scholarly journals Brain circuits mediating baroreflex bradycardia inhibition in rats: an anatomical and functional link between the cuneiform nucleus and the periaqueductal grey

2011 ◽  
Vol 589 (8) ◽  
pp. 2079-2091 ◽  
Author(s):  
Florence Netzer ◽  
Jean-François Bernard ◽  
Anthony J. M. Verberne ◽  
Michel Hamon ◽  
Françoise Camus ◽  
...  
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.


2020 ◽  
Vol 13 (12) ◽  
pp. e238545
Author(s):  
Papa Dasari ◽  
Smitha Priyadarshini

A teenage primigravida at 13 weeks of gestation presented with hyperemesis gravidarum of 45 days and a history of giddiness and inability to walk due to involuntary movements of limbs and eyes since 2 days. She was treated with intravenous fluids, thiamine and antiemetics. MRI brain showed hyperintensities in bilateral dorsomedial thalami, periaqueductal grey matter in T2-weighted and FLAIR images. A diagnosis of Wernicke encephalopathy was made and she was managed in intensive care unit and received injection thiamine as per the guidelines and her weakness and ataxia improved over 3 weeks and she was discharged at 17 weeks of pregnancy in good state of health.


Author(s):  
Leandro F. Vendruscolo ◽  
George F. Koob

Alcohol use disorder is a chronically relapsing disorder that involves (1) compulsivity to seek and take alcohol, (2) difficulty in limiting alcohol intake, and (3) emergence of a negative emotional state (e.g., dysphoria, anxiety, irritability) in the absence of alcohol. Alcohol addiction encompasses a three-stage cycle that becomes more intense as alcohol use progresses: binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation. These stages engage neuroadaptations in brain circuits that involve the basal ganglia (reward hypofunction), extended amygdala (stress sensitization), and prefrontal cortex (executive function disorder). This chapter discusses key neuroadaptations in the hypothalamic and extrahypothalamic stress systems and the critical role of glucocorticoid receptors. These neuroadaptations contribute to negative emotional states that powerfully drive compulsive alcohol drinking and seeking. These changes in association with a disruption of prefrontal cortex function that lead to cognitive deficits and poor decision making contribute to the chronic relapsing nature of alcohol dependence.


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