Dual oxidase gene <i>Duox</i> and Toll-like receptor 3 gene <i>TLR3</i> in the Toll pathway suppress zoonotic pathogens through regulating the intestinal bacterial community homeostasis in <i>Hermetia illucens</i> L.
Bibliographic record
Abstract
Abstract Black soldier fly (BSF; Hermetia illucens L.) larvae can convert fresh pig manure into protein and fat-rich biomass, which can then be used as livestock feed. Currently, it is the only insect approved for such purposes in Europe, Canada, and the USA. Pig manure is rich in zoonotic pathogens (e.g., Staphylococcus aureus and Salmonella spp.). BSF larvae inhibit these zoonotic pathogens; however, the mechanism is unclear. We employed RNAi, qRT-PCR, and Illumina MiSeq bacterial 16S rDNA high-throughput sequencing molecular techniques to study the interaction between the two immune genes ( Duox in Duox-reactive oxygen species [ROS] immune system and TLR3 in the Toll signaling pathway) and zoonotic pathogens to determine the mechanisms resulting in pathogen suppression. Results indicated that Bsf Duox-TLR3 RNAi increased bacterial load but decreased the relative abundance of Providencia and Dysgonomonas intestinal symbionts. Concurrently, Bsf Duox-TLR3 RNAi inactivated the NF-κ B signaling pathway, downregulated the expression of antimicrobial peptides, and diminished inhibitory effects on zoonotic pathogen. The resulting dysbiosis stimulated an immune response by activating BsfDuox and promoting ROS, which regulated the composition and structure of the gut bacterial community. Thus, BsfDuox and BsfTLR3 are important factors in regulating the gut key bacteria Providencia and Dysgonomonas homeostasis while inhibiting target zoonotic pathogens.
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 | 0.001 |
| 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".