OrthoDB v11: annotation of orthologs in the widest sampling of organismal diversity.

OrthoDB provides evolutionary and functional annotations of genes in a diverse sampling of eukaryotes, prokaryotes, and viruses. Genomics continues to accelerate our exploration of gene diversity and orthology is the most precise way of bridging gene functional knowledge with the rapidly expanding universe of genomic sequences. OrthoDB samples the most diverse organisms with the best quality genomics data to provide the leading coverage of species diversity. This update of the underlying data to over 18 000 prokaryotes and almost 2000 eukaryotes with over 100 million genes propels the coverage to another level. This achievement also demonstrates the scalability of the underlying OrthoLoger software for delineation of orthologs, freely available from https://orthologer.ezlab.org. In addition to the ab-initio computations of gene orthology used for the OrthoDB release, the OrthoLoger software allows mapping of novel gene sets to precomputed orthologs and thereby links to their annotations. The LEMMI-style benchmarking of OrthoLoger ensures its state-of-the-art performance and is available from https://lemortho.ezlab.org. The OrthoDB web interface has been further developed to include a pairwise orthology view from any gene to any other sampled species. OrthoDB-computed evolutionary annotations as well as extensively collated functional annotations can be accessed via REST API or SPARQL/RDF, downloaded or browsed online from https://www.orthodb.org.

An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study.

AIMS/HYPOTHESIS: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value. METHODS: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA1c, HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic. RESULTS: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA1c) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance. CONCLUSIONS/INTERPRETATION: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification. DATA AVAILABILITY: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch .

Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials.

AIMS/HYPOTHESIS: The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events. METHODS: Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed. RESULTS: For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period. CONCLUSIONS/INTERPRETATION: Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.

Anti-cancer activity of ultra-short single-stranded polydeoxyribonucleotides.

One of the features that differentiate cancer cells is their increased proliferation rate, which creates an opportunity for general anti-tumor therapy directed against the elevated activity of replicative apparatus in tumor cells. Besides DNA synthesis, successful genome replication requires the reparation of the newly synthesized DNA. Malfunctions in reparation can cause fatal injuries in the genome and cell death. Recently we have found that the ultra-short single-stranded deoxyribose polynucleotides of random sequence (ssDNA) effectively inhibit the catalytic activity of DNA polymerase [Formula: see text]. This effect allowed considering these substances as potential anti-tumor drugs, which was confirmed experimentally both in vitro (using cancer cell cultures) and in vivo (using cancer models in mice). According to the obtained results, ssDNA significantly suppresses cancer development and tumor growth, allowing consideration of them as novel candidates for anti-cancer drugs.

Triggering gel-sol transition by weak magnetic field.

The self-assembly of small and always chiral molecules into fiber-like structures is a mysterious process, as the physics underlying such self-assembly is unclear. The energy necessary for this process exceeds the one provided by common dispersion interactions and hydrogen bonding. The recent results obtained by the scientific group of Prof. Naaman from the Weizmann Institute of Science fed light on the nature of forces providing for the self-assembly of chiral molecules and attributed these forces to spin-exchange interactions. Therefore, the self-assembly of chiral molecules should be magneto-sensitive. We found such sensitivity in solutions of trifluoroacetylated α -amino alcohols, and the process was inhibited by the magnetic field when fibers grew on the surface of the substrate. On the contrary, in bulk, the self-assembly was enhanced by the magnetic field and led to the formation of a dense gel, while no gelation was observed in the absence of the external magnetic field. The latter observations are the theme of this short report, aimed to declare the effect itself but not pretend to describe it in full.

OrthoDB in 2020: evolutionary and functional annotations of orthologs.

OrthoDB provides evolutionary and functional annotations of orthologs, inferred for a vast number of available organisms. OrthoDB is leading in the coverage and genomic diversity sampling of Eukaryotes, Prokaryotes and Viruses, and the sampling of Bacteria is further set to increase three-fold. The user interface has been enhanced in response to the massive growth in data. OrthoDB provides three views on the data: (i) a list of orthologous groups related to a user query, which are now arranged to visualize their hierarchical relations, (ii) a detailed view of an orthologous group, now featuring a Sankey diagram to facilitate navigation between the levels of orthology, from more finely-resolved to more general groups of orthologs, as well as an arrangement of orthologs into an interactive organism taxonomy structure, and (iii) we added a gene-centric view, showing the gene functional annotations and the pair-wise orthologs in example species. The OrthoDB standalone software for delineation of orthologs, Orthologer, is freely available. Online BUSCO assessments and mapping to OrthoDB of user-uploaded data enable interactive exploration of related annotations and generation of comparative charts. OrthoDB strives to predict orthologs from the broadest coverage of species, as well as to extensively collate available functional annotations, and to compute evolutionary annotations such as evolutionary rate and phyletic profile. OrthoDB data can be assessed via SPARQL RDF, REST API, downloaded or browsed online from https://orthodb.org.

Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study.

AIMS/HYPOTHESIS: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. METHODS: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort's cluster centres. Finally, we compared the time to insulin requirement for each cluster. RESULTS: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6-90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression. CONCLUSIONS/INTERPRETATION: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration.

Incorporating heterogeneous sampling probabilities in continuous phylogeographic inference - Application to H5N1 spread in the Mekong region.

MOTIVATION: The potentially low precision associated with the geographic origin of sampled sequences represents an important limitation for spatially explicit (i.e. continuous) phylogeographic inference of fast-evolving pathogens such as RNA viruses. A substantial proportion of publicly available sequences is geo-referenced at broad spatial scale such as the administrative unit of origin, rather than more precise locations (e.g. geographic coordinates). Most frequently, such sequences are either discarded prior to continuous phylogeographic inference or arbitrarily assigned to the geographic coordinates of the centroid of their administrative area of origin for lack of a better alternative. RESULTS: We here implement and describe a new approach that allows to incorporate heterogeneous prior sampling probabilities over a geographic area. External data, such as outbreak locations, are used to specify these prior sampling probabilities over a collection of sub-polygons. We apply this new method to the analysis of highly pathogenic avian influenza H5N1 clade data in the Mekong region. Our method allows to properly include, in continuous phylogeographic analyses, H5N1 sequences that are only associated with large administrative areas of origin and assign them with more accurate locations. Finally, we use continuous phylogeographic reconstructions to analyse the dispersal dynamics of different H5N1 clades and investigate the impact of environmental factors on lineage dispersal velocities. AVAILABILITY AND IMPLEMENTATION: Our new method allowing heterogeneous sampling priors for continuous phylogeographic inference is implemented in the open-source multi-platform software package BEAST 1.10. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs.

OrthoDB (https://www.orthodb.org) provides evolutionary and functional annotations of orthologs. This update features a major scaling up of the resource coverage, sampling the genomic diversity of 1271 eukaryotes, 6013 prokaryotes and 6488 viruses. These include putative orthologs among 448 metazoan, 117 plant, 549 fungal, 148 protist, 5609 bacterial, and 404 archaeal genomes, picking up the best sequenced and annotated representatives for each species or operational taxonomic unit. OrthoDB relies on a concept of hierarchy of levels-of-orthology to enable more finely resolved gene orthologies for more closely related species. Since orthologs are the most likely candidates to retain functions of their ancestor gene, OrthoDB is aimed at narrowing down hypotheses about gene functions and enabling comparative evolutionary studies. Optional registered-user sessions allow on-line BUSCO assessments of gene set completeness and mapping of the uploaded data to OrthoDB to enable further interactive exploration of related annotations and generation of comparative charts. The accelerating expansion of genomics data continues to add valuable information, and OrthoDB strives to provide orthologs from the broadest coverage of species, as well as to extensively collate available functional annotations and to compute evolutionary annotations. The data can be browsed online, downloaded or assessed via REST API or SPARQL RDF compatible with both UniProt and Ensembl.

Precise control of the size and gap between gold nanocubes by surface-based synthesis for high SERS performance.

The optical properties of a monolayer of nanocomposite film (PMMA/gold nanocubes) were provided by fitting a proposed theoretical model to spectroscopic ellipsometry (SE) measurements. For such a thin film, these features cannot be successfully determined by means of experimental and conventional effective medium theory such as Maxwell-Garnett or Bruggeman. To make it possible, we developed a model of two classical Lorentz oscillators; one for a PMMA layer and the other for GNCs, revealing one homogeneous layer and rapid analysis without the need for large computational resources. Additionally, we tailored both the size and number of GNCs in the PMMA layer by tuning the synthesis parameters as seen in scanning electron microscopy (SEM) images. In parallel, SE measurements clearly highlighted the change in the optical properties of GNCs as a function of their density on the substrate and dimensions. Our findings demonstrate that SE is an alternative method to characterize layered GNCs on opaque substrates efficiently, which has potential implications for designing other morphologies in the future.

Nuclear spin selectivity in enzymatic catalysis: A caution for applied biophysics.

Nuclear magnetic ions 25Mg2+, 43Ca2+, and 67Zn2+ suppress DNA synthesis by 3-5 times with respect to ions with nonmagnetic nuclei. This observation unambiguously evidences that the DNA synthesis occurs by radical pair mechanism, which is well known in chemistry and implies pairwise generation of radicals by electron transfer between reaction partners. This mechanism coexists with generally accepted nucleophilic one; it is switched on, when at least two ions enter into the catalytic site. It is induced by both sorts of ions, magnetic and nonmagnetic but it functions by 3-5 times more efficiently with magnetic ions stimulating radical pair mechanism. Decreasing catalytic activity of polymerases by 3-5 times, nuclear magnetic ions 25Mg2+, 43Ca2+, and 67Zn2+ even more strongly, by 30-50 times, increase mortality of cancer cells. The two reasons of this unique phenomenon are suggested: first, the high concentration of nuclear magnetic ions delivered by specific nano-container into the cancer cells, and, second, generation of short DNA fragments by polymerases loaded with nuclear magnetic ions, which is known to activate protein p53, efficiently stimulating apoptosis of cancer cells.

OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs.

OrthoDB is a comprehensive catalog of orthologs, genes inherited by extant species from a single gene in their last common ancestor. In 2016 OrthoDB reached its 9th release, growing to over 22 million genes from over 5000 species, now adding plants, archaea and viruses. In this update we focused on usability of this fast-growing wealth of data: updating the user and programmatic interfaces to browse and query the data, and further enhancing the already extensive integration of available gene functional annotations. Collating functional annotations from over 100 resources, and enabled us to propose descriptive titles for 87% of ortholog groups. Additionally, OrthoDB continues to provide computed evolutionary annotations and to allow user queries by sequence homology. The OrthoDB resource now enables users to generate publication-quality comparative genomics charts, as well as to upload, analyze and interactively explore their own private data. OrthoDB is available from http://orthodb.org.

The role of zinc and its compounds in leukemia.

Zinc is one of the most important microelements necessary for normal body functioning. Zinc is marked in numerous diseases and, hence, its properties and behavior in the body have long been a subject of extensive study. This review considers trends in the assessment of the role of zinc and its compounds in the past decade. It becomes evident that redox-inactive zinc is the main supervisor in the conformation of the most important molecules in all body organs and tissues. We placed emphasis on the variety of zinc-binding sites and the role of zinc in the genesis and progress of different forms of leukemia. The importance of some families of transcription factors in the development and prognosis of treatment of various leukemia forms is examined; new directions of these studies are shown.

Addressing the Challenges of Structure Elucidation in Natural Products Possessing the Oxirane Moiety.

NMR data for natural products containing the epoxy moiety have been revisited and reanalyzed with the help of a recently developed parametric/DFT hybrid computational method, DU8+. More than 20 structures needed revision, which points to challenges in NMR solution structure assignment for molecules possessing this structural feature. Among the revised structures are achicretin 2, acremine P, aromaticane I, artanomalide B, botryosphaerihydrofuran, chloroklotzchin, crithmifolide, crotodichogamoin A, emervaridone C, 9α,15-epoxyafricanane, fischambiguine B, grandilobalide B, guaianolide A, guatterfriesols A and B, juncenolide G, roscotane D, secoafricane 7, taccalonolides AJ and AF, and related compounds.

Step-Economical Photoassisted Diversity-Oriented Synthesis: Sustaining Cascade Photoreactions in Oxalyl Anilides to Access Complex Polyheterocyclic Molecular Architectures.

Atom- and step-economy in photoassisted diversity-oriented synthesis (DOS) is achieved with a versatile oxalyl linker offering rapid access to complex alkaloid mimics in very few experimentally simple steps: (i) it allows for fast tethering of the photoactive core to the unsaturated pendants, especially important in the case of (hetero)aromatic amines-essentially a one-pot reaction with no isolation of intermediates; (ii) the α-dicarbonyl tether acts as a chromophore enhancer, extending the conjugation chain and facilitating the "harvest" of the lower energy photons for the primary and secondary photoreactions; (iii) it enhances the quantum yield of intersystem crossing (ISC), i.e., it is capable of sensitizing secondary photochemical processes in the cascade; and (iv) the tether forms an additional heterocyclic moiety, imidazolidine-4,5-dione, a known pharmacophore. The overall photoassisted cascade is an efficient complexity-building process as quantified by computed step-normalized complexity indices, leading to extended polyheterocyclic molecular architectures comparable in complexity to natural products such as paclitaxel while requiring only 2-4 simple synthetic steps from readily available chemical feedstock.

Wnt directs the endosomal flux of LDL-derived cholesterol and lipid droplet homeostasis.

The Wnt pathway, which controls crucial steps of the development and differentiation programs, has been proposed to influence lipid storage and homeostasis. In this paper, using an unbiased strategy based on high-content genome-wide RNAi screens that monitored lipid distribution and amounts, we find that Wnt3a regulates cellular cholesterol. We show that Wnt3a stimulates the production of lipid droplets and that this stimulation strictly depends on endocytosed, LDL-derived cholesterol and on functional early and late endosomes. We also show that Wnt signaling itself controls cholesterol endocytosis and flux along the endosomal pathway, which in turn modulates cellular lipid homeostasis. These results underscore the importance of endosome functions for LD formation and reveal a previously unknown regulatory mechanism of the cellular programs controlling lipid storage and endosome transport under the control of Wnt signaling.

Triquinanes and Related Sesquiterpenes Revisited Computationally: Structure Corrections of Hirsutanols B and D, Hirsutenol E, Cucumin B, Antrodins C-E, Chondroterpenes A and H, Chondrosterins C and E, Dichrocephone A, and Pethybrene.

NMR data for 90+ natural sesquiterpenes possessing triquinane cores were examined with the help of a relatively fast parametric/DFT hybrid computational method, DU8+. Thirteen of these compounds, i.e., approximately 14% of the sample, required structure correction. This rate of misassignment is similar to the percentage of misassigned halogenated sesquiterpenes reported previously.

Retinoblastoma: Magnetic Isotope Effects Might Make a Difference in the Current Anti-Cancer Research Strategy.

Human retinoblastoma cells were proven to possess some very unusual DNApolß species. Being 23.5 kDa monomers, which itself is not common for the DNApolß superfamily members, these chromatin associated proteins manifests most of the DNApolß-specifc functional peculiarities making them legitimate targets for DNA repair cytostatic inhibitors. Particularly, these tumor specific enzymes were found to be very sensitive to 25Mg2+-, 43Ca2+- and 67Zn2+-promoted magnetic isotope effects (MIE) caused a marked DNA sequence growth limitation as well as a formation of the size-invalid, i.e. too short in length, DNA fragments, totally inappropriate for the DNA repair purpose. This MIE-DNApolß match may serve a starting point for further move towards the paramagnetic path in current developments of anti-cancer strategies.

The SwissLipids knowledgebase for lipid biology.

MOTIVATION: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. RESULTS: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology-SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. AVAILABILITY: SwissLipids is freely available at http://www.swisslipids.org/. CONTACT: alan.bridge@isb-sib.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Photoassisted Synthesis of Complex Molecular Architectures: Dearomatization of Benzenoid Arenes with Aza-o-xylylenes via an Unprecedented [2+4] Reaction Topology.

A new method was developed for the photoinduced dearomatization of arenes through an intramolecular cycloaddition with aza-o-xylylenes generated by excited-state intramolecular proton transfer (ESIPT) in the readily available photoprecursors. The [2+4] topology of this cycloaddition is unprecedented for photo-dearomatizations of benzenoid aromatic carbocycles. It provides rapid access to novel heterocycles, cyclohexadieno-oxazolidino-quinolinols, as valuable synthons for a broad range of post-photochemical transformations.