Functional link among tail pinch-induced eating, emotion, and locomotion in rats

2011 ◽  
Vol 71 ◽  
pp. e165-e166
Author(s):  
Nami Someya ◽  
Kimiya Narikiyo ◽  
Akira Masuda ◽  
Shuji Aou
Keyword(s):  
2018 ◽  
Vol 68 (6) ◽  
pp. 799-805 ◽  
Author(s):  
Nami Aso-Someya ◽  
Kimiya Narikiyo ◽  
Akira Masuda ◽  
Shuji Aou

2019 ◽  
Vol 476 (21) ◽  
pp. 3281-3293 ◽  
Author(s):  
Elodie Lebredonchel ◽  
Marine Houdou ◽  
Hans-Heinrich Hoffmann ◽  
Kateryna Kondratska ◽  
Marie-Ange Krzewinski ◽  
...  

TMEM165 was highlighted in 2012 as the first member of the Uncharacterized Protein Family 0016 (UPF0016) related to human glycosylation diseases. Defects in TMEM165 are associated with strong Golgi glycosylation abnormalities. Our previous work has shown that TMEM165 rapidly degrades with supraphysiological manganese supplementation. In this paper, we establish a functional link between TMEM165 and SPCA1, the Golgi Ca2+/Mn2+ P-type ATPase pump. A nearly complete loss of TMEM165 was observed in SPCA1-deficient Hap1 cells. We demonstrate that TMEM165 was constitutively degraded in lysosomes in the absence of SPCA1. Complementation studies showed that TMEM165 abundance was directly dependent on SPCA1's function and more specifically its capacity to pump Mn2+ from the cytosol into the Golgi lumen. Among SPCA1 mutants that differentially impair Mn2+ and Ca2+ transport, only the Q747A mutant that favors Mn2+ pumping rescues the abundance and Golgi subcellular localization of TMEM165. Interestingly, the overexpression of SERCA2b also rescues the expression of TMEM165. Finally, this paper highlights that TMEM165 expression is linked to the function of SPCA1.


Author(s):  
Sarat Chandra Nayak ◽  
Subhranginee Das ◽  
Mohammad Dilsad Ansari

Background and Objective: Stock closing price prediction is enormously complicated. Artificial Neural Networks (ANN) are excellent approximation algorithms applied to this area. Several nature-inspired evolutionary optimization techniques are proposed and used in the literature to search the optimum parameters of ANN based forecasting models. However, most of them need fine-tuning of several control parameters as well as algorithm specific parameters to achieve optimal performance. Improper tuning of such parameters either leads toward additional computational cost or local optima. Methods: Teaching Learning Based Optimization (TLBO) is a newly proposed algorithm which does not necessitate any parameters specific to it. The intrinsic capability of Functional Link Artificial Neural Network (FLANN) to recognize the multifaceted nonlinear relationship present in the historical stock data made it popular and got wide applications in the stock market prediction. This article presents a hybrid model termed as Teaching Learning Based Optimization of Functional Neural Networks (TLBO-FLN) by combining the advantages of both TLBO and FLANN. Results and Conclusion: The model is evaluated by predicting the short, medium, and long-term closing prices of four emerging stock markets. The performance of the TLBO-FLN model is measured through Mean Absolute Percentage of Error (MAPE), Average Relative Variance (ARV), and coefficient of determination (R2); compared with that of few other state-of-the-art models similarly trained and found superior.


Metabolites ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 432
Author(s):  
Iván Ponce ◽  
Nelson Garrido ◽  
Nicolás Tobar ◽  
Francisco Melo ◽  
Patricio C. Smith ◽  
...  

Breast tumors belong to the type of desmoplastic lesion in which a stiffer tissue structure is a determinant of breast cancer progression and constitutes a risk factor for breast cancer development. It has been proposed that cancer-associated stromal cells (responsible for this fibrotic phenomenon) are able to metabolize glucose via lactate production, which supports the catabolic metabolism of cancer cells. The aim of this work was to investigate the possible functional link between these two processes. To measure the effect of matrix rigidity on metabolic determinations, we used compliant elastic polyacrylamide gels as a substrate material, to which matrix molecules were covalently linked. We evaluated metabolite transport in stromal cells using two different FRET (Fluorescence Resonance Energy Transfer) nanosensors specific for glucose and lactate. Cell migration/invasion was evaluated using Transwell devices. We show that increased stiffness stimulates lactate production and glucose uptake by mammary fibroblasts. This response was correlated with the expression of stromal glucose transporter Glut1 and monocarboxylate transporters MCT4. Moreover, mammary stromal cells cultured on stiff matrices generated soluble factors that stimulated epithelial breast migration in a stiffness-dependent manner. Using a normal breast stromal cell line, we found that a stiffer extracellular matrix favors the acquisition mechanistical properties that promote metabolic reprograming and also constitute a stimulus for epithelial motility. This new knowledge will help us to better understand the complex relationship between fibrosis, metabolic reprogramming, and cancer malignancy.


BIOspektrum ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 10-13
Author(s):  
Alicia Konrath ◽  
Ann-Kathrin Schmidt ◽  
Holger Bastians

AbstractChromosomal instability (CIN) is a hallmark of cancer and contributes to tumorigenesis and tumor progression. While structural CIN (S-CIN) leads to structural chromosome aberrations, whole chromosome instability (W-CIN) is defined by perpetual gains or losses of chromosomes during mitosis causing aneuploidy. Mitotic defects, but also abnormal DNA replication (replication stress) can lead to W-CIN. However, the functional link between replication stress, mitosis and aneuploidy is little understood.


Author(s):  
Sunil Kumar Jangir ◽  
Nakul Joshi ◽  
Manish Kumar ◽  
Dilip Kumar Choubey ◽  
Shatakshi Singh ◽  
...  

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