Characterization and molecular evolution analysis of <i>Periploca forrestii</i> inferred from its complete chloroplast genome sequence
Bibliographic record
Abstract
Periploca forrestii, a medicinal plant of the family Apocynaceae, is known as an effective and widely used clinical prescription for the treatment of rheumatoid diseases. In this study, we de novo sequenced and assembled the completement chloroplast (cp) genome of P. forrestii based on combined Oxford Nanopore PromethION and Illumina data. The cp genome was 153 724 bp in length and had four subregions. Moreover, an 84 433 bp large single-copy and a 17 731 bp small single-copy were separated by 25 780 bp inverted repeats (IRs). The cp genome included 132 genes with 18 duplicates in the IRs. A total of 45 repeat structures and 183 simple sequence repeats were detected. Codon usage showed a bias toward A/T-ending codons. A comparative study of Apocynaceae revealed that an IR expansion occurred on P. forrestii. The Ka/Ks values of eight species of Apocynaceae suggested that positive selection was exerted on the psaI and ycf2 genes, which might reflect specific adaptions to the P. forrestii particular growth environment. Phylogenetic analysis indicated that Periplocoideae was a sister to Asclepiadoideae, forming a monophyletic group in the family Apocynaceae. This study provided an important P. forrestii genomic resource for future evolutionary studies and the phylogenetic reconstruction of the family Apocynaceae.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".