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Record W2009542873 · doi:10.3791/51526

Understanding Early Organogenesis Using a Simplified <em>In Situ</em> Hybridization Protocol in <em>Xenopus</em>

2015· article· en· W2009542873 on OpenAlexafffund
Steven Deimling, Rami Halabi, Stephanie A. Grover, Jean H. Wang, Thomas A. Drysdale

Bibliographic record

VenueJournal of Visualized Experiments · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsChildren's Hospital of Western OntarioSickKids FoundationWestern UniversityChildren’s Health Research InstituteHospital for Sick Children
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOrganogenesisXenopusIn situ hybridizationBiologyIn situPrimordiumComputational biologyCell biologyGeneticsGeneMessenger RNAChemistry

Abstract

fetched live from OpenAlex

Organogenesis is the study of how organs are specified and then acquire their specific shape and functions during development. The Xenopuslaevis embryo is very useful for studying organogenesis because their large size makes them very suitable for identifying organs at the earliest steps in organogenesis. At this time, the primary method used for identifying a specific organ or primordium is whole mount in situ hybridization with labeled antisense RNA probes specific to a gene that is expressed in the organ of interest. In addition, it is relatively easy to manipulate genes or signaling pathways in Xenopus and in situ hybridization allows one to then assay for changes in the presence or morphology of a target organ. Whole mount in situ hybridization is a multi-day protocol with many steps involved. Here we provide a simplified protocol with reduced numbers of steps and reagents used that works well for routine assays. In situ hybridization robots have greatly facilitated the process and we detail how and when we utilize that technology in the process. Once an in situ hybridization is complete, capturing the best image of the result can be frustrating. We provide advice on how to optimize imaging of in situ hybridization results. Although the protocol describes assessing organogenesis in Xenopus laevis, the same basic protocol can almost certainly be adapted to Xenopus tropicalis and other model systems.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.090
GPT teacher head0.408
Teacher spread0.318 · 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.

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

Citations4
Published2015
Admission routes2
Has abstractyes

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