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Record W4288033708 · doi:10.3389/fendo.2022.951990

Editorial: Recent Progress and Perspectives in Neurosteroid Research

2022· editorial· en· W4288033708 on OpenAlexaff
Hubert Vaudry, Takayoshi Ubuka, Kiran K. Soma, Kazuyoshi Tsutsui

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typeeditorial
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeuroactive steroidNeuroscienceBiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Recent Progress and Perspectives in Neurosteroid ResearchThe term "Neurosteroids" designates pregnenolone-derived bioactive compounds that are synthesized or catalyzed by neural cells and act locally on the central or peripheral nervous systems.At the molecular level, the actions of neurosteroids are mainly mediated through membrane receptors i.e. via their cognate receptors and/or via allosteric modulation of other receptors.At the cellular level, neurosteroids act as neurohormones, neuromodulators, neurotransmitters and/or neurotrophic factors.At the organismal level, neurosteroids regulate several physiological processes including arousal, sleep, learning, social and sexual behaviors.Thus, neurosteroids are now considered an important class of intercellular/intracellular signaling molecules in the nervous system, in very much the same as neurotransmitters, neuropeptides and growth factors.Not surprisingly, neurosteroids appear to be implicated in a number of pathophysiological conditions such as pain, neurodegenerative diseases, autism, stress, anxiety, depression, etc.Therefore, drugs targeting neurosteroid biosynthetic enzymes or neurosteroid receptors have strong potential for the development of novel therapeutic approaches.This Research Topic compiles a series of review and original articles that provide a broad view of the current knowledge on the biosynthesis, functional roles and pathophysiological implications of neurosteroids, and highlights new concepts in this field.We want to dedicate this Research Topic to the memory of our colleague and dear friend Kazuyoshi Tsutsui, an undisputed leader in neurosteroid research who, very sadly, passed away on September 16, 2021.Progesterone and allopregnanolone are two neuroactive steroids that act primarily through membrane receptors (1).Progesterone can activate five metabotropic membrane receptors belonging to the progestin and adipoQ receptor (PAQR) family that are distinct from the GPCR family (2).Allopregnanolone and its 3b-methylated synthetic analog ganaxolone act as positive allosteric modulators of GABA A receptors (Pinna).The review by Thomas and Pang summarizes the current knowledge on the neuroprotective actions of allopregnanolone and ganaxolone.Concurrently, Pinna describes the long journey between the discovery of allopregnanolone in the adrenal cortex (3) and the characterization of its anxiolytic and antidepressant properties (4, 5).The recent validation of allopregnanolone-based treatment of postpartum depression (6) opens new avenues for the development of other neurosteroid-derived drugs in neuropsychiatry.Apolipoprotein A1 regulatory protein-1 (ARP-1), a member of the steroid receptor superfamily whose ligand is unknown (orphan receptor), regulates transcriptional activity of numerous genes

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)0.006
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.001
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0040.002
Research integrity0.0120.016
Insufficient payload (model declined to judge)0.0140.012

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 head0.058
GPT teacher head0.355
Teacher spread0.297 · 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
GenreEditorial

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

Citations7
Published2022
Admission routes1
Has abstractyes

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