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Record W2937140987 · doi:10.21037/lcm.2019.04.01

Gut flora “the second brain” connects Eastern and Western medicine: intestinal hyper-permeability or Qi deficiency can affect brain, mind, and whole body

2019· article· en· W2937140987 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLonghua Chinese Medicine · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsIntestinal permeabilityAffect (linguistics)Flora (microbiology)Western medicineMedicineNeuroscienceBiologyPsychologyInternal medicinePathologyCommunicationAlternative medicineTraditional Chinese medicineGenetics

Abstract

fetched live from OpenAlex

There are two famous “the Father of Modern Medicine”—Hippocrates (a Greek physician) said “all disease begins in the gut” and Sir William Osler (a Canadian physician) said “a man is as old as his arteries.” It is known that gut microbiota imbalance (dysbiosis) and intestinal hyper-permeability are related to high level of advanced glycation end-products (AGEs) which damage blood vessel’s endothelial function and potentially cause multi-organ dysfunction. On the other hand, Traditional Chinese Medicine (TCM) doctors already knew the importance of digestive system thousands of years ago since the production of “Qi” which is vital energy for whole body largely rely on abdominal condition, and Qi deficiency triggers multiple mental and physical symptoms. It may sound two leading Integrative Medicine (IM) systems, Western IM and TCM use “different languages,” but it is not well known that their essence is very similar (illness is a result of “dis-ease” or “dysfunction of Qi.”). Genome analysis technology, such as DNA sequencing and microbiota researches have enabled us to understand how intestinal dysbiosis is related to obesity, metabolic syndrome, brain disorders, autoimmune diseases, or mood disorders (Brain-Mind-Gut axis). In addition, making the most of artificial intelligence’s (AI) “deep learning” technology might be a potential “prescription” to heal worldwide medical-economical crisis, spend more time with patients (for medical providers), and prevent providers’ burnout. AI-assisted TCM-style history taking computer and portable wrist pulse diagnostic device are about to be used in China. In the new era of preventive medicine, gut microbiota research, precision medicine with genome analysis, AI technology and TCM ancient wisdom can be combined together. Blending the new and the old will make it possible to detect and treat “pre-clinical disease” before real diseases happen since Western IM and TCM are actually using a “same language.”

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.283
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it