International Conference on Pharmaceutical & Health Sciences 2024
Bibliographic record
Abstract
Background: Mpox (Monkeypox), a zoonotic Orthopoxvirus, produces a disease in humans similar to smallpox but with a significantly lower death rate.The largest outbreak in history began in May 2022 and has since spread rapidly worldwide, with over 70 countries reporting cases.Objective: The objective of this research work is to highlight the significant role of 3D-printed microneedles in the delivery of Mpox vaccines.Materials and methods: Vaccines can be administered before and after exposure to the virus, with optimal protection achieved through pre-exposure vaccination.Data indicate that vaccination within 4 days after first exposure to Mpox can reduce the risk of disease by up to 85%.Even individuals who have previously received smallpox vaccines remain at risk for Mpox.The MVA-BN (Modified Vaccinia Ankara-Bavarian Nordic) vaccine, approved in 2019 for the prevention of smallpox and monkeypox in the USA and Canada, is administered subcutaneously in the upper arm.Recent studies show that 3D-printed microneedles, measuring a few hundred micrometers in height, can penetrate the skin's outer layer without reaching deeper tissues, thereby delivering therapeutics effectively and minimally invasively.Results: Research demonstrates that 3D-printed microneedle delivery systems enhance skin cargo retention by up to 50% compared to traditional injection methods, activate immune cells more effectively, and elicit stronger immune responses.Microneedles minimize discomfort and are suitable for self-administration, which reduces reliance on healthcare providers and enhances vaccination accessibility.Conclusion: Health systems must continuously enhance awareness and update preparedness plans for Mpox outbreaks.This includes establishing clear protocols for surveillance, testing, vaccination, and treatment, along with strategies for communication and coordination among various stakeholders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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; both teacher heads agree on what is shown here.
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".