Isolation and characterization of a sulfated polysaccharide from the brown alga <i>Sargassum patens</i> and determination of its anti-herpes activity
Bibliographic record
Abstract
Bioactivity-guided fractionation of the hot water extract from the brown alga Sargassun patens led to the isolation of a polysaccharide as an antiviral component against herpes simplex viruses which are the cause of cold sores (HSV-1) and genital herpes (HSV-2). The polysaccharide contained a sulfur group that could be present as a sulfate ester. It is thus a sulfated polysaccharide with a molecular mass of about 424 kDa, and is designated SP-2a. Gas chromatographic assay showed that the polysaccharide consisted of fucose, galactose, mannose, xylose, glucose, and galactosamine. The fucose is the major constituent sugar (35.3%), followed by galactose (18.4%). The 50% effective concentration (EC50) against HSV-2, HSV-1, and HSV-1 acyclovir resistant strain was 1.3, 5.5, and 4.1 microg/mL, respectively. The 50% cytotoxic concentration (CC50) of SP-2a on the growth of normal Vero cell line was more than 4000 microg/mL. Therefore SP-2a of S. patens may be a potent agent for treating HSV infections.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".