A prominent feature of gene transcription regulatory networks is the presence in large numbers of motifs, i.e., patterns of interconnection, in the networks. One such motif is the feed forward loop (FFL) consisting of three genes X, Y and Z. The protein product x of X controls the synthesis of protein product y of Y. Proteins x and y jointly regulate the synthesis of z proteins from the gene Z. The FFLs, depending on the nature of the regulating interactions, can be of eight different types which can again be classified into two categories: coherent and incoherent. In this paper, we study the noise characteristics of FFLs using the Langevin formalism and the Monte Carlo simulation technique based on the Gillespie algorithm. We calculate the variances around the mean protein levels in the steady states of the FFLs and find that, in the case of coherent FFLs, the most abundant FFL, namely, the type-1 coherent FFL, is the least noisy. This is shown to be true for all parameter values when the FFLs operate above their thresholds of activation/repression. In the case of incoherent FFLs, no such general conclusion can be shown. The results suggest possible relationships between noise, functionality and abundance.
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http://dx.doi.org/10.1088/1478-3967/2/1/005 | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Chemistry, Center for BioAnalytical Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Tsinghua University, Beijing, 100084, China.
Single nanoparticle analysis is crucial for various applications in biology, materials, and energy. However, precisely profiling and monitoring weakly scattering nanoparticles remains challenging. Here, it is demonstrated that deep learning-empowered plasmonic microscopy (Deep-SM) enables precise sizing and collision detection of functional chemical and biological nanoparticles.
View Article and Find Full Text PDFHealthcare (Basel)
January 2025
Department of Computer Science, Institute of Mathematics and Statistics, University of São Paulo (USP), São Paulo 05508-220, SP, Brazil.
Background/objectives: The aim of this paper was to compare voice and speech characteristics between post-COVID-19 and control subjects. The hypothesis was that acoustic parameters of voice and speech may differentiate subjects infected by COVID-19 from control subjects. Additionally, we expected to observe the persistence of symptoms in women.
View Article and Find Full Text PDFLangmuir
January 2025
Department of Bioinformatics and Medical Engineering, Asia University, Taichung 413305, Taiwan.
Photoelectrochemical sensors have been studied for glucose detection because of their ability to minimize background noise and unwanted reactions. Titanium dioxide (TiO), a highly efficient material in converting light into electricity, cannot utilize visible light. In this regard, we developed a nonenzymatic glucose sensor by using a simple one-step electrospinning technique to combine cupric oxide with TiO to create a heterojunction.
View Article and Find Full Text PDFEar Hear
January 2025
Dutch Foundation of the Deaf and Hard of Hearing Child (NSDSK), Amsterdam, The Netherlands.
Objectives: One important aspect in facilitating language access for children with hearing loss (HL) is the auditory environment. An optimal auditory environment is characterized by high signal to noise ratios (SNRs), low background noise levels, and low reverberation times. In this study, the authors describe the auditory environment of early intervention groups specifically equipped for young children with HL.
View Article and Find Full Text PDFNoise Health
January 2025
School of Public Health, Anhui University of Science and Technology, Huainan, Anhui, People's Republic of China.
Objectives: This study aims to investigate the relationship between noise kurtosis and cardiovascular disease (CVD) risk while exploring the potential of kurtosis assessment in evaluating CVD risk associated with complex noise exposure in coal mines.
Methods: This cross-sectional study started in April 2021 and ended in November 2022. It involved 705 coal miners selected from 1045 participants.
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