T-cell Receptor Is a Threshold Detector: Sub- and Supra-Threshold Stochastic Resonance in TCR-MHC Clusters on the Cell Surface

Bene, László; Bagdány, Miklós; Damjanovich, László

doi:10.3390/e24030389

Cited by 4 publications

(1 citation statement)

References 82 publications

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“…In soluble MHC:peptide multimer (dimers, trimers, and tetramers) experiments, the aggregation of MHC molecules can significantly increase the efficiency of the response in T cells. Several recent publications have reported on the location of immunological synapse molecules according to a certain order (organizing into "supramolecular" clusters) [35,[43][44][45][46][47][48][49]. In light of these facts, we can presume that some of the reviewed associates (e.g., the homoassociation; the HLA class II-HLA class I and the ICAM-1-HLA class I or class II heteroassociation) play a role in the process of antigen presentation and in regulating its efficiency.…”

Section: Discussionmentioning

confidence: 97%

HLA DQ protein changes the cell surface distribution pattern of HLA proteins as monitored by Förster resonance energy transfer and high‐resolution electron microscopy

Kormos,

Veres,

Imre

et al. 2023

Cytometry Pt A

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Peptide presentation by MHC class I and MHC class II molecules plays important roles in the regulation of the immune response. One factor in these displays is the density of antigen, which must exceed a critical threshold for the effective activation of T cells. Nonrandom distribution of MHC class I and class II has already been detected at the nanometer level and at higher hierarchical levels. It is not clear how the absence and reappearance of some protein molecules can influence the nonrandom distribution. Therefore, we performed experiments on HLA II‐deficient bare lymphocyte syndrome (BLS1) cells: we created a stable transfected cell line, tDQ6‐BLS‐1, and were able to detect the effect of the appearance of HLA‐DQ6 molecules on the homo and heteroassociation of different cell surface molecules by comparing Förster resonance energy transfer (FRET) efficiency on transfected cells to that on nontransfected BLS‐1 and JY human B‐cell lines. Our FRET results show a decrease in homoassociation FRET between HLA I chains in HLA‐DQ6‐transfected tDQ6‐BLS‐1 cells compared with the parent BLS‐1 cell line and an increase in heteroassociation FRET between HLA I and HLA II (compared with JY cells), suggesting a similar pattern of antigen presentation by the HLA‐DQ6 allele. Transmission electron microscopy (TEM) revealed that both HLA class I and class II molecules formed clusters at higher hierarchical levels on the tDQ6‐BLS‐1 cells, and the de novo synthesized HLA DQ molecules did not intersperse with HLA class I islands. These observations could be important in understanding the fine tuning of the immune response.

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Section: Discussionmentioning

confidence: 97%

HLA DQ protein changes the cell surface distribution pattern of HLA proteins as monitored by Förster resonance energy transfer and high‐resolution electron microscopy

Kormos,

Veres,

Imre

et al. 2023

Cytometry Pt A

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A novel coupled two-dimensional unsaturated asymmetric bistable stochastic resonance system for bearing fault detection

Zhang

Zhu

Jiang³

2022

Measurement

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Robust neural networks using stochastic resonance neurons

Manuylovich,

Argüello Ron,

Kamalian-Kopae

et al. 2024

Commun Eng

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Various successful applications of deep artificial neural networks are effectively facilitated by the possibility to increase the number of layers and neurons in the network at the expense of the growing computational complexity. Increasing computational complexity to improve performance makes hardware implementation more difficult and directly affects both power consumption and the accumulation of signal processing latency, which are critical issues in many applications. Power consumption can be potentially reduced using analog neural networks, the performance of which, however, is limited by noise aggregation. Following the idea of physics-inspired machine learning, we propose here a type of neural network using stochastic resonances as a dynamic nonlinear node and demonstrate the possibility of considerably reducing the number of neurons required for a given prediction accuracy. We also observe that the performance of such neural networks is more robust against the impact of noise in the training data compared to conventional networks.

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T-cell Receptor Is a Threshold Detector: Sub- and Supra-Threshold Stochastic Resonance in TCR-MHC Clusters on the Cell Surface

Cited by 4 publications

References 82 publications

HLA DQ protein changes the cell surface distribution pattern of HLA proteins as monitored by Förster resonance energy transfer and high‐resolution electron microscopy

HLA DQ protein changes the cell surface distribution pattern of HLA proteins as monitored by Förster resonance energy transfer and high‐resolution electron microscopy

A novel coupled two-dimensional unsaturated asymmetric bistable stochastic resonance system for bearing fault detection

Robust neural networks using stochastic resonance neurons

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