In search of the <scp>pH</scp> limit of growth in halo‐alkaliphilic cyanobacteria
Bibliographic record
Abstract
Cyanobacteria have many biotechnological applications. Increasing their cultivation pH can assist in capturing carbon dioxide and avoiding invasion by other organisms. However, alkaline media may have adverse effects on cyanobacteria, such as reducing the Carbon-Concentrating Mechanism's efficiency. Here, we cultivated two halo-alkaliphilic cyanobacteria consortia in chemostats at pH 10.2-11.4. One consortium was dominated by Ca. Sodalinema alkaliphilum, the other by a species of Nodosilinea. These two cyanobacteria dominate natural communities in Canadian and Asian alkaline soda lakes. We show that increasing the pH decreased biomass yield. This decrease was caused, in part, by a dramatic increase in carbon transfer to heterotrophs. At pH 11.4, cyanobacterial growth became limited by bicarbonate uptake, which was mainly ATP dependent. In parallel, the higher the pH, the more sensitive cyanobacteria became to light, resulting in photoinhibition and upregulation of DNA repair systems.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".