Search

Background: Antineoplastic agents represent the most common class of drugs causing Adverse Drug Reactions (ADRs). Mutant alleles of genes coding for drug-metabolizing enzymes are the best studied individual risk factors for these ADRs. Although the correlation between genetic polymorphisms and ADRs is well-known, pharmacogenetic tests are limited to centralized laboratories with expensive or dedicated instrumentation used by specialized personnel. Nowadays, DNA chips have overcome the major limitations in terms of sensibility, specificity or small molecular detection, allowing the simultaneous detection of several genetic polymorphisms with time and costs-effective advantages. In this work, we describe the design of a novel silicon-based lab-on-chip assay able to perform low-density and high-resolution multi-assay analysis (amplification and hybridization reactions) on the In-Check platform., Methods: The novel lab-on-chip was used to screen 17 allelic variants of three genes associated with adverse reactions to common chemotherapeutic agents: DPYD (Dihydropyrimidine dehydrogenase), MTHFR (5,10-Methylenetetrahydrofolate reductase) and TPMT (Thiopurine S-methyltransferase)., Results: Inter- and intra assay variability were performed to assess the specificity and sensibility of the chip. Linear regression was used to assess the optimal hybridization temperature set at 52 °C (R 2 ≈ 0.97). Limit of detection was 50 nM., Conclusions: The high performance in terms of sensibility and specificity of this lab-on-chip supports its further translation to clinical diagnostics, where it may effectively promote precision medicine.

Smart agriculture based on new types of sensors, data analytics and automation, is an important enabler for optimizing yields and maximizing efficiency to feed the world's growing population while limiting environmental pollution. The aim of this paper is to describe a multi-sensor Internet of Things (IoT) system for agriculture consisting of a soil probe, an air probe and a smart data logger. The implementation details will focus of the integration element and the innovative Artificial Intelligence based gas identification sensor. Furthermore, the paper focuses on the analytics and decision support system implementation that provides farming recommendations and is enhanced with a feedback loop from farmers and a social trust index that will increase the reliability of the system.

The KRAS oncogene is involved in the pathogenesis of several types of cancer, particularly colorectal cancer (CRC). The most frequent mutations in this gene are associated with poor survival, increased tumor aggressiveness and resistance to therapy with anti-epidermal growth factor receptor (EGFR) antibodies. For this reason, KRAS mutation testing has become increasingly common in clinical practice for personalized cancer treatments of CRC patients. Detection methods for KRAS mutations are currently expensive, laborious, time-consuming and often lack of diagnostic sensitivity and specificity. In this study, we describe the development of a Lab-on-Chip assay for genotyping of KRAS mutational status. This assay, based on the In-Check platform, integrates microfluidic handling, a multiplex polymerase chain reaction (PCR) and a low-density microarray. This integrated sample-to-result system enables the detection of KRAS point mutations, including those occurring in codons 12 and 13 of exon 2, 59 and 61 of exon 3, 117 and 146 of exon 4. Thanks to its miniaturization, automation, rapid analysis, minimal risk of sample contamination, increased accuracy and reproducibility of results, this Lab-on-Chip platform may offer immediate opportunities to simplify KRAS genotyping into clinical routine., Competing Interests: The authors declare no conflict of interest.

In the last decades, molecular biology has moved from gene-by-gene analysis to more complex studies using a genome-wide scale. Thanks to high-throughput genomic technologies, such as microarrays and next-generation sequencing, a huge amount of information has been generated, expanding our knowledge on the genetic basis of various diseases. Although some of this information could be transferred to clinical diagnostics, the technologies available are not suitable for this purpose. In this review, we will discuss the drawbacks associated with the use of traditional DNA microarrays in diagnostics, pointing out emerging platforms that could overcome these obstacles and offer a more reproducible, qualitative and quantitative multigenic analysis. New miniaturized and automated devices, called Lab-on-Chip, begin to integrate PCR and microarray on the same platform, offering integrated sample-to-result systems. The introduction of this kind of innovative devices may facilitate the transition of genome-based tests into clinical routine., (Copyright © 2014. Published by Elsevier Inc.)

This manuscript describes the use of a novel biochip platform for the rapid analysis/identification of nucleic acids, including DNA and microRNAs, with very high specificity. This approach combines a unique dynamic chemistry approach for nucleic acid testing and analysis developed by DestiNA Genomics with the STMicroelectronics In-Check platform, which comprises two microfluidic optimized and independent PCR reaction chambers, and a sequential microarray area for nucleic acid capture and identification by fluorescence. With its compact bench-top "footprint" requiring only a single technician to operate, the biochip system promises to transform and expand routine clinical diagnostic testing and screening for genetic diseases, cancers, drug toxicology and heart disease, as well as employment in the emerging companion diagnostics market.

The multigenic program underlying neuronal apoptosis is mostly unknown. To study the program, we used genome-scale screening by oligonucleotide microarrays during serum and potassium deprivation-induced apoptosis of cerebellar granule neurons. From the 8740 genes interrogated by the arrays, 423 genes were found to be regulated at both the transcriptional and the posttranscriptional level and segregated into distinct clusters. Semantic clustering based on gene ontologies showed coordinated expression of genes with common biological functions and metabolic pathways. Among the genes implicated in apoptotic cerebellar granule neurons, 70 were in common with those differentially expressed in cortical neurons exposed to amyloid beta-protein, indicating the existence of common mechanisms responsible for neuronal cell death. Our results offer a genomic view of the changes that accompany neuronal apoptosis and yield new insights into the underlying molecular basis.