Anti-Mouse CD105 (Endoglin) PE 200 ug
- Known as:
- Antibody toMouse CD105 (Endoglin) PE 200 ug
- Catalog number:
- 12-1051-83
- Category:
- -
- Supplier:
- eBioscience
- Gene target:
- Anti-Mouse CD105 (Endoglin) 200
Related genes to: Anti-Mouse CD105 (Endoglin) PE 200 ug
- Gene:
- ENG NIH gene
- Name:
- endoglin
- Previous symbol:
- ORW1, ORW
- Synonyms:
- END, HHT1, CD105
- Chromosome:
- 9q34.11
- Locus Type:
- gene with protein product
- Date approved:
- 1993-03-03
- Date modifiied:
- 2019-04-23
Related products to: Anti-Mouse CD105 (Endoglin) PE 200 ug
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- Circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are pivotal biomarkers in liquid biopsy, providing minimally invasive access to tumor dynamics for monitoring disease progression, treatment response, and resistance. However, their scarcity and molecular heterogeneity pose analytical challenges that often exceed the sensitivity, specificity, and clinical applicability of conventional platforms. Electrochemical biosensors have emerged as a powerful alternative, distinguished by low detection limits, portability, scalability, and compatibility with point-of-care settings. Unlike previous reviews, this work highlights strategies specifically designed for epithelial-mesenchymal transition (EMT)-associated CTC phenotypes and explores AI- and IoT-enabled implementations for decentralized oncology. A comprehensive evaluation of electrochemical approaches for CTC and ctDNA detection is provided, with emphasis on molecular recognition interfaces, electrode surface engineering, and amperometric, potentiometric, and impedance-based readouts. Recent advances in nanomaterial-enhanced electrodes, aptamer- and antibody-based capture, and nucleic acid-driven amplification, including rolling circle amplification, terminal deoxynucleotidyl transferase (TdT)-mediated polymerization, and DNA nanomachines, are critically examined. Integration with microfluidics, smartphone-based potentiostats, and AI-enhanced analytics for multiplexed profiling is discussed alongside translational challenges such as sensor fouling, matrix interference, fabrication variability, and clinical validation. Emerging solutions, including antifouling surfaces, federated learning frameworks, and ISO-compliant standardization, are outlined to support clinical translation. - Source: PubMed
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