Characterization of Hexachlorocyclohexane Isomer Dehydrochlorination by LinA1 and LinA2 Using Multi-element Compound-Specific Stable Isotope Analysis
Bibliographic record
Abstract
Dehydrochlorination is one of the main (thus far discovered) processes for aerobic microbial transformation of hexachlorocyclohexane (HCH) which is mainly catalyzed by LinA enzymes. In order to gain a better understanding of the reaction mechanisms, multi-element compound-specific stable isotope analysis was applied for evaluating α- and γ-HCH transformations catalyzed by LinA1 and LinA2 enzymes. The isotopic fractionation (ε E ) values for particular elements of (+)α-HCH (ε C = −10.8 ± 1.0‰, ε Cl = −4.2 ± 0.5‰, ε H = −154 ± 16‰) were distinct from the values for (−)α-HCH (ε C = −4.1 ± 0.7‰, ε Cl = −1.6 ± 0.2‰, ε H = −68 ± 10‰), whereas the dual-isotope fractionation patterns were almost identical for both enantiomers (Λ C–Cl = 2.4 ± 0.4 and 2.5 ± 0.2, Λ H–C = 12.9 ± 2.4 and 14.9 ± 1.1). The ε E of γ-HCH transformation by LinA1 and LinA2 were −7.8 ± 1.0‰ and −7.5 ± 0.8‰ (ε C ), −2.7 ± 0.3‰ and −2.5 ± 0.4‰ (ε Cl ), −170 ± 25‰ and −150 ± 13‰ (ε H ), respectively. Similar Λ C–Cl values (2.7 ± 0.2 and 2.9 ± 0.2) were observed as well as similar Λ H–C values (20.1 ± 2.0 and 18.4 ± 1.9), indicating a similar reaction mechanism by both enzymes during γ-HCH transformation. This is the first data set on 3D isotope fractionation of α- and γ-HCH enzymatic dehydrochlorination, which gave a more precise characterization of the bond cleavages, highlighting the potential of multi-element compound-specific stable isotope analysis to characterize different transformation processes (e.g., dehydrochlorination and reductive dehalogenation).
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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 | 0.000 | 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 | 0.000 |
| 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".