Screening and HPLC methods for carotenoids in sweetpotato, cassava and maize for plant breeding trials

Analytical methods for sweetpotato, cassava and maize were developed. In orange and salmon-fleshed sweetpotatoes, (all-E)-beta-carotene predominated and results of spectrophotometric screening and HPLC quantification did not differ significantly. In yellow-fleshed sweetpotato and cassava, however, spectrophotometric screening overestimated the HPLC values because of the presence of several minor carotenoids. Aside from (all-E)-beta-carotene, Z-isomers were present in cassava in appreciable amounts. For both crops, extraction with acetone or tetrahydrofuran: methanol. (1: 1), using a mortar and pestle or a Polytron homogenizer, gave equivalent results. Rehydration of dry maize at room temperature for 30 min or at 85 degrees C for 5, 10 or 15 min gave equivalent results. Concentrations obtained with the C18 and C30 columns did not differ significantly for zeaxanthin, lutein, beta-cryptoxanthin and beta-carotene in the all-E-configuration, but their Z-isomers were difficult to locate in the chromatogram obtained with the C30 column. Extraction with tetrahydrofuran:methanol (1:1) gave significantly lower results for zeaxanthin and lutein. (c) 2005 Elsevier Ltd. All rights reserved.

Evaluation of the effects of different extraction methods for main volatile compounds from Bambusa textilis leaves

Bambusa textilis is widely used in popular medicine to treat all kinds of wound inflammation, chronic fever, pulmonary and infectious diseases. The aim of this study was to compare the chemical composition of the extracts of B. textilis leaves obtained by three different extraction methods: solid/liquid extraction, Soxhlet and Clevenger system using gas chromatography with flame ionization detector (GC-FID) and gas chromatography with mass spectrometry (GC-MS) analyses. The analytical characteristics of the extracts showed some differences and the GC-MS analysis indicated the presence of higher concentrations of nitro compounds and alkalis. © VSP 2005.

DEVELOPMENT OF AN ALGORITHM TO ANALYZE CARTOGRAPHIC FEATURES EXTRACTION METHODS IN DIGITAL IMAGES

The algorithm creates a buffer area around the cartographic features of interest in one of the images and compare it with the other one. During the comparison, the algorithm calculates the number of equals and different points and uses it to calculate the statistical values of the analysis. One calculated statistical value is the correctness, which shows the user the percentage of points that were correctly extracted. Another one is the completeness that shows the percentage of points that really belong to the interest feature. And the third value shows the idea of quality obtained by the extraction method, since that in order to calculate the quality the algorithm uses the correctness and completeness previously calculated. All the performed tests using this algorithm were possible to use the statistical values calculated to represent quantitatively the quality obtained by the extraction method executed. So, it is possible to say that the developed algorithm can be used to analyze extraction methods of cartographic features of interest, since that the results obtained were promising.

Systematic Evaluation of Extraction Methods for Multiplatform-Based Metabotyping: Application to the Fasciola hepatica Metabolome

Combining data from multiple analytical platforms is essential for comprehensive study of the molecular phenotype (metabotype) of a given biological sample. The metabolite profiles generated are intrinsically dependent on the analytical platforms, each requiring optimization of instrumental parameters, separation conditions, and sample extraction to deliver maximal biological information. An in-depth evaluation of extraction protocols for characterizing the metabolome of the hepatobiliary fluke Fasciola hepatica, using ultra performance liquid chromatography and capillary electrophoresis coupled with mass spectroscopy is presented. The spectrometric methods were characterized by performance, and metrics of merit were established, including precision, mass accuracy, selectivity, sensitivity, and platform stability. Although a core group of molecules was common to all methods, each platform contributed a unique set, whereby 142 metabolites out of 14,724 features were identified. A mixture design revealed that the chloroform:methanol:water proportion of 15:59:26 was globally the best composition for metabolite extraction across UPLC-MS and CE-MS platforms accommodating different columns and ionization modes. Despite the general assumption of the necessity of platform-adapted protocols for achieving effective metabotype characterization, we show that an appropriately designed single extraction procedure is able to fit the requirements of all technologies. This may constitute a paradigm shift in developing efficient protocols for high-throughput metabolite profiling with more-general analytical applicability.

Training and search methods for speech recognition.

Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance.

Analysis of carrier phase extraction methods in 112-Gbit/s NRZ-PDM-QPSK coherent transmission system

We present a comparative analysis on three carrier phase extraction approaches, including a one-tap normalized least mean square method, a block-average method, and a Viterbi-Viterbi method, in coherent transmission system considering equalization enhanced phase noise. © OSA 2012.

Intercomparison of soil pore water extraction methods for stable isotope analysis

Peer reviewed

The neurotoxin β-N-methylamino-L-alanine (BMAA) : Sources, bioaccumulation and extraction procedures

β-methylamino-L-alanine (BMAA) is a neurotoxin linked to neurodegeneration, which is manifested in the devastating human diseases amyotrophic lateral sclerosis, Alzheimer’s and Parkinson’s disease. This neurotoxin is known to be produced by almost all tested species within the cyanobacterial phylum including free living as well as the symbiotic strains. The global distribution of the BMAA producers ranges from a terrestrial ecosystem on the Island of Guam in the Pacific Ocean to an aquatic ecosystem in Northern Europe, the Baltic Sea, where annually massive surface blooms occur. BMAA had been shown to accumulate in the Baltic Sea food web, with highest levels in the bottom dwelling fish-species as well as in mollusks. One of the aims of this thesis was to test the bottom-dwelling bioaccumulation hypothesis by using a larger number of samples allowing a statistical evaluation. Hence, a large set of fish individuals from the lake Finjasjön, were caught and the BMAA concentrations in different tissues were related to the season of catching, fish gender, total weight and species. The results reveal that fish total weight and fish species were positively correlated with BMAA concentration in the fish brain. Therefore, significantly higher concentrations of BMAA in the brain were detected in plankti-benthivorous fish species and heavier (potentially older) individuals. Another goal was to investigate the potential production of BMAA by other phytoplankton organisms. Therefore, diatom cultures were investigated and confirmed to produce BMAA, even in higher concentrations than cyanobacteria. All diatom cultures studied during this thesis work were show to contain BMAA, as well as one dinoflagellate species. This might imply that the environmental spread of BMAA in aquatic ecosystems is even higher than previously thought. Earlier reports on the concentration of BMAA in different organisms have shown highly variable results and the methods used for quantification have been intensively discussed in the scientific community. In the most recent studies, liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the instrument of choice, due to its high sensitivity and selectivity. Even so, different studies show quite variable concentrations of BMAA. In this thesis, three of the most common BMAA extraction protocols were evaluated in order to find out if the extraction could be one of the sources of variability. It was found that the method involving precipitation of proteins using trichloroacetic acid gave the best performance, complying with all in-house validation criteria. However, extractions of diatom and cyanobacteria cultures with this validated method and quantified using LC-MS/MS still resulted in variable BMAA concentrations, which suggest that also biological reasons contribute to the discrepancies. The current knowledge on the environmental factors that can induce or reduce BMAA production is still limited. In cyanobacteria, production of BMAA was earlier shown to be negative correlated with nitrogen availability – both in laboratory cultures as well as in natural populations. Based on this observation, it was suggested that in unicellular non-diazotrophic cyanobacteria, BMAA might take part in nitrogen metabolism. In order to find out if BMAA has a similar role in diatoms, BMAA was added to two diatom species in culture, in concentrations corresponding to those earlier found in the diatoms. The results suggest that BMAA might induce a nitrogen starvation signal in diatoms, as was earlier observed in cyanobacteria. However, diatoms recover shortly by the extracellular presence of excreted ammonia. Thus, also in diatoms, BMAA might be involved in the nitrogen balance in the cell.

Classification Of Frankfurters By Ft-raman Spectroscopy And Chemometric Methods.

Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.

Comparative study of intermaxillary relationships of manual and swallowing methods

This study compared the mandibular displacement from three methods of centric relation record using an anterior jig associated with (A) chin point guidance, (B) swallowing (control group) and (C) bimanual manipulation. Ten patients aged 25-39 years were selected if they met the following inclusion criteria: complete dentition (up to the second molars), Angle class I and absence of signs and symptoms of temporomandibular disorders and diagnostic casts showing stability in the maximum intercuspation (MI) position. Impressions of maxillary and mandibular arches were made with an irreversible hydrocolloid impression material. Master casts of each patient were obtained, mounted on a microscope table in MI as a reference position and 5 records of each method were made per patient. The mandibular casts were then repositioned with records interposed and new measurements were obtained. The difference between the two readings allowed measuring the displacement of the mandible in the anteroposterior and lateral axes. Data were analyzed statistically by ANOVA and Tukey's test at 5% significance level. There was no statistically significant differences (p>0.05) among the three methods for measuring lateral displacement (A=0.38 ± 0.26, B=0.32 ± 0.25 and C=0.32 ± 0.23). For the anteroposterior displacement (A=2.76 ± 1.43, B=2.46 ± 1.48 and C=2.97 ± 1.51), the swallowing method (B) differed significantly from the others (p<0.05), but no significant difference (p>0.05) was found between chin point guidance (A) and bimanual manipulation (C). In conclusion, the swallowing method produced smaller mandibular posterior displacement than the other methods.

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.

New Rapid Derivative Spectrophotometric and Chromatographic Methods for Assay of Loratadine in Tablets and Syrups

New rapid first-derivative spectrophotometric (UVDS) and a stability-indicating high performance liquid chromatographic (HPLC) methods were developed, validated and successfully applied in the analysis of loratadine (LT) in tablets and syrups. In the UVDS method, 0.1 M HCl was used as solvent. The measurements were made at 312.4 nm in the first order derivative spectra. The HPLC method was carried out on a RP-18 column with a mobile phase composed of methanol-water-tetrahydrofuran (50:30:20, v/v/v). UV detection was made at 247 nm. For HPLC methods the total analysis time was <3min, adequate for routine quality control of tablets and syrups containing loratadine.

Quantification of chlorpheniramine maleate enantiomers by ultraviolet spectroscopy and chemometric methods

Chlorpheniramine maleate (CLOR) enantiomers were quantified by ultraviolet spectroscopy and partial least squares regression. The CLOR enantiomers were prepared as inclusion complexes with beta-cyclodextrin and 1-butanol with mole fractions in the range from 50 to 100%. For the multivariate calibration the outliers were detected and excluded and variable selection was performed by interval partial least squares and a genetic algorithm. Figures of merit showed results for accuracy of 3.63 and 2.83% (S)-CLOR for root mean square errors of calibration and prediction, respectively. The ellipse confidence region included the point for the intercept and the slope of 1 and 0, respectively. Precision and analytical sensitivity were 0.57 and 0.50% (S)-CLOR, respectively. The sensitivity, selectivity, adjustment, and signal-to-noise ratio were also determined. The model was validated by a paired t test with the results obtained by high-performance liquid chromatography proposed by the European pharmacopoeia and circular dichroism spectroscopy. The results showed there was no significant difference between the methods at the 95% confidence level, indicating that the proposed method can be used as an alternative to standard procedures for chiral analysis.

Biotype stability of Candida albicans isolates after culture storage determined by randomly amplified polymorphic DNA and phenotypical methods

P>Typing methods to evaluate isolates in relation to their phenotypical and molecular characteristics are essential in epidemiological studies. In this study, Candida albicans biotypes were determined before and after storage in order to verify their stability. Twenty C. albicans isolates were typed by Randomly Amplified Polymorphic DNA (RAPD), production of phospholipase and proteinase exoenzymes (enzymotyping) and morphotyping before and after 180 days of storage in Sabouraud dextrose agar (SDA) and sterilised distilled water. Before the storage, 19 RAPD patterns, two enzymotypes and eight morphotypes were identified. The fragment patterns obtained by RAPD, on the one hand, were not significantly altered after storage. On the other hand, the majority of the isolates changed their enzymotype and morphotype after storage. RAPD typing provided the better discriminatory index (DI) among isolates (DI = 0.995) and maintained the profile identified, thereby confirming its utility in epidemiological surveys. Based on the low reproducibility observed after storage in SDA and distilled water by morphotyping (DI = 0.853) and enzymotyping (DI = 0.521), the use of these techniques is not recommended on stored isolates.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.