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Record W4405561830 · doi:10.1093/conphys/coae080

Blubber biopsy biomarkers for baleen whales

2024· article· en· W4405561830 on OpenAlexaff
Ian A. Bouyoucos

Bibliographic record

VenueConservation Physiology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBlubberBiologyBaleenFisheryMarine mammalWhaleZoology

Abstract

fetched live from OpenAlex

Whales, dolphins and porpoises—collectively, cetaceans—are among the charismatic ocean giants that captivate and inspire future generations of marine biologists. In recent years, a draw to study cetaceans has, regrettably, been the need to urgently conserve them. As of 2023, the Cetacean Specialist Group of The International Union for Conservation of Nature identified that one in four cetacean species are threatened with extinction. By studying the health of wild cetaceans, scientists ultimately hope to better understand and effectively manage threats to populations (Fig. 1). But how do researchers even go about studying how healthy a cetacean is in its natural habitat? From flying drones over humpback whales’ blowholes to collect samples from their breath to chasing down fresh scat from killer whales in dinghies, researchers are constantly innovating to overcome a simple, inconvenient truth: many cetaceans are enormous, and cannot be restrained and studied in a laboratory! Joanna Kershaw and colleagues (Kershaw et al., 2024) are bringing cetacean conservation physiology into the 21st century with ‘omics’ techniques. Because many omics techniques are foreign to the world of cetacean conservation science, Kershaw and colleagues sought to add ‘shotgun proteomics’ to the conservation physiology toolbox. Proteomics describes the ‘proteome’, or all the proteins present in a sample, including potential biomarkers of the health of wild whales. For their study, Kershaw and colleagues collected blubber biopsies from 10 female minke whales (Balaenoptera acutorostrata) in the Gulf of St. Lawrence (Canada) during their summer feeding season. The blubber biopsies were collected from a small, inflatable boat using a crossbow (no, not a shotgun) with a hollow-tipped arrow. Illustration: Kaitlin Barham ([email protected]) Blubber is a promising tissue to generate a snapshot of the health of wild cetaceans. Logistically, researchers can easily and safely collect it. Ethically, blubber biopsies only penetrate several centimetres, which is a fraction of how thick blubber is in many whales. Physiologically, blubber is a highly vascularized fatty tissue just under the skin, so blubber proteins reflect processes within the skin and fat, and proteins present in circulation from the blood. To analyze their samples, the blubber biopsies underwent a standard shotgun proteomics pipeline. First, the blubber proteins are extracted and isolated from all the fatty tissue. Then the isolated proteins are digested into smaller peptides that are then separated and sequenced by liquid chromatography tandem mass spectrometry. Finally, the peptide sequences are aligned against known protein sequences for humans and assigned ‘biological process’ classifications based on their functions. For the first time, Kershaw and colleagues demonstrated that shotgun proteomics can produce a valuable snapshot of the health of wild whales. Their approach allowed them to identify over 400 proteins. Most of the proteins identified were important for lipid metabolism, which means they are critical for managing energy stores in blubber. Indeed, Kershaw and colleagues posited that their approach could meaningfully reflect metabolic changes as minke whales fatten up in the Gulf of St. Lawrence each summer. Kershaw and colleagues also identified many blubber proteins that are important for the immune system and antioxidant defence. Importantly, these blubber proteins are critical biomarkers for the overall health of wild minke whales. Ultimately, Kershaw and colleagues write that molecular techniques like theirs can contribute to marine mammal management and conservation; indeed, their study demonstrates that proteomic profiling of blubber biopsies is a promising approach to assessing the health of wild cetaceans.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.270
Teacher spread0.242 · 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 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
Published2024
Admission routes1
Has abstractno

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