Longitudinal structural MRI, MRS, and behavioral data for mice prenatally exposed to maternal immune activation at gestational day 9
Bibliographic record
Abstract
Previous evidence from our lab (https://cobralab.ca/) and others suggest that prenatal exposure to maternal immune activation (MIA) can impact trajectories of neurodevelopment as measured through brain anatomy and behavior in mice. Yet, there are still open questions regarding the alterations to developmental trajectories, as well as the impact on brain chemistry, that this data set seeks to explore. The dataset presented here includes magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) data from two timepoints, adolescence (postnatal day [PND 35]) and young adulthood (PND 60) in C57BL/6J mice prenatally exposed either to poly I:C (POL) inducing maternal immune activation (MIA) or saline (SAL) at gestational day (GD) 9. The dataset also includes three behaviors acquired after each scanning session with 2 days of rest between the scans and each behavior: open field test, social novel object preference test, and prepule inhibition. Finally, the data also include cytokine assays acquired from a separate sample of pregnant mice and a test-retest of MRS acquired from a voxel in the anterior cingulate area. The data here published were collected and analyzed for a paper under review, available as a preprint where more details can be found here: https://www.preprints.org/manuscript/202203.0136/v1. In brief, using whole-brain, voxelwise analysis techniques (deformation-based morphometry) we found MIA subtly altered developmental trajectories, reducing volume relative to SAL offspring in the hippocampus and the anterior, right caudate putamen, and increasing volume in the posterior, left caudate putamen and cerebellum. Additionally, there was a trending decrease of myo-inositol and GABA in MIA offspring at PND 60 compared to SAL controls. Finally, there was a trending decrease in ratio of distance travelled in the anxiogenic center zone of an open field compared to the outer areas at PND 35 for MIA offspring. In this dataset you will find a total of 80 preprocessed structural MRIs in minc format acquired at postnatal day ~35 and ~60 in mice exposed to 5mg/kg poly I:C or vehicle control (0.9% sterile saline) at GD9. The images are included in CUPO_MIA_mncs.zip. These are T1-weighted structural images with two averages; repetition time (TR)/echo time (TE) = 21.55 ms/5.13 ms, matrix size = 260 x 158 x 210, voxel dimensions = 70 µm isotropic, flip angle = 20°, 23 min total using 5% isoflurane for induction, 1.5% for maintenance of anesthesia during the scan on a cryogenically-cooled surface coil. T1-weighted scans were preprocessed by stripping native coordinates, flipping left-right to maintain fidelity, denoising, correcting inhomogeneities in the bias field using the N4 algorithm, and registering in LSQ6 alignment (i.e. 6 degrees of freedom are allowed for imagine alignment: translations and rotations along x, y, and z dimensions). The demographics information for each animal is included in the demographics.csv file. Behavioural tests were performed following the postnatal day 35 and 60 scans in all animals with a 2 day rest period. These include: open field test, three chambered social approach, and prepulse inhibition. The data for all of these tests is presented in individual .csv spreadsheet and includes data for both the timepoints evaluated. Additionally, cytokine panels were collected from an independent cohort of 7 dams. MRS data are included in two formats: 1) preprocessed quantifications from LCModel software in csvs, and 2) raw data with press and press_w (respectively water supressed and unsupressed acquisitions) for analysis. The raw data will be released in upload version 1.2.0. MRS was acquired from a 1.2 x 2.6 x 2.5 mm3 voxel in the ACA with a Point Resolved Spectroscopy sequence (PRESS; TR/TE=3000/8.5 ms, 256 averages). Included in this data set are the structural MRIs in MINC format, the behavioural .csv data, the MRS data (csvs and raw files), and a README file providing further detail on the data structure and content, and on how to interpret the data column titles. DICOMS are also available for the structural MRI data, as are the raw (not-preprocessed) MINC files, available upon request to the authors.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".