Identifying Individuals at Risk for Fracture in Guatemala

INTRODUCTION: The FRAX calculator combines a set of clinical risk factors with country-specific incidence rates to determine the ten-year absolute risk of major osteoporotic fracture. However, regional or country-specific databases from Central American countries are not available. We compared the use of various FRAX databases and the Pluijm algorithm in determining risk of fracture. METHODS: We collected clinical risk factor data needed for the FRAX calculator and Pluijm algorithm of Hispanic women in Guatemala and calculated the FRAX absolute risk measures of major osteoporotic fracture and hip fracture. Subjects were postmenopausal women greater than age 40 with no history of using medication that affect bone. A random sample of 204 women in 34 different regions women in Guatemala City was visited in their homes to complete the surveys. The Pluijm risk score and FRAX risk score using the US Hispanic, Spain, and Mexican databases were calculated. RESULTS: We used the US NOF guidelines for treatment which suggest a treatment threshold for patients with a 10-year hip fracture probability ≥ 3% or a 10-year major osteoporotic fracture risk ≥ 20%. The number of patients meeting the suggested threshold limits for treatment using the Spain and Mexico calculators were identical. There was 100% conformity in threshold limits for both hip and major osteoporotic fracture risk. The mean conformity for any fracture risk between US Hispanic and the other two databases was 97.5%. Conformity was 99.0% based on major osteoporotic fracture and 97.5% based on risk of hip fracture. The Pluijm evaluation shows conformity of 87.2% and 83.3%, respectively, when compared to the US Hispanic and Spain/Mexico FRAX thresholds for risk of fracture. DISCUSSION: Although the different FRAX databases provide variations in the absolute risk of fracture, the overall conformity to treatment thresholds amongst the US Hispanic, Spain, and Mexico databases show the database used would have little effect as to the decision to treat. The Pluijm tool conforms to the FRAX thresholds and can be used as well. It does not matter which country-specific calculator or assessment tool is used, as there are a similar number of patients that would meet the intervention threshold

New Selective Estrogen Receptor Modulators (SERMs) in Development

Selective estrogen receptor modulators (SERMs) or estrogen agonists/antagonists have shown promise in osteoporosis in that they have the potential to reduce the risk of fracture, and also reduce the risk of breast cancer. SERMs maybe classified according to their core structure, which is typically a variation of the 17 beta-estradiol template and subclassified according to the side chain at the helix 12 affector region. The best known are the triphenylethylenes such as tamoxifen, used in the management of breast cancer. However, the clinical application of this class of SERMs has been limited due to endometrial stimulation. A second class is the benzothiophenes such as raloxifene and arzoxifene, which have skeletal benefit with little, if any, uterine stimulation. Indole-based SERMs such as bazedoxifene have a 2-phenyl ring system that serves as a core binding unit. Other classes include benzopyrans and naphthalenes (eg, lasofoxifene). In this review article, I will discuss raloxifene and three new SERMs—arzoxifene, bazedoxifene, and lasofoxifene—that have been recently studied. I will discuss their effect on bone, breast, and the cardiovascular system, as well as on safety

Restoring identity: The use of religion as a mechanism to transition between an identity of sexual offending to a non-offending identity

This study examines the unique experience of participants who during their reintegration back into the community, following a conviction for sexual offending, re-engaged with religious and spiritual communities. To explore meaning Interpretative Phenomenological Analysis (IPA) was adopted. Four in-depth interviews of men convicted for sexual crimes were undertaken and analysed. Findings indicate that through religious affiliation participants were: exposed to new prosocial networks; provided opportunities to seek forgiveness; felt a sense of belonging and affiliation; and were psychologically comforted. However, the study also found that the process of identity transition from ‘offender’ to ‘non-offender’ was not seamless or straightforward for those with an innate sexual deviancy towards children, caution is therefore advised

Cell cycle regulatory proteins and oral squamous cell carcinoma development

Abstract no. 1279published_or_final_versio

Density-Based Unsupervised Classification for Remote Sensing *

Most image classification methods are supervised and use a parametric model of the classes that have to be detected. The models of the different classes are trained by means of a set of training regions that usually have to be marked and classified by a human interpreter. Unsupervised classification methods are data-driven methods that do not use such a set of training samples. Instead, these methods look for (repeated) structures in the data. In this paper we describe a non-parametric unsupervised classification method. The method uses biased sampling to obtain a learning sample with little noise. Next, density estimation based clustering is used to find the structure in the learning data. The method generates a non-parametric model for each of the classes and uses these models to classify the pixels in the image

A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics

Fluphenazine reduces proteotoxicity in C. elegans and mammalian models of alpha-1-antitrypsin deficiency

The classical form of α1-antitrypsin deficiency (ATD) is associated with hepatic fibrosis and hepatocellular carcinoma. It is caused by the proteotoxic effect of a mutant secretory protein that aberrantly accumulates in the endoplasmic reticulum of liver cells. Recently we developed a model of this deficiency in C. Elegans and adapted it for high-content drug screening using an automated, image-based array scanning. Screening of the Library of Pharmacologically Active Compounds identified fluphenazine (Flu) among several other compounds as a drug which reduced intracellular accumulation of mutant α1-antitrypsin Z (ATZ). Because it is representative of the phenothiazine drug class that appears to have autophagy enhancer properties in addition to mood stabilizing activity, and can be relatively easily re-purposed, we further investigated its effects on mutant ATZ. The results indicate that Flu reverses the phenotypic effects of ATZ accumulation in the C. elegans model of ATD at doses which increase the number of autophagosomes in vivo . Furthermore, in nanomolar concentrations, Flu enhances the rate of intracellular degradation of ATZ and reduces the cellular ATZ load in mammalian cell line models. In the PiZ mouse model Flu reduces the accumulation of ATZ in the liver and mediates a decrease in hepatic fibrosis. These results show that Flu can reduce the proteotoxicity of ATZ accumulation in vivo and, because it has been used safely in humans, this drug can be moved rapidly into trials for liver disease due to ATD. The results also provide further validation for drug discovery using C. elegans models that can be adapted to high-content drug screening platforms and used together with mammalian cell line and animal models. © 2014 Li et al

Cigarette, cigar and pipe smoking, passive smoke exposure, and risk of pancreatic cancer: a population-based study in the San Francisco Bay Area

Abstract Background To examine the influence of cigarette, cigar and pipe smoking, cessation of cigarette smoking and passive smoke exposure on the risk of pancreatic cancer. Methods Exposure data were collected during in-person interviews in a population-based case-control study of pancreatic cancer (N = 532 cases, N = 1701 controls) in the San Francisco Bay Area. Odds ratios (ORs) were adjusted for potential confounders. Results The adjusted odds ratio (OR) of pancreatic cancer among current smokers was 1.9 (95% confidence interval (CI), 1.4-2.7). A significant, positive trend in risk with increasing pack-years of smoking was observed (P-trend <0.0001). Compared with participants who continued to smoke, former smokers had no statistically significant elevation in risk of pancreatic cancer 10 years after smoking cessation, with risk reduced to that of never smokers regardless of prior smoking intensity. Both men and women experienced similar increased risk of pancreatic cancer with increasing smoking duration. Cigar and pipe smoking and exposure to passive smoke were not associated with pancreatic cancer. Conclusions Cigarette smoking is associated with an increased risk of pancreatic cancer. Smokers who had quit for ≥10 years no longer experienced an increased risk. Future work will help to determine the effect of declining smoking rates on pancreatic cancer incidence

Beautiful Mirrors at the LHC

We explore the "Beautiful Mirrors" model, which aims to explain the measured value of $A^b_{FB}$, discrepant at the $2.9\sigma$ level. This scenario introduces vector-like quarks which mix with the bottom, subtly affecting its coupling to the $Z$. The spectrum of the new particles consists of two bottom-like quarks and a charge -4/3 quark, all of which have electroweak interactions with the third generation. We explore the phenomenology and discovery reach for these new particles at the LHC, exploring single mirror quark production modes whose rates are proportional to the same mixing parameters which resolve the $A_{FB}^b$ anomaly. We find that for mirror quark masses $\lesssim 500 GeV, a 14 TeV LHC with 300 {\rm fb}^{-1}$ is required to reasonably establish the scenario and extract the relevant mixing parameters.Comment: version to be published in JHE

In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation