Effect of Faradarmani Consciousness Field on proliferation, telomerase activity, and telomere length of the human mesenchymal stem cells
Bibliographic record
Abstract
Taheri Consciousness (T-Consciousness) was introduced and defined by Mohammad Ali Taheri as one of the constituent components of the Cosmos in addition to matter and energy, from which Taheri Consciousness Fields (TCFs) are derived. TCFs are not matter or energy, but they can be proven by scientific experiments. The effect of Faradarmani CF, as one of TCFs, was examined in this study. Telomerase is an important enzyme, which adds DNA sequence repeats to the ends of chromosomes, thus prevents from their shortening. Telomerase activity is associated with cell proliferation, organism growth, and aging. This study aimed to study proliferation, telomerase activity, and telomere length in the Faradarmani CF treated mesenchymal stem cells (MSCs). Human MSCs were isolated from bone marrow and the morphology, proliferation of cells, length of telomere, and activity of telomerase were evaluated in Faradarmani CF treatment and control groups. The results showed that Faradarmani CF significantly increased the proliferation, length of telomere, and activity of telomerase in hMSCs compared with the control group (p<0.05). Considering the effects of Faradarmani on telomere length and telomerase activity, which are two important factors for cures of several age-related diseases, it is recommended that more experiments be performed in this regard to clarify the effect of TCFs on ageing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".