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SUMMARY PARAGRAPH Fanconi anemia (FA) is a monogenic inherited disease associated with mutations in genes that encode for proteins participating in the FA/BRCA DNA repair pathway. Mutations in FA genes result in chromosomal instability and cell death, leading to cancer risks and progressive cell mortality, most notably in hematopoietic stem and progenitor cells (HSPC). Recently, we showed the first clinical evidence that gene therapy confers engraftment and proliferative advantage of gene-corrected HSPCs in FA patients1. Despite this and many other gene therapy advances, the question of whether the molecular pathways affected in monogenic diseases can be reverted by lentiviral-mediated gene therapy has never been addressed. This is even more challenging in DNA repair syndromes such as FA since in these cases, transcriptional defects in affected cells might not be restored due to DNA damage accumulated prior to gene therapy. Using single-cell RNA sequencing in HSPCs from FA-A patients previously treated by ex vivo gene therapy, we demonstrate that lentiviral-mediated gene therapy prior to severe bone marrow failure not only restores the expression of the defective gene, but also induces a long-term correction of the transcriptional program in FA HSPCs, which then acquire a signature characteristic of healthy HSPCs. Our results reveal new molecular evidence showing the potential of gene therapy to fully rescue phenotypic defects in FA, a devastating HSPC disease characterized by defective DNA repair.

Raindrop impact exerts a force on the leaf resulting in a decaying oscillation of the leaf inclination angle. Nondestructive measurements of leaf oscillations is important for predicting changes in leaf angles in the field based on morphometric properties of leaves. The objectives of this study were to determine if a second order impulse response could describe experimentally observed changes in leaf inclination angle, to determine if field measurable, nondestructive leaf traits significantly correlate with model parameters, and to determine if the model parameters were species-specific. This study examined leaf oscillations for three common species in Colorado, USA (Acer saccharinum, Quercus gambelii, and Ulmus pumila) due to two different raindrop sizes. The drop impact was created by releasing a single drop of known size from a known height. The resulting leaf motion was recorded using a high-speed video camera. The images were then processed to measure the leaf inclination angle as a function of time, and a model was used to fit the data. The model was evaluated for quality of fit to the data. The experimental data closely fit the modeled data, indicating that the impulse response appropriately predicts leaf oscillations after raindrop impact. Strong linear relationships existed between leaf mass and maximum change in leaf inclination angle after drop impact for both the experimental and the modeled data. The model parameters were also found to be species-specific. The oscillations in leaf inclination angle are accurately described with a second order impulse response. The parameters of the impulse response correlate with field measurable leaf traits and the parameters are species-specific. The data and approach in this study provided a nondestructive tool for the prediction of changes in leaf inclination angle for many broad-leaved species with diverse leaf morphometric properties.

The wide spread of projected temperature changes in climate projections does not predominately originate from uncertainty across climate models; instead it is the broad range of different global socio-economic scenarios and the implied energy production that results in high uncertainty about future climate change. It is therefore important to assess the observational tracking of these scenarios. Here we compare these socio-economic scenarios created in both 1992 and 2000 against the recent observational record to investigate the coupling of economic growth and fossil-fuel CO2 emissions. We find that global emission intensity (fossil fuel CO2 emissions per GDP) rose in the first part of the 21st century despite all major climate projections foreseeing a decline. Proposing a method to disaggregate differences between scenarios and observations in global growth rates to country-by-country contributions, we find that the relative discrepancy was driven by unanticipated GDP growth in Asia and Eastern Europe, in particular in Russia and China. The growth of emission intensity over the 2000s highlights the relevance of unforeseen local shifts in projections on a global scale., Highlights • The wide range of socio-economic scenarios in climate projections results in high uncertainty about climate change. • We compare socio-economic scenario projections to observations over 1990–2010. • Global CO2 emission intensity increased despite all major scenarios projecting a decline. • Under-projection of emission intensity raises concerns about achieving emission targets.