Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

MicroRNA-199a induces differentiation of induced pluripotent stem cells into endothelial cells by targeting sirtuin 1

The ability to reprogram induced pluripotent stem (iPS) cells from somatic cells may facilitate significant advances in regenerative medicine. MicroRNAs (miRNAs) are involved in a number of core biological processes, including cardiogenesis, hematopoietic lineage differentiation and oncogenesis. An improved understanding of the complex molecular signals that are required for the differentiation of iPS cells into endothelial cells (ECs) may allow specific targeting of their activity in order to enhance cell differentiation and promote tissue regeneration. The present study reports that miR‑199a is involved in EC differentiation from iPS cells. Augmented expression of miR‑199a was detected during EC differentiation, and reached higher levels during the later stages of this process. Furthermore, miR‑199a inhibited the differentiation of iPS cells into smooth muscle cells. Notably, sirtuin 1 was identified as a target of miR‑199a . Finally, the ability of miR‑199a to induce angiogenesis was evaluated in vitro, using Matrigel plugs assays. This may indicate a novel function for miR‑199a as a regulator of the phenotypic switch during vascular cell differentiation. The present study provides support to the notion that with an understanding of the molecular mechanisms underlying vascular cell differentiation, stem cell regenerative therapy may ultimately be developed as an effective treatment for cardiovascular disease.

A let-7 microRNA-binding site polymorphism in 3'-untranslated region of KRAS gene predicts response in wild-type KRAS patients with metastatic colorectal cancer treated with cetuximab monotherapy

PURPOSE: recent studies have found that KRAS mutations predict resistance to monoclonal antibodies targeting the epidermal growth factor receptor in metastatic colorectal cancer (mCRC). A polymorphism in a let-7 microRNA complementary site (lcs6) in the KRAS 3' untranslated region (UTR) is associated with an increased cancer risk in non-small-cell lung cancer and reduced overall survival (OS) in oral cancers. We tested the hypothesis whether this polymorphism may be associated with clinical outcome in KRAS wild-type (KRASwt) mCRC patients treated with cetuximab monotherapy.

PATIENTS AND METHODS: the presence of KRAS let-7 lcs6 polymorphism was evaluated in 130 mCRC patients who were enrolled in a phase II study of cetuximab monotherapy (IMCL-0144). Genomic DNA was extracted from dissected formalin-fixed paraffin-embedded tumor tissue, KRAS mutation status and polymorphism were assessed using direct sequencing and PCR restriction fragment length polymorphism technique.

RESULTS: KRAS let-7 lcs6 polymorphism was found to be related to object response rate (ORR) in mCRC patients whose tumors had KRASwt. The 12 KRASwt patients harboring at least a variant G allele (TG or GG) had a 42% ORR compared with a 9% ORR in 55 KRASwt patients with let-7 lcs6 TT genotype (P = 0.02, Fisher's exact test). KRASwt patients with TG/GG genotypes had trend of longer median progression-free survival (3.9 versus 1.3 months) and OS (10.7 versus 6.4 months) compared to those with TT genotypes.

CONCLUSIONS: these results are the first to indicate that the KRAS 3'UTR polymorphism may predict for cetuximab responsiveness in KRASwt mCRC patients, which warrants validation in other clinical trials.

Considerations for optimization of microRNA PCR assays for molecular diagnosis

The remarkable stability of microRNAs in biofluids underlies their potential as biomarkers, but their small size presents challenges for detection by RT-qPCR. The heterogeneity of microRNAs, with each one comprising a series of variants or 'isomiRs', adds additional complexity. Presented here are the key considerations for use of RT-qPCR to measure microRNAs and their isomiRs, with a focus on plasma. Modified nucleotides can be incorporated into primer sequences to enhance affinity and provide increased specificity and sensitivity for RT-qPCR assays. Approaches based upon polyA tailing and use of a common oligo(dT)-based reverse transcription oligonucleotide will detect most isomiRs. Conversely, stem-loop RT oligonucleotides and sequence specific probes can enable detection of specific isomiRs of interest. Next generation sequencing of all the products of a microRNA RT-PCR reaction is a promising new approach for both microRNA quantification and characterization.