Long-range Angular Correlations On The Near And Away Side In P-pb Collisions At √snn=5.02 Tev

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Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities 1,2 . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity 3�6 . Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55 of the global rise in mean BMI from 1985 to 2017�and more than 80 in some low- and middle-income regions�was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing�and in some countries reversal�of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories. © 2019, The Author(s)

Sodiation as a tool for enhancing the diagnostic value of MALDI-TOF/TOF-MS spectra of complex astaxanthin ester mixtures from Haematococcus pluvialis

The microalga Haematococcus pluvialis produces the pigment astaxanthin mainly in esterified form with a multitude of fatty acids, which results in a complex mixture of carotenol mono- and diesters. For rapid fingerprinting of these esters, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF/TOF-MS) might be an alternative to traditional chromatographic separation combined with MS. Investigation of ionization and fragmentation of astaxanthin mono- and diester palmitate standards in MALDI-TOF/TOF-MS showed that sodium adduct parent masses [M + Na]+ gave much simpler MS2 spectra than radical / protonated [M]+¿ / [M+H]+ parents. [M + Na]+ fragments yielded diagnostic polyene-specific eliminations and fatty acid neutral losses, whereas [M]+¿ / [M+H]+ fragmentation resulted in a multitude of non-diagnostic daughters. For diesters, a benzonium fragment, formed by polyene elimination, was required for identification of the second fatty acid attached to the astaxanthin backbone. Parents were forced into [M + Na]+ ionization by addition of sodium acetate, and best signal-to-noise ratios were obtained in the 0.1 to 1.0mM range. This method was applied to fingerprinting astaxanthin esters in a crude H. pluvialis extract. Prior to MALDI-TOF/TOF-MS, the extract was fractionated by normal phase Flash chromatography to obtain fractions enriched in mono- and diesters and to remove pheophytin a, which compromised monoester signals. All 12 types of all-trans esterified esters found in LC were identified with MALDI-TOF/TOF-MS, with the exception of two minor monoesters

Fractal Behavior Of Gleason And Srigley Grading Systems

INTRODUCTION / BACKGROUND: Prostate cancer remains one of the major malignancies of modern society. The need of grading this malignancy is still in dispute. Two major grading systems have emerged and are world-wide adapted: Gleason grading system [1] and Srigley grading system [2]. Both systems use optical subjective descriptions of different architec- tural growth patterns of prostate adenocarcinoma. The fractal dimension (FD) is used in the medical field as an objective feature for describing a given image rather than showing a precise value for a known fractal. The FD can be an objective measurement for different patterns description. AIMS: The aim of our study is to assess the fractal behavior of images labeled according to Gleason and Srigley grading systems both in terms of in-class and inter-class variation. METHODS: 299 Gömöri stained microscopic digital images of prostate adenocarcinoma were labeled independently according to Gleason and Srigley patterns. Each image was firstly transformed to grayscale then a maximum cropped square of the image was resized to a standard 256x256 pixel image. For the resulted images the fractal dimension was approximated with two different algorithms: a standard box-counting algorithm (applied to the binary image obtained with Roberts’s method for edge detection) and a novel algorithm that is applied to the grayscale version of the image consisting in the ratio between image’s volume and area (R-VA) at different scales [3]. In-class variation was assessed as the average standard deviation (SD).Lower SDmeans better discrimination. For the inter-class variation assessment each class was compared with all other classes using a two-tail, Student’s t-test. The resulted value was defined as the ratio between the statistically different means and the total number of comparisons. The maximum possible value for Gleason grading system was 28, be- cause there were no images labeled as Gleason pattern 1, while for the Srigley grading system the maximum possible value was 6. RESULTS: In-class variation was 0.045 using the box-counting algorithm and 0.048 using the R-VA algorithm for Gleason grading system and 0.161 using the box-counting algorithm and 0.178 using the R-VA algorithm for Srigley grading system. Inter-class variation was, for Gleason grading system 13/28 using the box-counting algorithm and 20/28 using the R-VA algorithm while for the Srigley grading system was 3/6 using the box-counting algorithm and 5/6 using the R-VA algorithm respectively. Srigley grading system seems to perform better than Gleason’s on inter-class variation, but has lower performance on in-class variation. Nevertheless, we must note that there is a large difference between the two systems regarding the number of classes. The FD computed with the R-VA algorithm has better discrimination results than the one computed with the box-counting algorithm in both grading systems, thus proving once again the R-VA’s performance [3]

Serum cholesterol decline and depression in the postpartum period

We examined the relation between total serum cholesterol decline and depression in the postpartum period in a prospective study of 266 Dutch women, who were followed until 34 weeks after delivery. The decline in serum cholesterol between week 32 of pregnancy and week 10 postpartum was similar for women who became depressed (n=63) in the subsequent period and women who did not (difference, 0.10 mmol/l; 95% confidence interval [CI] -0.16 to 0.37). Adjusting for age, multiparity, education level, smoking status, concurrent illness, and social support, the odds ratio of depression was 1.4 (95% CI, 0.64 to 2.9) for women in the highest tertile of serum cholesterol decline and 0.61 (95% CI, 0.28 to 1.3) for women in the intermediate tertile, as compared with women in the lowest tertile. Our results do not support the hypothesis that rapid serum cholesterol decline increases risk of depression in the postpartum period

Carotenoid composition of berries and leaves from six Romanian sea buckthorn (Hippophae rhamnoides L.) varieties

Berries and leaves from six varieties of Carpathians’ sea buckthorn (Hippophae rhamnoides L., ssp. Carpatica) were analysed for their carotenoid composition (free and esterified) using a combination of HPLC-PAD, GC–MS and UHPLC–PAD–ESI-MS techniques. GC–MS techniques revealed the fatty acid profile specific for each berry variety, while targeted UHPLC–MS analysis identified the fatty acids involved in carotenoids esterification: palmitic (C16:0), myristic (C14:0) and stearic (C18:0). Total carotenoid content varied between 53 and 97 mg/100 g dry weight in berries, and between 3.5 and 4.2 mg/100 g DW in leaves. The carotenoid di-esters represented the main fraction among berry varieties having zeaxanthin di-palmitate as major compound, while leaves contained only free carotenoids like lutein, ß-carotene, violaxanthin and neoxanthin. Principal component analysis identified the suitable carotenoid biomarkers characteristic for the Carpathians’ sea buckthorn from Romania with contribution to their taxonomic classification and authenticity recognition

UHPLC/PDA–ESI/MS Analysis of the Main Berry and Leaf Flavonol Glycosides from Different Carpathian Hippophaë rhamnoides L. Varieties

Introduction - Sea buckthorn (Hippophaë rhamnoides L.) is known to be rich in many bioactive compounds (such as vitamins, phenolics, carotenoids) important for human health and nutrition. Among the phenolics, berries and leaves contain a wide range of flavonols that are good quality and authenticity biomarkers. Objective - To compare the composition of the main flavonols of Romanian sea buckthorn berry and leaf varieties and to identify the specific biomarkers that contribute to sample differentiation among varieties. Material and methods - Six varieties of cultivated sea buckthorn (ssp. Carpatica) berries and leaves were analysed by UHPLC/PDA–ESI/MS. Results - Berries and leaves contained mainly isorhamnetin (I) glycosides in different ratios. Whereas I-3-neohesperidoside, I-3-glucoside, I-3-rhamnosylglucoside, I-3-sophoroside-7-rhamnoside and free isorhamnetin were predominant for berries (out of 17 compounds identified), I-3-rhamnosylglucoside, I-3-neohesperidoside, I-3-glucoside, quercetin-3-pentoside, kaempferol-3-rutinoside, and quercetin-3-glucoside were predominant in leaves (out of 19 compounds identified). Berries contained, on average, 917¿mg/100¿g DW flavonol glycosides. Leaves had higher content of flavonol glycosides than berries, on average 1118¿mg/100¿g DW. The variation of the quantitative dataset analysed using principal component analysis accounted for 91% of the total variance in the case of berries and 73% in case of leaves, demonstrating a good discrimination among samples. Conclusion - Based on quantitative analysis, by principal component analysis, the flavonol derivatives can be considered as biomarkers to discriminate among varieties and to recognise specifically the berry versus leaf compositio