MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202611000257 A) filed by Lala Lajpat Rai University Of Veterinary And Animal Sciences; Haryana State Council For Science, Innovation & Technology; and Dr. Ankit Magotra, Hisar, Haryana, on Jan. 2, for 'an mrna-based rna expression panel and method for early prediction of litter size in goats.'
Inventor(s) include Dr. Ankit Magotra; Dr. Yogesh C. Bangar; and Dr. Sandeep Kumar.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "The advanced mRNA-based RNA expression panel introduces an innovative multi-target molecular framework for comprehensive litter size prediction that integrates transcriptomic validation protocols with adaptive expression determination mechanisms, facilitating real-time reproductive status calculations, dynamic genetic optimization, and robust pregnancy confirmation while maintaining seamless veterinary integration and diagnostic accuracy for consistent livestock breeding applications. [510] The comprehensive molecular framework employs adaptive bioinformatics algorithms and intuitive expression protocols, utilizing embedded computational processing arrays and energy-efficient sequencing systems to ensure timely reproductive identification, enhanced breeding understanding, and optimal pregnancy reliability while maintaining continuous expression monitoring capabilities. [515] The integrated methodology combines multi-dimensional transcriptomic techniques with artificial intelligence-driven pattern recognition systems, leveraging variable-precision expression signals and multi-factor reproductive indicators to optimize breeding procedures and diagnostic workflows for maximum reproductive accuracy and minimal prediction uncertainty during critical veterinary applications. [520] The novel responsive molecular architecture features engineered high-precision expression components with specialized transcriptomic fingerprinting protocols, enabling complex multi-stage pregnancy verification while ensuring diagnostic consistency and performance optimization across various veterinary instruments without compromising system reliability. [525] The innovative design incorporates strategic validation mechanisms for enhanced reproductive identification and genetic security, utilizing optimized multi-function systems and adaptive expression technology to ensure legitimate pregnancy assignment while maintaining functionality across diverse veterinary environments and breeding scenarios. [530] Implementation methodology emphasizes scalable molecular integration and efficient diagnostic sequences, implementing interactive expression measures and pattern recognition algorithms to achieve superior reproductive determination, enhanced genetic identification, and unauthorized prediction prevention while ensuring technological simplicity during veterinary monitoring. [535] The system demonstrates exceptional adaptability through comprehensive integration of reproductive identification protocols and intelligent expression technologies, validating its effectiveness across various multifunctional breeding configurations and veterinary scenarios while maintaining consistent diagnostic performance and operational efficiency under diverse conditions. [540] The developed framework enables sustainable and reliable prediction of litter size through streamlined, AI-powered expression systems, providing significant advantages over traditional reproductive approaches through variable validation mechanisms, adaptive identification protocols, and improved genetic assignment while maintaining superior diagnostic accuracy during critical veterinary breeding procedures."
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