Prevention of nodules and enhancement of antibody response to genetically engineered recombinant vaccine against Human Chorionic Gonadotropin (hCG) for contraception
Bibliographic record
Abstract
OBJECTIVE: Human Chorionic Gonadotropin (hCG) plays a crucial role in embryo implantation and in maintenance of pregnancy. An immuno-contraceptive approach involves the use of a recombinant hCGβ-LTB vaccine formulated with adjuvant Mycobacterium indicus pranii (MIP), to prevent pregnancy without disturbing ovulation, hormonal profiles, and menstrual cycles in women. The present work in mice was designed to address issues encountered in clinical trials conducted with hCGβ-LTB vaccine, with focus on two primary concerns. Firstly, it aimed to determine the optimal vaccine dosage required to induce a high level of anti-hCG antibodies. Secondly, it aimed to assess the safety profile of the vaccine, specifically injection site reactions in the form of nodules, observed in some of the subjects. METHODS AND RESULTS: Studies undertaken indicate that a 2 µg dose of the protein version of the vaccine, administered in mice through the intramuscular route, can induce high anti-hCG titres. Furthermore, administering a booster dose enhances the antibody response. Our findings suggest that the concentration and frequency of administration of the adjuvant MIP can also be reduced without compromising vaccine efficacy. CONCLUSION: The issue of nodule formation at the injection site can be mitigated either by administering the vaccine along with MIP intramuscularly or injecting hCG vaccine and MIP at separate intradermal sites. Thus, protein vaccine administered at a 2µg dose via the intramuscular route addresses both efficacy and safety concerns.
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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".