| Keyword search (4,164 papers available) | ![]() |
"Diagnosis" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | Joint enhancement of automatic chest x-ray diagnosis and radiological gaze prediction with multistage cooperative learning | Qiu Z; Rivaz H; Xiao Y; | 40665596 ENCS |
| 2 | Microfluidic Liquid Biopsy Minimally Invasive Cancer Diagnosis by Nano-Plasmonic Label-Free Detection of Extracellular Vesicles: Review | Neriya Hegade KP; Bhat RB; Packirisamy M; | 40650129 ENCS |
| 3 | Alzheimer's early detection in post-acute COVID-19 syndrome: a systematic review and expert consensus on preclinical assessments | Vandersteen C; Plonka A; Manera V; Sawchuk K; Lafontaine C; Galery K; Rouaud O; Bengaied N; Launay C; Guérin O; Robert P; Allali G; Beauchet O; Gros A; | 37416323 CONCORDIA |
| 4 | Primary and Secondary Progressive Aphasia in Posterior Cortical Atrophy | Brodeur C; Belley É; Deschênes LM; Enriquez-Rosas A; Hubert M; Guimond A; Bilodeau J; Soucy JP; Macoir J; | 35629330 IMAGING |
| 5 | X-Vectors: New Quantitative Biomarkers for Early Parkinson's Disease Detection From Speech | Jeancolas L; Petrovska-Delacrétaz D; Mangone G; Benkelfat BE; Corvol JC; Vidailhet M; Lehéricy S; Benali H; | 33679361 PERFORM |
| 6 | Hybrid multi-mode machine learning-based fault diagnosis strategies with application to aircraft gas turbine engines. | Shen Y, Khorasani K | 32673847 ENCS |
| 7 | The Comprehensive Assessment of Neurodegeneration and Dementia: Canadian Cohort Study. | Chertkow H, Borrie M, Whitehead V, Black SE, Feldman HH, Gauthier S, Hogan DB, Masellis M, McGilton K, Rockwood K, Tierney MC, Andrew M, Hsiung GR, Camicioli R, Smith EE, Fogarty J, Lindsay J, Best S, Evans A, Das S, Mohaddes Z, Pilon R, Poirier J, Phillips NA, MacNamara E, Dixon RA, Duchesne S, MacKenzie I, Rylett RJ | 31309917 PSYCHOLOGY |
| 8 | Deep model integrated with data correlation analysis for multiple intermittent faults diagnosis. | Yang J, Xie G, Yang Y, Zhang Y, Liu W | 31174854 ENCS |
| Title: | Microfluidic Liquid Biopsy Minimally Invasive Cancer Diagnosis by Nano-Plasmonic Label-Free Detection of Extracellular Vesicles: Review | ||||
| Authors: | Neriya Hegade KP, Bhat RB, Packirisamy M | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/40650129/ | ||||
| DOI: | 10.3390/ijms26136352 | ||||
| Publication: | International journal of molecular sciences | ||||
| Keywords: | cancer diagnosis; cancer prognosis; exosomes; extracellular vesicles; liquid biopsy; microfluidics; minimally invasive diagnosis; nano-plasmonic detection; | ||||
| PMID: | 40650129 | Category: | Date Added: | 2025-07-13 | |
| Dept Affiliation: |
ENCS
1 Optical Bio-Microsystems Laboratory, Department of Mechanical and Industrial Engineering, Concordia University, Montreal, QC H3G 1M8, Canada. |
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Description: |
Cancer diagnosis requires alternative techniques that allow for early, non-invasive, or minimally invasive identification. Traditional methods, like tissue biopsies, are highly invasive and can be traumatic for patients. Liquid biopsy, a less invasive option, detects cancer biomarkers in body fluids such as blood and urine. However, early-stage cancer often presents low biomarker levels, making sensitivity a challenge for integrating liquid biopsy into early diagnosis. Recent studies revealed that extracellular vesicles (EVs) secreted by cells are apt markers for liquid biopsy. Detecting extracellular vesicles (EVs) for liquid biopsy faces challenges like low sensitivity, EV subtype heterogeneity, and difficulty isolating pure populations. Label-free methods, such as plasmonic biosensors and Raman spectroscopy, offer potential solutions by enabling direct analysis without markers, improving accuracy, and reducing complexity. This review paper discusses current challenges in EV-based liquid biopsy for cancer diagnosis and prognosis. It addresses the effective use of microfluidics and nano-plasmonic approaches to address these challenges. Enhancing label-free EV detection in liquid biopsy could revolutionize early cancer diagnosis by offering non-invasive, cost-effective, and rapid testing. This could improve patient outcomes through personalized treatment and ease the burden on healthcare systems. |



