Multiple cutaneous nerve sheath tumours with myxoid differentiation in farmed Russian sturgeons (Acipenser gueldenstaedtii, Brandt and Ratzeburg 1833)
Bibliographic record
Abstract
Sturgeon species are well-suited for aquaculture because of their favourable characteristics, including robustness, suitability for farming in facilities unsuitable for other fish species, and adaptability to diverse farming conditions. The Russian sturgeon (Acipenser gueldenstaedtii, Brandt and Ratzeburg 1833) is one of the most prominent farmed species; however, like other aquaculture species, it is susceptible to significant losses from bacterial and viral diseases. Beyond infectious causes, there are few reports documenting conditions that produce cutaneous masses in Russian sturgeons. This study presents a multidisciplinary investigation of six farmed Russian sturgeons exhibiting discrete, multiple cutaneous masses. Bacteriological analysis of tissue samples revealed the presence of Morganella morganii and Aeromonas veronii biovar sobria, identified as opportunistic bacteria. Virological assays targeting the principal viruses affecting sturgeon, Acipenser iridovirus and Acipenser herpesvirus, yielded negative results. Ultrastructural analysis with direct negative staining revealed no evidence of biological agents. Histologically, the dermal masses were well-demarcated, expansile, and moderately cellular, consisting of spindle-to-stellate neoplastic cells that were multifocally periodic acid-Schiff-positive and embedded in abundant alcianophilic ground substance. Immunohistochemistry with the S-100 antibody confirmed cytoplasmic staining of the neoplastic cells. A final diagnosis of cutaneous nerve sheath tumour with myxoid differentiation was made, replicating findings from a similar tumour in rainbow trout. To the best of our knowledge, this represents the first description of multiple cutaneous nerve sheath tumours in sturgeon species. The potential factors contributing to the development of this neoplastic condition are discussed.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".