Molecular Identification and Phylogenetic Study of Digenetic Trematodes in Indian Freshwater Fishes
Bibliographic record
Abstract
Digenetic trematodes represent one of the most ecologically significant groups of helminth parasites affecting freshwater fishes, with implications for biodiversity, aquaculture productivity, and zoonotic health. The present study investigated the prevalence, morphological diversity, molecular identity, and phylogenetic relationships of trematodes infecting freshwater fishes in the Azamgarh district of Uttar Pradesh, India. Systematic sampling was conducted across six sites representing diverse hydro-ecological habitats of the Ghaghara River system. A total of 642 fish specimens belonging to Channa punctata, Clarias batrachus, and Heteropneustesfossilis were examined seasonally for one year. Overall prevalence of trematode infection was 54.8%, with peak levels recorded during the monsoon season. Morphological characterization revealed species such as Clinostomumcomplanatum, Allocreadiumhandiai, Maseniavittatusi, and Opisthorchis sp. Histopathological analyses confirmed significant tissue damage in gills, intestine, and liver of infected hosts. Molecular characterization using ITS1 and COI gene markers validated morphological identifications and revealed >97% similarity with global Gen Bank entries. Phylogenetic analyses clustered Indian isolates with their respective families, with evidence of host-associated haplotypes and possible cryptic diversity. The study highlights the ecological, pathological, and public health relevance of trematode infections and underscores the need for integrated monitoring in Indian freshwater ecosystems.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".