Discovery of a piperazine urea based compound as a potent, selective, orally bioavailable melanocortin subtype-4 receptor partial agonist

We report the discovery of piperazine urea based compound 1, a potent, selective, orally bioavailable melanocortin subtype-4 receptor partial agonist. Compound 1 shows anti-obesity efficacy without potentiating erectile activity in the rodent models.     

Universal definition of loss to follow-up in HIV treatment programs: a statistical analysis of 111 facilities in Africa, Asia, and Latin America

Background

Although patient attrition is recognized as a threat to the long-term success of antiretroviral therapy programs worldwide, there is no universal definition for classifying patients as lost to follow-up (LTFU). We analyzed data from health facilities across Africa, Asia, and Latin America to empirically determine a standard LTFU definition.

Methods and Findings

At a set “status classification” date, patients were categorized as either “active” or “LTFU” according to different intervals from time of last clinic encounter. For each threshold, we looked forward 365 d to assess the performance and accuracy of this initial classification. The best-performing definition for LTFU had the lowest proportion of patients misclassified as active or LTFU. Observational data from 111 health facilities—representing 180,718 patients from 19 countries—were included in this study. In the primary analysis, for which data from all facilities were pooled, an interval of 180 d (95% confidence interval [CI]: 173–181 d) since last patient encounter resulted in the fewest misclassifications (7.7%, 95% CI: 7.6%–7.8%). A secondary analysis that gave equal weight to cohorts and to regions generated a similar result (175 d); however, an alternate approach that used inverse weighting for cohorts based on variance and equal weighting for regions produced a slightly lower summary measure (150 d). When examined at the facility level, the best-performing definition varied from 58 to 383 d (mean = 150 d), but when a standard definition of 180 d was applied to each facility, only slight increases in misclassification (mean = 1.2%, 95% CI: 1.0%–1.5%) were observed. Using this definition, the proportion of patients classified as LTFU by facility ranged from 3.1% to 45.1% (mean = 19.9%, 95% CI: 19.1%–21.7%).

Conclusions

Based on this evaluation, we recommend the adoption of ≥180 d since the last clinic visit as a standard LTFU definition. Such standardization is an important step to understanding the reasons that underlie patient attrition and establishing more reliable and comparable program evaluation worldwide. Please see later in the article for the Editors'' Summary     

Understanding type 1 diabetes through genetics: advances and prospects

Starting with early crucial discoveries of the role of the major histocompatibility complex, genetic studies have long had a role in understanding the biology of type 1 diabetes (T1D), which is one of the most heritable common diseases. Recent genome-wide association studies (GWASs) have given us a clearer picture of the allelic architecture of genetic susceptibility to T1D. Fine mapping and functional studies are gradually revealing the complex mechanisms whereby immune self-tolerance is lost, involving multiple aspects of adaptive immunity. The triggering of these events by dysregulation of the innate immune system has also been implicated by genetic evidence. Finally, genetic prediction of T1D risk is showing promise of use for preventive strategies.     

Expanding the understanding of biases in development of clinical-grade molecular signatures: a case study in acute respiratory viral infections

Background

The promise of modern personalized medicine is to use molecular and clinical information to better diagnose, manage, and treat disease, on an individual patient basis. These functions are predominantly enabled by molecular signatures, which are computational models for predicting phenotypes and other responses of interest from high-throughput assay data. Data-analytics is a central component of molecular signature development and can jeopardize the entire process if conducted incorrectly. While exploratory data analysis may tolerate suboptimal protocols, clinical-grade molecular signatures are subject to vastly stricter requirements. Closing the gap between standards for exploratory versus clinically successful molecular signatures entails a thorough understanding of possible biases in the data analysis phase and developing strategies to avoid them.

Methodology and Principal Findings

Using a recently introduced data-analytic protocol as a case study, we provide an in-depth examination of the poorly studied biases of the data-analytic protocols related to signature multiplicity, biomarker redundancy, data preprocessing, and validation of signature reproducibility. The methodology and results presented in this work are aimed at expanding the understanding of these data-analytic biases that affect development of clinically robust molecular signatures.

Conclusions and Significance

Several recommendations follow from the current study. First, all molecular signatures of a phenotype should be extracted to the extent possible, in order to provide comprehensive and accurate grounds for understanding disease pathogenesis. Second, redundant genes should generally be removed from final signatures to facilitate reproducibility and decrease manufacturing costs. Third, data preprocessing procedures should be designed so as not to bias biomarker selection. Finally, molecular signatures developed and applied on different phenotypes and populations of patients should be treated with great caution.     

A comprehensive evaluation of multicategory classification methods for microarray gene expression cancer diagnosis

MOTIVATION: Cancer diagnosis is one of the most important emerging clinical applications of gene expression microarray technology. We are seeking to develop a computer system for powerful and reliable cancer diagnostic model creation based on microarray data. To keep a realistic perspective on clinical applications we focus on multicategory diagnosis. To equip the system with the optimum combination of classifier, gene selection and cross-validation methods, we performed a systematic and comprehensive evaluation of several major algorithms for multicategory classification, several gene selection methods, multiple ensemble classifier methods and two cross-validation designs using 11 datasets spanning 74 diagnostic categories and 41 cancer types and 12 normal tissue types. RESULTS: Multicategory support vector machines (MC-SVMs) are the most effective classifiers in performing accurate cancer diagnosis from gene expression data. The MC-SVM techniques by Crammer and Singer, Weston and Watkins and one-versus-rest were found to be the best methods in this domain. MC-SVMs outperform other popular machine learning algorithms, such as k-nearest neighbors, backpropagation and probabilistic neural networks, often to a remarkable degree. Gene selection techniques can significantly improve the classification performance of both MC-SVMs and other non-SVM learning algorithms. Ensemble classifiers do not generally improve performance of the best non-ensemble models. These results guided the construction of a software system GEMS (Gene Expression Model Selector) that automates high-quality model construction and enforces sound optimization and performance estimation procedures. This is the first such system to be informed by a rigorous comparative analysis of the available algorithms and datasets. AVAILABILITY: The software system GEMS is available for download from http://www.gems-system.org for non-commercial use. CONTACT: alexander.statnikov@vanderbilt.edu.     

2-Piperazinecarboxamides as potent and selective melanocortin subtype-4 receptor agonists

We report the discovery and optimization of substituted 2-piperazinecarboxamides as potent and selective agonists of the melanocortin subtype-4 receptor. The 5- and 6-alkylated piperazine compounds exhibit low bioactivation potential as measured by covalent binding in microsome preparations.     

Annexin II is a novel receptor for Pseudomonas aeruginosa

Infections with Pseudomonas aeruginosa (P. aeruginosa) are critical in ventilated and poly-traumatized patients. Most important, these bacteria cause frequent and chronic pulmonary infections in patients with cystic fibrosis. Therefore, identification of molecular mechanisms that mediate the infection of mammalian cells with P. aeruginosa is urgently required. Here, we aimed to identify novel receptors that are involved in internalization of P. aeruginosa into mammalian epithelial cells. Employing SDS-PAGE purification and mass spectrometry we demonstrate that annexin II specifically binds to P. aeruginosa. The significance of the interaction of annexin II with P. aeruginosa for the infection of mammalian cells is indicated by the finding that neutralization of the ligands on P. aeruginosa by incubation of the bacteria with recombinant, soluble annexin II prevents internalization of P. aeruginosa into human epithelial cells.     

Calcium and magnesium binding to human centrin 3 and interaction with target peptides

There are four isoforms of centrin in mammals, with variable sequence, tissue expression, and functional properties. We have recently characterized a number of structural, ion, and target binding properties of human centrin isoform HsCen2. This paper reports a similar characterization of HsCen3, overexpressed in Escherichia coli and purified by phase-reversed chromatography. Equilibrium and dynamic binding studies revealed that HsCen3 has one mixed Ca(2+)/Mg(2+) binding site of high affinity (K(d) = 3 and 10 microM for Ca(2+) and Mg(2+), respectively) and two Ca(2+)-specific sites of low affinity (K(d) = 140 microM). The metal-free protein is fragmented by an unidentified protease into a polypeptide segment of 11 kDa, which was purified by HPLC, and identified by mass spectrometry as the segment of residues 21-112. Similarly, controlled trypsinolysis on Ca(2+)-bound HsCen3 yielded a mixture of segments of residues 1-124 and 1-125. The Ca(2+)/Mg(2+) site could be assigned to this segment and thus resides in the N-terminal half of HsCen3. Temperature denaturation experiments, circular dichroism, and utilization of fluorescence hydrophobic probes allowed us to propose that the metal-free protein has molten globule characteristics and that the dication-bound forms are compact with a polar surface for the Mg(2+) form and a hydrophobic exposed surface for the Ca(2+) form. Thus, HsCen3 could be classified as a Ca(2+) sensor protein. In addition, it is able to bind strongly to a model target peptide (melittin), as well as to peptides derived from the protein XPC and Kar1p, with a moderate Ca(2+) dependence.     

Stimuli inducing gregarious colouration and behaviour in nymphs of Schistocerca gregaria

Solitarious nymphs of Schistocerca gregaria were reared under various conditions in both Jerusalem and Oxford to tease apart cues involved in behavioural and colour phase change. Treatments included rearing nymphs from the IInd or IIIrd until the final nymphal stadium in physical contact with similarly aged conspecific groups or with another locust species, Locusta migratoria migratorioides, as well as confining single nymphs in mesh cages, which were kept within crowds of S. gregaria or L. migratoria migratorioides, providing visual and olfactory but no physical contact with other locusts. In the Oxford experiments, an extra treatment was included which provided olfactory cues without visual or contact stimulation. Our results confirm that transformation from the solitarious to the gregarious phase of locusts is complex, and that different phase characteristics not only follow different time courses, but are also controlled by different suites of cues. As predicted from earlier studies, behavioural phase change was evoked by non-species-specific cues. Rearing in contact with either species was fully effective in inducing gregarious behaviour, as was the combination of the sight and smell of other locusts, but odour alone was ineffective. Colour phase change was shown to comprise two distinct elements that could be dissociated: black patterning and yellow background. The former of these could be induced as effectively by rearing S. gregaria nymphs in a crowd of L. migratoria migratorioides as by rearing with conspecifics. Sight and smell of other locusts also triggered black patterning and, unlike behavioural change, some black patterning was induced by odour cues alone. Hence, physical contact was not needed to induce gregarious black patterning. Yellow colouration, however, was only fully induced when locusts were reared in contact with conspecifics, implying the presence of a species-specific contact chemical cue.