Elimination of Endocrine Disrupting Chemicals using White Rot Fungi and their Lignin Modifying Enzymes: A Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The ability of white rot fungi (WRF) and their lignin modifying enzymes (LMEs), i.e. laccase and lignin‐ and manganese‐dependent peroxidase, to treat endocrine disrupting chemicals (EDCs) is extensively reviewed in this paper. These chemicals cause adverse health effects by mimicking endogenous hormones in receiving organisms. The alkylphenolic EDCs nonylphenol, bisphenol A and triclosan, the phthalic acid esters dibutylphthalate, diethylphthalate and di‐(2‐ethylhexyl)phthalate, the natural estrogens estrone, 17β‐estradiol, estriol and 17α‐ethynylestradiol and the phytoestrogens genistein and β‐sitosterol have been shown to be eliminated by several fungi and LMEs. WRF have manifested a highly efficient removal of EDCs in aqueous media and soil matrices using both LME and non LME‐systems. The ligninolytic system of WRF could also be used for the elimination of several EDCs and the associated hormone‐mimicking activity. The transformation of EDCs by LMEs and WRF is supported by emerging knowledge on the physiology and biochemistry of these organisms and the biocatalytic properties of their enzymes. Due to field reaction conditions, which drastically differ from laboratory conditions, further efforts will have to be directed towards developing robust and reliable biotechnological processes for the treatment of EDC‐contaminated environmental matrices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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