Feto-Marenal Interactions – Undisputable Evidence for the Concept of Neuroimmune Biology
Bibliographic record
Abstract
Neuroimmune Biology (NIB) was conceived in 2000. At that time it was predicted that neuroimmune mechanisms play a major regulatory role in Biology. Hence the term, Neuroimmune Biology was introduced [1]. Now it is apparent that in feto-maternal interactions, which represent Reproduction Biology, the Neuroimmune Supersystem plays a fundamental role. Reproduction Biology is a perfect example for how Neuroimmune mechanisms regulate bodily functions. With the development of transplantation immunology it has been realized that the fetus is a semiallogeneic allograft as the father’s transplantation antigens are expressed in fetal tissues. According to the rules of transplantation the semiallogeneic fetus should have been rejected but fetuses survive as a rule. Pregnancy was an exception to Transplantation Immunology. Medawar predicted that neuroendocrine and immune regulatory mechanisms should be involved in the protection of the fetus [2]. First immunological tolerance has been tested as a survival mechanism for the fetus, but it could not be proven. Next the Th1-Th2 switch was examined as the possible mechanism but it was not the case either. Finally it became gradually clear that the immune system plays a very active role during gestation. It helps actively growth and development of the fetus with growth factors, cytokines and possible even classical hormones [3]. The immune system is capable of producing cytokines, chemokines and also classical hormones, which is delivered into target areas, such as the fetus [4]. Some years ago the noted Canadian scientist, Tom Wegman declared that “the fetus is bathed in cytokines”. However, the amniotic fluid contains the most prolactin in the body and is also very rich in placental lactogenic hormones [5] and steroid hormones and other mediators [6]. Clearly the amniotic fluid contains numerous important biological regulators. So, the above statement should sound like this: “the fetus is bathed in hormones, cytokines, chemokines and neuropeptides etc.”, pretty well everything what is significant in Biological regulation. These mediators act on the skin and also internally as the fetus consumes amniotic fluid continuously. Theoretically animal growth is regulated by hormones that provide the animal tissues with competence for growth. Such hormones are growth hormone, prolactin and placental lactogens, also type I (gamma c) cytokines. The next stage is progression. Insulin like growth factor (IGF-I) and some cytokines serve as progression factors [7]. Numerous other mediators regulate differentiation and function. A likely source of most of these mediators is the placenta as it transforms into an endocrine organ with the aim of protecting the fetus against maternal influences and interests [5, 6]. The mothers adaptive immune system recognizes the fetus and produces antibodies. The immune system must be activated in order for successful pregnancy to
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".