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Record W2774227043 · doi:10.1071/rdv30n1ab105

105 P75 Neuronal Cells and Fibers in the Bovine Ovary

2017· article· en· W2774227043 on OpenAlexaffabout
Rodrigo A. Carrasco, C. E. P. Leonardi, Jaswant Singh, Gregory P. Adams

Bibliographic record

VenueReproduction Fertility and Development · 2017
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsOvarian CortexOvaryBiologyMedullaParaformaldehydeFollicular phaseOvarian follicleFollicleInternal medicineEndocrinologyAntral follicleAndrologyPathologyOvarian tissue

Abstract

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Neurotrophins are molecules involved in the development and survival of neurons and its cellular projections. Results of recent studies have implicated the local role of the high affinity neurotropin receptor, trkA, in bovine ovarian follicle selection and early luteogenesis (Carrasco et al. 2016 Reprod. Biol. Endocrinol. 14, 47), but innervation and neuropeptide control remains an unexplored aspect of ovarian function. P75 is the low-affinity receptor for all neurotrophins and is expressed in ovarian tissue. The objective of this study was to explore the distribution of P75 neurons and fibres within the ovary and to examine the relationship of these components with follicular development. The ovaries of cows (n = 5) were collected at the time of slaughter, 36 h after induced luteolysis (i.e. proestrus). The ovaries were fixed in 4% paraformaldehyde for 48 h, and samples from the ovarian hilus, medulla, and cortex (3 blocks per ovary) were cryo-sectioned (20–50 µm). Tissue sections were incubated for 48 h with a rabbit antibody against rat P75 or a mouse monoclonal antibody against neurofilament. Immunodetection was visualised by an amplification procedure with horseradish peroxidase using nickel DAB as a chromogen. Sections were counterstained with nuclear fast red for follicle identification. Immunoreactive cell bodies were counted in 10 to 20 fields (40×) per section, and data were expressed based on ovarian areas (cortex, medulla, or hilus) as an average count per 40× field per animal. Data among ovarian regions were compared by ANOVA; differences were considered significant when P < 0.05. Antral follicles =5 mm displayed strong immunoreactivity in the theca layer, without reaction in the granulosa cells. In contrast, preovulatory follicles were devoid of P75 immuno-reactivity in the theca layer. Oval P75 immunoreactive neuron-like cells were present in all ovarian areas studied. The neuronal nature of the P75 immunoreactive cells was confirmed by the presence of a similar pattern when adjacent sections were stained for neurofilaments, a protein characteristic of neurons. In the stroma of the ovarian cortex and medulla, neurons were present individually (scattered) rather than grouped; however, a dense network of neurons and fibres was detected immediately beneath the ovarian surface epithelium. No differences between the cortex, medulla, and hilus were found in the mean number of immunoreactive cells (10.6 ± 2.8, 14.4 ± 3.6 and 13.9 ± 2.0 cells/40× field, respectively). Immunoreactive neuron-like cells and fibres were in close proximity to blood vessels in the ovarian medulla. Corpora lutea were devoid of P75 immunoreactivity. In conclusion, results document the existence of a neuronal network in the bovine ovary, displaying an association with follicles at different stages of development. The abundance of neuronal components (i.e. neuron cell bodies and axons) in the ovarian stromal and surface epithelium implies a role of innervation (either extrinsic or intrinsic) in the control of ovarian follicular development and function. Research was supported by the Natural Sciences and Engineering Research Council of Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.284
Teacher spread0.243 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2017
Admission routes2
Has abstractyes

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