Isolation and Characterization of <i>HvNRT2.3</i>and <i>HvNRT2.4</i>, cDNAs Encoding High-Affinity Nitrate Transporters from Roots of Barley
Bibliographic record
Abstract
Two full-length cDNAs, HvNRT2.3 and HvNRT2.4, were isolated from roots of barley (Hordeum vulgare), using reverse transcriptase-PCR and RACE-PCR. The corresponding polypeptides, consisting of 507 amino acids (molecular masses of 54.6 kD), belong to the major facilitator superfamily (MFS), and are closely related (>87% identity) to those encoded by HvNRT2.1 and HvNRT2.2 (formerly BCH1 and BCH2, respectively) from roots of barley. The latter are considered to encode inducible high-affinity NO(3)(-) transporters (Trueman et al., 1996). HvNRT2 transcripts were undetectable in NO(3)(-)-deprived plants. Following exposure to either NO(3)(-) or NO(2)(-), transcript abundance and (13)NO(3)(-) influx increased to a maximum by 6 to 12 h, then declined in HvNRT2.1, HvNRT2.2, and HvNRT2.3. The pattern of HvNRT2.4 transcript abundance was different, remaining high after achieving peak abundance. When external NO(3)(-) concentrations were varied from 0 to 500 microM under steady-state conditions of NO(3)(-) supply, HvNRT2 transcript accumulation and (13)NO(3)(-) influx were highest in 50 microM NO(3)(-) -grown plants. When NH(4)(+) was provided together with NO(3)(-), transcript accumulation during the first 2 h was similar to that due to NO(3)(-) alone, but by 4 h the transcript level was significantly reduced. HvNRT2 transcript was undetectable in leaf tissues.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.001 |
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".