Two new sponge species (Demospongiae: Chalinidae and Suberitidae) isolated from hyperarid mangroves of Qatar with notes on their potential antibacterial bioactivity
Bibliographic record
Abstract
This study presents the taxonomic description of two new sponge species that are intimately associated with the hyperarid mangrove ecosystem of Qatar. The study includes a preliminary evaluation of the sponges' potential bioactivity against pathogens. Chalinula qatari sp. nov. is a fragile thinly encrusting sponge with a vivid maroon colour in life, often with oscular chimneys and commonly recorded on pneumatophores in the intertidal and shallow subtidal zone. Suberites luna sp. nov. is a massive globular-lobate sponge with a greenish-black colour externally and a yellowish orange colour internally, recorded on pneumatophores in the shallow subtidal zone, with large specimens near the seagrass ecosystem that surrounds the mangrove. For both species, a drug extraction protocol and an antibacterial experiment was performed. The extract of Suberites luna sp. nov. was found to be bioactive against recognized pathogens such as Staphylococcus epidermidis, Staphylococcus aureus and Enterococcus faecalis, but no bioactive activity was recorded for Chalinula qatari sp. nov. This study highlights the importance of increasing bioprospecting effort in hyperarid conditions and the importance of combining bioprospecting with taxonomic studies for the identification of novel marine drugs.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".