Stratification strength and light climate explain variation in chlorophyll a at the continental scale in a European multilake survey in a heatwave summer

To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L−1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4°C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature

Accelerated syntheses of amine-bis(phenol) ligands in polyethylene glycol or “on water” under microwave irradiation

Pure amine-bis(phenol) ligands are readily accessible in high yield, often >90%, when the Mannich condensation reactions are performed “on water” or in poly(ethyleneglycol) (PEG). Microwave-assisted synthesis dramatically reduces the time and energy required to prepare these molecules, typically from 24 h to 5 min. The approach seems to be widely applicable (7 amines and 5 phenols were tested to yield a diverse set of bis(phenol) ligands). Significant improvements in yield were observed for ligands derived from di-tert-amyl and di-tert-butyl phenols, possibly resulting from a hydrophobic effect. Single crystal X-ray diffraction data for the ligand derived from p-cresol and N,N′-dimethylethylenediamine is reported

Alien plant invasion hotspots and invasion debt in European woodlands

[Questions] European woodlands harbor at least 386 alien plant species but the factors driving local invasions remain unknown. By using a large vegetation-plot database, we asked how local richness and abundance of alien species vary by regions, elevation, climate, soil properties, human disturbance, and habitat types.[Location] Western, central and southern Europe.[Methods] We linked consolidated data from the European Vegetation Archive (16,211 plots) to a habitat classification scheme, climate, soil properties and human disturbance variables. In addition, we used 250 km × 250 km regional grid cells to test whether local patterns differ among regions. We used generalized additive models (GAMs) and quantile GAMs to explore how relative alien species richness and the sum of alien species covers per plot relate to predictors. Random Forest analyses (RFs) were employed to assess the importance of individual predictors that were not multicollinear.[Results] Relative alien species richness and the sum of alien species covers varied across regions and habitat types, with effects being more pronounced at the maximum rather than average responses. Both response variables declined with increasing elevation and distance to the nearest road or railroad and increased with the amount of sealed soil. Maxima in fitted functions matched plots from regional invasion hotspots in northwestern and central Europe. RFs accounted for 39.6% and 20.9% of the total variation in relative alien species richness and the sum of alien species covers, respectively, with region and habitat being the most important variables.[Conclusions] The importance of maximum response quantiles and the prevalence of regional hotspots point to invasion debt in European woodlands. As alien plants expand further, their species richness and abundance in woodlands will be likely driven by the shared effects of the introduction and planting history, differences in the invaded habitat types, and dispersal corridors.VW initiated this study as a part of the InvasEVe project financed by the SoMoPro II program and considers it as part of her Discovery Grant from the Canadian Natural Science and Engineering Research Council. VW's research leading to these results has acquired a financial grant from the People Program (Marie Curie Action) of the Seventh Framework Program of the EU according to REA Grant Agreement No. 291782, and it was further co-financed by the South-Moravian Region. MV and MC were supported by the Czech Science Foundation (19-28491X). PP and JP were supported by the Czech Science Foundation (19-28807X) and the Czech Academy of Sciences (RVO 67985939). JCS considers this work a contribution to his VILLUM Investigator project “Biodiversity Dynamics in a Changing World” funded by VILLUM FONDEN (grant 16549). IB and JAC were funded by the Basque Government (IT936-16). FFG was funded by the Plan Propio of the UCLM (2020-GRIN-29214)Peer reviewe

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.Therapeutic cell differentiatio