Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

Preliminary reference values for electrocardiography, echocardiography and myocardial morphometry in the European brown hare (Lepus europaeus)

The study aimed at defining reference values for electrocardiographic (ECG) and echocardiographic parameters as well as macroscopic dimensions of the heart and microscopic dimensions of cardiomyocytes in the European brown hare. The studies were conducted on 30 adult, clinically healthy hares of either sex caught in Poland. ECG and echocardiography were performed supravitally on anaesthetized hares. After euthanasia, gross and microscopic myocardial and cardiomyocyte dimensions were determined. Heart rate amounted to 140 ± 37.5 beats/min, the leading rhythm involved the sinus rhythm. P wave time was 26 ± 5 ms, PQ time was 80 ms, QRS time was 29 ± 3.5 ms, and ST was 97.5 ± 7 ms. Echocardiography determined a left ventricular wall end-diastolic diameter of 8.6 ± 2.0 mm and an intraventricular septum end-diastolic diameter of 5.75 ± 1.0 mm. The thickness of the interventricular septum corresponded to that of the free wall of the left ventricle, a finding consistent with physiological hypertrophy. Preliminary reference values were established for echocardiography. The findings were similar to those obtained at necropsy. The ECG and echocardiographic studies represent the first supravital examination of cardiac function in the hare. The obtained results illustrate adaptation of hare's myocardium to its mode of life. The cardiac findings resemble the athlete's heart syndrome described in humans. The findings may prove useful in further studies on the physiology of the cardio-vascular system in the hare

The Hydrophobic Core of Twin-Arginine Signal Sequences Orchestrates Specific Binding to Tat-Pathway Related Chaperones

Redox enzyme maturation proteins (REMPs) bind pre-proteins destined for translocation across the bacterial cytoplasmic membrane via the twin-arginine translocation system and enable the enzymatic incorporation of complex cofactors. Most REMPs recognize one specific pre-protein. The recognition site usually resides in the N-terminal signal sequence. REMP binding protects signal peptides against degradation by proteases. REMPs are also believed to prevent binding of immature pre-proteins to the translocon. The main aim of this work was to better understand the interaction between REMPs and substrate signal sequences. Two REMPs were investigated: DmsD (specific for dimethylsulfoxide reductase, DmsA) and TorD (specific for trimethylamine N-oxide reductase, TorA). Green fluorescent protein (GFP) was genetically fused behind the signal sequences of TorA and DmsA. This ensures native behavior of the respective signal sequence and excludes any effects mediated by the mature domain of the pre-protein. Surface plasmon resonance analysis revealed that these chimeric pre-proteins specifically bind to the cognate REMP. Furthermore, the region of the signal sequence that is responsible for specific binding to the corresponding REMP was identified by creating region-swapped chimeric signal sequences, containing parts of both the TorA and DmsA signal sequences. Surprisingly, specificity is not encoded in the highly variable positively charged N-terminal region of the signal sequence, but in the more similar hydrophobic C-terminal parts. Interestingly, binding of DmsD to its model substrate reduced membrane binding of the pre-protein. This property could link REMP-signal peptide binding to its reported proofreading function

Large Scale Structure of the Universe

Galaxies are not uniformly distributed in space. On large scales the Universe displays coherent structure, with galaxies residing in groups and clusters on scales of ~1-3 Mpc/h, which lie at the intersections of long filaments of galaxies that are >10 Mpc/h in length. Vast regions of relatively empty space, known as voids, contain very few galaxies and span the volume in between these structures. This observed large scale structure depends both on cosmological parameters and on the formation and evolution of galaxies. Using the two-point correlation function, one can trace the dependence of large scale structure on galaxy properties such as luminosity, color, stellar mass, and track its evolution with redshift. Comparison of the observed galaxy clustering signatures with dark matter simulations allows one to model and understand the clustering of galaxies and their formation and evolution within their parent dark matter halos. Clustering measurements can determine the parent dark matter halo mass of a given galaxy population, connect observed galaxy populations at different epochs, and constrain cosmological parameters and galaxy evolution models. This chapter describes the methods used to measure the two-point correlation function in both redshift and real space, presents the current results of how the clustering amplitude depends on various galaxy properties, and discusses quantitative measurements of the structures of voids and filaments. The interpretation of these results with current theoretical models is also presented.Comment: Invited contribution to be published in Vol. 8 of book "Planets, Stars, and Stellar Systems", Springer, series editor T. D. Oswalt, volume editor W. C. Keel, v2 includes additional references, updated to match published versio

Comparison of hospital charge prediction models for gastric cancer patients: neural network vs. decision tree models

<p>Abstract</p> <p>Background</p> <p>In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients.</p> <p>Methods</p> <p>Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes.</p> <p>Results</p> <p>After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model.</p> <p>Conclusion</p> <p>ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.</p

No evidence for UV-based nest-site selection in sticklebacks

BACKGROUND: Nests are built in various animal taxa including fish. In systems with exclusive male parental care, the choice of a nest site may be an important component of male fitness. The nest site may influence male attractiveness as a mate, and male, embryo, and juvenile survival probabilities. Reproductively active three-spined stickleback males establish and defend a territory in which they build a nest. Territories can differ remarkably in qualities that influence male and female reproductive success like predation risk or abiotic factors such as dissolved oxygen concentration or lighting conditions. The latter may be important because in sticklebacks the extended visual capability into the ultraviolet (UV) wave range plays a role in female mate choice. Males are thus expected to be choosy about the habitat in which they will build their nest. RESULTS: We tested nest-site choice in male three-spined sticklebacks with respect to different UV lighting conditions. Reproductively active males were given the simultaneous choice to build their nest either in an UV-rich (UV+) or an UV-lacking (UV-) environment. Males exhibited no significant nest-site preferences with respect to UV+ or UV-. However, larger males and also heavier ones completed their nests earlier. CONCLUSION: We found that UV radiation as well as differences in luminance had no influence on nest-site choice in three-spined sticklebacks. Males that built in the UV-rich environment were not different in any trait (body traits and UV reflection traits) from males that built in the UV-poor environment. There was a significant effect of standard length and body mass on the time elapsed until nest completion in the UV experiment. The larger and heavier a male, the faster he completed his nest. In the brightness control experiment there was a significant effect only of body mass on the duration of nest completion. Whether nest building preferences with respect to UV lighting conditions are context dependent needs to be tested for instance by nest-site choice experiment under increased predation risk

DNA damage induced by cis- and carboplatin as indicator for in vitro sensitivity of ovarian carcinoma cells

<p>Abstract</p> <p>Background</p> <p>The DNA damage by platinum cytostatics is thought to be the main cause of their cytotoxicity. Therefore the measurement of the DNA damage induced by cis- and carboplatin should reflect the sensitivity of cancer cells toward the platinum chemotherapeutics.</p> <p>Methods</p> <p>DNA damage induced by cis- and carboplatin in primary cells of ovarian carcinomas was determined by the alkaline comet assay. In parallel, the reduction of cell viability was measured by the fluorescein diacetate (FDA) hydrolysis assay.</p> <p>Results</p> <p>While in the comet assay the isolated cells showed a high degree of DNA damage after a 24 h treatment, cell viability revealed no cytotoxicity after that incubation time. The individual sensitivities to DNA damage of 12 tumour biopsies differed up to a factor of about 3. DNA damage after a one day treatment with cis- or carboplatin correlated well with the cytotoxic effects after a 7 day treatment (r = 0,942 for cisplatin r = 0.971 for carboplatin). In contrast to the platinum compounds the correlation of DNA damage and cytotoxicity induced by adriamycin was low (r = 0,692), or did not exist for gemcitabine.</p> <p>Conclusion</p> <p>The measurement of DNA damage induced by cis- and carboplatin is an accurate method to determine the in vitro chemosensitivity of ovarian cancer cells towards these cytostatics, because of its quickness, sensitivity, and low cell number needed.</p