The Quest for Anti-inflammatory and Anti-infective Biomaterials in Clinical Translation
Bibliographic record
Abstract
Biomaterials are now being used or evaluated clinically as implants to supplement the severe shortage of available human donor organs. To date, however, such implants have mainly been developed as scaffolds to promote the regeneration of failing organs due to old age or congenital malformations. In the real world, however, infection or immunological issues often compromise patients. For example, bacterial and viral infections can result in uncontrolled immunopathological damage and lead to organ failure. Hence, there is a need for biomaterials and implants that not only promote regeneration but also address issues that are specific to compromised patients, such as infection and inflammation. Different strategies are needed to address the regeneration of organs that have been damaged by infection or inflammation for successful clinical translation. Therefore, the real quest is for multifunctional biomaterials with combined properties that can combat infections, modulate inflammation, and promote regeneration at the same time. These strategies will necessitate the inclusion of methodologies for management of the cellular and signaling components elicited within the local microenvironment. In the development of such biomaterials, strategies range from the inclusion of materials that have intrinsic anti-inflammatory properties, such as the synthetic lipid polymer, 2-methacryloyloxyethyl phosphorylcholine (MPC), to silver nanoparticles that have antibacterial properties, to inclusion of nano- and micro-particles in biomaterials composites that deliver active drugs. In this present review, we present examples of both kinds of materials in each group along with their pros and cons. Thus, as a promising next generation strategy to aid or replace tissue/organ transplantation, an integrated smart programmable platform is needed for regenerative medicine applications to create and/or restore normal function at the cell and tissue levels. Therefore, now it is of utmost importance to develop integrative biomaterials based on multifunctional biopolymers and nanosystem for their practical and successful clinical translation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".