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Optical information storage, in virtue of its large capacity, high stability, and long longevity, holds promising prospects in mass storage, while being limited by the trade‐off between readout quality and error rate. The emerging intersection of optical storage and deep learning presents a valuable opportunity to achieve high‐fidelity data storage. Here, a novel paradigm of error‐free long‐lifespan optical storage enhanced is proposed by deep learning, harnessing neural network to extract optical information from birefringence measurements. It is demonstrated that using neural networks outperforms traditional approaches in terms of efficiency and accuracy. Moreover, by adding extra birefringence information as input to the neural network, nearly 100%$100\%$ accuracy is achieved on an established five‐bit dataset. Remarkably, even under extremely severe ambiguity, the paradigm still fulfills error‐free readout and maintains a long lifespan. The experimental storage scheme is significantly conducive to the development of large‐scale error‐free storage, and paves the way for robust optical storage with environmental and temporal tolerance in practical scenarios. [ABSTRACT FROM AUTHOR]

One new and three known triterpenoid saponins were isolated and identified from Camellia oleifera seeds through IR, NMR, HR-ESI-MS and GC-MS spectroscopic methods, namely oleiferasaponin A3, oleiferasaponin A1, camelliasaponin B1, and camelliasaponin B2. The structure of oleiferasaponin A3 was elucidated as 16α-hydroxy-21β-O-angeloyl-22α-O-cinnamoyl-23α-aldehyde-28-dihydroxymethylene-olean-12-ene-3β-O-[β-D-galactopyranosyl-(1!2)]-[β-D-xylopyranosyl-(1!2)-β-D-galactopyranosyl-(1→3)]-β-D-gluco-pyranosiduronic acid. Camelliasaponin B1 and camelliasaponin B2 exhibited potent cytotoxic activity on three human tumour cell lines (human lung tumour cells (A549), human liver tumour cells (HepG2), cervical tumour cells (Hela)). The hypoglycemic activity of oleiferasaponin A1 was testified by protecting pancreatic β-cell lines from high-glucose damage. [ABSTRACT FROM AUTHOR]

Candida albicans and Cryptococcus neoformans, worldwide human pathogenic fungi, are receiving increasing attention due to the high morbidity and mortality in immunocompromised patients. In the present work, 110 fungus pairs were constructed by co-culturing 16 wood-decaying basidiomycetes, among which the co-culture of Trametes robiniophila Murr and Pleurotus ostreatus was identified to strongly inhibit pathogenic fungi through bioactivity-guided assays. A combination of metabolomics and molecular network analysis discovered that 44 features were either newly synthesized or highly produced in this co-culture system, six of which belonged to a family of novel and unusual linear sesterterpenes contributed to high activity with minimum inhibitory concentrations of 1 to 32 µg/mL against pathogenic fungi. Furthermore, dynamic 13C-labeling analysis revealed an association between induced features and corresponding fungus. Unusual sesterterpenes were 13C-labeled only in P. ostreatus in a time course after stimulation by the co-culture, suggesting that these sesterterpenes were synthesized by P. ostreatus instead of T. robiniophila Murr. Sesterterpenes 1 to 3 were renamed as postrediene A-C. qRT-PCR analysis revealed that transcriptional levels of three genes encoding for terpene synthase, farnesyl-diphosphate farnesyltransferase and oxidase were identified respectively to be 8.2, 88.7 and 21.6-fold higher in the co-culture than that in the mono-culture, indicating that biosynthetic gene cluster 10 was most likely responsible for the synthesis of these sesterterpenes. A putative biosynthetic pathway of postrediene A-C was then proposed based on structures of sesterterpenes and molecular network analysis. [ABSTRACT FROM AUTHOR]