Single-walled carbon nanotube-based polymer monoliths for the enantioselective nano-liquid chromatographic separation of racemic pharmaceuticals

Many protocols have been used for extraction of DNA from Thraustochytrids. These generally involve the use of CTAB, phenol/chloroform and ethanol. They also feature mechanical grinding, sonication, N2 freezing or bead beating. However, the resulting chemical and physical damage to extracted DNA reduces its quality. The methods are also unsuitable for large numbers of samples. Commercially-available DNA extraction kits give better quality and yields but are expensive. Therefore, an optimized DNA extraction protocol was developed which is suitable for Thraustochytrids to both minimise expensive and time-consuming steps prior to DNA extraction and also to improve the yield. The most effective method is a combination of single bead in TissueLyser (Qiagen) and Proteinase K. Results were conclusive: both the quality and the yield of extracted DNA were higher than with any other method giving an average yield of 8.5 µg/100 mg biomass.

A 2-hour diagnostic protocol for possible cardiac chest pain in the emergency department: A randomized clinical trial

IMPORTANCE Patients with chest pain represent a high health care burden, but it may be possible to identify a patient group with a low short-term risk of adverse cardiac events who are suitable for early discharge. OBJECTIVE To compare the effectiveness of a rapid diagnostic pathway with a standard-care diagnostic pathway for the assessment of patients with possible cardiac chest pain in a usual clinical practice setting. DESIGN, SETTING, AND PARTICIPANTS A single-center, randomized parallel-group trial with blinded outcome assessments was conducted in an academic general and tertiary hospital. Participants included adults with acute chest pain consistent with acute coronary syndrome for whom the attending physician planned further observation and troponin testing. Patient recruitment occurred from October 11, 2010, to July 4, 2012, with a 30-day follow-up. INTERVENTIONS An experimental pathway using an accelerated diagnostic protocol (Thrombolysis in Myocardial Infarction score, 0; electrocardiography; and 0- and 2-hour troponin tests) or a standard-care pathway (troponin test on arrival at hospital, prolonged observation, and a second troponin test 6-12 hours after onset of pain) serving as the control. MAIN OUTCOMES AND MEASURES Discharge from the hospital within 6 hours without a major adverse cardiac event occurring within 30 days. RESULTS Fifty-two of 270 patients in the experimental group were successfully discharged within 6 hours compared with 30 of 272 patients in the control group (19.3% vs 11.0%; odds ratio, 1.92; 95% CI, 1.18-3.13; P = .008). It required 20 hours to discharge the same proportion of patients from the control group as achieved in the experimental group within 6 hours. In the experimental group, 35 additional patients (12.9%) were classified as low risk but admitted to an inpatient ward for cardiac investigation. None of the 35 patients received a diagnosis of acute coronary syndrome after inpatient evaluation. CONCLUSIONS AND RELEVANCE Using the accelerated diagnostic protocol in the experimental pathway almost doubled the proportion of patients with chest pain discharged early. Clinicians could discharge approximately 1 of 5 patients with chest pain to outpatient follow-up monitoring in less than 6 hours. This diagnostic strategy could be easily replicated in other centers because no extra resources are required.

A phase 1b study of placenta-derived mesenchymal stromal cells in patients with idiopathic pulmonary fibrosis

BACKGROUND AND OBJECTIVE: Idiopathic pulmonary fibrosis (IPF) is a degenerative disease characterized by fibrosis following failed epithelial repair. Mesenchymal stromal cells (MSC), a key component of the stem cell niche in bone marrow and possibly other organs including lung, have been shown to enhance epithelial repair and are effective in preclinical models of inflammation-induced pulmonary fibrosis, but may be profibrotic in some circumstances. METHODS: In this single centre, non-randomized, dose escalation phase 1b trial, patients with moderately severe IPF (diffusing capacity for carbon monoxide (DLCO ) ≥ 25% and forced vital capacity (FVC) ≥ 50%) received either 1 × 10(6) (n = 4) or 2 × 10(6) (n = 4) unrelated-donor, placenta-derived MSC/kg via a peripheral vein and were followed for 6 months with lung function (FVC and DLCO ), 6-min walk distance (6MWD) and computed tomography (CT) chest. RESULTS: Eight patients (4 female, aged 63.5 (57-75) years) with median (interquartile range) FVC 60 (52.5-74.5)% and DLCO 34.5 (29.5-40)% predicted were treated. Both dose schedules were well tolerated with only minor and transient acute adverse effects. MSC infusion was associated with a transient (1% (0-2%)) fall in SaO2 after 15 min, but no changes in haemodynamics. At 6 months FVC, DLCO , 6MWD and CT fibrosis score were unchanged compared with baseline. There was no evidence of worsening fibrosis. CONCLUSIONS: Intravenous MSC administration is feasible and has a good short-term safety profile in patients with moderately severe IPF.

Long, vertically aligned single-walled carbon nanotubes from plasmas: Morpho-kinetic and alignment controls

The enhanced large-scale model and numerical simulations are used to clarify the growth mechanism and the differences between the plasma- and neutral gas-grown carbon nanotubes, and to reveal the underlying physics and the key growth parameters. The results show that the nanotubes grown by plasma can be longer due to the effects of hydrocarbon ions with velocities aligned with the nanotubes. We show that the low-temperature growth is possible when the hydrocarbon ion flux dominates over fluxes of other species. We have also analysed the dependencies of the nanotube growth rates on nanotube and process parameters. The results are verified by a direct comparison with the experimental data. The model is generic and can be used for other types of carbon nanostructures such as carbon nanowalls, vertical graphenes, etc.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Single nucleotide polymorphisms in clinics: Fantasy or reality for cancer?

Single nucleotide polymorphisms (SNPs) have been classically used for dissecting various human complex disorders using candidate gene studies. During the last decade, large scale SNP analysis i.e. genome-wide association studies (GWAS) have provided an agnostic approach to identify possible genetic loci associated with heterogeneous disease such as cancer susceptibility, prognosis of survival or drug response. Further, the advent of new technologies, including microarray based genotyping as well as high throughput next generation sequencing has opened new avenues for SNPs to be used in clinical practice. It is speculated that the utility of SNPs to understand the mechanisms, biology of variable drug response and ultimately treatment individualization based on the individual’s genome composition will be indispensable in the near future. In the current review, we discuss the advantages and disadvantages of the clinical utility of genetic variants in disease risk-prediction, prognosis, clinical outcome and pharmacogenomics. The lessons and challenges for the utility of SNP based biomarkers are also discussed, including the need for additional functional validation studies.

Genetic insights into common pathways and complex relationships among iImmune-mediated diseases

Shared aetiopathogenic factors among immune-mediated diseases have long been suggested by their co-familiality and co-occurrence, and molecular support has been provided by analysis of human leukocyte antigen (HLA) haplotypes and genome-wide association studies. The interrelationships can now be better appreciated following the genotyping of large immune disease sample sets on a shared SNP array: the 'Immunochip'. Here, we systematically analyse loci shared among major immune-mediated diseases. This reveals that several diseases share multiple susceptibility loci, but there are many nuances. The most associated variant at a given locus frequently differs and, even when shared, the same allele often has opposite associations. Interestingly, risk alleles conferring the largest effect sizes are usually disease-specific. These factors help to explain why early evidence of extensive 'sharing' is not always reflected in epidemiological overlap. © 2013 Macmillan Publishers Limited. All rights reserved.

Visual analytics for large-scale bioinformatic data sets

Rapid advances in sequencing technologies (Next Generation Sequencing or NGS) have led to a vast increase in the quantity of bioinformatics data available, with this increasing scale presenting enormous challenges to researchers seeking to identify complex interactions. This paper is concerned with the domain of transcriptional regulation, and the use of visualisation to identify relationships between specific regulatory proteins (the transcription factors or TFs) and their associated target genes (TGs). We present preliminary work from an ongoing study which aims to determine the effectiveness of different visual representations and large scale displays in supporting discovery. Following an iterative process of implementation and evaluation, representations were tested by potential users in the bioinformatics domain to determine their efficacy, and to understand better the range of ad hoc practices among bioinformatics literate users. Results from two rounds of small scale user studies are considered with initial findings suggesting that bioinformaticians require richly detailed views of TF data, features to compare TF layouts between organisms quickly, and ways to keep track of interesting data points.

Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity

To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of 3 genome-wide association studies (GWAS) and 2 independent data sets genotyped on the Immunochip, including 10,588 cases and 22,806 controls. We identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals. We also identified, using conditional analyses, five independent signals within previously known loci. The newly identified loci shared with other autoimmune diseases include candidate genes with roles in regulating T-cell function (such as RUNX3, TAGAP and STAT3). Notably, they included candidate genes whose products are involved in innate host defense, including interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C) and nuclear factor (NF)-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense. © 2012 Nature America, Inc. All rights reserved.

Permissions in Deontic Event-Calculus

Permissions are special case of deontic effects and play important role compliance. Essentially they are used to determine the obligations or prohibitions to contrary. A formal language e.g., temporal logic, event-calculus et., not able to represent permissions is doomed to be unable to represent most of the real-life legal norms. In this paper we address this issue and extend deontic-event-calculus (DEC) with new predicates for modelling permissions enabling it to elegantly capture the intuition of real-life cases of permissions.

Genetic, functional, and histopathological evaluation of two C-terminal BRCA1 missense variants

Background: The vast majority of BRCA1 missense sequence variants remain uncharacterised for their possible effect on protein expression and function, and therefore are unclassified in terms of their pathogenicity. BRCA1 plays diverse cellular roles and it is unlikely that any single functional assay will accurately reflect the total cellular implications of missense mutations in this gene. Objective: To elucidate the effect of two BRCA1 variants, 5236G>C (G1706A) and 5242C>A (A1708E) on BRCA1 function, and to survey the relative usefulness of several assays to direct the characterisation of other unclassified variants in BRCA genes. Methods and Results: Data from a range of bioinformatic, genetic, and histopathological analyses, and in vitro functional assays indicated that the 1708E variant was associated with the disruption of different cellular functions of BRCA1. In transient transfection experiments in T47D and 293T cells, the 1708E product was mislocalised to the cytoplasm and induced centrosome amplification in 293T cells. The 1708E variant also failed to transactivate transcription of reporter constructs in mammalian transcriptional transactivation assays. In contrast, the 1706A variant displayed a phenotype comparable to wildtype BRCA1 in these assays. Consistent with functional data, tumours from 1708E carriers showed typical BRCA1 pathology, while tumour material from 1706A carriers displayed few histopathological features associated with BRCA1 related tumours. Conclusions: A comprehensive range of genetic, bioinformatic, and functional analyses have been combined for the characterisation of BRCA1 unclassified sequence variants. Consistent with the functional analyses, the combined odds of causality calculated for the 1706A variant after multifactorial likelihood analysis (1:142) indicates a definitive classification of this variant as "benign". In contrast, functional assays of the 1708E variant indicate that it is pathogenic, possibly through subcellular mislocalisation. However, the combined odds of 262:1 in favour of causality of this variant does not meet the minimal ratio of 1000:1 for classification as pathogenic, and A1708E remains formally designated as unclassified. Our findings highlight the importance of comprehensive genetic information, together with detailed functional analysis for the definitive categorisation of unclassified sequence variants. This combination of analyses may have direct application to the characterisation of other unclassified variants in BRCA1 and BRCA2.

Sequence specific interaction of Mycobacterium smegmatis topoisomerase I with duplex DNA

We have identified strong topoisomerase sites (STS) for Mycobacteruim smegmatis topoisomerase I in double-stranded DNA context using electrophoretic mobility shift assay of enzyme-DNA covalent complexes; Mg2+, an essential component for DNA relaxation activity of the enzyme, is not required for binding to DNA, The enzyme makes single-stranded nicks, with transient covalent interaction at the 5'-end of the broken DNA strand, a characteristic akin to prokaryotic topoisomerases. More importantly, the enzyme binds to duplex DNA having a preferred site with high affinity, a. property similar to the eukaryotic type I topoisomerases, The preferred cleavage site is mapped on a 65 bp duplex DNA and found to be CG/TCTT. Thus, the enzyme resembles other prokaryotic type I topoisomerases in mechanistics of the reaction, but is similar to eukaryotic enzymes in DNA recognition properties.

Label-free isolation of a prostate cancer cell among blood cells and the single-cell measurement of drug accumulation using an integrated microfluidic chip

Circulating tumor cells (CTCs) are found in the blood of patients with cancer. Although these cells are rare, they can provide useful information for chemotherapy. However, isolation of these rare cells from blood is technically challenging because they are small in numbers. An integrated microfluidic chip, dubbed as CTC chip, was designed and fabricated for conducting tumor cell isolation. As CTCs usually show multidrug resistance (MDR), the effect of MDR inhibitors on chemotherapeutic drug accumulation in the isolated single tumor cell is measured. As a model of CTC isolation, human prostate tumor cells were mixed with mouse blood cells and the labelfree isolation of the tumor cells was conducted based on cell size difference. The major advantages of the CTC chip are the ability for fast cell isolation, followed by multiple rounds of single-cell measurements, suggesting a potential assay for detecting the drug responses based on the liquid biopsy of cancer patients.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).