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Ciliates learn to diagnose and correct classical error syndromes in mating strategies

Overview of attention for article published in Frontiers in Microbiology, January 2013
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Title
Ciliates learn to diagnose and correct classical error syndromes in mating strategies
Published in
Frontiers in Microbiology, January 2013
DOI 10.3389/fmicb.2013.00229
Pubmed ID
Authors

Kevin B. Clark

Abstract

Preconjugal ciliates learn classical repetition error-correction codes to safeguard mating messages and replies from corruption by "rivals" and local ambient noise. Because individual cells behave as memory channels with Szilárd engine attributes, these coding schemes also might be used to limit, diagnose, and correct mating-signal errors due to noisy intracellular information processing. The present study, therefore, assessed whether heterotrich ciliates effect fault-tolerant signal planning and execution by modifying engine performance, and consequently entropy content of codes, during mock cell-cell communication. Socially meaningful serial vibrations emitted from an ambiguous artificial source initiated ciliate behavioral signaling performances known to advertise mating fitness with varying courtship strategies. Microbes, employing calcium-dependent Hebbian-like decision making, learned to diagnose then correct error syndromes by recursively matching Boltzmann entropies between signal planning and execution stages via "power" or "refrigeration" cycles. All eight serial contraction and reversal strategies incurred errors in entropy magnitude by the execution stage of processing. Absolute errors, however, subtended expected threshold values for single bit-flip errors in three-bit replies, indicating coding schemes protected information content throughout signal production. Ciliate preparedness for vibrations selectively and significantly affected the magnitude and valence of Szilárd engine performance during modal and non-modal strategy corrective cycles. But entropy fidelity for all replies mainly improved across learning trials as refinements in engine efficiency. Fidelity neared maximum levels for only modal signals coded in resilient three-bit repetition error-correction sequences. Together, these findings demonstrate microbes can elevate survival/reproductive success by learning to implement classical fault-tolerant information processing in social contexts.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 17%
Professor > Associate Professor 2 11%
Student > Master 2 11%
Student > Ph. D. Student 2 11%
Lecturer > Senior Lecturer 1 6%
Other 4 22%
Unknown 4 22%
Readers by discipline Count As %
Economics, Econometrics and Finance 2 11%
Psychology 2 11%
Agricultural and Biological Sciences 2 11%
Business, Management and Accounting 1 6%
Immunology and Microbiology 1 6%
Other 5 28%
Unknown 5 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 August 2013.
All research outputs
#20,198,525
of 22,716,996 outputs
Outputs from Frontiers in Microbiology
#22,147
of 24,561 outputs
Outputs of similar age
#248,774
of 280,757 outputs
Outputs of similar age from Frontiers in Microbiology
#264
of 407 outputs
Altmetric has tracked 22,716,996 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,561 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 407 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.