scholarly journals Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells

2017 ◽  
Author(s):  
Emanuel Gonçalves ◽  
Marco Sciacovelli ◽  
Ana S. H. Costa ◽  
Timothy Isaac Johnson ◽  
Daniel Machado ◽  
...  
Keyword(s):  
Translational Regulation ◽  
Fumarate Hydratase ◽  
Computational Modelling ◽  
Central Carbon Metabolism ◽  
Post Translational Modifications ◽  
Novel Approach ◽  
Regulation Of Metabolism ◽  
Regulatory Phosphorylation ◽  
Metabolic Transformation ◽  
Modelling Approach

AbstractDeregulated signal transduction pathways and energy metabolism are hallmarks of cancer and both play a fundamental role in the process of tumorigenesis. While it is increasingly recognised that signalling and metabolism are highly interconnected, the underpinning mechanisms of their co-regulation are still largely unknown. Here we designed and acquired proteomics, phosphoproteomics, and metabolomics experiments in fumarate hydratase (FH) deficient cells and developed a computational modelling approach to identify putative regulatory phosphorylation-sites of metabolic enzymes. We identified previously reported functionally relevant phosphosites and potentially novel regulatory residues in enzymes of the central carbon metabolism. In particular, we show that pyruvate dehydrogenase (PDHA1) enzymatic activity is inhibited by increased phosphorylation in FH-deficient cells. Our work provides a novel approach to investigate how post-translational modifications of enzymes regulate metabolism and could have important implications for understanding the metabolic transformation of FH-deficient cancers.

scholarly journals Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells

2018 ◽  
Vol 45 ◽  
pp. 149-157 ◽  
Author(s):  
Emanuel Gonçalves ◽  
Marco Sciacovelli ◽  
Ana S.H. Costa ◽  
Maxine Gia Binh Tran ◽  
Timothy Isaac Johnson ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Translational Regulation ◽  
Fumarate Hydratase ◽  
Regulation Of Metabolism

scholarly journals Gut inference: A computational modelling approach

2021 ◽  
pp. 108152
Author(s):  
Ryan Smith ◽  
Ahmad Mayeli ◽  
Samuel Taylor ◽  
Obada Al Zoubi ◽  
Jessyca Naegele ◽  
...  
Keyword(s):  
Computational Modelling ◽  
Modelling Approach

A computational modelling approach to human-elephant interactions in the Bunda District, Tanzania

2021 ◽  
Vol 443 ◽  
pp. 109449
Author(s):  
Abel Ansporthy Mamboleo ◽  
Crile Doscher ◽  
Adrian Paterson
Keyword(s):  
Computational Modelling ◽  
Modelling Approach

Epigenetic regulation of genes in learning and memory

2010 ◽  
Vol 48 ◽  
pp. 263-274 ◽  
Author(s):  
Tania L. Roth ◽  
Eric D. Roth ◽  
J. David Sweatt
Keyword(s):  
Learning And Memory ◽  
Cognitive Dysfunction ◽  
Epigenetic Regulation ◽  
Memory Formation ◽  
Covalent Modification ◽  
Gene Activity ◽  
Neural Function ◽  
Post Translational Modifications ◽  
Novel Approach ◽  
Induced Changes

Rapid advances in the field of epigenetics are revealing a new way to understand how we can form and store strong memories of significant events in our lives. Epigenetic modifications of chromatin, namely the post-translational modifications of nuclear proteins and covalent modification of DNA that regulate gene activity in the CNS (central nervous system), continue to be recognized for their pivotal role in synaptic plasticity and memory formation. At the same time, studies are correlating aberrant epigenetic regulation of gene activity with cognitive dysfunction prevalent in CNS disorders and disease. Epigenetic research, then, offers not only a novel approach to understanding the molecular transcriptional mechanisms underlying experience-induced changes in neural function and behaviour, but potential therapeutic treatments aimed at alleviating cognitive dysfunction. In this chapter, we discuss data regarding epigenetic marking of genes in adult learning and memory formation and impairment thereof, as well as data showcasing the promise for manipulating the epigenome in restoring memory capacity.

Transient plasto-elastohydrodynamic lubrication concerning surface features with application to split roller bearings

2020 ◽  
pp. 135065012092756
Author(s):  
Tobias Hultqvist ◽  
Aleks Vrček ◽  
Tomas Johannesson ◽  
Pär Marklund ◽  
Roland Larsson
Keyword(s):  
Internal Combustion Engines ◽  
Roller Bearing ◽  
Elastohydrodynamic Lubrication ◽  
Combustion Engines ◽  
Transient Effects ◽  
Finite Element Software ◽  
Accumulated Damage ◽  
Roller Bearings ◽  
Novel Approach ◽  
Modelling Approach

The use of roller bearings as crankshaft main bearings has shown potential in reducing the fuel consumption of internal combustion engines. An effective way to mount the roller bearing onto the crankshaft is to split the outer ring. However, this may lead to a severe out-of-roundness in the split region when the bearing is mounted, further implying increased noise, vibrations and contact stresses. In this work, a novel approach to study the plasto-elastohydrodynamic contact using commercial finite element software is developed. The modelling approach is based on the contact moving in space, allowing for the stress history based on the lubricant pressure to be studied in a straight-forward manner. The model is first utilised to study the influence of asperities on the lubricating conditions, indicating that stresses may exceed the yield strength of the material due to the transient effects taking place when the surface feature is over-rolled. Thereafter, the model is used to analyse the step in a mounted crankshaft roller bearing with the purpose of specifying a critical step height, which implies zero plasticity and thereby a reduced risk of accumulated damage in the vicinity of the step.

Sentiment classification of Chinese cosmetic reviews based on integration of collocations and concepts

2019 ◽  
Vol 38 (1) ◽  
pp. 155-169
Author(s):  
Chihli Hung ◽  
You-Xin Cao
Keyword(s):  
Design Methodology ◽  
Classification Performance ◽  
Sentiment Classification ◽  
Support Vector ◽  
Research Approach ◽  
Content Type ◽  
Novel Approach ◽  
The Relationship ◽  
Modelling Approach

Purpose This paper aims to propose a novel approach which integrates collocations and domain concepts for Chinese cosmetic word of mouth (WOM) sentiment classification. Most sentiment analysis works by collecting sentiment scores from each unigram or bigram. However, not every unigram or bigram in a WOM document contains sentiments. Chinese collocations consist of the main sentiments of WOM. This paper reduces the complexity of the document dimensionality and makes an improvement for sentiment classification. Design/methodology/approach This paper builds two contextual lexicons for feature words and sentiment words, respectively. Based on these contextual lexicons, this paper uses the techniques of associated rules and mutual information to build possible Chinese collocation sets. This paper applies preference vector modelling as the vector representation approach to catch the relationship between Chinese collocations and their associated concepts. Findings This paper compares the proposed preference vector models with benchmarks, using three classification techniques (i.e. support vector machine, J48 decision tree and multilayer perceptron). According to the experimental results, the proposed models outperform all benchmarks evaluated by the criterion of accuracy. Originality/value This paper focuses on Chinese collocations and proposes a novel research approach for sentiment classification. The Chinese collocations used in this paper are adaptable to the content and domains. Finally, this paper integrates collocations with the preference vector modelling approach, which not only achieves a better sentiment classification performance for Chinese WOM documents but also avoids the curse of dimensionality.

scholarly journals A Hybrid Deep Learning Model for Predicting Protein Hydroxylation Sites

2018 ◽  
Vol 19 (9) ◽  
pp. 2817 ◽  
Author(s):  
Haixia Long ◽  
Bo Liao ◽  
Xingyu Xu ◽  
Jialiang Yang
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Learning Model ◽  
New Drugs ◽  
Post Translational Modifications ◽  
Novel Approach ◽  
Benchmark Datasets ◽  
Memory Network ◽  
Scoring Matrix ◽  
Deep Learning Model

Protein hydroxylation is one type of post-translational modifications (PTMs) playing critical roles in human diseases. It is known that protein sequence contains many uncharacterized residues of proline and lysine. The question that needs to be answered is: which residue can be hydroxylated, and which one cannot. The answer will not only help understand the mechanism of hydroxylation but can also benefit the development of new drugs. In this paper, we proposed a novel approach for predicting hydroxylation using a hybrid deep learning model integrating the convolutional neural network (CNN) and long short-term memory network (LSTM). We employed a pseudo amino acid composition (PseAAC) method to construct valid benchmark datasets based on a sliding window strategy and used the position-specific scoring matrix (PSSM) to represent samples as inputs to the deep learning model. In addition, we compared our method with popular predictors including CNN, iHyd-PseAAC, and iHyd-PseCp. The results for 5-fold cross-validations all demonstrated that our method significantly outperforms the other methods in prediction accuracy.

scholarly journals Ubiquitination and Ubiquitin-Like Modifications in Multiple Myeloma: Biology and Therapy

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3764
Author(s):  
Matthias Wirth ◽  
Markus Schick ◽  
Ulrich Keller ◽  
Jan Krönke
Keyword(s):  
Multiple Myeloma ◽  
Translational Regulation ◽  
Proteasome Inhibitors ◽  
Ubiquitin Proteasome System ◽  
Organ Damage ◽  
Post Translational Modifications ◽  
Damage Repair ◽  
Ubiquitin Proteasome ◽  
New Treatments ◽  
Effective Drugs

Multiple myeloma is a genetically heterogeneous plasma cell malignancy characterized by organ damage and a massive production of (in-)complete monoclonal antibodies. Coping with protein homeostasis and post-translational regulation is therefore essential for multiple myeloma cells to survive. Furthermore, post-translational modifications such as ubiquitination and SUMOylation play key roles in essential pathways in multiple myeloma, including NFκB signaling, epigenetic regulation, as well as DNA damage repair. Drugs modulating the ubiquitin–proteasome system, such as proteasome inhibitors and thalidomide analogs, are approved and highly effective drugs in multiple myeloma. In this review, we focus on ubiquitin and ubiquitin-like modifications in the biology and current developments of new treatments for multiple myeloma.

Two-digit number processing: holistic, decomposed or hybrid? A computational modelling approach

2010 ◽  
Vol 75 (4) ◽  
pp. 290-306 ◽  
Author(s):  
K. Moeller ◽  
S. Huber ◽  
H.-C. Nuerk ◽  
K. Willmes
Keyword(s):  
Computational Modelling ◽  
Number Processing ◽  
Digit Number ◽  
Modelling Approach

scholarly journals Computational modelling of the heat transfer through two-layer woven structure ensembles

2020 ◽  
Vol 71 (04) ◽  
pp. 393-397
Author(s):  
ANGELOVA A. RADOSTINA ◽  
MIROSLAV KYOSOV ◽  
PETER STANKOV
Keyword(s):  
Heat Transfer ◽  
Numerical Simulation ◽  
Indoor Air ◽  
Software Package ◽  
Computational Modelling ◽  
Cross Flow ◽  
The Body ◽  
Novel Approach ◽  
Woven Structure ◽  
Indoor Conditions

The purpose of the present study was to investigate the heat transfer through a system of two consecutive textile layers with woven macrostructures by numerical simulation, using FLUENT CFD software package. A novel approach for modelling of the textile structure was applied, based on jet systems. The heat transfer through the systems of layers was studied for indoor conditions, simulating skin and indoor air temperature, as well as the effect of the convective cross flow around the human body. The results of the study showed that the heat transfer through a system of two layers is strongly influenced by the porosity and thickness of the fabrics, as well as their arrangement in the systems as an insulating barrier between the body and the environment.

Sign in / Sign up

Export Citation Format

Share Document