transform (DWT) is an effective data compression and noise suppression tool. Compression can be performed at different levels, in each, the size of signal part of the data reduces to half the size. This work includes an approach for determining an acceptable level of compression of data where the aim is to achieve minimal loss of information and no significant change in the structure of data, which could mean, e.g. no loss in predictive ability or the effective rank of the data-set. The method is based on estimation of the Singular Values (SVs) from a data matrix and the Singular Values at each level of compression followed by the application of Median Absolute Deviation (MAD) of the correlation between original SVs and compression SVs as a simple statistical test for the determination of the optimum level of compression. We illustrate the method using FT-Raman data from aqueous solutions of three sugars (glucose, trehalose and sucrose) and NMR data from mixtures of three alcohols. A sudden change in prediction error sum of square plots from Partial Least Squares (PLS) modeling confirms the results from MAD statistics.
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Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults.
PLoS ONE
PUBLISHED: 01-11-2010
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Recent evidence suggests that there is a link between metabolic diseases and bacterial populations in the gut. The aim of this study was to assess the differences between the composition of the intestinal microbiota in humans with type 2 diabetes and non-diabetic persons as control.
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Effect of gel firmness at cutting time, pH, and temperature on rennet coagulation and syneresis: an in situ 1H NMR relaxation study.
J. Agric. Food Chem.
PUBLISHED: 01-07-2010
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The objective of this study was to monitor rennet-induced milk gel formation and mechanically induced gel syneresis in situ by low-field NMR. pH, temperature, and gel firmness at cutting time were varied in a factorial design. The new curve-fitting method Doubleslicing revealed that during coagulation two proton populations with distinct transverse relaxation times (T2,1=181, T2,2=465 ms) were present in fractions (f1=98.9%, f2=1.1%). Mechanical cutting of the gel in the NMR tube induced macrosyneresis, which led to the appearance of an additional proton population (T2,3=1500-2200 ms) identified as whey. On the basis of NMR quantification of whey water the syneresis rate was calculated and found to be significantly dependent on pH and temperature.
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Metabolomic insight into soy sauce through (1)H NMR spectroscopy.
J. Agric. Food Chem.
PUBLISHED: 07-14-2009
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Soy sauce, a well-known seasoning in Asia and throughout the world, consists of many metabolites that are produced during fermentation or aging and that have various health benefits. However, their comprehensive assessment has been limited due to targeted or instrumentally specific analysis. This paper presents for the first time a metabolic characterization of soy sauce, especially that aged up to 12 years, to obtain a global understanding of the metabolic variations through (1)H NMR spectroscopy coupled with multivariate pattern recognition techniques. Elevated amino acids and organic acids and the consumption of carbohydrate were associated with continuous involvement of microflora in aging for 12 years. In particular, continuous increases in the levels of betaine were found during aging for up to 12 years, demonstrating that microbial- or enzyme-related metabolites were also coupled with osmotolerant or halophilic bacteria present during aging. This work provides global insights into soy sauce through a (1)H NMR-based metabolomic approach that enhances the current understanding of the holistic metabolome and allows assessment of soy sauce quality.
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Evidence of vintage effects on grape wines using 1H NMR-based metabolomic study.
Anal. Chim. Acta
PUBLISHED: 05-15-2009
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The chemical composition of grape wines varies with grape variety, environmental factors of climate and soil, and bacterial strains, which can each affect the wine quality. Using (1)H NMR analysis coupled with multivariate statistical data sets, we investigated the effects of grape vintage on metabolic profiles of wine and the relationship between wine metabolites and meteorological data. Principal component analysis (PCA) showed a clear differentiation between Meoru wines that were vinified with the same yeast strain and Meoru grapes harvested from the same vineyard but with a different vintage. The metabolites contributing to the differentiation were identified as 2,3-butandiol, lactic acid, alanine, proline, gamma-aminobutyric acid (GABA), choline, and polyphenols, by complementary PCA loading plot. Markedly higher levels of proline, lactic acid and polyphenols were observed in the 2006 vintage wines compared to those of 2007 vintage, showing excellent agreement with the meteorological data that the sun-exposed time and rainfall in 2006 were approximately two times more and four times less, respectively, than those in 2007. These results revealed the important role of climate during ripening period in the chemical compositions of the grape. This study highlights the reliability of NMR-based metabolomic data by integration with meteorological data in characterizing wine or grape.
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Metabolomic studies on geographical grapes and their wines using 1H NMR analysis coupled with multivariate statistics.
J. Agric. Food Chem.
PUBLISHED: 02-06-2009
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Environmental vineyard conditions can affect the chemical composition or metabolites of grapes and their wines. Grapes grown in three different regions of South Korea were collected and separated into pulp, skin, and seed. The grapes were also vinified after crushing. (1)H NMR spectroscopy with pattern recognition (PR) methods was used to investigate the metabolic differences in pulp, skin, seed, and wines from the different regions. Discriminatory compounds among the grapes were Na, Ca, K, malate, citrate, threonine, alanine, proline, and trigonelline according to PR methods of principal component analysis (PCA) or partial least-squares discriminant analysis (PLS-DA). Grapes grown in regions with high sun exposure and low rainfall showed higher levels of sugar, proline, Na, and Ca together with lower levels of malate, citrate, alanine, threonine, and trigonelline than those grown in regions with relatively low sun exposure and high rainfall. Environmental effects were also observed in the complementary wines. This study demonstrates that (1)H NMR-based metabolomics coupled with multivariate statistical data sets can be useful for determining grape and wine quality.
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(1)H NMR-based metabolomic approach for understanding the fermentation behaviors of wine yeast strains.
Anal. Chem.
PUBLISHED: 01-01-2009
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(1)H NMR spectroscopy coupled with multivariate statistical analysis was used for the first time to investigate metabolic changes in musts during alcoholic fermentation and wines during aging. Three Saccharomyces cerevisiae yeast strains (RC-212, KIV-1116, and KUBY-501) were also evaluated for their impacts on the metabolic changes in must and wine. Pattern recognition (PR) methods, including PCA, PLS-DA, and OPLS-DA scores plots, showed clear differences for metabolites among musts or wines for each fermentation stage up to 6 months. Metabolites responsible for the differentiation were identified as valine, 2,3-butanediol (2,3-BD), pyruvate, succinate, proline, citrate, glycerol, malate, tartarate, glucose, N-methylnicotinic acid (NMNA), and polyphenol compounds. PCA scores plots showed continuous movements away from days 1 to 8 in all musts for all yeast strains, indicating continuous and active fermentation. During alcoholic fermentation, the highest levels of 2,3-BD, succinate, and glycerol were found in musts with the KIV-1116 strain, which showed the fastest fermentation or highest fermentative activity of the three strains, whereas the KUBY-501 strain showed the slowest fermentative activity. This study highlights the applicability of NMR-based metabolomics for monitoring wine fermentation and evaluating the fermentative characteristics of yeast strains.
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Relationship between meat toughness and properties of connective tissue from cows and young bulls heat treated at low temperatures for prolonged times.
Meat Sci.
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The aim of the current study was to elucidate whether cows and young bulls require different combinations of heating temperature and heating time to reduce toughness of the meat. The combined effect of heating temperature and time on toughness of semitendinosus muscle from the two categories of beef was investigated and the relationship to properties of connective tissue was examined. Measurements of toughness, collagen solubility, cathepsin activity and protein denaturation of beef semitendinosus heated at temperatures between 53°C and 63°C for up to 19 1/2 h were conducted. The results revealed that slightly higher temperatures and prolonged heating times were required to reduce toughness of semitendinosus from cows to the same level as in young bulls. Reduced toughness of semitendinosus as a result of low temperature for prolonged time is suggested to result from weakening of the connective tissue, caused partly by denaturation or conformational changes of the proteins and/or by solubilization of collagen.
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Fast-track to a solid dispersion formulation using multi-way analysis of complex interactions.
J Pharm Sci
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Several factors with complex interactions influence the physical stability of solid dispersions, thus highlighting the need for efficient experimental design together with robust and simple multivariate model. Design of Experiments together with ANalysis Of VAriance (ANOVA) model is one of the central tools when establishing a design space according to the Quality by Design (QbD) approach. However, higher order interaction terms are often significant in these ANOVA models, making the final model difficult to interpret and understand. As this is ordinarily the purpose of applying ANOVA, it poses an obvious problem. In the current study, the GEneralized Multiplicative ANOVA (GEMANOVA) model is proposed as an alternative for the ANOVA model. Two complex multivariate data sets obtained by monitoring the physical stability of a solid dispersion with image analysis and X-ray powder diffraction (XRPD) as responses were subjected to GEMANOVA analysis. The results showed that the obtained GEMANOVA model was easier to interpret and understand than the additive ANOVA model. Furthermore, the GEMANOVA model has additional advantages such as the possibility of readily including multivariate responses (e.g., an entire spectral data set), model uniqueness, and curve resolution abilities.
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A novel image analysis methodology for online monitoring of nucleation and crystal growth during solid state phase transformations.
Int J Pharm
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This study focuses on the development of an automated image analysis method to extract information on nucleation and crystal growth from polarized light micrographs. Using the developed image analysis method, four parameters related to nucleation and crystal growth could be extracted from the images. These parameters were crystalline count (applied as a measure of nucleation), percentage area coverage, average equivalent diameter and average crystalline area (three last parameters applied as a measure for crystal growth). The developed image analysis method was used to investigate two pharmaceutically relevant case studies: first, nitrendipine antisolvent crystallization, and second, recrystallization of amorphous piroxicam solid dispersion in an aqueous environment. In both case studies, an amorphous-to-crystalline phase transformation were observed, which were successfully monitored using real-time Raman spectroscopy. For the both case studies, the parameters related to crystallization kinetics estimated by image analysis were in close agreement with the parameters estimated by Raman spectroscopy. The developed image analysis method proved to be a valuable tool for quantitative monitoring of nucleation and crystal growth with an obvious potential for high throughput screening.
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Current Advances and Future Trends in Characterizing Poorly Water-Soluble Drugs Using Spectroscopic, Imaging and Data Analytical Techniques.
Curr. Pharm. Des.
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A common feature of many new analytical techniques that allows fast and non-destructive analysis of poorly-water-soluble drug is that they generate a large amount of data with a multivariate character within a short time frame, which in turn highlights the need for advanced data analytical methods in extracting information from the complex data set. The current review critically examines how spectroscopy and imaging techniques can be utilized for fast and non-destructive characterization of solid state poorly water-soluble drug formulations. The first part of the present review describes the basics behind many of the currently used methods including Raman, near infrared (NIR), infrared (IR) spectroscopy and X-ray powder diffractometry. Key emphasis was placed on a critical review of the currently used spectral preprocessing methods, and the influence of selected preprocessing on spectral data sets is exemplified. Further the existing uni- and multivariate spectral data analytical methods in analyzing complex spectral data sets are reviewed, covering estimation of spectral peak moments, peak modeling, variations of Principal Component Analysis (PCA), variations of Partial Least Squares (PLS) analysis and Multivariate Curve Resolution (MCR). The second part of the present review discusses hyperspectral imaging, UV imaging, optical microscopy imaging and process imaging methods suitable for characterization of poorly-water-soluble solid state drug formulations. Image analytical techniques suitable for analyzing hyperspectral image data set are described. Further, the application of various image analytical techniques leading to the estimation of nucleation and crystal growth rates from polarized light microscopy is described.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.