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Updated: Nov 1, 2025
MicroRNA Amplification and Recognition through Locked-nucleic-acid In situ Hybridization as A Novel Detection and Quantification Method
Published on: October 7, 2025
Analytical design of multi-threshold and high fan-in DNA-based logical sensors to profile the pattern of MS microRNAs
Mercedeh Sanjabi1, Ali Jahanian1
1Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran.
Abstract:
Early detection of diseases is very important to increase the life quality and reduce the treatment cost for the patient. MicroRNAs have been introduced in recent years as an efficient class of biomarkers for detecting the risky situation of many diseases such as cancers, Multiple sclerosis (MS), and heart attacks, and other diseases. Now, real-time PCR has been used to profile the microRNA expression, which is expensive, time-consuming, and has low accuracy. Most recently, DNA logic gates are used to detect the MicroRNA expression level that is more accurate and faster than previous methods. In this paper, we improved the design of multi-threshold and multi-input DNA-based logic gates in response to specific microRNA (miRNA) inputs. The proposed design style can simultaneously recognize multiple miRNAs with different rising and falling thresholds. The proposed structure in this paper is used to diagnose Multiple Sclerosis (MS) as a case study. We simulated this system to understand its performance and compare it with other existing methods. The simulation results show the efficiency of the proposed method in terms of accuracy, efficiency, and speed. In this analysis, unwanted reactions, fault positive, and the probability of generating the final output using the formal method are investigated in depth. Finally, the proposed solutions are improved based on the results of these analyses. The analytic approach of this paper helps to design the DNA-based logic gates for real diseases.
Insights
This study introduces improved DNA logic gates for early disease detection using microRNA biomarkers. The novel design offers faster, more accurate multi-miRNA detection, crucial for diagnosing conditions like Multiple Sclerosis.
Area of Science:
- Biotechnology
- Molecular Diagnostics
- Bioengineering
Background:
- Early disease detection improves patient quality of life and reduces healthcare costs.
- MicroRNAs (miRNAs) are promising biomarkers for various diseases, including cancers and Multiple Sclerosis (MS).
- Current miRNA profiling methods like real-time PCR are costly, slow, and lack precision.
Purpose of the Study:
- To enhance multi-threshold, multi-input DNA logic gates for specific microRNA detection.
- To develop a system capable of simultaneously recognizing multiple miRNAs with varying thresholds.
- To apply and validate the improved DNA logic gate system for Multiple Sclerosis diagnosis.
Main Methods:
- Designed and simulated advanced multi-threshold, multi-input DNA logic gates.
- Utilized a formal method to analyze system performance, including unwanted reactions and fault positives.
- Compared the proposed system's efficiency against existing miRNA detection methods.
Main Results:
- The improved DNA logic gates demonstrated high accuracy, efficiency, and speed in miRNA detection.
- The system successfully identified specific miRNA patterns relevant to Multiple Sclerosis.
- Formal analysis confirmed the robustness and reliability of the proposed DNA logic gate design.
Conclusions:
- The enhanced DNA logic gate design offers a superior alternative for microRNA profiling.
- This technology holds significant potential for the early and accurate diagnosis of complex diseases like MS.
- The analytical approach provides a framework for designing DNA-based logic gates for clinical applications.
