Cord Blood Serum Zinc Levels and the Intrauterine Growth Status in Preterm Neonates
Bibliographic record
Abstract
Background: The risk of death is higher if the SGA baby is accompanied by prematurity. Intrauterine growth is considered to have an important role in the occurrence of premature birth and SGA, so many recent studies are trying to find that can support intrauterine growth, one of which is research on the role of the micronutrient zinc, which is a trace element that the body cannot produce. Zinc is an essential micronutrient for organ development and growth. Zinc plays a role in DNA synthesis and the signaling pathway of the IGF-1 receptor. Umbilical cord blood serum zinc levels can reflect intrauterine zinc status, indicating maternal zinc supply to the fetus. Objectives: To assess the relationship between cord blood serum zinc levels and intrauterine growth status in pretermneonates. Methods: This research is an observational study with a cross-sectional approach. The sample for this study was 85 pretermneonates, consisting of 53 neonates with AGA (appropriate for gestational age) and 32 neonates with SGA (small for gestational age). A cord blood sample was collected immediately after birth, and zinc levels were determined by the atomic absorption spectrophotometer method. Results: The median serum zinc levels of the SGA and AGA groups were 41.87 µg/dl (20.43 - 56.04 µg/dl) and 52.12 µg/dl (35.54 - 62.46 µg/dl), respectively, and the difference between the two groups was found to be statistically significant. Conclusion: There was a relationship between cord blood serum zinc levels and the intrauterine growth status of pretermneonates.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".