Non‐antibiotic approaches to combat motile <i>Aeromonas</i> infections in aquaculture: Current state of knowledge and future perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Inland aquaculture contributed by three major fish groups, including carps, tilapias, and catfish plays a vital role in global food security and nutrition, particularly in low and middle‐income countries. However, the sustainable development of this sector is hampered by disease epidemics, especially those caused by bacteria such as Aeromonas species. At least eight pathogenic motile Aeromonas species ( A. hydrophila , A. veronii , A. jandaei , A. caviae , A. sobria , A. bestiarum , A. dhakensis and A. schubertii ) have been reported in aquaculture with some causing up to 100% mortality during disease outbreaks. Simultaneously, emerging multidrug‐resistant Aeromonas due to a long‐inappropriate use of antibiotics is alarming and highlights a global public health concern and negative socioeconomic impacts. Here, we provide a comprehensive overview of motile Aeromonas infections, antibiotic use and antimicrobial resistance of Aeromonas species . This contribution also highlights the non‐antibiotic approaches (the solutions for preventing or treating of bacterial diseases without resorting to antibiotic use) to control motile Aeromonas infections. In addition to the current state of knowledge and limitations of each prophylaxis/therapy, perspectives for future research are discussed critically, including oral/immersion multivalent vaccines, microencapsulated synbiotics, exogenous metabolites, and novel lytic bacteriophage cocktails. Some emerging applicable nanotechnology themes such as nanovaccines, nanobioactive compounds, and nanobubbles are also included in this review. In summary, combating motile Aeromonas infections in aquaculture, including multidrug‐resistant aeromonads, as well as other bacterial diseases, is a lengthy battle that requires a strategic combination of multiple non‐antibiotic approaches coherent with the One Health philosophy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it