godfather of surgery

Chapter 1316 Sub-health Status

Elena's case report continues to be updated dynamically in Medicine.

Sanbo Institute received a lawyer's letter from a large American medical group that owns dozens of cancer screening centers and many oncology hospitals.

The letter was politely but coldly worded, pointing out that the "unverified prevention plan" published by Yang Ping's team could lead to delays in standard preventive surgery for high-risk patients, posing a "potential medical risk." It demanded that the Sanbo Institute "retract the dynamically updated paper" and issue a statement to eliminate the misleading information to the public.

Song Ziming placed the letter on Yang Ping's desk. "Tumor treatment is an important part of their business. If Elena's success is replicated, this business may shrink."

Yang Ping glanced at the letter: "Ignore them. Who do they think they are? We have made a statement on the institute's official website that all our public publications have clearly indicated the nature of the research. Patient Elena Volkova participated in the experiment with full informed consent. We will not respond to or pay attention to any legal questions in the future."

Following this, "professional analyses" appeared on social media: some oncologists wrote articles calculating in detail the probability of success in a single case, concluding that "even completely ineffective treatments have a certain probability of showing seemingly positive results in a single patient"; some patient rights organizations spoke out, praising the new option on the one hand, and worrying on the other hand that "this might lead insurance companies to refuse to reimburse standard drug treatments and surgeries, forcing patients to choose cheaper but unproven new methods"; and some conspiracy theorists linked the craze for the Yellow Emperor's Inner Classic, claiming that "all of this is the infiltration of Eastern mysticism into Western rational medicine."

In academia, similar rifts are beginning to emerge.

The International Society of Cancer issued a statement acknowledging the "innovativeness" of Yang Ping's team's work, but stressed that "currently, for precancerous lesions, preventive surgery remains the only intervention supported by large-scale evidence to reduce mortality," and called for "clinical practice not to be changed before rigorous multicenter randomized controlled trials are conducted."

On the other hand, more than one hundred cancer researchers co-signed an open letter, which was published on the Science magazine website.

The letter states: "The significance of the Elena case lies not in proving the effectiveness of a particular therapy, but in demonstrating the possibility of a completely new medical model based on strategies such as systemic regulation rather than confrontation and organ removal. This model can be used not only for treatment but also for prevention, integrating treatment and prevention. The potential value of this shift in medical model is so great that we have an ethical responsibility to accelerate its validation rather than slowly delaying it with outdated methodologies."

Yang Ping did not participate in the public debate; he remained focused on his research, and his systematic study of K therapy expanded further.

Song Ziming is in charge of initiating a new research project: designing a large-scale, multicenter, randomized controlled trial for Lynch syndrome carriers. They need to determine inclusion criteria, intervention protocols, control settings, and endpoints. Unlike traditional trials, they not only need to assess hard endpoints such as cancer incidence, but also design a composite set of indicators of systemic health status: TIM expression profile stability, immune microenvironment characteristics, metabolomics trajectory, and even patient-reported quality of life and functional status.

Currently, Lynch syndrome patients are the best precancerous research cases because Yang Ping has the ability to design a K factor targeting them.

Tang Shun was responsible for delving into the mechanisms behind Elena's case. They studied all the data from Elena's continuous monitoring: weekly blood multi-omics, monthly fecal microbiome, daily wearable device records, heart rate variability, sleep structure, activity level, and so on.

They need to answer a core question: how do regulatory signals create a chain reaction throughout the body? From TIM binding to colonic adenoma regression, how many transmission pathways are there? Is there a master node controlling the system's coordination?

Yang Ping personally took charge of exploring a more fundamental question: If the hypothesis of "system regulation" holds true, then for people who do not have clear genetic defects but are in a sub-healthy or chronic disease state, is there also a possibility of similar "regulatory intervention"?
Western medicine excels at defining diseases, while traditional Chinese medicine excels at describing imbalances.

However, a significant gray area exists between these two extremes, including chronic fatigue, borderline abnormal metabolic indicators, chronic mild inflammation, and age-related functional decline. These conditions do not yet constitute disease, but they deviate from health. Traditional medicine either waits for disease to develop before intervening or provides general lifestyle recommendations. What if we could use a systemic approach to precisely bring these states back to a healthy track?

These are unrelated to tumors, but from the perspective of the essence of the "regulation" theory, they are the same.

Moreover, this slight imbalance is the best case study for regulating theory.

Yang Ping retrieved a set of data: 100,000 annual physical examination records from the Sanbo Research Institute's Physical Examination Center, of which 38% were marked as being in a "sub-healthy" state. Preliminary analysis of this data revealed significant but subtle differences between sub-healthy individuals and healthy individuals in the distribution of blood immune cell subsets, inflammatory factor profiles, and metabolic small molecule profiles.

These differences are not random; they exhibit several specific deviation patterns. These include metabolic inertia, low immune activation, and neuroendocrine tension. Each pattern may correspond to a specific system state logic.

Lu Xiaolu questioned Yang Ping's expansion of the research scope: "Professor, we haven't even fully understood the regulation of cancer yet, and we're already expanding to sub-health? Isn't that too radical?"

Yang Ping's depth of thought far surpasses theirs, because to achieve regulation, there must be a prerequisite: there must be some scattered, principle-based results in the basic research of this disease that can be applied. Otherwise, it would be an extremely large project to study these mechanisms from scratch and then connect and integrate them to form a system.

Only by adopting a broad-based research approach and making full use of existing medical knowledge can breakthroughs be achieved in single or multiple areas.

“We need to work on multiple fronts simultaneously,” Yang Ping said. “Moreover, regulating sub-health may be simpler than regulating cancer. According to our theory, they are essentially the same. The sub-health system deviates less, the signals required for error correction are milder, the feedback mechanism is more complete, and fewer parameters and mechanisms are needed for regulation. Studying it may actually help us understand the basic principles of regulation.”

After Yang Ping explained it this way, Lu Xiaolu understood Yang Ping's good intentions. Professor Yang's way of looking at problems went straight to the essence and he no longer used traditional thinking.

Just then, Mainstein sent an urgent message from Berlin. "Professor, there's something you need to know." Mainstein's expression was grave in the video. "A senior advisor to the European Medicines Agency privately revealed that several major pharmaceutical companies are lobbying to include any drug or treatment based on your modulation theory in the 'orphan drug' or 'breakthrough therapy' expedited approval pathway. However, they are also pushing to unify the efficacy evaluation criteria for 'systemic modulation' with those for traditional chemotherapy and targeted therapies."

Yang Ping immediately understood the trap: "In other words, they want to use traditional standards to evaluate regulatory therapies? But these indicators are simply not applicable to preventative applications. In this way, they implicitly restrict drugs and treatments derived from the systemic regulation theory in advance, preventing them from entering any disease preventative treatment and limiting them to the field of tumor treatment, thus reducing the impact of new therapies on their existing technologies."

“Exactly,” Mainstein nodded. “If the lobbying is successful, regulators may require you to measure the results with an old yardstick. Worse still, these pharmaceutical companies have a lot of new drugs in their own pipelines that follow traditional blocking approaches. They want to hitch a ride on your coattails, get regulatory approval for their new drugs, and then include these drugs in your regulatory theory, deliberately creating confusion to achieve rapid market entry.”

This is because capital has seen an opportunity, but wants to shape it according to its own logic.

“We need to define the standards in advance,” Yang Ping said decisively. “We need to explicitly include our proposed ‘system health status indicators’ in the design of the new research plan and start lobbying regulatory agencies to accept this new evaluation system. At the same time, we need to publish a document to clarify the fundamental difference between ‘TIM regulation’ and ‘traditional blocking’: the former is a systemic dialogue, while the latter is still a targeted attack.”

In an effort to gain a voice in the field, Yang Ping published an opinion piece three days later in *Nature Medicine*, with the straightforward title: "K-Therapy: The Practice of a New Medical Model."

The article clearly outlines the technical path: TIM serves as the signaling hub for cellular identity state → designing regulators to fine-tune its conformation and signal output → the goal is to "restore the normalization of cellular identity logic," triggering the system's self-order reconstruction. This is "dialogue and error correction."

The article uses data from Elena's case to demonstrate that what was observed was the "benignification" of adenomatous cells, a decrease in system entropy, and an increase in systemic synergy, rather than simple cell death. The article concludes by urging: "Regulatory science needs to keep pace with the paradigm shift in biomedicine. For system-level interventions, we need system-level assessment tools, rather than confusing this new theory with traditional theories."

An associate director of the FDA's Center for Drug Evaluation and Research retweeted the article and commented: "We really need to think about how our review framework should adapt as the goal of treatment shifts from 'eliminating lesions' to 'restoring systemic health'. This is not only a scientific issue, but also an ethical and social one."

When the draft of the "new plan" was submitted to twelve leading medical centers worldwide for feedback, it received more than three hundred suggestions for revision. The focus of the debate centered on the setup of the control group.

Traditionalists insist that the control group should be "standard monitoring," meaning regular colonoscopies, with surgery performed upon detection of progression. They believe this is the currently accepted standard, and any new approach must be compared to it.

They also proposed a radical viewpoint: the control group should be "standard monitoring + lifestyle intervention." Their reasoning is that since the core concept of modal therapy is restoring systemic health, simply comparing "pharmaceutical regulation" with "passive monitoring" is unfair, because healthy lifestyles, such as diet, exercise, and stress management, themselves have a regulatory effect on the body. The real scientific question should be: on top of optimizing lifestyle, how much incremental benefit can additional, precise modulators bring?
“This makes experimental design extremely complex,” Song Ziming frowned. “Lifestyle interventions are difficult to standardize, and compliance is hard to control.”

The final new plan adopted a stratified design: all enrolled patients received basic health education; then they were randomly assigned to three groups: standard monitoring, standard monitoring + structured lifestyle intervention, and structured lifestyle intervention + personalized systemic regulation. The primary endpoint was the five-year incidence of colorectal cancer, but as many as seventeen secondary endpoints were pre-specified, covering pathological reversal, systemic stability indicators, quality of life, etc.

The release of the plan sparked heated discussions on its methodology.

The Lancet published a special editorial calling it "the first super clinical trial to attempt to integrate biomedicine, behavioral science and systems thinking," arguing that regardless of the outcome, its design itself will drive progress in clinical research methodology.

Just as preparations for the experiment were in full swing, a stranger contacted Yang Ping.

The caller was Chen Qiwen, a Chinese American, a chair professor in the Department of Bioengineering at Stanford University, and one of the world’s earliest pioneers in using artificial intelligence for drug discovery.

“Professor Yang, I have been following your work for a long time, especially your concepts of ‘system regulation’ and ‘life logic simulator’. I have a suggestion that may greatly accelerate all of this.”

Chen Qiwen explained that his team developed an artificial intelligence platform called "Deep Life Network." Unlike traditional knowledge graphs based on known pathways, this platform uses unsupervised learning to autonomously discover potential rules and key regulatory nodes for cell state transitions from massive amounts of single-cell multi-omics data, protein interaction data, and clinical outcome data.

“Simply put,” Chen Qiwen said, “your ‘Life Logic Simulator’ starts from a theoretical hypothesis (identity verification), builds a model, and then verifies it. Our ‘Deep Life Network’ starts from the ocean of data, lets AI discover patterns on its own, and then we interpret them. The combination of the two may produce remarkable results.”

He proposed a specific collaboration plan: Sanbo would provide high-dimensional time series data such as Elena's, as well as the massive amount of data that the "new plan" would generate; his team would use "deep life networks" to analyze the data, with the goal of identifying common paths, key hubs, and predictive biomarkers for the "migration of the system from a disordered state to a healthy state".

"This helps us understand why regulation works well for some people but poorly for others; why some lesions disappear while others remain stubborn; and most importantly," Chen Qiwen paused, "how to design a more intelligent and adaptive regulation scheme, not a fixed dose and frequency, but a 'closed-loop regulation system' that can be dynamically adjusted based on real-time biofeedback."

However, what Dr. Chen mentioned, the AI ​​based on digital humans at Nandu Medical University has already achieved. The life simulator is just a simplified version of this digital human, used to simulate some simple experiments.

Moreover, Dr. Chen completely misunderstood Yang Ping's regulation theory, and Yang Ping had no interest in cooperating with him.

(End of this chapter)