117,987 research outputs found
Preliminary evaluation of the use of a disposable electrochemical sensor for selective identification of Δ9-tetrahydrocannabinol and cannabidiol by multivariate analysis
No full textThe widespread diffusion of products deriving from Cannabis sativa L. led to the necessity of rapid and reliable
methods for the identification of samples containing Δ9-tetrahydrocannabinol (THC), the psychoactive component
of the plant, which imparts mental distortions and hallucinations. Although some efficient electrochemical
sensors have been already proposed for such a purpose, they do not consider that the plant may also contain huge
amounts of cannabidiol (CBD), which possesses an electroactive moiety quite similar to that of THC. The definition
of both THC and CBD concentration is at the basis of discrimination between recreational-type and fibretype
cannabis samples; detection of these species is not only important in vegetable samples but also in relevant
commercial products and in biological fluids. We proposed here a screen-printed electrode coated with a layer of
carbon black for the rapid identification of samples containing THC irrespectively of the simultaneous presence
of CBD. The most performing carbon black typology used for such a purpose was chosen among various commercial
products tested on the basis of preliminary tests performed on 1,3-dihydroxybenzene, constituting the
redox active moiety of cannabinoids. The voltammetric responses collected in various solutions containing
different amount of THC and CBD were initially elaborated by Principal Component Analysis, assessing the
possibility of identifying samples with similar concentrations of THC irrespectively of the CBD concentration
values, and vice-versa. Afterwards a preliminary Partial Last Square regression was performed to evaluate the
possibility of a quantitative analysis of both THC and CBD. This approach suggests the possibility of using the
sensor proposed to screen samples containing THC even in the presence of high amounts of CBD
Mixture design and multivariate image analysis to monitor the colour of strawberry yoghurt purée
No full textFood colour is a commercial added value, since it represents the first appealing factor for consumers. In this context, this study was aimed at evaluating the effect of strawberry yoghurt purée (SYP) formulation on the corresponding colour and on its variation over time, which is mainly due to degradation and browning phenomena. To this aim, a combined approach was used that included mixture design and multivariate analysis of RGB images. Strawberry purée, sugar, lemon juice and two types of thickener were mixed in different proportions by I-optimal mixture design to obtain 44 SYP formulations. The samples were subjected to light and temperature stress conditions for five weeks; during this time the RGB images of the samples were acquired using a flatbed scanner, along with the images of the corresponding control samples. The dimensionality of the acquired images was reduced by two different approaches: i) the conversion of images into signals, namely colourgrams, which can be seen as the colour fingerprint of the imaged samples, and ii) the calculation of the median values of various colour-related parameters. The colourgrams dataset was then subjected to exploratory data analysis using Principal Component Analysis, while the median values of colour-related parameters were analysed using Response Surface Methodology and Partial Least Squares-Discriminant Analysis. The aim of data analysis was both to find the best colour parameters to describe colour variability over time, and to investigate the cause-effect relationship between mixture proportions and colour response. The results highlighted that, among the considered colour parameters, relative green (i.e., the ratio of green to lightness) and red could be used to monitor colour changes. Colour variation due to stress conditions was more pronounced for samples with a high percentage of strawberry purée, and the type of thickener also affected the colour degradation kinetics
Classification of Arabica and Robusta coffee samples subjected to different technological treatments using various image analysis methods
No full textCoffee varietal differentiation based on NIR spectroscopy has been widely investigated in the last
20 years [1-3]. In this work, we have applied hyperspectral imaging in the NIR range (900-1700
nm) for the classification of Arabica and Robusta coffee varieties, considering coffee beans
subjected to different processing methods, i.e., the so-called dry method (to produce natural coffee),
wet method (to produce washed coffee) and a somewhat intermediate processing method, referred to
as polishing method (to produce polished coffee).
PCA has been used as an exploratory technique both on the image mean spectra and on the
hyperspectrograms obtained from the images. The hyperspectrograms are built by compressing the
useful information contained in each hyperspectral image into a signal composed by the frequency
distribution curves of quantities calculated by PCA [4]. This procedure allows to compress the
information conveyed by the hyperspectral images, maintaining at the same time both spatial- and
spectral-related features.
The PCA models obtained showed a clear clustering of Arabica and Robusta samples, whereas,
considering the technological treatment, the polished coffee samples are clearly distinguishable
from the others, while natural and washed coffee samples are quite superimposed.
Image mean spectra and hyperspectrograms were then subjected to PLS-DA classification after
preprocessing using SNV followed by meancentering or meancentering only. Concerning the
discrimination of coffee samples between Arabica and Robusta categories, the same value of
classification efficiency in prediction (EFFPRED = 86.3%) has been obtained considering both the
mean spectra and the hyperspectrograms. After forward iPLS-DA variable selection, EFFPRED
increased up to 98.6% for models calculated using the mean spectra and up to 100% for the models
calculated using the hyperspectrograms.
As for the discrimination of the coffee samples into the three natural, polished and washed
processing categories, the PLS-DA models calculated using mean spectra led to EFFPRED values
equal to 81.1%, 95.7% and 49.8%, respectively, while the PLS-DA models calculated using
hyperspectrograms led to EFFPRED values equal to 94.7%, 100% and 92.4%, respectively. In this
case, iPLS-DA variable selection led to an increase of the performances of the model calculated on
mean spectra (EFFPRED equal to 82.9%, 98.6% and 86.5%, respectively) and to a decrease of the
performances of the model calculated using hyperspectrograms (EFFPRED equal to 82.9%, 89.3%
and 86.5%, respectively)
Characterization of common wheat flours (Triticum aestivum L.) through multivariate analysis of conventional rheological parameters and gluten peak test indices
No full textThe GlutoPeak consists in high speed mixing of a small amount of wheat flour (<10 g) added with water, and in registering a torque vs. time curve in a very short time (<10 min). Peak torque, peak maximum time, and energy values are calculated from the curve, and used to estimate the aggregation behavior of gluten. The information brought by the GlutoPeak indices is still difficult to interpret correctly, also in relation to the conventional approaches in the field of cereal science. A multivariate approach was used to investigate the correlations existing between the GlutoPeak indices and the conventional rheological parameters. 120 wheat flours- different for protein, dough stability, extensibility, tenacity, and strength, and end-uses - were analyzed using the GlutoPeak and conventional instrumentation. The parameters were subjected to a data exploration step through Principal Component Analysis. Then, multivariate Partial Least Squares Regression (PLSR) models were developed using the GlutoPeak indices to predict the conventional parameters. The values of the squared correlation coefficients in prediction of an external test set showed that acceptable to good results (0.61 ≤ R2PRED ≤ 0.96) were obtained for the prediction of 18 out of the 26 conventional parameters here considered
The inhibitory receptor LILRB4 (ILT3) modulates antigen presenting cell phenotype and, along with LILRB2 (ILT4), is upregulated in response to Salmonella infection.
No full textBACKGROUND: Leukocyte Ig-like receptors (LILR) are a family of innate immune receptors with immunomodulatory functions. High-level expression of the receptors LILRB2 (ILT4) and LILRB4 (ILT3) is a feature of tolerogenic antigen presenting cells and has been observed in cancer and transplant situations. There are relatively few studies regarding these receptors in the context of infection and it is not yet clear how LILRB4 exerts its inhibitory effects.
RESULTS: We studied the effects of LILRB4 ligation on antigen presenting cell phenotype, and the expression of LILRB2 and LILRB4 on Salmonella-infected antigen presenting cells. Ligation of LILRB4 throughout in vitro culture of dendritic cells led to an upregulation of the co-stimulatory protein CD86. Alterations in the production of IL-8 and IL-10 by LILRB4-ligated macrophages were also observed. Infection with Salmonella typhimurium or TLR stimulation with Salmonella components led to an upregulation of LILRB2 and LILRB4.
CONCLUSION: Our results indicate that the inhibitory effects of LILRB4 do not result from a failure to upregulate co-stimulatory proteins. In addition to the high level expression that can render antigen presenting cells tolerogenic, there may be a role for lower level expression and activity of LILRB2 and LILRB4 in response to TLR signalling during an immune response to bacterial infection
Classification of bread wheat flours in different quality categories by a wavelet-based feature selection/classification algorithm on NIR spectra
No full textIn the Italian context, bread wheat flour is commercially classified in different quality categories on the basis of a Synthetic Index of Quality (Indice Sintetico di Qualit, ISQ), which is defined by means of specific parameters, i.e., hectolitric weight, falling number, protein content, alveographic indexes (W, P/L) and farinograph stability. The analyses involved in the determination of these parameters are expensive, time consuming and require specialized personnel, thus there is concern to develop alternative methods to be applied during the commercial transactions, when the products need to be characterized in very short times. For this reason, a fast technique such as an automated classification on the basis of NIR spectra acquired on the wheat flour samples could be a very useful tool. In this work, various wheat flour samples belonging to four different ISQ classes have been analysed by means of NIR spectroscopy, and the obtained spectra have been classified both by SIMCA applied to the signals subjected to different pretreatment methods, and by using a wavelet-based feature selection/classification algorithm, called WPTER. Due to the high overlap of the two intermediate quality classes, it was not possible to classify all the data set signals. However, when considering only the two extreme categories, an acceptable degree of class separation can be gained after feature selection by WPTER. Moreover, this approach allowed us to locate the NIR spectral regions that are mainly involved in the assignment of the wheat flour samples to these two quality categories
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Viremia copy-years and risk of estimated glomerular filtration rate reduction in adults living with perinatal HIV infection
No full textAmong people with perinatal HIV infection (PHIV), non-communicable diseases, such as chronic kidney disease, are increasing. Both HIV replication and antiretroviral therapy are recognised causes of renal impairment. Objective of the study is to describe the impact of viremia copy-years (VCY) and antiretroviral therapy on trend of estimated glomerular filtration rate (eGFR) in a cohort of adults with perinatal HIV infection. We conducted a multicentre observational study in sixty adults living with PHIV across a 9-year period, from January 2010 to December 2018. The mean values of eGFR were analysed at the first (T0) and last year of observation (T1). VCY was defined as the area under HIV-RNA curve during the study period. We analysed data according to antiretroviral therapy: tenofovir disoproxil (TDF), non-nucleoside reverse transcriptase inhibitors (NNRTI), boosted protease inhibitors (PI/b), integrase inhibitors (INI). We observed a mean overall eGFR reduction from 126.6 mL/min (95%CI: 119.6–133.5) to 105.0 mL/min (95%CI: 99.55–110.6) (p2 log10. Our study outlines a progressive eGFR reduction in young adults with PHIV, related to the lower control on HIV-RNA VCY and related to aging
Square Dancing with the Stars to Enhance Dynamic Hirschman Linkages?
No full textIn this Presidential Address, the author takes the reader on a reconnaissance of his life and time as a regional scientist. He points out scenery he found scintillating along the way, hoping that some may pick up the banner and chew on a few of the ideas for a while. He suggests a revisit to Albert O. Hirschman’s notion of key sectors and more empirical analysis related to Marcus Berliant’s and Masahisa Fujita’s notion of knowledge creation and transfer.Presidential Address, San Antonio, Texas, March 29, 2014 (53rd Meetings of the Southern Regional Science Association
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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