Results 41 to 50 of about 148,113 (146)
Clinical and Molecular Features of Patients With Congenital Disorders of Glycosylation in Japan
JIMD Reports, Volume 66, Issue 3, May 2025.ABSTRACT Congenital disorders of glycosylation (CDG) are a heterogeneous group of diseases caused by defects in various steps of the glycosylation pathway. There are over 200 known human glycosylation‐related disorders. Many of these defects lead to multisystemic manifestations, commonly involving the central nervous system, with symptoms ranging from ...
Nobuhiko Okamoto +2 more
wiley +1 more source
Mass Spectrometry Reviews, Volume 44, Issue 3, Page 213-453, May/June 2025.Abstract The use of matrix‐assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well‐established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022.
David J. Harvey
wiley +1 more source
Extensive regulation of metabolism and growth during the cell division cycle [PDF]
arXiv, 2014 Yeast cells grown in culture can spontaneously synchronize their respiration, metabolism, gene expression and cell division. Such metabolic oscillations in synchronized cultures reflect single-cell oscillations, but the relationship between the oscillations in single cells and synchronized cultures is poorly understood.
arxiv
arXiv, 2017 Expressing the energy content of food as the heat energy released by its combustion is potentially misleading. Food is used to produce adenosine triphosphate (ATP). The free energy of conversion of ATP into adenosine diphosphate is used directly for processes such as muscular contraction, without the need for intermediate heat production. The number of
arxiv
Plant Biotechnology Journal, Volume 23, Issue 5, Page 1585-1600, May 2025.Summary Cytosine methylation (mCG) is an important heritable epigenetic modification, yet its functions remain to be fully defined in important crops. This study investigates mCG in soybean following the loss‐of‐function mutation of two GmMET1 genes.
Ying Wang +10 more
wiley +1 more source
The protein cost of metabolic fluxes: prediction from enzymatic rate laws and cost minimization [PDF]
, 2016 Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering.
arxiv +1 more source
Films of Bacteria at Interfaces (FBI): Remodeling of Fluid Interfaces by Pseudomonas aeruginosa [PDF]
arXiv, 2017 Bacteria at fluid interfaces endure physical and chemical stresses unique to these highly asymmetric environments. The responses of Pseudomonas aeruginosa PAO1 and PA14 to a hexadecane-water interface are compared. PAO1 cells form elastic films of bacteria, excreted polysaccharides and proteins, whereas PA14 cells move actively without forming an ...
arxiv
MealMeter: Using Multimodal Sensing and Machine Learning for Automatically Estimating Nutrition Intake [PDF]
arXivAccurate estimation of meal macronutrient composition is a pre-perquisite for precision nutrition, metabolic health monitoring, and glycemic management. Traditional dietary assessment methods, such as self-reported food logs or diet recalls are time-intensive and prone to inaccuracies and biases. Several existing AI-driven frameworks are data intensive.
arxiv
Banana skin: a novel material for a low-cost production of laccase [PDF]
arXiv, 2008 Laccases (benzenodiol: oxygen oxidoreductases; EC 1.10.3.2) are multicopper oxidases of wide substrate specificity mainly found in white-rot fungi, which are the only microorganisms able to degrade the whole wood components, but they are also expressed in bacteria and higher plants. Laccases are used currently in biotechnological processes because this
arxiv
A Dual-Hormone Closed-Loop Delivery System for Type 1 Diabetes Using Deep Reinforcement Learning [PDF]
arXiv, 2019 We propose a dual-hormone delivery strategy by exploiting deep reinforcement learning (RL) for people with Type 1 Diabetes (T1D). Specifically, double dilated recurrent neural networks (RNN) are used to learn the hormone delivery strategy, trained by a variant of Q-learning, whose inputs are raw data of glucose \& meal carbohydrate and outputs are dual-
arxiv