Safe and efficient transportation of clinical samples for molecular detection of African swine fever virus
Bibliographic record
Abstract
African swine fever (ASF) continues to devastate swine populations across the globe. The causative agent, ASF virus (ASFV), is very stable and can remain infectious over long periods of time especially in contaminated blood and tissue samples. Therefore, the transport of clinical samples from the field to diagnostic laboratories requires special precautions to reduce the risk of spreading the disease. Inactivation of ASFV in the clinical samples prior to transporting to the lab eliminates the risk and the requirement of higher biosafety facilities to perform ASF diagnostics. This study evaluated the use of a commercial molecular transport medium (MTM) to inactivate ASFV and stabilize the viral DNA in cell culture and clinical samples collected from pigs inoculated with different ASFV strains. In all the sample types tested, complete inactivation of ASFV was observed, without affecting the subsequent detection of ASFV genomic material by real time polymerase chain reaction (real time PCR). The MTM preserved the stability of ASFV genomic material eliminating the need to refrigerate clinical samples. The data shows that the MTM can be used reliably to ensure safety and stability of routine clinical samples such as whole blood, spleen swabs and alternative sample types such as oral fluid, allowing expansion and streamlining ASF molecular diagnostics.
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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".