Efficient production and characterization of melanin from Thermothelomyces hinnuleus SP1, isolated from the coal mines of Chhattisgarh, India
Why this work is in the frame
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Bibliographic record
Abstract
In the present study, fungi were isolated and screened from barren land in south-eastern Coalfields limited (SECL) in Chhattisgarh, India. Out of 14 isolated fungi, only three fungal isolates exhibited pigmentation in screening studies. The isolated fungal strain SP1 exhibited the highest pigmentation, which was further utilized for in vivo production, purification, and characterization of melanin pigment. The physical and chemical properties of the fungal pigment showed insolubility in organic solvents and water, solubility in alkali, precipitation in acid, and decolorization with oxidizing agents. The physiochemical characterization and analytical studies of the extracted pigment using ultraviolet–visible spectroscopy and Fourier transform infrared (FTIR) confirmed it as a melanin pigment. The melanin-producing fungus SP1 was identified as Thermothelomyces hinnuleus based on 18S-rRNA sequence analysis. Furthermore, to enhance melanin production, a response surface methodology (RSM) was employed, specifically utilizing the central composite design (CCD). This approach focused on selecting efficient growth as well as progressive yield parameters such as optimal temperature (34.4°C), pH (5.0), and trace element concentration (56.24 mg). By implementing the suggested optimal conditions, the production rate of melanin increased by 62%, resulting in a yield of 28.3 mg/100 mL, which is comparatively higher than the actual yield (17.48 ± 2.19 mg/100 mL). Thus, T. hinnuleus SP1 holds great promise as a newly isolated fungal strain that could be used for the industrial production of melanin.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it