Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

Intergenerational Metabolomic Analysis of Mothers with a History of Gestational Diabetes Mellitus and Their Offspring

Shared metabolomic patterns at delivery have been suggested to underlie the mother-to-child transmission of adverse metabolic health. This study aimed to investigate whether mothers with gestational diabetes mellitus (GDM) and their offspring show similar metabolomic patterns several years postpartum. Targeted metabolomics (including 137 metabolites) was performed in plasma samples obtained during an oral glucose tolerance test from 48 mothers with GDM and their offspring at a cross-sectional study visit 8 years after delivery. Partial Pearson’s correlations between the area under the curve (AUC) of maternal and offspring metabolites were calculated, yielding so-called Gaussian graphical models. Spearman’s correlations were applied to investigate correlations of body mass index (BMI), Matsuda insulin sensitivity index (ISI-M), dietary intake, and physical activity between generations, and correlations of metabolite AUCs with lifestyle variables. This study revealed that BMI, ISI-M, and the AUC of six metabolites (carnitine, taurine, proline, SM(-OH) C14:1, creatinine, and PC ae C34:3) were significantly correlated between mothers and offspring several years postpartum. Intergenerational metabolite correlations were independent of shared BMI, ISI-M, age, sex, and all other metabolites. Furthermore, creatinine was correlated with physical activity in mothers. This study suggests that there is long-term metabolic programming in the offspring of mothers with GDM and informs us about targets that could be addressed by future intervention studies.     

The use of natural (Pinus pinaster) resin in the production of printing ink and the printability effect

Alkyd resins are generally used in the production of printing inks. All industries look for alternative raw materials in the production of ink with the growing inclination toward using natural products. Resins forming the vehicle of the ink to be obtained from natural resources will provide benefits for the environment, nature, and living creatures. The aim of the study was to promote the use of natural resin in the ink system. Natural Pinus pinaster resin was added into vegetable and mineral oil-based solvents in pure form with alkyd resin in different amounts and ink varnishes of different combinations were prepared. Then, printing inks were produced from these varnishes in pure and hybrid form. Following the assessment of the rheological properties of the inks prepared, printing tests were conducted to assess the printing quality parameters. Ideal mixing ratios of the natural resins in the ink were determined for printability. The environmental importance and advantages of the use of natural resins were discussed. Recommendations were given in line with the results to encourage widespread use of natural resins in near future.     

Methyltransferase Contingencies in the Pathway of Everninomicin D Antibiotics and Analogues

Everninomicins are orthoester oligosaccharide antibiotics with potent activity against multidrug-resistant bacterial pathogens. Everninomicins act by disrupting ribosomal assembly in a distinct region in comparison to clinically prescribed drugs. We employed microporous intergeneric conjugation with Escherichia coli to manipulate Micromonospora for targeted gene-replacement studies of multiple putative methyltransferases across the octasaccharide scaffold of everninomicin effecting the A₁, C, F, and H rings. Analyses of gene-replacement and genetic complementation mutants established the mutability of the everninomicin scaffold through the generation of 12 previously unreported analogues and, together with previous results, permitted assignment of the ten methyltransferases required for everninomicin biosynthesis. The in vitro activity of A₁- and H-ring-modifying methyltransferases demonstrated the ability to catalyze late-stage modification of the scaffold on an A₁-ring phenol and H-ring C-4’ hydroxy moiety. Together these results establish the potential of the everninomicin scaffold for modification through mutagenesis and in vitro modification of advanced biosynthetic intermediates.     

Detailed study on fusion characteristics of rigid poly(vinyl chloride) nanocomposites: The comparison of using multiple regression analysis and artificial neural network

Fusion behavior of poly(vinyl chloride) (PVC) compounds plays an important role in the development of physical properties of processed material. The fusion characteristics in PVC processing are governed by material variables that affect the fusion with some interactions. In this research, the aim was to characterize the effects of formulation ingredients on fusion characteristics of PVC. Four material parameters, including the contents of nanoclay (NC), azodicarbonamide, calcium stearate, and processing aid, are proposed as affecting variables. The fusion time (FT) as well as fusion factor (FF) are considered fusion indicators and are experimentally determined in some different levels of affecting parameters. The multivariable regression analysis (MRA) and the Artificial Neural Network (ANN) modeling are considered as two analytical methods. The regression analysis result for the FT denotes, in part, significant linear and quadratic effects of NC and also its significant interactions with azodicarbonamide and calcium stearate, whereas that of FF indicates only a linear effect of NC. ANN modeling is performed with a three‐layer (input, hidden, and output) neural network. The results of the comparison of the MRA and ANN predictions with experimental values are reported as the correlation coefficient (R²), mean‐square error, and mean absolute percentage error for both FF and FT parameters. The obtained values clearly denote that the ANN results are more precise and especially more general than those of MRA. However, in the case of FT, improvement of the ANN modeling is much greater than that of FF. J. VINYL ADDIT. TECHNOL., 21:147–155, 2015. © 2014 Society of Plastics Engineers     

A novel context-aware recommender system based on a deep sequential learning approach (CReS)

Neural Computing and Applications - With an increase in online longitudinal users’ interactions, capturing users’ precise preferences and giving accurate recommendations have become an...     

Site-Specific PEGylation of Therapeutic Proteins

The use of proteins as therapeutics has a long history and is becoming ever more common in modern medicine. While the number of protein-based drugs is growing every year, significant problems still remain with their use. Among these problems are rapid degradation and excretion from patients, thus requiring frequent dosing, which in turn increases the chances for an immunological response as well as increasing the cost of therapy. One of the main strategies to alleviate these problems is to link a polyethylene glycol (PEG) group to the protein of interest. This process, called PEGylation, has grown dramatically in recent years resulting in several approved drugs. Installing a single PEG chain at a defined site in a protein is challenging. Recently, there is has been considerable research into various methods for the site-specific PEGylation of proteins. This review seeks to summarize that work and provide background and context for how site-specific PEGylation is performed. After introducing the topic of site-specific PEGylation, recent developments using chemical methods are described. That is followed by a more extensive discussion of bioorthogonal reactions and enzymatic labeling.