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1.
Int Immunol ; 36(9): 465-470, 2024 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-38666722

RESUMO

The long-term value of efficient antigen discovery includes gaining insights into the variety of potential cancer neoantigens, effective vaccines lacking adverse effects, and adaptive immune receptor (IR) targets for blocking adaptive IR-antigen interactions in autoimmunity. While the preceding goals have been partially addressed via big data approaches to HLA (human leukocyte antigen)-epitope binding, there has been little such progress in the big data setting for adaptive IR-epitope binding. This delay in progress for the latter is likely due to, among other things, the much more complicated adaptive IR repertoire in an individual compared to individual HLA alleles. Thus, results described here represent the application of an algorithm for efficient assessment of immunoglobulin heavy chain complementarity determining region-3 (IGH CDR3)-gliadin epitope interactions, with a focus on epitopes known to be associated with an immune response in celiac disease. The hydrophobic, chemical complementarity between celiac case IGH CDR3s and known celiac epitopes was found to be greater in comparison to the hydrophobic, chemical complementarity between the same celiac case IGH CDR3s and a series of control epitopes. Thus, the approaches indicated here likely offer guidance for the development of conveniently applied algorithms for antigen verification and discovery.


Assuntos
Doença Celíaca , Regiões Determinantes de Complementaridade , Gliadina , Cadeias Pesadas de Imunoglobulinas , Humanos , Doença Celíaca/imunologia , Doença Celíaca/genética , Regiões Determinantes de Complementaridade/genética , Regiões Determinantes de Complementaridade/imunologia , Regiões Determinantes de Complementaridade/química , Cadeias Pesadas de Imunoglobulinas/genética , Cadeias Pesadas de Imunoglobulinas/imunologia , Gliadina/imunologia , Gliadina/química , Epitopos/imunologia , Algoritmos
2.
Med Phys ; 51(4): 2967-2974, 2024 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-38456557

RESUMO

BACKGROUND: Position verification and motion monitoring are critical for safe and precise radiotherapy (RT). Existing approaches to these tasks based on visible light or x-ray are suboptimal either because they cannot penetrate obstructions to the patient's skin or introduce additional radiation exposure. The low-cost mmWave radar is an ideal solution for these tasks as it can monitor patient position and motion continuously throughout the treatment delivery. PURPOSE: To develop and validate frequency-modulated continuous wave (FMCW) mmWave radars for position verification and motion tracking during RT delivery. METHODS: A 77 GHz FMCW mmWave module was used in this study. Chirp Z Transform-based (CZT) algorithm was developed to process the intermediate frequency (IF) signals. Absolute distances to flat Solid Water slabs and human shape phantoms were measured. The accuracy of absolute distance and relative displacement were evaluated. RESULTS: Without obstruction, mmWave based on the CZT algorithm was able to detect absolute distance within 1 mm for a Solid Water slab that simulated the reflectivity of the human body. Through obstructive materials, the mmWave device was able to detect absolute distance within 5 mm in the worst case and within 3.5 mm in most cases. The CZT algorithm significantly improved the accuracy of absolute distance measurement compared with Fast Fourier Transform (FFT) algorithm and was able to achieve submillimeter displacement accuracy with and without obstructions. The surface-to-skin distance (SSD) measurement accuracy was within 8 mm in the anterior of the phantom. CONCLUSIONS: With the CZT signal processing algorithm, the mmWave radar is able to measure the absolute distance to a flat surface within 1 mm. But the absolute distance measurement to a human shape phantom is as large as 8 mm at some angles. Further improvement is necessary to improve the accuracy of SSD measurement to uneven surfaces by the mmWave radar.


Assuntos
Processamento de Sinais Assistido por Computador , Água , Humanos , Movimento (Física) , Radiografia
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