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Unraveling the persistent renal impact of intrauterine growth restriction and catch-up growth: integrating morphological insights with metabolomic profiling
The study aimed to investigate the long-term effects of IUGR and consequent catch-up growth on metabolic health by using a comprehensive approach that included histopathological, immunohistochemical, biochemical, and metabolomics analyses. Sprague–Dawley pregnant rats either undergo bilateral uterine artery ligation or a sham surgery on the 19th day of gestation. The offspring reached catch-up growth, kidney samples were collected at postnatal weeks 2, 4, and 8 for analysis. IUGR rats exhibited a spectrum of changes including reduced glomeruli number, proliferating cell number, altered oxidative stress markers, various enzymes involved in Krebs cycle, mitochondrial dynamics, and energy metabolism. Examination of the 8-week-old cohort identified a broader spectrum of metabolic alterations, notably in the biosynthesis of phenylalanine, tyrosine, and tryptophan, phenylalanine, tyrosine, glyoxylate, dicarboxylate, pyruvate, alanine, aspartate, and glutamate metabolism, glycolysis/gluconeogenesis and citrate (TCA) cycle. Our metabolomics analysis provides insights into the potential disease susceptibility of individuals born with IUGR, including obesity, diabetes, hypertriglyceridemia, cardiovascular diseases, and mental retardation. These findings underscore the intricate interplay between intrauterine conditions and long-term metabolic health outcomes, highlighting the need for further investigation into preventive and therapeutic strategies to mitigate the risk of metabolic diseases in individuals with a history of IUGR.
Enhancing imputation accuracy for catch-all missing data mechanisms with DFBETAS and leverage
This paper addresses the challenge of missing data in scientific research. It specifically examines the case of missing data arising from a “catch-all” missing not at ran (MNAR) mechanism, where missing values are disproportionately from one category, such as income or ethnicity in surveys. The study introduces the use of the regression diagnostic DFBETAS along with Leverage to improve the imputation of categorical data under such conditions. DFBETAS, a measure of influence in regression, is adapted to capture the intrinsic information of missing values, thereby enhancing the imputation process within a Bayesian multiple imputation (MI) framework. We validate the proposed approach through Monte Carlo simulations with data generating mechanisms based on probability distributions. The results show that incorporating DFBETAS and Leverage significantly improves the accuracy of imputations, optimizes the balance between its sensitivity and specificity reduces bias, and enhances confidence interval coverage of imputed estimates, especially as the strength of the catch-all mechanism increases. The study demonstrates that MI with DFBETAS and Leverage outperforms standard MI methods, offering a robust solution for handling categorical data with catch-all MNAR mechanisms. This advancement in imputation methodology provides a more accurate and efficient means of dealing with missing data in various research fields.
First, Catch : Study of a Spring Meal
NOMINATED FOR THE 2018 ANDRE SIMON FOOD & DRINK BOOK OF THE YEARBBC RADIO 4 FOOD PROGRAMME BEST FOOD BOOKS OF 2018THE TIMES BEST FOOD BOOKS OF 2018FINANCIAL TIMES SUMMER FOOD BOOKS OF 2018'A one-off, the kind of food book that I believed was no longer being published... When I reached the last page, I went back to the beginning.'– Bee Wilson, The Times'A book as rich and rewarding as the rabbit stew he spends so many chapters making.'– Jenny Linford, Times Literary Supplement'A wonderful taste of fresh air... First, Catch is almost revolutionary... His words are delicious, musical heaven.'– William Sitwell‘Thom Eagle's writing is pure joy – effortless and unaffected. Even such a seemingly banal and simple thing as boiling vegetables is engaging and illuminating in his hands. He is easily one of my favourite writers, and this book deserves to become a classic.” – Olia Hercules, author of Mamushka and Kaukasis'It feels so tantalisingly transgressive to find a book that looks beautiful, feels lovely in the hand and just contains words — gorgeous, thoughtful essays... from a talented chef and writer.'- Tim Hayward, Financial Times‘The thing to do is just begin. The question, of course, is where?'So opens Thom Eagle's hymn to a singular early spring meal. A cookbook without recipes, this is an invitation to journey through the mind of a chef as they work. Stand next to Thom in the kitchen as he muses on the very best way to coax flavour out of an onion (slowly, and with more care than you might expect), or considers the crucial role of salt in the creation of the perfect assembly for early green shoots and leaves.In an era when we are so distracted that we eat almost without realising what we've just put in our mouth, this is food and writing to savour, gently steering the cook back towards simplicity, confidence and, above all, taste.
Chinese cabbage as a catch crop decreases soil soluble N and labile organic N during one-month summer fallow in greenhouse vegetable production
Summer catch crops can reduce soil soluble nitrogen (N) during the summer fallow period in Chinese greenhouse vegetable production. However, the influence of growing fast-growing leafy vegetables as catch crops on soil organic N pools remain insufficiently understood. The aim of this study was to investigate the effects of growing Chinese cabbage (Kuaicai) on soil N pools in the top 0.3 m soil layer during a one-month fallow period in two years. Treatments included Kuaicai cultivation and a fallow treatment for comparison. Results show that soil soluble N pools and non-hydrolysable N (NHN) in the top 0.3 m soil layer were increased during the summer fallow period in the fallow treatment. Kuaicai accumulated 40–114 kg N ha−1 each year, improving N use efficiency by 9.2–26.3%. Growing Kuaicai with drip irrigation to 90% field capacity reduced soil total N (TN) by 12–16% and total soluble N (TSN) by 37–83%. Growing Kuaicai reduced labile N fractions, specifically ammonium N (AN) in the top 0.2 m soil layer by 13–26% and amino acid N (AAN) in the 0.1–0.2 m soil layer by 5–17%. The partial least squares path modelling (a goodness of fit = 0.67) revealed that fallow period management had direct effects on TSN, NHN, and TN, and an indirect effect on labile organic N fractions. The AN and AAN were direct contributors to TSN. These findings suggest that growing Kuaicai as a catch crop is an effective strategy for reducing soluble N pools and labile organic N fractions, thereby lowering the risk of N loss in the next growing season.