The immunogenic radiation and new players in immunotherapy and targeted therapy for head and neck cancer

Frontiers in Oral Health, Journal Year: 2023, Volume and Issue: 4

Published: July 11, 2023

Although treatment modalities for head and neck cancer have evolved considerably over the past decades, survival rates plateaued. The options remained limited to definitive surgery, surgery followed by fractionated radiotherapy with optional chemotherapy, a combination of chemotherapy. Lately, immunotherapy has been introduced as fourth modality treatment, mainly administered single checkpoint inhibitor recurrent or metastatic disease. While other regimens combinations targeted therapy are being tested in clinical trials, adapting appropriate patients predicting their outcomes yet reach setting. Radiotherapy is regarded means target cells while minimizing unwanted peripheral effect. fractionation designed serve this purpose, systemic effect radiation on immune response rarely considered factor designing treatment. To bridge gap, review will highlight tumor microenvironment locally, systemically. We methodology identify potential targets scientific basis combining radiotherapy. describe current experience preclinical models test these propose how challenges realm may be faced. new players utilization drive immunogenic against cancer. outline factors contributing heterogeneity

Language: Английский

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A Simple and Sensitive Electrochemical Sandwich‐Like Immunosensor for Interleukin‐8 Utilizing Carbon Black as a Sensing Platform and Silver‐Ferrocene as a Signal Amplifier

ChemistrySelect, Journal Year: 2023, Volume and Issue: 8(10)

Published: March 7, 2023

Abstract Designing sensitive and low‐cost method for interleukin‐8 (IL‐8) determination is of great significance in the early diagnosis oral cancer. In present work, a simple, sandwich‐like electrochemical immunosensor IL‐8 was developed by introducing perylene tetracarboxylic acid‐carbon black (PTCA‐CB) as sensing platform silver‐ferrocene (Ag−Fc) signal amplifier. PTCA‐CB can offer large surface area high conductivity well stable supporter to assemble primary antibody (Ab 1 ), while Ag could carry Fc probe secondary antibodies 2 ) produce Ab −Ag−Fc presence with different concentrations, peak currents from formed structure −Ag−Fc/IL‐8/Ab /CB increase concentration, thus constructed based on this principle. After optimizing related control conditions, wide linear range (3.0 pg mL −1 2.0 ng very low detection limit (1.0 were achieved, it's convinced sensor has important clinical applications.

Language: Английский

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Deep Learning Techniques for Oral Cancer Detection: Enhancing Clinical Diagnosis by ResNet and DenseNet Performance

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 59 - 72

Published: Oct. 18, 2024

Language: Английский

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Predicting Bacterial Antibiotic Resistance using MALDI-TOF Mass Spectrometry Databases with ELM Applications.

Journal of Computer Science and Technology, Journal Year: 2024, Volume and Issue: 24(2), P. e08 - e08

Published: Oct. 18, 2024

Early detection of antibiotic resistance is a crucial task, especially for vulnerable patients under prolonged treatments with single antibiotic. To solve this, machine learning approaches have been reported in the state art. Researchers used MALDI-TOF MS order to predict and/or susceptibility bacterial samples. Weis, et al. implemented LR, LightGBM and ANN study on strains Escherichia Coli, Staphylococcus Aureus, Klebsiella Pneumoniae. Despite promising results, models not achieved perfect accuracy, specifically when classes are unbalanced. On other hand, Extreme Learning Machine (ELM) training algorithm forward propagation hidden layer neural networks, which converges much faster than traditional methods offers performance along less programmer intervention. In this way, introduced improved ELMs, including two weighted ELMs proposed by Zong, SMOTE technique create new synthetic samples minority class. After heuristic optimization ELM hiper-parameters, results demonstrated 85% accuracy geometric mean classification problem case 1 subject oversampling.

Language: Английский

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A Machine Learning Method for a Blood Diagnostic Model of Pancreatic Cancer Based on microRNA Signatures

Critical Reviews in Immunology, Journal Year: 2023, Volume and Issue: 44(3), P. 13 - 23

Published: Dec. 8, 2023

This study aimed to construct a blood diagnostic model for pancreatic cancer (PC) using miRNA signatures by combination of machine learning and biological experimental verification. Gene expression profiles patients with PC transcriptome normalization data were obtained from the Expression Omnibus (GEO) database. Using random forest algorithm, lasso regression multivariate cox analyses, classifier differentially expressed miRNAs was identified based on algorithms functional properties. Next, ROC curve analysis used evaluate predictive performance model. Finally, we analyzed two specific in Capan-1, PANC-1, MIA PaCa-2 cells qRT-PCR. Integrated microarray revealed that 33 common exhibited significant differences between tumor normal groups (P value < 0.05 |logFC| > 0.3). Pathway showed related P00059 p53 pathway, hsa04062 chemokine signaling cancer-related pathways including PC. In ENCORI database, hsa-miR-4486 hsa-miR-6075 algorithm introduced as major markers diagnosis. Further, receiver operating characteristic achieved area under score 80%, showing good sensitivity specificity two-miRNA signature Additionally, genes expressions three all up-regulated summary, these findings suggest miRNAs, hsa-miR-6075, could serve valuable prognostic

Language: Английский

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