An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing

The authors would like to thank the support on this research by the CRISP Project (Combinatorial Responses In Stress Pathways) funded by the BBSRC (BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative.Peer reviewedPublisher PD

Survival from cancer in teenagers and young adults in England, 1979–2003

Cancer is the leading cause of disease-related death in teenagers and young adults aged 13–24 years (TYAs) in England. We have analysed national 5-year relative survival among more than 30 000 incident cancer cases in TYAs. For cancer overall, 5-year survival improved from 63% in 1979–84 to 74% during 1996–2001 (P<0.001). However, there were no sustained improvements in survival over time among high-grade brain tumours and bone and soft tissue sarcomas. Survival patterns varied by age group (13–16, 17–20, 21–24 years), sex and diagnosis. Survival from leukaemia and brain tumours was better in the youngest age group but in the oldest from germ-cell tumours (GCTs). For lymphomas, bone and soft tissue sarcomas, melanoma and carcinomas, survival was not significantly associated with age. Females had a better survival than males except for GCTs. Most groups showed no association between survival and socioeconomic deprivation, but for leukaemias, head and neck carcinoma and colorectal carcinoma, survival was significantly poorer with increasing deprivation. These results will aid the development of national specialised service provision for this age group and identify areas of clinical need that present the greatest challenges

Total knee arthroplasty in a patient with a fused ipsilateral hip

10.1186/s13018-015-0271-zJournal of Orthopaedic Surgery and Research10112

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain

Imaging techniques based on optical contrast analysis can be used to visualize dynamic and functional properties of the nervous system via optical signals resulting from changes in blood volume, oxygen consumption and cellular swelling associated with brain physiology and pathology. Here we report in vivo noninvasive transdermal and transcranial imaging of the structure and function of rat brains by means of laser-induced photoacoustic tomography (PAT). The advantage of PAT over pure optical imaging is that it retains intrinsic optical contrast characteristics while taking advantage of the diffraction-limited high spatial resolution of ultrasound. We accurately mapped rat brain structures, with and without lesions, and functional cerebral hemodynamic changes in cortical blood vessels around the whisker-barrel cortex in response to whisker stimulation. We also imaged hyperoxia- and hypoxia-induced cerebral hemodynamic changes. This neuroimaging modality holds promise for applications in neurophysiology, neuropathology and neurotherapy

The Chop Gene Contains an Element for the Positive Regulation of the Mitochondrial Unfolded Protein Response

We have previously reported on the discovery of a mitochondrial specific unfolded protein response (mtUPR) in mammalian cells, in which the accumulation of unfolded protein within the mitochondrial matrix results in the transcriptional activation of nuclear genes encoding mitochondrial stress proteins such as chaperonin 60, chaperonin 10, mtDnaJ, and ClpP, but not those encoding stress proteins of the endoplasmic reticulum (ER) or the cytosol. Analysis of the chaperonin 60/10 bidirectional promoter showed that the CHOP element was required for the mtUPR and that the transcription of the chop gene is activated by mtUPR. In order to investigate the role of CHOP in the mtUPR, we carried out a deletion analysis of the chop promoter. This revealed that the transcriptional activation of the chop gene by mtUPR is through an AP-1 (activator protein-1) element. This site lies alongside an ERSE element through which chop transcription is activated in response to the ER stress response (erUPR). Thus CHOP can be induced separately in response to 2 different stress response pathways. We also discuss the potential signal pathway between mitochondria and the nucleus for the mtUPR

A Computational Method for Prediction of Excretory Proteins and Application to Identification of Gastric Cancer Markers in Urine

A novel computational method for prediction of proteins excreted into urine is presented. The method is based on the identification of a list of distinguishing features between proteins found in the urine of healthy people and proteins deemed not to be urine excretory. These features are used to train a classifier to distinguish the two classes of proteins. When used in conjunction with information of which proteins are differentially expressed in diseased tissues of a specific type versus control tissues, this method can be used to predict potential urine markers for the disease. Here we report the detailed algorithm of this method and an application to identification of urine markers for gastric cancer. The performance of the trained classifier on 163 proteins was experimentally validated using antibody arrays, achieving >80% true positive rate. By applying the classifier on differentially expressed genes in gastric cancer vs normal gastric tissues, it was found that endothelial lipase (EL) was substantially suppressed in the urine samples of 21 gastric cancer patients versus 21 healthy individuals. Overall, we have demonstrated that our predictor for urine excretory proteins is highly effective and could potentially serve as a powerful tool in searches for disease biomarkers in urine in general