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Record W4387728732 · doi:10.1007/s13659-023-00408-w

Cytotoxic phenazine and antiallergic phenoxazine alkaloids from an arctic Nocardiopsis dassonvillei SCSIO 502F

2023· article· en· W4387728732 on OpenAlexaff
Yue Song, Q. Li, Mengjing Cong, Xiaoyan Pang, Bo Chen, Yonghong Liu, Li Liao, Junfeng Wang

Bibliographic record

VenueNatural Products and Bioprospecting · 2023
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsMcGill University
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceNational Key Research and Development Program of ChinaSouth China Sea Institute of Oceanology, Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsPhenazinePhenoxazineIC50Bioorganic chemistryChemistryMicrobiologyBiologyIn vitroBiochemistryPharmacology

Abstract

fetched live from OpenAlex

Abstract Microbes well-adapted to the Arctic Ocean are promising for producing novel compounds, due to their fancy strategies for adaptation and being under-investigated. Two new phenazine alkaloids (1 and 2) and one new phenoxazine (3) were isolated from Nocardiopsis dassonvillei 502F, a strain originally isolated from Arctic deep-sea sediments. AntiSMASH analysis of the genome of Nocardiopsis dassonvillei 502F revealed the presence of 16 putative biosynthetic gene clusters (BGCs), including a phenazine BGC. Most of the isolated compounds were evaluated for their antibacterial, antiallergic, and cytotoxic activities. Among them, compounds 4 and 5 exhibited potent in vitro cytotoxic activities against osteosarcoma cell line 143B with IC50 values 0.16 and 20.0 μM, respectively. Besides, the results of antiallergic activities of compounds 6–8 exhibited inhibitory activities with IC50 values of 10.88 ± 3.05, 38.88 ± 3.29, and 2.44 ± 0.17 μg/mL, respectively (IC50 91.6 μM for the positive control loratadine). Graphical Abstract

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.263
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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