Biochemical analysis of Hyalomma dromedarii salivary glands and gut tissues using SR-FTIR micro-spectroscopy
Bibliographic record
Abstract
Ticks are obligatory voracious blood feeders infesting diverse vertebrate hosts, that have a crucial role in the transmission of diverse pathogens that threaten human and animal health. The continuous emergence of tick-borne diseases due to combined worldwide climatic changes, human activities, and acaricide-resistant tick strains, necessitates the development of novel ameliorative tick control strategies such as vaccines. The synchrotron-based Fourier transform infrared micro-spectroscopy (SR-FTIR) is a bioanalytical microprobe capable of exploring the molecular chemistry within microstructures at a cellular or subcellular level and is considered as a nondestructive analytical approach for biological specimens. In this study, SR-FTIR analysis was able to explore a qualitative and semi-quantitative biochemical composition of gut and salivary glands of Hyalomma dromedarii (H. dromedarii) tick detecting differences in the biochemical composition of both tissues. A notable observation regarding Amide I secondary structure protein profile was the higher ratio of aggregated strands in salivary gland and beta turns in gut tissues. Regarding the lipid profile, there was a higher intensity of lipid regions in gut tissue when compared to salivary glands. This detailed information on the biochemical compositions of tick tissues could assist in selecting vaccine and/or control candidates. Altogether, these findings confirmed SR-FTIR spectroscopy as a tool for detecting differences in the biochemical composition of H. dromedarii salivary glands and gut tissues. This approach could potentially be extended to the analysis of other ticks that are vectors of important diseases such as babesiosis and theileriosis.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".