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Record W2768957966 · doi:10.3390/md15110359

Lactones from the Sponge-Derived Fungus Talaromyces rugulosus

2017· article· en· W2768957966 on OpenAlexfundno aff
Lisa Küppers, Weaam Ebrahim, Mona El‐Neketi, Ferhat Can Özkaya, Attila Mándi, Tibor Kurtán, Raha Orfali, Wernér E.G. Müller, Rudolf Hartmann, Wenhan Lin, Weiguo Song, Zhen Liu, Peter Proksch

Bibliographic record

VenueMarine Drugs · 2017
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsnot available
FundersNational Research, Development and Innovation OfficeKing Saud UniversityInstitute of Population and Public HealthNemzeti Kutatási Fejlesztési és Innovációs HivatalDeutsche Forschungsgemeinschaft
KeywordsSpongeFungusBiologyMicrobiologyBotany

Abstract

fetched live from OpenAlex

The marine-derived fungus Talaromyces rugulosus isolated from the Mediterranean sponge Axinella cannabina and cultured on solid rice medium yielded seventeen lactone derivatives including five butenolides (1–5), seven (3S)-resorcylide derivatives (6–12), two butenolide-resorcylide dimers (13 and 14), and three dihydroisocoumarins (15–17). Among them, fourteen compounds (1–3, 6–16) are new natural products. The structures of the isolated compounds were elucidated by 1D and 2D NMR (Nuclear Magnetic Resonance) spectroscopy as well as by ESI-HRMS (ElectroSpray Ionization-High Resolution Mass Spectrometry). TDDFT-ECD (Time-Dependent Density Functional Theory-Electronic Circular Dichroism) calculations were performed to determine the absolute configurations of chiral compounds. The butenolide-resorcylide dimers talarodilactones A and B (13 and 14) exhibited potent cytotoxicity against the L5178Y murine lymphoma cell line with IC50 values of 3.9 and 1.3 µM, respectively.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0010.000

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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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

Citations45
Published2017
Admission routes1
Has abstractyes

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