Development and validation of mitochondrial DNA based approach for rapid identification of environmental chemical exposed victims
Bibliographic record
Abstract
The rising toll of mortality due to different accidental or occupational environmental exposures necessitates early identification of exposed victims for their appropriate therapeutic intervention. However, this is mainly restricted by the lack of precise biomarkers and effective detection methodologies. Since, mitochondria are the prime target of different environmental exposures, these sub-cellular organelles offer possibilities of getting utilized for developing effective exposure associated strategies. The presence of unique inheritance pattern, rapid evolutionary rate, low recombination rate, higher copy number and resistance to degradation make mtDNA an important and indispensable tool for such studies. Therefore, we aim to design an mtDNA based molecular approach for rapid identification of the environmental chemical exposure associated victims. In order to analyze whole genome sequence of mtDNA, particular attention was devoted for primer selection from established libraries to adjust the melting temperature of all pairs. The specificity of selected primers was checked through BLAST analysis to avoid nDNA co-amplification. Total DNA was extracted from both human peripheral blood and lymphocytes and quantified for mtDNA amplification. Results of our PCR analysis showed clear amplification of whole ~16000 bp of mtDNA without co-amplification of NUMTs. Gel pictures showed the presence of a clear band of all the 9 fragments which correlated with their respective size. For absolute quantification real-time PCR analysis using primers for mt-ND1 (NADH dehydrogenase, subunit 1) gene (ND1-F, 50 CCCTAAAACCCGCCACATCT 30; ND1-R, 50 GAGCGATGGTGAGAGCTAAGGT 30) in mtDNA and other primer pair for the amplification of nuclear gene human (β-actin) was further performed. The ratio of mtDNA copy number to nDNA value was determined to identify absolute mtDNA copies (Mean 0.69 ± 0.05). After ascertaining the empty DNA copy numbers, the amplified products were purified for downstream mtDNA sequencing studies. The analysis was performed in collaboration with SciGenom Labs by using ABI 3730 XI equipped with 30 cm capillary array to facilitate the mtDNA fragment analysis. Currently, the investigations are ongoing and the obtained results may help to design novel mtDNA based fluorescence resonance energy transfer hybridization (FRET) - real time PCR assay for rapid identification of environmental chemical exposed victims.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".