If imOmics provides the theory and methods, then the Global imOme Project (GiP) is the grand blueprint for pushing the Life = f(Environment, t) scientific framework towards globalized, standardized, and industrialized practice (Bip, 2023; Yue Jeff Xu, 2025).

GiP aims to build a dynamic database of life-environment interactions across species, scales, and regions by deploying standardized intelligent monitoring nodes worldwide. Its core objectives are:

1.     Achieve a Paradigm Shift in Scientific Research: Promote a fundamental transformation in life sciences from "describing phenomena" to "predicting and regulating"(Yue Jeff Xu, 2025).

1.     Restructure Industrial Ecosystems: Based on a deep understanding of Life = f(Environment, t), foster multi-billion dollar emerging industrial clusters in fields such as precision medicine, smart agriculture, and environmental governance.

1.     Establish International Standards: Develop technical standards, data standards, and algorithm standards for in vivo functional detection to enhance research and application efficiency.

The value of GiP is ultimately reflected in its ability to address major scientific and social problems. The following examples from the literature illustrate the specific application and validation of this formula in different fields.

In agriculture, the Life = f(Environment, t) formula directly relates to crop yield and stress resistance.

        Case: Rice Salt Tolerance Mechanism

      Life: Growth and survival of rice.

    Environment: High salt stress (e.g., 100mM NaCl).

    t: Different time points after salt stress treatment (minutes, hours, days).

    f (Functional Mechanism): NMT studies revealed that the key mechanism in salt-tolerant rice varieties lies in their roots' ability to rapidly activate genes like SOS1 upon Na⁺ shock, actively excreting toxic Na⁺ (manifested as sustained Na⁺ efflux) while maintaining K⁺ uptake (stable K⁺ influx), thereby preserving intracellular ion homeostasis (Sugita, R.等, 2022; K. Lu et al., 2023; Shahzad et al., 2022; Yue et al., 2012; Zhu et al., 2015). Salt-sensitive varieties, in contrast, show massive Na⁺ influx and K⁺ efflux. Here, the ion flux data are the specific quantitative results of f(High salt environment, time), directly predicting the "Life" state of the rice (tolerant or dead).

In medicine, this formula provides new ideas for early disease diagnosis, intraoperative navigation, and personalized treatment.

        Case: Real-time Tumor Border Monitoring During Surgery

      Life: Normal tissue vs. Cancerous tissue.

    Environment: Tumor microenvironment (TME), characterized by acidity (low pH) and abnormal ion concentrations.

    t: Real-time during surgery.

    f (Functional Mechanism): Due to the "Warburg effect" in cancer cells, they secrete large amounts of lactate, acidifying the TME. NMT technology can scan the surgical margin in real-time, detecting H⁺ flux. Areas with abnormally high H⁺ flux (strong efflux) indicate regions with residual cancer cells (Carmona-Fontaine et al., 2013; Hsu & Sabatini, 2008; Iorio et al., 2019; Liu et al., 2004; Potter et al., 2016; Shamsi et al., 2018; C. Yang & Li, 2019; X. Yang et al., n.d.). Surgeons can use this real-time feedback "f" value to precisely remove the tumor while maximizing the preservation of healthy tissue. This application pushes Life = f(Environment, t) from laboratory research into clinical practice.

        Case: Early Warning for Alzheimer's Disease (AD)

      Life: Health and functional state of neuronal cells.

    Environment: Specific drugs or electrophysiological stimuli.

    t: Millisecond to minute-level response time after stimulation.

    f (Functional Mechanism): Studies found that neurons in AD model animals exhibit significantly different ion flow patterns (e.g., abnormal Ca²⁺ influx or efflux) in their Ca²⁺ signaling pathways upon stimulation compared to normal neurons. This unique ion flow "fingerprint" holds promise as an ultra-early biomarker for AD years before clinical symptoms appear (T. Li et al., 2020).

This formula is also applicable to macro-ecosystems for assessing and warning of impacts from environmental changes.

        Case: Coral Reef Bleaching Early Warning

      Life: Health of the coral-zooxanthellae symbiosis.

    Environment: Rising seawater temperature, ocean acidification (decreasing pH).

    t: Duration of environmental pressure.

    f (Functional Mechanism): Corals are highly sensitive to environmental stress. Long before visible bleaching occurs, abnormalities appear in the exchange of key ions like Ca²⁺ and H⁺ on their tissue surface. Monitoring changes in the flux of these key ions using NMT can help build early warning models to alert before the collapse of the coral reef ecosystem, buying valuable time for intervention.

        Case: Heavy Metal Pollution Remediation

      Life: Ability of plants or microorganisms to absorb and detoxify heavy metals.

    Environment: Concentration of heavy metal ions (e.g., Cd²⁺) in soil or water.

    t: Duration of exposure to the polluted environment.

    f (Functional Mechanism): NMT can precisely measure the absorption rate of Cd²⁺ by plant roots and simultaneously monitor how Cd²⁺ stress affects the plant's uptake of essential ions like K⁺ (杨海, 2019). This data not only reveals the toxic mechanism of heavy metals but also provides a rapid and precise method for screening and cultivating plants with high remediation efficiency (i.e., plants with a specific "f" capability).