A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer

Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR) to neoadjuvant chemotherapy(NAC). Here, we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS) in 755 HRpositive breast cancer patients(273, 265, and 217 in the training, internal, and external validation sets, respectively). This model,pres...     

Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3‐PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960–2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha^?1 year^?1 km^?1 for P. abies and 0.93 ± 0.010 Mg C ha^?1 year^?1 km^?1 for F. sylvatica). During warm–dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm‐dry extremes. Importantly, cold–dry extremes had negative impacts on regional forest NPP comparable to warm–dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.     

A quantitative trait locus involved in maize yield is tightly associated to the r1 gene on the long arm of chromosome 10

We produced and studied for 3?years two synthetic populations of maize differing in their constitution only for the selected alleles present at the red color 1 (r1) locus (R-sc vs. r?Cr). r1 is a regulatory gene conferring anthocyanin pigmentation in different tissues: the R-sc allele confers pigmentation only in the aleurone seed layer, while the r?Cr allele confers pigmentation in several tissues such as root, silk and anther but the seed is colourless. The colourless population (r?Cr/r?Cr) was characterized by improved agronomic features, such as ear weight and plant height, compared with the R-sc/R-sc coloured population. This finding was confirmed by studying single F4 R/r families where the presence of the r?Cr allele conferred positive features, acting as a dominant trait. Quantitative trait locus (QTL) analysis performed using molecular markers on the long arm of chromosome 10 (bin 10.06), where the r1 gene maps, identified a QTL map position for plant height tightly associated to the r1 gene. Thus the r1 gene may represent a major QTL or it could be closely linked to another gene involved in the agronomic performance of the two populations studied.     

Reverse engineering and analysis of genome-wide gene regulatory networks from gene expression profiles using high-performance computing

Regulation of gene expression is a carefully regulated phenomenon in the cell. “Reverse-engineering” algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). Mammalian cells express tens of thousands of genes; hence, hundreds of gene expression profiles are necessary in order to have acceptable statistical evidence of interactions between genes. As the number of profiles to be analyzed increases, so do computational costs and memory requirements. In this work, we designed and developed a parallel computing algorithm to reverse-engineer genome-scale gene regulatory networks from thousands of gene expression profiles. The algorithm is based on computing pairwise Mutual Information between each gene-pair. We successfully tested it to reverse engineer the Mus Musculus (mouse) gene regulatory network in liver from gene expression profiles collected from a public repository. A parallel hierarchical clustering algorithm was implemented to discover “communities” within the gene network. Network communities are enriched for genes involved in the same biological functions. The inferred network was used to identify two mitochondrial proteins.     

Oscillations in the prefrontal cortex: a gateway to memory and attention

We consider the potential role of oscillations in the prefrontal cortex (PFC) in mediating attention, working memory and memory consolidation. Activity in the theta, beta, and gamma bands is related to communication between PFC and different brain areas. While gamma/beta oscillations mediate bottom-up and top-down interactions between PFC and visual cortices, related to attention, theta rhythms are engaged by hippocampal/PFC interplay. These interactions are dynamic, depending on the nature and relevance of the information currently being processed. The profound modifications of the PFC neuronal network associated with changes in oscillatory coherence are controlled by neuromodulators such as dopamine, which thereby allow or prevent the formation of cell assemblies for information encoding and storage.     

Conserving the functional and phylogenetic trees of life of European tetrapods

Protected areas (PAs) are pivotal tools for biodiversity conservation on the Earth. Europe has had an extensive protection system since Natura 2000 areas were created in parallel with traditional parks and reserves. However, the extent to which this system covers not only taxonomic diversity but also other biodiversity facets, such as evolutionary history and functional diversity, has never been evaluated. Using high-resolution distribution data of all European tetrapods together with dated molecular phylogenies and detailed trait information, we first tested whether the existing European protection system effectively covers all species and in particular, those with the highest evolutionary or functional distinctiveness. We then tested the ability of PAs to protect the entire tetrapod phylogenetic and functional trees of life by mapping species'' target achievements along the internal branches of these two trees. We found that the current system is adequately representative in terms of the evolutionary history of amphibians while it fails for the rest. However, the most functionally distinct species were better represented than they would be under random conservation efforts. These results imply better protection of the tetrapod functional tree of life, which could help to ensure long-term functioning of the ecosystem, potentially at the expense of conserving evolutionary history.     

Adapting Stand‐Alone Renewable Energy Technologies for the Circular Economy through Eco‐Design and Recycling

Renewable energy (RE) technologies are looked upon favorably to provide for future energy demands and reduce greenhouse gas (GHG) emissions. However, the installation of these technologies requires large quantities of finite material resources. We apply life cycle assessment to 100 years of electricity generation from three stand‐alone RE technologies—solar photovoltaics, run‐of‐river hydro, and wind—to evaluate environmental burden profiles against baseline electricity generation from fossil fuels. We then devised scenarios to incorporate circular economy (CE) improvements targeting hotspots in systems’ life cycle, specifically (1) improved recycling rates for raw materials and (ii) the application of eco‐design. Hydro presented the lowest environmental burdens per kilowatt‐hour of electricity generation compared with other RE technologies, owing to its higher efficiency and longer life spans for main components. Distinct results were observed in the environmental performance of each system based on the consideration of improved recycling rates and eco‐design. CE measures produced similar modest savings in already low GHG emissions burdens for each technology, while eco‐design specifically had the potential to provide significant savings in abiotic resource depletion. Further research to explore the full potential of CE measures for RE technologies will curtail the resource intensity of RE technologies required to mitigate climate change.     

Deregulation of signalling pathways in prognostic subtypes of hepatocellular carcinoma: Novel insights from interspecies comparison

Hepatocellular carcinoma is a frequent and fatal disease. Recent researches on rodent models and human hepatocarcinogenesis contributed to unravel the molecular mechanisms of hepatocellular carcinoma dedifferentiation and progression, and allowed the discovery of several alterations underlying the deregulation of cell cycle and signalling pathways. This review provides an interpretive analysis of the results of these studies. Mounting evidence emphasises the role of up-regulation of RAS/ERK, PI3K/AKT, IKK/NF-kB, WNT, TGF-β, NOTCH, Hedgehog, and Hippo signalling pathways as well as of aberrant proteasomal activity in hepatocarcinogenesis. Signalling deregulation often occurs in preneoplastic stages of rodent and human hepatocarcinogenesis and progressively increases in carcinomas, being most pronounced in more aggressive tumours. Numerous changes in signalling cascades are involved in the deregulation of carbohydrate, lipid, and methionine metabolism, which play a role in the maintenance of the transformed phenotype. Recent studies on the role of microRNAs in signalling deregulation, and on the interplay between signalling pathways led to crucial achievements in the knowledge of the network of signalling cascades, essential for the development of adjuvant therapies of liver cancer. Furthermore, the analysis of the mechanisms involved in signalling deregulation allowed the identification of numerous putative prognostic markers and novel therapeutic targets of specific hepatocellular carcinoma subtypes associated with different biologic and clinical features. This is of prime importance for the selection of patient subgroups that are most likely to obtain clinical benefit and, hence, for successful development of targeted therapies for liver cancer.