Recent Advances in Phytochemical-Based Topical Applications for the Management of Eczema: A Review
Bibliographic record
Abstract
Eczema (atopic dermatitis, AD) is a skin disease characterized by skin barrier dysfunction due to various factors, including genetics, immune system abnormalities, and environmental triggers. Application of emollients and topical drugs such as corticosteroids and calcineurin inhibitors form the mainstay of treatments for this challenging condition. This review aims to summarize the recent advances made in phytochemical-based topical applications to treat AD and the different carriers that are being used. In this review, the clinical efficacy of several plant extracts and bioactive phytochemical compounds in treating AD are discussed. The anti-atopic effects of the herbs are evident through improvements in the Scoring Atopic Dermatitis (SCORAD) index, reduced epidermal thickness, decreased transepidermal water loss, and alleviated itching and dryness in individuals affected by AD as well as in AD mouse models. Histopathological studies and serum analyses conducted in AD mouse models demonstrated a reduction in key inflammatory factors, including thymic stromal lymphopoietin (TSLP), serum immunoglobulin E (IgE), and interleukins (IL). Additionally, there was an observed upregulation of the filaggrin (FLG) gene, which regulates the proteins constituting the stratum corneum, the outermost layer of the epidermis. Carriers play a crucial role in topical drug applications, influencing dose delivery, retention, and bioavailability. This discussion delves into the efficacy of various nanocarriers, including liposomes, ethosomes, nanoemulsions, micelles, nanocrystals, solid-lipid nanoparticles, and polymeric nanoparticles. Consequently, the potential long-term side effects such as atrophy, eruptions, lymphoma, pain, and allergic reactions that are associated with current topical treatments, including emollients, topical corticosteroids, topical calcineurin inhibitors, and crisaborole, can potentially be mitigated through the use of phytochemical-based natural topical treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".