Short figure development multi-dimensional data fusion evaluation system based on enteric-cerebral-hepatic axis quantitative model

By constructing a multidimensional data fusion evaluation system based on a quantitative model of the gut-brain-liver axis, the problem that existing systems cannot reflect the dynamic interaction characteristics of intestinal metabolites and liver growth protein expression is solved. This achieves accuracy and stability in growth and development evaluation, identifies potential obstacles in the growth axis, and provides more accurate developmental assessment.

CN122050837APending Publication Date: 2026-05-15GUANGZHOU RED CROSS HOSPITAL
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Patent Information

Application Number
CN202610272509.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-06
Publication Date
2026-05-15

AI Technical Summary

Technical Problem

Existing developmental assessment systems cannot effectively reflect the dynamic interaction characteristics of gut metabolites with the expression of liver-derived growth proteins, leading to logical biases and assessment errors in the assessment models. They also lack causal alignment in the time dimension and axial signal gating mapping, making it difficult to identify the biochemical associations between growth axis-related proteins and gut metabolites.

Method used

A multidimensional data fusion evaluation system based on the gut-brain-liver axis quantitative model was constructed. The system acquires the gut, liver, and neuroendocrine components through the data acquisition module, determines the conduction delay and performs asynchronous offset processing using the axial gating mapping module, calculates the gating calibration coefficient, and combines the growth steady-state evaluation module for gain compensation and data fusion to generate growth and development evaluation indicators.

Benefits of technology

It enables precise evaluation of the biochemical association between growth hormone axis-related proteins and intestinal metabolites, eliminates asynchronous interference in biochemical signal transduction, improves the accuracy and stability of evaluation, identifies the dynamic bottleneck of the growth axis, and provides more accurate early warning of developmental stagnation.

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Abstract

The invention relates to the field of information systems and cloud platforms for interaction detection of proteins and metabolites and health correlation in biological material test and analysis, and discloses a short figure development multi-dimensional data fusion evaluation system based on an intestinal brain liver axis quantitative model. Comprising a data acquisition module, an axial gating mapping module and a growth steady state evaluation module, and the data acquisition module acquires an intestinal metabolism component, a liver growth axis component and a neuroendocrine component of a subject; the axial gating mapping module is used for determining signal transduction time delay, calling an intestinal metabolism component at the T-tau moment as a parameter reference through asynchronous offset processing, and determining a gating calibration coefficient in combination with a neuroendocrine component fluctuation slope; and the growth steady state evaluation module performs gain compensation on the liver growth axis component according to the calibration coefficient and outputs a growth and development evaluation index. According to the invention, asynchronous interference of biochemical signal circulation is solved, evaluation model drift caused by phase dislocation is eliminated, and the accuracy of development blocking reason screening is enhanced.
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