Combining frequency and time domain approaches to systems with multiple spike train input and output

A frequency domain approach and a time domain approach have been combined in an investigation of the behaviour of the primary and secondary endings of an isolated muscle spindle in response to the activity of two static fusimotor axons when the parent muscle is held at a fixed length and when it is subjected to random length changes. The frequency domain analysis has an associated error process which provides a measure of how well the input processes can be used to predict the output processes and is also used to specify how the interactions between the recorded processes contribute to this error. Without assuming stationarity of the input, the time domain approach uses a sequence of probability models of increasing complexity in which the number of input processes to the model is progressively increased. This feature of the time domain approach was used to identify a preferred direction of interaction between the processes underlying the generation of the activity of the primary and secondary endings. In the presence of fusimotor activity and dynamic length changes imposed on the muscle, it was shown that the activity of the primary and secondary endings carried different information about the effects of the inputs imposed on the muscle spindle. The results presented in this work emphasise that the analysis of the behaviour of complex systems benefits from a combination of frequency and time domain methods

Economic burden of illness of acute coronary syndromes: medical and productivity costs

<p>Abstract</p> <p>Background</p> <p>The significant economic burden associated with acute coronary syndromes (ACS) provides a need to evaluate both medical costs and productivity costs, according to evolving guideline-driven ACS treatment strategies, medical management (MM), percutaneous coronary intervention (PCI), or coronary artery bypass graft (CABG).</p> <p>Methods</p> <p>Commercially insured individuals, aged 18-64, with an emergency room (ER) visit or hospitalization accompanied by an ACS diagnosis (index event) were identified from a large claims database between 01/2004 and 12/2005 with a 1-year follow-up period. Patients who had an ACS diagnosis in the 12 months prior to their index event were excluded. Patients were divided into 3 groups according to treatment strategies during the index event: MM, PCI, or CABG. A subset of patients was identified for the productivity cost analysis exploring short-term disability and absenteeism costs. Multivariate generalized linear models were performed to examine the ACS costs by 3 different treatment strategies.</p> <p>Results</p> <p>A total of 10,487 patients were identified for the medical cost analysis. The total 1-year medical costs (index event costs plus the 1-year follow-up costs) were lowest for MM patients ($34,087), followed by PCI patients ($52,673) and CABG patients ($86,914). Of the 3,080 patients in the productivity costs analysis, 2,454 patients were identified in the short-term disability cohort and 626 patients were identified in the absenteeism cohort. Both the estimated mean total 1-year short-term disability and absenteeism costs were highest for CABG patients ($17,335, $14,960, respectively) compared to MM patients ($6,048, $9,826, respectively) and PCI patients ($9,221, $9,460, respectively).</p> <p>Conclusions</p> <p>Both total 1-year medical costs and 1-year productivity costs are substantial for working-aged individuals with ACS. These costs differ according to the type of treatment strategy, with CABG having higher costs compared to either PCI or MM.</p

A poisson regression approach for modelling spatial autocorrelation between geographically referenced observations

Abstract Background Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, omission of that autocorrelation can bias parameter estimates and yield incorrect standard error estimates. Methods We used age standardised incidence ratios (SIRs) of esophageal cancer (EC) from the Babol cancer registry from 2001 to 2005, and extracted socioeconomic indices from the Statistical Centre of Iran. The following models for SIR were used: (1) Poisson regression with agglomeration-specific nonspatial random effects; (2) Poisson regression with agglomeration-specific spatial random effects. Distance-based and neighbourhood-based autocorrelation structures were used for defining the spatial random effects and a pseudolikelihood approach was applied to estimate model parameters. The Bayesian information criterion (BIC), Akaike's information criterion (AIC) and adjusted pseudo R2, were used for model comparison. Results A Gaussian semivariogram with an effective range of 225 km best fit spatial autocorrelation in agglomeration-level EC incidence. The Moran's I index was greater than its expected value indicating systematic geographical clustering of EC. The distance-based and neighbourhood-based Poisson regression estimates were generally similar. When residual spatial dependence was modelled, point and interval estimates of covariate effects were different to those obtained from the nonspatial Poisson model. Conclusions The spatial pattern evident in the EC SIR and the observation that point estimates and standard errors differed depending on the modelling approach indicate the importance of accounting for residual spatial correlation in analyses of EC incidence in the Caspian region of Iran. Our results also illustrate that spatial smoothing must be applied with care.</p

Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh

<p>Abstract</p> <p>Background</p> <p>The study attempts to develop an ordinal logistic regression (OLR) model to identify the determinants of child malnutrition instead of developing traditional binary logistic regression (BLR) model using the data of Bangladesh Demographic and Health Survey 2004.</p> <p>Methods</p> <p>Based on weight-for-age anthropometric index (Z-score) child nutrition status is categorized into three groups-severely undernourished (< -3.0), moderately undernourished (-3.0 to -2.01) and nourished (≥-2.0). Since nutrition status is ordinal, an OLR model-proportional odds model (POM) can be developed instead of two separate BLR models to find predictors of both malnutrition and severe malnutrition if the proportional odds assumption satisfies. The assumption is satisfied with low p-value (0.144) due to violation of the assumption for one co-variate. So partial proportional odds model (PPOM) and two BLR models have also been developed to check the applicability of the OLR model. Graphical test has also been adopted for checking the proportional odds assumption.</p> <p>Results</p> <p>All the models determine that age of child, birth interval, mothers' education, maternal nutrition, household wealth status, child feeding index, and incidence of fever, ARI & diarrhoea were the significant predictors of child malnutrition; however, results of PPOM were more precise than those of other models.</p> <p>Conclusion</p> <p>These findings clearly justify that OLR models (POM and PPOM) are appropriate to find predictors of malnutrition instead of BLR models.</p

Using a 3D virtual muscle model to link gene expression changes during myogenesis to protein spatial location in muscle

Background: Myogenesis is an ordered process whereby mononucleated muscle precursor cells (myoblasts) fuse into multinucleated myotubes that eventually differentiate into myofibres, involving substantial changes in gene expression and the organisation of structural components of the cells. To gain further insight into the orchestration of these structural changes we have overlaid the spatial organisation of the protein components of a muscle cell with their gene expression changes during differentiation using a new 3D visualisation tool: the Virtual Muscle 3D (VMus3D)

Model Selection in Time Series Studies of Influenza-Associated Mortality

Background: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.published_or_final_versio

Follicle Stimulating Hormone is an accurate predictor of azoospermia in childhood cancer survivors

Funding: RTM is supported by a Wellcome Trust Intermediate Clinical Fellowship (grant no: 098522), https://wellcome.ac.uk/what-we-do/directories/intermediate-clinical-fellowships-people-funded. TWK is supported by Engineering and Physical Sciences Research Council grant EP/P015638/1, http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/P015638/1.The accuracy of Follicle Stimulating Hormone as a predictor of azoospermia in adult survivors of childhood cancer is unclear, with conflicting results in the published literature. A systematic review and post hoc analysis of combined data (n = 367) were performed on all published studies containing extractable data on both serum Follicle Stimulating Hormone concentration and semen concentration in survivors of childhood cancer. PubMed and Medline databases were searched up to March 2017 by two blind investigators. Articles were included if they contained both serum FSH concentration and semen concentration, used World Health Organisation certified methods for semen analysis, and the study participants were all childhood cancer survivors. There was no evidence for either publication bias or heterogeneity for the five studies. For the combined data (n = 367) the optimal Follicle Stimulating Hormone threshold was 10.4 IU/L with specificity 81% (95% CI 76%–86%) and sensitivity 83% (95% CI 76%–89%). The AUC was 0.89 (95%CI 0.86–0.93). A range of threshold FSH values for the diagnosis of azoospermia with their associated sensitivities and specificities were calculated. This study provides strong supporting evidence for the use of serum Follicle Stimulating Hormone as a surrogate biomarker for azoospermia in adult males who have been treated for childhood cancer.Publisher PDFPeer reviewe

Tracking Cats: Problems with Placing Feline Carnivores on δ18O, δD Isoscapes

Several felids are endangered and threatened by the illegal wildlife trade. Establishing geographic origin of tissues of endangered species is thus crucial for wildlife crime investigations and effective conservation strategies. As shown in other species, stable isotope analysis of hydrogen and oxygen in hair (δD(h), δ(18)O(h)) can be used as a tool for provenance determination. However, reliably predicting the spatial distribution of δD(h) and δ(18)O(h) requires confirmation from animal tissues of known origin and a detailed understanding of the isotopic routing of dietary nutrients into felid hair.We used coupled δD(h) and δ(18)O(h) measurements from the North American bobcat (Lynx rufus) and puma (Puma concolor) with precipitation-based assignment isoscapes to test the feasibility of isotopic geo-location of felidae. Hairs of felid and rabbit museum specimens from 75 sites across the United States and Canada were analyzed. Bobcat and puma lacked a significant correlation between H/O isotopes in hair and local waters, and also exhibited an isotopic decoupling of δ(18)O(h) and δD(h). Conversely, strong δD and δ(18)O coupling was found for key prey, eastern cottontail rabbit (Sylvilagus floridanus; hair) and white-tailed deer (Odocoileus virginianus; collagen, bone phosphate).Puma and bobcat hairs do not adhere to expected pattern of H and O isotopic variation predicted by precipitation isoscapes for North America. Thus, using bulk hair, felids cannot be placed on δ(18)O and δD isoscapes for use in forensic investigations. The effective application of isotopes to trace the provenance of feline carnivores is likely compromised by major controls of their diet, physiology and metabolism on hair δ(18)O and δD related to body water budgets. Controlled feeding experiments, combined with single amino acid isotope analysis of diets and hair, are needed to reveal mechanisms and physiological traits explaining why felid hair does not follow isotopic patterns demonstrated in many other taxa

Factors associated with testicular self-examination among unaffected men from multiple-case testicular cancer families

<p>Abstract</p> <p>Background</p> <p>The lifetime testicular cancer (TC) risk in the general population is relatively low (~1 in 250), but men with a family history of TC are at 4 to 9 times greater risk than those without. Some health and professional organizations recommend consideration of testicular self-examination (TSE) for certain high-risk groups (e.g. men with a family history of TC). Yet little is known about factors associated with TSE behaviors in this at-risk group.</p> <p>Methods</p> <p>We collected information on this subject during an on-going NCI multidisciplinary, etiologically-focused, cross-sectional Familial Testicular Cancer (FTC) study. We present the first report specifically targeting TSE behaviors among first- and second-degree relatives (n = 99) of affected men from families with ≥ 2 TC cases. Demographic, medical, knowledge, health belief, and psychological factors consistent with the Health Belief Model (HBM) were evaluated as variables related to TSE behavior, using chi-square tests of association for categorical variables, and t-tests for continuous variables.</p> <p>Results</p> <p>For men in our sample, 46% (n = 46) reported performing TSE regularly and 51% (n = 50) reported not regularly performing TSE. Factors associated (p < .05) with regularly performing TSE in multivariate analysis were physician recommendation and testicular cancer worry. This is the first study to examine TSE in unaffected men from FTC families.</p> <p>Conclusion</p> <p>The findings suggest that, even in this high-risk setting, TSE practices are sub-optimal. Our data provide a basis for further exploring psychosocial issues that are specific to men with a family history of TC, and formulating intervention strategies aimed at improving adherence to TSE guidelines.</p

Does the early frog catch the worm? Disentangling potential drivers of a parasite age–intensity relationship in tadpoles

The manner in which parasite intensity and aggregation varies with host age can provide insights into parasite dynamics and help identify potential means of controlling infections in humans and wildlife. A significant challenge is to distinguish among competing mechanistic hypotheses for the relationship between age and parasite intensity or aggregation. Because different mechanisms can generate similar relationships, testing among competing hypotheses can be difficult, particularly in wildlife hosts, and often requires a combination of experimental and model fitting approaches. We used field data, experiments, and model fitting to distinguish among ten plausible drivers of a curvilinear age–intensity relationship and increasing aggregation with host age for echinostome trematode infections of green frogs. We found little support for most of these proposed drivers but did find that the parsimonious explanation for the observed age–intensity relationship was seasonal exposure to echinostomes. The parsimonious explanation for the aggregated distribution of parasites in this host population was heterogeneity in exposure. A predictive model incorporating seasonal exposure indicated that tadpoles hatching early or late in the breeding season should have lower trematode burdens at metamorphosis, particularly with simulated warmer climates. Application of this multi-pronged approach (field surveys, lab experiments, and modeling) to additional parasite–host systems could lead to discovery of general patterns in the drivers of parasite age–intensity and age–distribution relationships