scholarly journals Phosphorylation of LSD1 by PKCα Is Crucial for Circadian Rhythmicity and Phase Resetting

2014 ◽  
Vol 53 (5) ◽  
pp. 791-805 ◽  
Author(s):  
Hye Jin Nam ◽  
Kyungjin Boo ◽  
Dongha Kim ◽  
Dong-Hee Han ◽  
Han Kyoung Choe ◽  
...  
Keyword(s):  
Circadian Rhythmicity ◽  
Phase Resetting

Aging alters the phase-resetting properties of a serotonin agonist on hamster circadian rhythmicity

1995 ◽  
Vol 268 (1) ◽  
pp. R293-R298 ◽  
Author(s):  
P. D. Penev ◽  
P. C. Zee ◽  
E. P. Wallen ◽  
F. W. Turek
Keyword(s):  
Receptor Agonist ◽  
Activity Rhythm ◽  
Circadian System ◽  
Circadian Rhythmicity ◽  
Phase Shifting ◽  
Phase Resetting ◽  
Serotonin Agonist ◽  
Age Related ◽  
Temporal Adaptation ◽  
Circadian Time

Serotonergic mechanisms are believed to play a considerable role in mediating the effects of photic and nonphotic stimuli on circadian rhythmicity. Because aging is associated with significant changes in the responsiveness of the rodent circadian system to major synchronizing agents in the environment, this study examined the phase-shifting effects of the 5-HT1A receptor agonist, 8-hydroxy-2-(di-n-propylamino)tetralin [8-OH-DPAT; 2.0, 5.0, and 8.0 mg/kg ip at circadian time 8 (CT 8)], on the 24-h activity rhythm of young (3-4 mo old) and old (18-19 mo old) golden hamsters. Aging was associated with a dramatic attenuation of the phase-shifting effects of 8-OH-DPAT in this species. The results suggest the existence of age-related deficits in the serotonergic control of mammalian circadian rhythmicity, which could interfere with the temporal adaptation of the senescent organism to its environment.

scholarly journals Acute ethanol impairs photic and nonphotic circadian phase resetting in the Syrian hamster

2009 ◽  
Vol 296 (2) ◽  
pp. R411-R418 ◽  
Author(s):  
Christina L. Ruby ◽  
Rebecca A. Prosser ◽  
Marc A. DePaul ◽  
Randy J. Roberts ◽  
J. David Glass
Keyword(s):  
Circadian Clock ◽  
Activity Rhythm ◽  
Direct Action ◽  
Glutamate Release ◽  
Extracellular Fluid ◽  
Circadian Rhythmicity ◽  
Phase Resetting ◽  
Circadian Phase ◽  
Acute Ethanol

Disrupted circadian rhythmicity is associated with ethanol (EtOH) abuse, yet little is known about how EtOH affects the mammalian circadian clock of the suprachiasmatic nucleus (SCN). Clock timing is regulated by photic and nonphotic inputs to the SCN involving glutamate release from the retinohypothalamic tract and serotonin (5-HT) from the midbrain raphe, respectively. Our recent in vitro studies in the SCN slice revealed that EtOH blocks photic phase-resetting action of glutamate and enhances the nonphotic phase-resetting action of the 5-HT1A,7 agonist, 8-OH-DPAT. To explore the basis of these effects in the whole animal, we used microdialysis to characterize the pharmacokinetics of intraperitoneal injection of EtOH in the hamster SCN extracellular fluid compartment and then studied the effects of such EtOH treatment on photic and serotonergic phase resetting of the circadian locomotor activity rhythm. Peak EtOH levels (∼50 mM) from a 2 g/kg injection occurred within 20–40 min with a half-life of ∼3 h. EtOH treatment dose-dependently attenuated photic phase advances but had no effect on phase delays and, contrary to in vitro findings, markedly attenuated 8-OH-DPAT-induced phase advances. In a complementary experiment using reverse microdialysis to deliver a timed SCN perfusion of EtOH during a phase-advancing light pulse, the phase advances were blocked, similar to systemic EtOH treatment. These results are evidence that acute EtOH significantly affects photic and nonphotic phase-resetting responses critical to circadian clock regulation. Notably, EtOH inhibition of photic signaling is manifest through direct action in the SCN. Such actions could underlie the disruption of circadian rhythmicity associated with alcohol abuse.

Role of miRNA in circadian rhythmicity: recent progress

2011 ◽  
Vol 31 (10) ◽  
pp. 1137-1139
Author(s):  
Qing-min WANG ◽  
Hui WAN ◽  
Fen-zhou SHI ◽  
Jun SHEN ◽  
Qiu-hong LIU
Keyword(s):  
Recent Progress ◽  
Circadian Rhythmicity

scholarly journals Transcriptomal dissection of soybean circadian rhythmicity in two geographically, phenotypically and genetically distinct cultivars

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanlei Yue ◽  
Ze Jiang ◽  
Enoch Sapey ◽  
Tingting Wu ◽  
Shi Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Circadian Clock ◽  
Chromosome Structure ◽  
Clock Genes ◽  
Expression Profiles ◽  
Circadian Rhythmicity ◽  
Rna Seq ◽  
Night Time ◽  
Time Points ◽  
Circadian Clock Genes

Abstract Background In soybean, some circadian clock genes have been identified as loci for maturity traits. However, the effects of these genes on soybean circadian rhythmicity and their impacts on maturity are unclear. Results We used two geographically, phenotypically and genetically distinct cultivars, conventional juvenile Zhonghuang 24 (with functional J/GmELF3a, a homolog of the circadian clock indispensable component EARLY FLOWERING 3) and long juvenile Huaxia 3 (with dysfunctional j/Gmelf3a) to dissect the soybean circadian clock with time-series transcriptomal RNA-Seq analysis of unifoliate leaves on a day scale. The results showed that several known circadian clock components, including RVE1, GI, LUX and TOC1, phase differently in soybean than in Arabidopsis, demonstrating that the soybean circadian clock is obviously different from the canonical model in Arabidopsis. In contrast to the observation that ELF3 dysfunction results in clock arrhythmia in Arabidopsis, the circadian clock is conserved in soybean regardless of the functional status of J/GmELF3a. Soybean exhibits a circadian rhythmicity in both gene expression and alternative splicing. Genes can be grouped into six clusters, C1-C6, with different expression profiles. Many more genes are grouped into the night clusters (C4-C6) than in the day cluster (C2), showing that night is essential for gene expression and regulation. Moreover, soybean chromosomes are activated with a circadian rhythmicity, indicating that high-order chromosome structure might impact circadian rhythmicity. Interestingly, night time points were clustered in one group, while day time points were separated into two groups, morning and afternoon, demonstrating that morning and afternoon are representative of different environments for soybean growth and development. However, no genes were consistently differentially expressed over different time-points, indicating that it is necessary to perform a circadian rhythmicity analysis to more thoroughly dissect the function of a gene. Moreover, the analysis of the circadian rhythmicity of the GmFT family showed that GmELF3a might phase- and amplitude-modulate the GmFT family to regulate the juvenility and maturity traits of soybean. Conclusions These results and the resultant RNA-seq data should be helpful in understanding the soybean circadian clock and elucidating the connection between the circadian clock and soybean maturity.

scholarly journals Phase resetting in central and peripheral sinoatrial node cell models

2005 ◽  
Author(s):  
D.G. Tsalikakis ◽  
H.G. Zhang ◽  
D.I. Fotiadis ◽  
G.P. Kremmydas
Keyword(s):  
Sinoatrial Node ◽  
Phase Resetting ◽  
Cell Models ◽  
Sinoatrial Node Cell

Pulse Inputs Affect Timings of Spikes in Neurons with or Without Time Delays

2019 ◽  
Vol 20 (3-4) ◽  
pp. 257-267
Author(s):  
Jiaoyan Wang ◽  
Xiaoshan Zhao ◽  
Chao Lei
Keyword(s):  
Time Delays ◽  
Single Neuron ◽  
Spiking Neurons ◽  
Phase Resetting ◽  
Subthreshold Oscillations ◽  
Weak Pulse

AbstractInputs can change timings of spikes in neurons. But it is still not clear how input’s parameters for example injecting time of inputs affect timings of neurons. HR neurons receiving both weak and strong inputs are considered. How pulse inputs affecting neurons is studied by using the phase-resetting curve technique. For a single neuron, weak pulse inputs may advance or delay the next spike, while strong pulse inputs may induce subthreshold oscillations depending on parameters such as injecting timings of inputs. The behavior of synchronization in a network with or without coupling delays can be predicted by analysis in a single neuron. Our results can be used to predict the effects of inputs on other spiking neurons.

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