Neural network-based estimation of biomechanical vocal fold parameters
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PROVIDER: S-EPMC10916882 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Candidate cell sources for vocal fold scar treatment include mesenchymal stromal cells from bone marrow (BM-MSC) and adipose tissue (AT-MSC). Mechanosensitivity of MSC can alter highly relevant aspects of their behavior, yet virtually nothing is known about how MSC might respond to the dynamic mechanical environment of the larynx. Our objective was to evaluate MSC as a potential cell source for vocal fold tissue engineering in a mechanically relevant context. A vibratory strain bioreactor and cDNA microarray were used to evaluate the similarity of AT-MSC and BM-MSC to the native cell source, vocal fold fibroblasts (VFF). Posterior probabilities for each of the microarray transcripts fitting into specific expression patterns were calculated, and the data were analyzed for Gene Ontology (GO) enrichment. Significant wound healing and cell differentiation GO terms are reported. In addition, proliferation and apoptosis were evaluated with immunohistochemistry. Results revealed that VFF shared more GO terms related to epithelial development, extracellular matrix (ECM) remodeling, growth factor activity, and immune response with BM-MSC than with AT-MSC. Similarity in glycosaminoglycan and proteoglycan activity dominated the ECM analysis. Analysis of GO terms relating to MSC differentiation toward osteogenic, adipogenic, and chondrogenic lineages revealed that BM-MSC expressed fewer osteogenesis GO terms in the vibrated and scaffold-only conditions compared to polystyrene. We did not evaluate if vibrated BM-MSC recover osteogenic expression markers when returned to polystyrene culture. Immunostaining for Ki67 and cleaved caspase 3 did not vary with cell type or mechanical condition. We conclude that VFF may have a more similar wound healing capacity to BM-MSC than to AT-MSC in response to short-term vibratory strain. Furthermore, BM-MSC appear to lose osteogenic potential in the vibrated and scaffold-only conditions compared to polystyrene, potentially attenuating the risk of osteogenesis for in vivo applications.
| S-EPMC4555478 | biostudies-literature
Project description:MotivationHuman voice is generated in the larynx by the two oscillating vocal folds. Owing to the limited space and accessibility of the larynx, endoscopic investigation of the actual phonatory process in detail is challenging. Hence the biomechanics of the human phonatory process are still not yet fully understood. Therefore, we adapt a mathematical model of the vocal folds towards vocal fold oscillations to quantify gender and age related differences expressed by computed biomechanical model parameters.MethodsThe vocal fold dynamics are visualized by laryngeal high-speed videoendoscopy (4000 fps). A total of 33 healthy young subjects (16 females, 17 males) and 11 elderly subjects (5 females, 6 males) were recorded. A numerical two-mass model is adapted to the recorded vocal fold oscillations by varying model masses, stiffness and subglottal pressure. For adapting the model towards the recorded vocal fold dynamics, three different optimization algorithms (Nelder-Mead, Particle Swarm Optimization and Simulated Bee Colony) in combination with three cost functions were considered for applicability. Gender differences and age-related kinematic differences reflected by the model parameters were analyzed.Results and conclusionThe biomechanical model in combination with numerical optimization techniques allowed phonatory behavior to be simulated and laryngeal parameters involved to be quantified. All three optimization algorithms showed promising results. However, only one cost function seems to be suitable for this optimization task. The gained model parameters reflect the phonatory biomechanics for men and women well and show quantitative age- and gender-specific differences. The model parameters for younger females and males showed lower subglottal pressures, lower stiffness and higher masses than the corresponding elderly groups. Females exhibited higher subglottal pressures, smaller oscillation masses and larger stiffness than the corresponding similar aged male groups. Optimizing numerical models towards vocal fold oscillations is useful to identify underlying laryngeal components controlling the phonatory process.
| S-EPMC5679561 | biostudies-literature
Project description:Despite the fact that vocal folds are subjected to extensive mechanical forces, the role of mechanical strain in vocal fold wound healing has been overlooked. Recent studies on other tissues have demonstrated that low physiological levels of mechanical forces are beneficial to injured tissues, reduce inflammation, and induce synthesis of matrix-associated proteins essential for enhanced wound healing. In this study, we speculated that mechanical strain of low magnitudes also attenuates the production of inflammatory mediators and alters the extracellular matrix synthesis to augment wound healing in cultured vocal fold fibroblasts. To test this hypothesis, fibroblasts from rabbit vocal folds were isolated and exposed to various magnitudes of cyclic tensile strain (CTS) in the presence or absence of interleukin-1beta (IL-1beta). Results suggest that IL-1beta activates proinflammatory gene transcription in vocal fold fibroblasts. Furthermore, CTS abrogates the IL-1beta-induced proinflammatory gene induction in a magnitude-dependent manner. In addition, CTS blocks IL-1beta-mediated inhibition of collagen type I synthesis, and thereby upregulates collagen synthesis in the presence of IL-1beta. These findings are the first to reveal the potential utility of low levels of mechanical signals in vocal fold wound healing, and support the emerging on vivo data suggesting beneficial effects of vocal exercise on acute phonotrauma.
| S-EPMC4948979 | biostudies-literature
Project description:Vocal cord healing is a dynamic process, and many genes and proteins are involved, which play varying roles at different regeneration stages after injury. Previous studies have shown that inflammatory responses occur at the early stage of vocal cord injury, where the fibroblasts proliferate exuberantly with intensive secretion and deposition of ECM. These activities reach the peak at 3-7 days and their intensity begins to decline 15 days later. A study based on the dermal system has shown that ECM remodeling during the repair of injury can last for several months. However, few studies have been conducted as to the dynamic changes of gene expressions and signaling pathway during the healing process of vocal cord injury. Plotting these changes will facilitate the understanding about the physiological changes during healing and the identification of key time points and target genes in fibrosis formation.
2019-10-26 | GSE139383 | GEO
Project description:Vocal cord healing is a dynamic process, and many genes and proteins are involved, which play varying roles at different regeneration stages after injury. Previous studies have shown that inflammatory responses occur at the early stage of vocal cord injury, where the fibroblasts proliferate exuberantly with intensive secretion and deposition of ECM. These activities reach the peak at 3-7 days and their intensity begins to decline 15 days later. A study based on the dermal system has shown that ECM remodeling during the repair of injury can last for several months. However, few studies have been conducted as to the dynamic changes of gene and microRNA expressions during the healing process of vocal cord injury. Plotting these changes will facilitate the understanding about the physiological changes during healing and the identification of key time points and target genes and microRNAs in fibrosis formation.
2020-03-25 | GSE147473 | GEO
Project description:We used microarrays to characterize transcriptome profiles of rat vocal fold tissue following surgical injury (vs. naive tissue); rat vocal fold fibroblasts harvested from scar tissue at the 60 d time point (vs. naive fibroblasts); rat vocal fold scar fibroblasts treated with siRNA against the collagen chaperone protein rat gp46 (vs. scramble siRNA). Adult Fischer 344 rat vocal fold tissue was harvested at 3, 14, and 60 days following surgical injury (control = age-matched naive tissue); rat vocal fold scar fibroblasts were obtained via explant culture of tissue obtained 60 days following surgical injury and harvested at 80% confluence during passage 1 (control = age-matched naive rat vocal fold fibroblasts); rat vocal fold scar fibroblasts were treated for 1 h with 50 nM liposome-delivered siRNA against rat gp46 when 80% confluent at passage 1, cultured for an additional 24 h in fresh media, then harvested (control = rat vocal fold scar fibroblasts treated with 50 nM liposome-delivered scramble siRNA).
2014-10-09 | E-GEOD-62204 | biostudies-arrayexpress
Project description:Most modeling in systems neuroscience has been descriptive where neural representations such as 'receptive fields', have been found by statistically correlating neural activity to sensory input. In the traditional physics approach to modelling, hypotheses are represented by mechanistic models based on the underlying building blocks of the system, and candidate models are validated by comparing with experiments. Until now validation of mechanistic cortical network models has been based on comparison with neuronal spikes, found from the high-frequency part of extracellular electrical potentials. In this computational study we investigated to what extent the low-frequency part of the signal, the local field potential (LFP), can be used to validate and infer properties of mechanistic cortical network models. In particular, we asked the question whether the LFP can be used to accurately estimate synaptic connection weights in the underlying network. We considered the thoroughly analysed Brunel network comprising an excitatory and an inhibitory population of recurrently connected integrate-and-fire (LIF) neurons. This model exhibits a high diversity of spiking network dynamics depending on the values of only three network parameters. The LFP generated by the network was computed using a hybrid scheme where spikes computed from the point-neuron network were replayed on biophysically detailed multicompartmental neurons. We assessed how accurately the three model parameters could be estimated from power spectra of stationary 'background' LFP signals by application of convolutional neural nets (CNNs). All network parameters could be very accurately estimated, suggesting that LFPs indeed can be used for network model validation.
| S-EPMC7083334 | biostudies-literature
Project description:We used microarrays to characterize transcriptome profiles of rat vocal fold tissue following surgical injury (vs. naive tissue); rat vocal fold fibroblasts harvested from scar tissue at the 60 d time point (vs. naive fibroblasts); rat vocal fold scar fibroblasts treated with siRNA against the collagen chaperone protein rat gp46 (vs. scramble siRNA).
2014-10-09 | GSE62204 | GEO
Project description:PurposeThis exploratory study aims to investigate variations in voice production in the presence of background noise (Lombard effect) in individuals with nonphonotraumatic vocal hyperfunction (NPVH) and individuals with typical voices using acoustic, aerodynamic, and vocal fold vibratory measures of phonatory function.MethodNineteen participants with NPVH and 19 participants with typical voices produced simple vocal tasks in three sequential background conditions: baseline (in quiet), Lombard (in noise), and recovery (5 min after removing the noise). The Lombard condition consisted of speech-shaped noise at 80 dB SPL through audiometric headphones. Acoustic measures from a microphone, glottal aerodynamic parameters estimated from the oral airflow measured with a circumferentially vented pneumotachograph mask, and vocal fold vibratory parameters from high-speed videoendoscopy were analyzed.ResultsDuring the Lombard condition, both groups exhibited a decrease in open quotient and increases in sound pressure level, peak-to-peak glottal airflow, maximum flow declination rate, and subglottal pressure. During the recovery condition, the acoustic and aerodynamic measures of individuals with typical voices returned to those of the baseline condition; however, recovery measures for individuals with NPVH did not return to baseline values.ConclusionsAs expected, individuals with NPVH and participants with typical voices exhibited a Lombard effect in the presence of elevated background noise levels. During the recovery condition, individuals with NPVH did not return to their baseline state, pointing to a persistence of the Lombard effect after noise removal. This behavior could be related to disruptions in laryngeal motor control and may play a role in the etiology of NPVH.Supplemental materialhttps://doi.org/10.23641/asha.20415600.
| S-EPMC9913286 | biostudies-literature
Project description:Comprehensive and precise knowledge about rocks' mechanical properties facilitate the drilling performance optimization, and hydraulic fracturing design and reduces the risk of wellbore-related problems. This paper is concerned with the failure parameters, namely, cohesion and friction angle which are conventionally estimated using Mohr's cycles that are drawn using compressional tests on rock samples. The availability, continuity and representability, and cost of acquiring those samples are major concerns. The objective of this paper is to investigate an alternative technique to estimate these parameters from the drilling data. In this work, more than 2200 data points were used to develop and test the correlations built by the artificial neural network. Each data point comprises the failure parameters and five drilling records that are available instantaneously in drilling rigs such as rate of penetration, weight on bit, and torque. The data were grouped into three datasets, training, testing, and validation with a corresponding percentage of 60/20/20, the former two sets were utilized in the models' building while the last one was hidden as a final check afterward. The models were optimized and evaluated using the correlation coefficient (R) and average absolute percentage error (AAPE). In general, the two models yielded good fits with the actual values. The friction angle model yielded R values around 0.86 and AAPE values around 4% for the three datasets. While the model for cohesion resulted in R values around 0.89 and APPE values around 6%. The equation and the parameters of those models are reported in the paper. These results show the ability of in-situ and instantaneous rock mechanical properties estimation with good reliability and at no additional costs.
| S-EPMC9950081 | biostudies-literature