Targeting TRAIL

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), also known as Apo2L, has been investigated in the past decade for its promising anticancer activity due to its ability to selectively induce apoptosis in tumoral cells by binding to TRAIL receptors (TRAIL-R). Macromolecules such as agonistic monoclonal antibodies and recombinant TRAIL have not proven efficacious in clinical studies, therefore several small molecules acting as TRAIL-R agonists are emerging in the scientific literature. In this work we focus on systemizing these drug molecules described in the past years, in order to better understand and predict the requirements for a novel anti-tumoral therapy based on the TRAIL-R-induced apoptotic mechanism.     

A gene for resistance to the Varroa mite (Acari) in honey bee (Apis mellifera) pupae

Social insect colonies possess a range of defences which protect them against highly virulent parasites and colony collapse. The host–parasite interaction between honey bees (Apis mellifera) and the mite Varroa destructor is unusual, as honey bee colonies are relatively poorly defended against this parasite. The interaction has existed since the mid‐20th Century, when Varroa switched host to parasitize A. mellifera. The combination of a virulent parasite and relatively naïve host means that, without acaricides, honey bee colonies typically die within 3 years of Varroa infestation. A consequence of acaricide use has been a reduced selective pressure for the evolution of Varroa resistance in honey bee colonies. However, in the past 20 years, several natural‐selection‐based breeding programmes have resulted in the evolution of Varroa‐resistant populations. In these populations, the inhibition of Varroa's reproduction is a common trait. Using a high‐density genome‐wide association analysis in a Varroa‐resistant honey bee population, we identify an ecdysone‐induced gene significantly linked to resistance. Ecdysone both initiates metamorphosis in insects and reproduction in Varroa. Previously, using a less dense genetic map and a quantitative trait loci analysis, we have identified Ecdysone‐related genes at resistance loci in an independently evolved resistant population. Varroa cannot biosynthesize ecdysone but can acquire it from its diet. Using qPCR, we are able to link the expression of ecdysone‐linked resistance genes to Varroa's meals and reproduction. If Varroa co‐opts pupal compounds to initiate and time its own reproduction, mutations in the host's ecdysone pathway may represent a key selection tool for honey bee resistance and breeding.     

<Emphasis Type="Italic">Steinmanniporella,</Emphasis> a new dasycladale genus name for “<Emphasis Type="Italic">Linoporella</Emphasis>” with two orders of laterals

After Barattolo (Abstracts of the 5th international symposium on fossil algae, 1991) and Barattolo and Romano (Bollettino della Societa Paleontologica Italiana, 44(3): 237–254, 2005) emended the diagnosis of the genus Linoporella Steinmann to include species with three orders of laterals, algae included formerly in this genus but with only two orders of laterals remained in open nomenclature. Comparisons of these algae with other Jurassic and Cretaceous dasycladaleans with two orders of laterals resulted in the introduction of the new genus Steinmanniporella.     

Computational modeling of epithelial–mesenchymal transformations

An epithelial–mesenchymal transformation (EMT) involves alterations in cell–cell and cell–matrix adhesion, the detachment of epithelial cells from their neighbors, the degradation of the basal lamina and acquisition of mesenchymal phenotype. Here we present Monte Carlo simulations for a specific EMT in early heart development: the formation of cardiac cushions. Cell rearrangements are described in accordance with Steinberg's differential adhesion hypothesis, which states that cells possess a type-dependent adhesion apparatus and are sufficiently motile to give rise to the tissue conformation with the largest number of strong bonds. We also implement epithelial and mesenchymal cell proliferation, cell type change and extracellular matrix production by mesenchymal cells. Our results show that an EMT is promoted more efficiently by an increase in cell–substrate adhesion than by a decrease in cell–cell adhesion. In addition to cushion tissue formation, the model also accounts for the phenomena of matrix invasion and mesenchymal condensation. We conclude that in order to maintain epithelial integrity during EMT the number of epithelial cells must increase at a controlled rate. Our model predictions are in qualitative agreement with available experimental data.     

The 2DX robot: A membrane protein 2D crystallization Swiss Army knife

Among the state-of-the-art techniques that provide experimental information at atomic scale for membrane proteins, electron crystallography, atomic force microscopy and solid state NMR make use of two-dimensional crystals. We present a cyclodextrin-driven method for detergent removal implemented in a fully automated robot. The kinetics of the reconstitution processes is precisely controlled, because the detergent complexation by cyclodextrin is of stoichiometric nature. The method requires smaller volumes and lower protein concentrations than established 2D crystallization methods, making it possible to explore more conditions with the same amount of protein. The method yielded highly ordered 2D crystals diffracting to high resolution from the pore-forming toxin Aeromonas hydrophila aerolysin (2.9 Å), the plant aquaporin SoPIP2;1 (3.1 Å) and the human aquaporin-8 (hAQP8; 3.3 Å). This new method outperforms traditional 2D crystallization approaches in terms of accuracy, flexibility, throughput, and allows the usage of detergents having low critical micelle concentration (CMC), which stabilize the structure of membrane proteins in solution.     

<Emphasis Type="Italic">Salpingoporella</Emphasis>? <Emphasis Type="Italic">popgrigorei</Emphasis>, a new species of Dasycladales (calcareous algae) from the Lower Aptian deposits of Pădurea Craiului (northern Apuseni Mountains,Romania)

A new dasycladalean alga Salpingoporella? popgrigorei n. sp. was identified in P?durea Craiului Mountains (northern Apuseni, Romania) in the Lower Aptian limestone of the Valea Bobdei Member. The new alga was found within the external platform coarse bioclastic facies with fragments of corals, sclerosponges, bivalves (including rudists), gastropods, echinoderms, brachiopods, and bryozoans. The micropaleontological assemblage consists of foraminifera, calcareous algae, rare rivulariacean-type cyanobacteria, and some problematic microfossils. The deposits are Early Bedoulian in age, as clearly indicated by the orbitolinid foraminifera Orbitolinopsis pygmaea, Paracoskinolina sunnilandensis and Palorbitolina lenticularis. Salpingoporella? popgrigorei n. sp. is a medium-sized dasycladalean alga showing funnel-like laterals with an euspondyl arrangement. The laterals consist of two distinctive parts. The proximal part is narrow and flattened. The distal part widens relatively suddenly, and then narrows slightly before the final widening towards the exterior, in the place where the laterals most probably formed an assimilatory cortex. The distinctive features of the new species are represented by the shape of the laterals. The new Salpingoporella best resembles the Upper Hauterivian–Lower Barremian p.p. Salpingoporella genevensis (Conrad), especially due to the quadrangular aspect of the laterals in middle-deep tangential section. However, differences refer to the laterals’ general shape, and to the typical features of the laterals in deep tangential section of Salpingoporella? popgrigorei n. sp.     

Analysis of signaling pathways in 90 cancer cell lines by protein lysate array

Multiple signal transduction pathways play a crucial role in cancer development, progression, and response to different therapies. An important issue is whether common signal transduction pathways are ubiquitously altered in all cancer types and some unique pathways are involved in different cancer types. Another important issue is whether and how transduction signaling molecules are heterogeneously expressed and activated in different cancer cells within and between cancer cell types. METHODS: To gain insight into these issues, we assembled a protein lysate array with 90 different cell lines of 12 different cell types. Each sample is diluted 2-fold six times, and samples from the dilution series were printed three times on the array. We then measured the expression levels and phosphorylation status of 52 different signaling proteins with specific antibodies and carried out statistical hierarchical clustering analysis. RESULTS: The most significant finding based on the cluster analysis was that the cell lines did not group based on tumor types, suggesting that the signaling pathways studied were commonly activated in most of the tumor types cultured in vitro. As expected, related proteins associated with specific signaling pathways clustered together, and analysis of the 30 most differentially expressed proteins revealed the PI3-K signaling pathway was upregulated in several different tumor types and the VEGF-angiogenesis pathway was downregulated in hematopoetic cancers. Another important observation, with clinical implications was that EGFR was the most heterogeneous among all the cell lines. We also observed signaling pathways unique to specific types of cancers such as the inverse relationship between p16ink and Rb, and the EGFR mediated pathway activation characteristic of pancreatic cancers. CONCLUSIONS: Using reverse phase lysate array analysis in this study, we were able to determine potential relationships and signaling pathways, both common and unique, to different types of cancer using cell lines in vitro. This data could be utilized for mining information related to an individual cancer of interest and combined with morphological and genomic profiles would help in creating a combination of expression markers and/or functional signaling maps for specific cancer diagnosis and therapy.     

Advances in application of machine learning to life cycle assessment: a literature review

Purpose

Life Cycle Assessment (LCA) is the process of systematically assessing impacts when there is an interaction between the environment and human activity. Machine learning (ML) with LCA methods can help contribute greatly to reducing impacts. The sheer number of input parameters and their uncertainties that contribute to the full life cycle make a broader application of ML complex and difficult to achieve. Hence a systems engineering approach should be taken to apply ML in isolation to aspects of the LCA. This study addresses the challenge of leveraging ML methods to deliver LCA solutions. The overarching hypothesis is that: LCA underpinned by ML methods and informed by dynamic data paves the way to more accurate LCA while supporting life cycle decision making.

Methods

In this study, previous research on ML for LCA were considered, and a literature review was undertaken.

Results

The results showed that ML can be a useful tool in certain aspects of the LCA. ML methods were shown to be applied efficiently in optimization scenarios in LCA. Finally, ML methods were integrated as part of existing inventory databases to streamline the LCA across many use cases.

Conclusions

The conclusions of this article summarise the characteristics of existing literature and provide suggestions for future work in limitations and gaps which were found in the literature.