Total Enteral Nutrition Facilitates Wound Healing Through Preventing Intestinal Atrophy, Keeping Protein Anabolism and Suppressing Inflammation
Bibliographic record
Abstract
BACKGROUND: In clinical settings, early total enteral nutrition (TEN) is known to reduce the postoperative complication and infection rate as well as duration of postoperative stay compared with total parenteral nutrition (TPN) in a variety of critical conditions. We aimed to compare effects TEN and TPN on wound healing and explore its possible mechanisms using rat model. METHODS: Seven days after operation for inserting enteral tube into gastric space for TEN, Sprague-Dawley rats were made burn (15 mm) in the back. Rats were administrated with either TEN (N = 17) or TPN (N = 15) and evaluated condition of wound healing as well as serum/urine immunological and biochemical parameters at 28 days. RESULTS: Burned area was significantly reduced in TEN than in TPN group. Although body weight, serum levels of total protein, albumin and transferrin were the same levels between the two groups, urine nitrogen and intestinal atrophy were significant in TPN group. Conversely, weight of small bowel showed positive linear relationship with levels of parameters calculated as follows: [medication nitrogen quantity - (urine nitrogen + feces nitrogen)]/[medication nitrogen - feces nitrogen quantity]. Weights of spleen and tumor necrotizing factor-a levels in serum were higher in TPN than in TEN. CONCLUSIONS: These results suggest that TEN may facilitate wound healing compared with TPN through preventing intestinal atrophy, keeping protein anabolism and suppressing inflammation.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".