Topological Phases near a Triple Degeneracy

We study the pattern of three state topological phases that appear in systems with real Hamiltonians and wave functions. We give a simple geometric construction for representing these phases. We then apply our results to understand previous work on three state phases. We point out that the ``mirror symmetry'' of wave functions noticed in microwave experiments can be simply understood in our framework.Comment: 4 pages, 1 figure, to appear in Phys. Rev. Let

Investigation of translocation, DNA unwinding, and protein displacement by NS3h, the helicase domain from the Hepatitis C virus helicase

Helicases are motor proteins that are involved in DNA and RNA metabolism, replication, recombination, transcription and repair. The motors are powered by ATP binding and hydrolysis. Hepatitis C virus encodes a helicase called non-structural protein (NS3). NS3 possesses protease and helicase activities on its N-terminal and C-terminal domains respectively. The helicase domain of NS3 protein is referred as NS3h. In vitro, NS3h catalyzes RNA and DNA unwinding in a 3’ to -5’ direction. The directionality for unwinding is thought to arise in part from the enzyme's ability to translocate along DNA, but translocation has not been shown explicitly. We examined the DNA translocase activity of NS3h by using single-stranded oligonucleotide substrates containing a fluorescent probe on the 5’ end. NS3h can bind to the ssDNA and in the presence of ATP, move towards the 5’-end. When the enzyme encounters the fluorescent probe, a fluorescence change is observed that allows translocation to be characterized. Under conditions that favor binding of one NS3h per DNA substrate (100 nM NS3h, 200 nM oligonucleotide) we find that NS3h translocates on ssDNA at a rate of 46 ± 5 nt s−1 and that it can move for 230 ± 60 nt before dissociating from the DNA. The translocase activity of some helicases is responsible for displacing proteins that are bound to DNA. We studied protein displacement by using a ssDNA oligonucleotide covalently linked to biotin on the 5’-end. Upon addition of streptavidin, a ‘protein-block’ was placed in the pathway of the helicase. Interestingly, NS3h was unable to displace streptavidin from the end of the oligonucleotide, despite its ability to translocate along the DNA. The DNA unwinding activity of NS3h was examined using a 22 bp duplex DNA substrate under conditions that were identical to those used to study translocation. NS3h exhibited little or no DNA unwinding under single cycle conditions, supporting the conclusion that NS3h is a relatively poor helicase in its monomeric form, as has been reported. In summary, NS3h translocates on ssDNA as a monomer, but the translocase activity does not correspond to comparable DNA unwinding activity or protein-displacement activity under identical conditions

Corrigendum: Evolution, ecology, and zoonotic transmission of betacoronaviruses: A review

In the published article, there was an error in the legend for Figure 1 as published. The figure legend did not indicate that it has been adapted from Plowright et al. (2017). Copyright permission was obtained from Springer Nature to adapt Figure 1 from Plowright et al. (2017). The corrected legend appears below. Figure 1. Zoonotic risk distribution, pathway to spillover, and the multimodal role of the determinants of spillover. The zoonotic risk is demonstrated by the accumulated distribution of reservoir hosts and vectors that play a role in the pathway to spillover. The risk of spillover is determined by a series of processes from the ecological dynamics of reservoir host distribution and density, to the susceptibility, replication and dissemination of the biological factors in the recipient host. This is also reflected in the multimodal role of the determinants of spillover, demonstrating the disciplines that are being used to study zoonotic transmission and the determinants of spillover. This figure was adapted from Figure 1 in Plowright et al. (2). Copyright permission was obtained with license number 55218980848529. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

The Novel Deacetylase Inhibitor AR-42 Demonstrates Pre-Clinical Activity in B-Cell Malignancies In Vitro and In Vivo

While deacetylase (DAC) inhibitors show promise for the treatment of B-cell malignancies, those introduced to date are weak inhibitors of class I and II DACs or potent inhibitors of class I DAC only, and have shown suboptimal activity or unacceptable toxicities. We therefore investigated the novel DAC inhibitor AR-42 to determine its efficacy in B-cell malignancies.In mantle cell lymphoma (JeKo-1), Burkitt's lymphoma (Raji), and acute lymphoblastic leukemia (697) cell lines, the 48-hr IC(50) (50% growth inhibitory concentration) of AR-42 is 0.61 microM or less. In chronic lymphocytic leukemia (CLL) patient cells, the 48-hr LC(50) (concentration lethal to 50%) of AR-42 is 0.76 microM. AR-42 produces dose- and time-dependent acetylation both of histones and tubulin, and induces caspase-dependent apoptosis that is not reduced in the presence of stromal cells. AR-42 also sensitizes CLL cells to TNF-Related Apoptosis Inducing Ligand (TRAIL), potentially through reduction of c-FLIP. AR-42 significantly reduced leukocyte counts and/or prolonged survival in three separate mouse models of B-cell malignancy without evidence of toxicity.Together, these data demonstrate that AR-42 has in vitro and in vivo efficacy at tolerable doses. These results strongly support upcoming phase I testing of AR-42 in B-cell malignancies

Safety and tolerability of sitagliptin in clinical studies: a pooled analysis of data from 10,246 patients with type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>In a previous pooled analysis of 12 double-blind clinical studies that included data on 6,139 patients with type 2 diabetes, treatment with sitagliptin, a dipeptidyl peptidase-4 (DPP-4) inhibitor, was shown to be generally well tolerated compared with treatment with control agents. As clinical development of sitagliptin continues, additional studies have been completed, and more patients have been exposed to sitagliptin. The purpose of the present analysis is to update the safety and tolerability assessment of sitagliptin by pooling data from 19 double-blind clinical studies.</p> <p>Methods</p> <p>The present analysis included data from 10,246 patients with type 2 diabetes who received either sitagliptin 100 mg/day (N = 5,429; sitagliptin group) or a comparator agent (placebo or an active comparator) (N = 4,817; non-exposed group). The 19 studies from which this pooled population was drawn represent the double-blind, randomized studies that included patients treated with the usual clinical dose of sitagliptin (100 mg/day) for between 12 weeks and 2 years and for which results were available as of July 2009. These 19 studies assessed sitagliptin taken as monotherapy, initial combination therapy with metformin or pioglitazone, or as add-on combination therapy with other antihyperglycemic agents (metformin, pioglitazone, a sulfonylurea ± metformin, insulin ± metformin, or rosiglitazone + metformin). Patients in the non-exposed group were taking placebo, metformin, pioglitazone, a sulfonylurea ± metformin, insulin ± metformin, or rosiglitazone + metformin. The analysis used patient-level data from each study to evaluate between-group differences in the exposure-adjusted incidence rates of adverse events.</p> <p>Results</p> <p>Summary measures of overall adverse events were similar in the sitagliptin and non-exposed groups, except for an increased incidence of drug-related adverse events in the non-exposed group. Incidence rates of specific adverse events were also generally similar between the two groups, except for increased incidence rates of hypoglycemia, related to the greater use of a sulfonylurea, and diarrhea, related to the greater use of metformin, in the non-exposed group and constipation in the sitagliptin group. Treatment with sitagliptin was not associated with an increased risk of major adverse cardiovascular events.</p> <p>Conclusions</p> <p>In this updated pooled safety analysis of data from 10,246 patients with type 2 diabetes, sitagliptin 100 mg/day was generally well tolerated in clinical trials of up to 2 years in duration.</p

Human Gastric Mucins Differently Regulate Helicobacter pylori Proliferation, Gene Expression and Interactions with Host Cells

Helicobacter pylori colonizes the mucus niche of the gastric mucosa and is a risk factor for gastritis, ulcers and cancer. The main components of the mucus layer are heavily glycosylated mucins, to which H. pylori can adhere. Mucin glycosylation differs between individuals and changes during disease. Here we have examined the H. pylori response to purified mucins from a range of tumor and normal human gastric tissue samples. Our results demonstrate that mucins from different individuals differ in how they modulate both proliferation and gene expression of H. pylori. The mucin effect on proliferation varied significantly between samples, and ranged from stimulatory to inhibitory, depending on the type of mucins and the ability of the mucins to bind to H. pylori. Tumor-derived mucins and mucins from the surface mucosa had potential to stimulate proliferation, while gland-derived mucins tended to inhibit proliferation and mucins from healthy uninfected individuals showed little effect. Artificial glycoconjugates containing H. pylori ligands also modulated H. pylori proliferation, albeit to a lesser degree than human mucins. Expression of genes important for the pathogenicity of H. pylori (babA, sabA, cagA, flaA and ureA) appeared co-regulated in response to mucins. The addition of mucins to co-cultures of H. pylori and gastric epithelial cells protected the viability of the cells and modulated the cytokine production in a manner that differed between individuals, was partially dependent of adhesion of H. pylori to the gastric cells, but also revealed that other mucin factors in addition to adhesion are important for H. pylori-induced host signaling. The combined data reveal host-specific effects on proliferation, gene expression and virulence of H. pylori due to the gastric mucin environment, demonstrating a dynamic interplay between the bacterium and its host

Known and unknown requirements in healthcare

We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications

High-performance liquid chromatography–tandem mass spectrometry in the identification and determination of phase I and phase II drug metabolites

Applications of tandem mass spectrometry (MS/MS) techniques coupled with high-performance liquid chromatography (HPLC) in the identification and determination of phase I and phase II drug metabolites are reviewed with an emphasis on recent papers published predominantly within the last 6 years (2002–2007) reporting the employment of atmospheric pressure ionization techniques as the most promising approach for a sensitive detection, positive identification and quantitation of metabolites in complex biological matrices. This review is devoted to in vitro and in vivo drug biotransformation in humans and animals. The first step preceding an HPLC-MS bioanalysis consists in the choice of suitable sample preparation procedures (biomatrix sampling, homogenization, internal standard addition, deproteination, centrifugation, extraction). The subsequent step is the right optimization of chromatographic conditions providing the required separation selectivity, analysis time and also good compatibility with the MS detection. This is usually not accessible without the employment of the parent drug and synthesized or isolated chemical standards of expected phase I and sometimes also phase II metabolites. The incorporation of additional detectors (photodiode-array UV, fluorescence, polarimetric and others) between the HPLC and MS instruments can result in valuable analytical information supplementing MS results. The relation among the structural changes caused by metabolic reactions and corresponding shifts in the retention behavior in reversed-phase systems is discussed as supporting information for identification of the metabolite. The first and basic step in the interpretation of mass spectra is always the molecular weight (MW) determination based on the presence of protonated molecules [M+H]+ and sometimes adducts with ammonium or alkali-metal ions, observed in the positive-ion full-scan mass spectra. The MW determination can be confirmed by the [M-H]- ion for metabolites providing a signal in negative-ion mass spectra. MS/MS is a worthy tool for further structural characterization because of the occurrence of characteristic fragment ions, either MSn analysis for studying the fragmentation patterns using trap-based analyzers or high mass accuracy measurements for elemental composition determination using time of flight based or Fourier transform mass analyzers. The correlation between typical functional groups found in phase I and phase II drug metabolites and corresponding neutral losses is generalized and illustrated for selected examples. The choice of a suitable ionization technique and polarity mode in relation to the metabolite structure is discussed as well

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs