Mild iron deficiency anaemia during pregnancy and lactation in guinea pigs alters amplitudes and auditory nerve velocity, but not brainstem transmission times in the offspring's auditory brainstem response
Bibliographic record
Abstract
OBJECTIVES: It is well known that postnatal/early childhood iron deficiency (ID) anaemia (IDA) adversely affects infants' cognitive development and neurophysiology. However, the effects of IDA during gestation and lactation on the offspring are largely unknown. To address this health issue, the impact of mild IDA during gestation and lactation on the offsprings' neural maturation was studied in the guinea pig, using auditory brainstem responses (ABRs) latencies and amplitudes. METHODS: Female guinea pigs (n = 10/group) were fed an iron sufficient (ISD) or deficient diet (IDD) (144 and 11.7 mg iron/kg) during the gestation and lactation periods. From postnatal day (PNd) 9 onward, the ISD was given to both groups of weaned offspring. The offsprings' ABRs were collected on PNd24 using a broad range of stimulus intensities in response to 2, 4, 8, 16, and 32 kHz tone pips. RESULTS: Although the IDA siblings (n = 8) did not differ in brainstem transmission times (BTTs) compared to the IS siblings (n = 8), they showed significant delayed peak I latency at 100 and 80 dB, respectively. Additionally, significantly higher ABR wave amplitudes were observed in the IDA female offspring between 35 and 50 dB (4 kHz), a phenomenon suggestive of a neural hyperactivity (hyperacusis). DISCUSSION: In support to our previous findings, the present results indicate that a mild IDA during gestation and lactation can have detrimental effects on early development of the offsprings' hearing and nervous systems, particularly on neural synchrony and auditory nerve conduction velocity, but not on BTT.
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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 | 0.000 |
| 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) | 0.001 | 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".