Liposomal Antioxidants for Protection against Oxidant-Induced Damage
Bibliographic record
Abstract
Reactive oxygen species (ROS), including superoxide anion, hydrogen peroxide, and hydroxyl radical, can be formed as normal products of aerobic metabolism and can be produced at elevated rates under pathophysiological conditions. Overproduction and/or insufficient removal of ROS result in significant damage to cell structure and functions. In vitro studies showed that antioxidants, when applied directly and at relatively high concentrations to cellular systems, are effective in conferring protection against the damaging actions of ROS, but results from animal and human studies showed that several antioxidants provide only modest benefit and even possible harm. Antioxidants have yet to be rendered into reliable and safe therapies because of their poor solubility, inability to cross membrane barriers, extensive first-pass metabolism, and rapid clearance from cells. There is considerable interest towards the development of drug-delivery systems that would result in the selective delivery of antioxidants to tissues in sufficient concentrations to ameliorate oxidant-induced tissue injuries. Liposomes are biocompatible, biodegradable, and nontoxic artificial phospholipid vesicles that offer the possibility of carrying hydrophilic, hydrophobic, and amphiphilic molecules. This paper focus on the use of liposomes for the delivery of antioxidants in the prevention or treatment of pathological conditions related to oxidative stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".