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Record W6927814616 · doi:10.34945/f5hc7p

Probiotic treatment in female Lewis rats following unilateral incomplete cervical (C5) contusion injury: behavior, histological and systemic cytokine data

2023· dataset· en· W6927814616 on OpenAlexaff

Bibliographic record

VenueUC San Diego · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProbioticLactobacillusForelimbBifidobacteriumLactobacillus acidophilusLactic acidSpinal cord

Abstract

fetched live from OpenAlex

STUDY PURPOSE: We tested whether a probiotic treatment immediately after a unilateral incomplete cervical spinal cord injury in female rats prevents gut dysbiosis, promotes motor recovery and dampens the related anxiety like behavior as we have previously reported for fecal matter transplants. DATA COLLECTED: Female Lewis rats (12 weeks and 180-220 g) received a 125 kdyn unilateral contusion on the right side of the spinal C4-5 level (1.25 mm right of midline, 25 mm drop height at a 15-degree angle) using an Infinite Horizon impactor. Probiotics were given immediately after SCI using VSL#3 containing eight different strains (Bifidobacterium breve, Bifidobacterium infantis, Bifidobacterium longum, Lactobacillus acidophilus, Lactobacillus bulgaricus, Lactobacillus casei, Lactobacillus planatarum, and Streptococcus salivarus subspecies thermophilus). VSL#3 was administered daily via oral gavage for 7 days at a dose of 5 billion CFU. Control group was gavaged with 0.5 ml of sterile water. After 7 DPI, the 5 billion CFU of VSL#3 doses were adjusted to ensure equivalent consumption and administered ad libitum in drinking water for a total of 35 days post injury (DPI). An open field test was used to assess motor function as well as depression/anxiety-like behavior. The elevated plus maze was carried out at baseline and 35 DPI by recording the rats for ten minutes and then analyze offline with customized software (https://github.com/cdoolin/rat-apps). The rats were placed in a cylinder for 5 min to record the number of left and right forelimb paw placements on the cylinder wall during rearing and recorded weekly after injury. For the light-dark exploration test, the distance traveled in the light chamber, total number of transitions, time spent in each chamber and latency to enter the light chamber were recorded and analyzed offline. The test was carried out at baseline and 35 DPI. The horizontal ladder served to examine skilled motor function, where a successful trial was concluded when rats walked across all rungs without rearing or stopping. Three successful trials were analyzed offline for the number of successful steps, missed steps, and forelimb slips.The von Frey test was used to assess mechanical allodynia. The overall gut microbiome was assessed prior to injury (baseline) and at 3, 7, 14, and 35 DPI by collecting fresh fecal matter from rats at the beginning of their dark cycle and submitted for 16S rRNA analysis. The microbiome report for this study is in the associated odc-sci dataset #688. Plasma samples were collected in the morning (animal's light cycle) and diluted 2-fold and run on the Rat Cytokine 27-Plex and Rat Stress Hormone 2-Plex discovery assays. Images of lesion extension were taken from cryosectioned tissue slices with an epifluorescence microscope at 5× magnification and analyzed using ImageJ. Lesion size was calculated and represented as the percent of spared tissue. Images at 5× magnification were taken to visualize the entire spinal cord cross section 0.25 cm rostral to the lesion, at its epicenter, and 0.25 cm caudal. To analyze microglia in the spinal cord tissue, the area of Iba-1+ immunoreactivity was divided by the total area of each individual spinal cord cross section and expressed as a percentage of Iba1+ area using thresholding. DATA USAGE NOTES:

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.082
GPT teacher head0.330
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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