MétaCan
Menu
Back to cohort
Record W2783539475 · doi:10.1073/pnas.1707663115

Targeted knockout of a chemokine-like gene increases anxiety and fear responses

2018· article· en· W2783539475 on OpenAlexaff
Jung-Hwa Choi, Yun-Mi Jeong, Sujin Kim, Boyoung Lee, Krishan Ariyasiri, Hyun-Taek Kim, Seung‐Hyun Jung, Kyu-Seok Hwang, Tae‐Ik Choi, Chulo Park, Won‐Ki Huh, Jill A. Rosenfeld, Salmo Raskin, Alan Ma, Jozef Gécz, Hyung‐Goo Kim, Jin‐Soo Kim, Ho‐Chul Shin, Doo-Sang Park, Robert Gerlai, Bradley B. Jamieson, Joon S. Kim, Karl J. Iremonger, Sang H. Lee, Hee‐Sup Shin, Cheol‐Hee Kim

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of Toronto
FundersInstitute for Basic ScienceNational Research Foundation of KoreaMinistry of Trade, Industry and EnergyNational Research Foundation
KeywordsZebrafishBiologyAnxietyKnockout mouseAutismNeuroscienceAmygdalaGeneGeneticsPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Significance Emotion-related responses, such as fear and anxiety, are important behavioral phenomena in most animal species, as well as in humans. However, the underlying mechanisms of fear and anxiety in animals and in humans are still largely unknown, and anxiety disorders continue to represent a large unmet medical need in the human clinic. Animal models may speed up discovery of these mechanisms and may also lead to betterment of human health. Herein, we report the identification of a chemokine-like gene family, samdori ( sam ), and present functional characterization of sam2 . We observed increased anxiety-related responses in both zebrafish and mouse knockout models. Taken together, these results support a crucial and evolutionarily conserved role of sam2 in regulating anxiety-like behavior.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.025
GPT teacher head0.325
Teacher spread0.300 · 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 designBench or experimental
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".

Quick stats

Citations50
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicZebrafish Biomedical Research ApplicationsFrench-language works237,207