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•Phenolic acids, stilbenes, flavanol, anthocyanin, flavonol and flavanone were detected in all flowers.•The orange flower cosmos presented the highest content of phenolic ...compounds.•Bioaccessibility of phenolics varied among the compounds and within the flower source.•Before in vitro digestion mini rose displayed the highest activity in FRAP and DPPH assays.•The dialyzed fraction of cravine showed the highest activity in DDPH assay.•Cosmos and mini rose are source of bioaccessible phenolics with great antioxidant activity.
This study assessed the phenolics and their bioaccessibility through an in vitro digestion system coupled to a simulated intestinal barrier in eight edible flowers of distinct colors, namely mini rose, torenia, mini daisy, clitoria, cosmos, cravine, begonia and tagete. The antioxidant activity of the flowers before in vitro digestion, in their derived dialyzed and non-dialyzed fractions was evaluated using distinct approaches. All flowers presented in their composition phenolic acids, stilbenes, flavanol, anthocyanin, flavonol and flavanone, however distinct compounds and contents were found in each flower. The bioaccessibility varied among the phenolics and within the flower source (p < 0.05). Cosmos presented the highest (p < 0.05) content of phenolics and activity in ORAC assay before in vitro digestion and in dialyzed and non-dialyzed fraction; the observed activity was correlated (r = 0.9) to its major compounds, hesperidin and rutin, as well as to caftaric acid and procyanidin B2. Mini rose displayed the highest antioxidant activity in FRAP and DPPH assays before in vitro digestion; its dialyzed and non-dialyzed fraction showed the highest activity in FRAP, correlated to pelargonidin 3,5-diglucoside, catechin, epicatechin galate, epicagocatechin galate, procyanidin A2, quercitin 3-glucoside and trans-resveratrol (r = 0.9). In DPPH assay, mini rose showed the highest activity in the non-dialyzed fraction, while cravine showed the highest activity in the dialyzed fraction, which was mainly correlated to syringic acid (r = 1.0), pelargonidin 3,5-diglucoside and epicatechin (r = 0.9). Results show great variability in the phenolic composition and their bioaccessibility among the edible flowers studied. Our findings indicate cosmos and mini rose as sources of bioaccessible phenolics with great antioxidant activity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty ...in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation.
Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively.
Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error.
Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Multiple factor analysis (MFA, also called multiple factorial analysis) is an extension of principal component analysis (PCA) tailored to handle multiple data tables that measure sets of variables ...collected on the same observations, or, alternatively, (in dual‐MFA) multiple data tables where the same variables are measured on different sets of observations. MFA proceeds in two steps: First it computes a PCA of each data table and ‘normalizes’ each data table by dividing all its elements by the first singular value obtained from its PCA. Second, all the normalized data tables are aggregated into a grand data table that is analyzed via a (non‐normalized) PCA that gives a set of factor scores for the observations and loadings for the variables. In addition, MFA provides for each data table a set of partial factor scores for the observations that reflects the specific ‘view‐point’ of this data table. Interestingly, the common factor scores could be obtained by replacing the original normalized data tables by the normalized factor scores obtained from the PCA of each of these tables. In this article, we present MFA, review recent extensions, and illustrate it with a detailed example. WIREs Comput Stat 2013, 5:149–179. doi: 10.1002/wics.1246
This article is categorized under:
Data: Types and Structure > Categorical Data
Statistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data Analysis
Statistical and Graphical Methods of Data Analysis > Multivariate Analysis
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
This review aims to gather and summarize information about the occurrence of emerging contaminants and antibiotic resistance genes in environmental matrices in Latin America. We aim to contribute to ...future research by compiling a list of priority pollutants adjusted to the needs and characteristics of Latin America, according to the data presented in this study. In order to perform a comprehensive research and secure a representative and unbiased amount of quality data concerning emerging contaminants in Latin America, the research was performed within the Scopus® database in a time frame from 2000 to July 2019. The countries with higher numbers of published articles were Brazil and México, while most studies were performed in the surroundings of Mexico City and in Southern and Southeastern Brazil. The main investigated environmental matrices were drinking water and surface water. The presence of antibiotic resistance was frequently reported, mainly in Brazil. Monitoring efforts should be performed in other countries in Latin America, as well as in other regions of Brazil and México. The suggested priority list for monitoring of emerging contaminants in Latin America covers: di(2-ethylhexyl) phthalate (DEHP), bisphenol-A (BP-A), 4-nonylphenol (4-NP), triclosan (TCS), estrone (E1), estradiol (E2), ethinylestradiol (EE2), tetracycline (TC), amoxicillin (AMOX), norfloxacin (NOR), ampicillin (AMP) and imipenem (IMP). We hope this list serves as a basis for the orientation of the future research and monitoring projects to better understand the distribution and concentration of the listed emerging substances.
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•There is a lack of information in most countries in Latin America.•Brazil and Mexico published most of the papers.•More research is necessary in soils, groundwater and coastal areas.•Further investigations about antibiotic resistance in the area should be performed.•The priority list cover plasticizers, phenols, antimicrobials and pharmaceuticals.
This paper is an overview of the published data of emerging contaminants and antibiotic resistance in Latin America, showing research gaps and suggesting a priority list for future regulation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
► Fish, meat, dairy products, eggs and fat/oils were analyzed for persistent organic pollutants (POPs) followed by per capita intake calculations. ► The highest levels of PCDD/F, PCB, PBDE, HBCD and ...chlorinated pesticides were found in the fish/fish products. ► The levels and intake of different POPs from food of animal origin in the market basket of 2005 seem to have decreased since the market basket study in 1999.
Based on consumption data statistics, food items from four regions in Sweden were sampled in a so-called market basket study. Food items from five food groups, i.e. fish, meat, dairy products, eggs and fat/oils, were analyzed for persistent organic pollutants (POPs) followed by per capita intake calculations. The highest levels of PCDD/F, PCB, PBDE, HBCD and chlorinated pesticides were found in the fish/fish products. The estimated market basket per capita intake of PCDD/F and dl-PCB was 0.7
pg WHO-TEQ
kg
bw
−1
d
−1 (TEFs from 1998). The intake of ∑PCB was estimated to 4.9
ng
kg
bw
−1
d
−1 and fish was found to be the major contributor with 64%. The intake of ∑PBDE was found to be 0.7
ng
kg
bw
−1
d
−1. Fish (38%) and dairy products (31%) were the largest contributors to the total PBDE intake. The intake of HBCD was estimated to 0.14
ng
kg
bw
−1
d
−1. HBCD mainly came from fish (65%), but also dairy products (24%) and meat (10%) contributed. Also regarding the chlorinated pesticides, fish was found to be the major contributor, with 51% of the ∑DDT coming from fish. The intake of ∑DDT, ∑HCH and HCB was 4.0, 1.0 and 1.1
ng
kg
bw
−1
d
−1, respectively. Most of the ∑HCH and HCB originate from dairy products (43% and 55%, respectively). This study shows that the levels, and intake, of different POPs from food of animal origin in the market basket of 2005 seem to have decreased since the market basket study in 1999.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and ...facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental.
This study investigated the profiles of volatile compounds produced by Lactobacillus paracasei during oat fermentation using gas chromatography‐mass spectrometry coupled with headspace solid‐phase ...microextraction method. A total of 60 compounds, including acids, alcohols, aldehydes, esters, furan derivatives, hydrocarbons, ketones, sulfur‐containing compounds, terpenes, and other compounds, were identified in fermented oat. Lipid oxidation products such as 2‐pentylfuran, 1‐octen‐3‐ol, hexanal, and nonanal were found to be the main contributors to oat samples fermented by L. paracasei with the level of 2‐pentylfuran being the highest. In addition, the contents of ketones, alcohols, acids, and furan derivatives in the oat samples consistently increased with the fermentation time. On the other hand, the contents of degradation products of amino acids, such as 3‐methylbutanal, benzaldehyde, acetophenone, dimethyl sulfide, and dimethyl disulfide, decreased in oat samples during fermentation. Principal component analysis (PCA) was applied to discriminate the fermented oat samples according to different fermentation times. The fermented oats were clearly differentiated on PCA plots. The initial fermentation stage was mainly affected by aldehydes, whereas the later samples of fermented oats were strongly associated with acids, alcohols, furan derivatives, and ketones. The application of PCA to data of the volatile profiles revealed that the oat samples fermented by L. paracasei could be distinguished according to fermentation time.
Practical Application
This study investigated the changes of volatile compounds in fermented oats inoculated with L. paracasei during fermentation. These results could be used to improve the quality of oat‐based products and in the development of oat‐based functional foods.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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•Synthesis of a pH sensitive bilayer coated nano iron oxide drug carrier.•Nanocomposite was characterized using various techniques.•Loading efficiency and capacity of curcumin and ...6-gingerol were examined.•In-vitro drug releasing behavior of curcumin and 6-gingerol was studied.•Mechanism of drug release from the nanocomposite of each situation was studied.
Developing a drug carrier system which could perform targeted and controlled release over a period of time is utmost concern in the pharmaceutical industry. This is more relevant when designing drug carriers for poorly water soluble drug molecules such as curcumin and 6-gingerol. Development of a drug carrier system which could overcome these limitations and perform controlled and targeted drug delivery is beneficial. This study describes a promising approach for the design of novel pH sensitive sodium alginate, hydroxyapatite bilayer coated iron oxide nanoparticle composite (IONP/HAp-NaAlg) via the co-precipitation approach. This system consists of a magnetic core for targeting and a NaAlg/HAp coating on the surface to accommodate the drug molecules. The nanocomposite was characterized using FT-IR spectroscopy, X-ray diffraction, scanning electron microscopy, transmission electron microscopy and thermogravimetric analysis. The loading efficiency and loading capacity of curcumin and 6-gingerol were examined. In vitro drug releasing behavior of curcumin and 6-gingerol was studied at pH 7.4 and pH 5.3 over a period of seven days at 37°C. The mechanism of drug release from the nanocomposite of each situation was studied using kinetic models and the results implied that, the release is typically via diffusion and a higher release was observed at pH 5.3. This bilayer coated system can be recognized as a potential drug delivery system for the purpose of curcumin and 6-gingerol release in targeted and controlled manner to treat diseases such as cancer.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection ...for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome.
This is a secondary analysis using a cohort of 252 mechanically ventilated subjects with the diagnosis of acute respiratory distress syndrome. Survival to day 7 with both day 0 (first day of presentation) and day 7 sample availability was required. Blood was collected for biomarker measurements at first presentation to the intensive care unit and on the seventh day. Biomarkers included cytokine-chemokines, dual-functioning cytozymes, and vascular injury markers. Logistic regression, latent class analysis, and classification and regression tree analysis were used to identify the plasma biomarkers most predictive of 28-day ARDS mortality.
From eight biologically relevant biomarker candidates, six demonstrated an enhanced capacity to predict mortality at day 0. Latent-class analysis identified two biomarker-based phenotypes. Phenotype A exhibited significantly higher plasma levels of angiopoietin-2, macrophage migration inhibitory factor, interleukin-8, interleukin-1 receptor antagonist, interleukin-6, and extracellular nicotinamide phosphoribosyltransferase (eNAMPT) compared to phenotype B. Mortality at 28 days was significantly higher for phenotype A compared to phenotype B (32% vs 19%, p = 0.04).
An adult biomarker-based risk model reliably identifies ARDS subjects at risk of death within 28 days of hospitalization.
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