20240021269. SYSTEMS AND METHODS FOR ANALYZING MICRO-RIBONUCLEIC ACID (miRNA) SIGNATURE PROFILES IN BIOTIC AND ABIOTIC SAMPLES simplified abstract (Convergent Animal Health, LLC)

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SYSTEMS AND METHODS FOR ANALYZING MICRO-RIBONUCLEIC ACID (miRNA) SIGNATURE PROFILES IN BIOTIC AND ABIOTIC SAMPLES

Organization Name

Convergent Animal Health, LLC

Inventor(s)

Nedal Saleh of San Jose CA (US)

Richard Vierling of Vernon TX (US)

SYSTEMS AND METHODS FOR ANALYZING MICRO-RIBONUCLEIC ACID (miRNA) SIGNATURE PROFILES IN BIOTIC AND ABIOTIC SAMPLES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240021269 titled 'SYSTEMS AND METHODS FOR ANALYZING MICRO-RIBONUCLEIC ACID (miRNA) SIGNATURE PROFILES IN BIOTIC AND ABIOTIC SAMPLES

Simplified Explanation

The patent application describes systems and methods for analyzing micro-ribonucleic acid (miRNA) signature profiles in a biological sample to identify profiles of a subject to biotic and abiotic agents. The system includes an extractor unit and a nucleic acid amplifying unit that communicate with one or more hardware processors. The extracted miRNA concentrations are amplified using a plurality of primers and statistical modeling-based techniques. The hardware processors analyze the miRNA profiling data to identify a plurality of miRNA signature sequences and profiles indicative of exposure to various biotic and abiotic agents. The sequences and profiles are compared with pre-defined miRNA signature sequences and profiles in a database and displayed to indicate the subject's response to each agent. The system can perform multiplexed extraction and amplification of miRNA sequences to improve efficiency.

  • The patent application describes a system for analyzing miRNA signature profiles in a biological sample.
  • The system includes an extractor unit, a nucleic acid amplifying unit, and one or more hardware processors.
  • The miRNA concentrations in the sample are extracted and amplified using a plurality of primers and statistical modeling-based techniques.
  • The hardware processors analyze the miRNA profiling data to identify miRNA signature sequences and profiles indicative of exposure to biotic and abiotic agents.
  • The identified sequences and profiles are compared with pre-defined ones in a database and displayed to indicate the subject's response to each agent.
  • The system can perform multiplexed extraction and amplification of miRNA sequences to improve efficiency.

Potential applications of this technology:

  • Identifying miRNA signature profiles in biological samples can be used in medical diagnostics to detect exposure to specific biotic and abiotic agents.
  • This technology can be applied in environmental monitoring to assess the impact of pollutants or pathogens on ecosystems.
  • It can also be used in agriculture to identify miRNA profiles indicative of plant stress or disease.

Problems solved by this technology:

  • Traditional methods for identifying exposure to biotic and abiotic agents may be time-consuming and require complex laboratory procedures.
  • This technology provides a more efficient and automated approach to analyze miRNA signature profiles, allowing for faster and more accurate identification of exposure.

Benefits of this technology:

  • The system allows for the identification of miRNA signature profiles indicative of exposure to specific agents, providing valuable information for medical, environmental, and agricultural applications.
  • The multiplexed extraction and amplification capabilities improve the efficiency of the analysis process, reducing the time and resources required.
  • The statistical modeling-based techniques enhance the accuracy of the analysis, increasing the reliability of the results.


Original Abstract Submitted

systems and methods for analyzing micro-ribonucleic acid (mirna) signature profiles in a biological sample to identify profiles of a subject to biotic and abiotic agents are disclosed. a system comprises an extractor unit and a nucleic acid amplifying unit that communicate with one or more hardware processors. extracted mirna concentrations using extractor unit are amplified by nucleic acid amplifying unit, using a plurality of primers, and statistical modeling-based techniques. the one or more hardware processors analyze mirna profiling data using statistical modeling-based techniques to identify a plurality of mirna signature sequences and profiles indicative of exposure to various biotic and abiotic agents. the processors compare sequences and profiles with pre-defined mirna signature sequences and profiles in a database and on a display, indicating the subject's response to each biotic or abiotic agent. the system can perform multiplexed extraction and amplification of mirna sequences to improve efficiency.

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