HPB Surgical Unit, Department of Surgery and Cancer, Imperial College, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK.
Published: March 2012
AI Article Synopsis
Article Abstract
miRNAs play a role in post-transcriptional gene regulation by translational repression and/or mRNA degradation in a very tissue-specific manner. In order to understand the function of a miRNA, it is best to identify the genes that it regulates. Putative mRNA targets of miRNAs identified from seed sequence matches are available using computational algorithms in various web-based databases. However, these tend to have high false-positive rates and, owing to a whole-genome approach, cannot identify tissue/tumor specificity of regulation. The evaluated article presents a large amount of data analyzing global RNA expression in breast cancer and examines whether miRNAs are prognostic due to their effects on mRNA targets. This valuable and important resource of combined miRNA and mRNA expression in breast cancer and its subtypes has been summarized. Many studies have now investigated the integrated analysis of miRNA:mRNA profiles in human malignancies, the goal as always being to identify novel biomarkers and therapeutic targets for each tumor.
Motivation: As genome graphs are powerful data structures for representing the genetic diversity within populations, they can help identify genomic variations that traditional linear references miss, but their complexity and size makes the analysis of genome graphs challenging. We sought to develop a genome graph analysis tool that helps these analyses to become more accessible by addressing the limitations of existing tools. Specifically, we improve scalability and user-friendliness, and we provide many new statistics tailored to variation graphs for graph evaluation, including sample-specific features.
Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization.
Septic shock is a complex syndrome characterized by signs of intense systemic inflammation and a profound dysregulation of the immune response. Large-scale gene expression analysis is a valuable tool in this scenario because sepsis affects various cellular components and signaling pathways. In this article, we provide an overview of the transcriptomic studies that investigated human sepsis from 2007 to 2024, highlighting their major contributions.
We experimentally demonstrate a cost-effective dual-polarization quadrature phase shift keying (DP-QPSK) coherent passive optical network (PON) system that operates at 100 Gbits/s/λ. This system utilizes distributed feedback lasers (DFBs) and a carrier recovery algorithm facilitated by a bifunctional frequency-domain pilot tone (FPT). To reduce costs in coherent PON implementations, low-cost DFBs are employed as the sole light sources, replacing the more expensive external cavity lasers (ECLs) at both the optical line terminal (OLT) and the optical network units (ONUs).
Sensitive detection of incident acoustic waves over a broad frequency band offers a faithful representation of photoacoustic pressure transients of biological microstructures. Here, we propose a plasmon waveguide resonance sensor for responding to the photoacoustic impulses. By sequentially depositing Au, MgF, and SiO films on a coverslip, a composite waveguide layer produces a tightly confined optical evanescent field at the SiO-water interface with extremely strong electric field intensity, enabling the retrieval of photoacoustic signals with an estimated noise-equivalent-pressure (NEP) sensitivity of ∼92 Pa and a -6-dB bandwidth of ∼208 MHz.
