Detection rate of FNA cytology in medullary thyroid carcinoma: a meta-analysis.

BACKGROUND: The early detection of medullary thyroid carcinoma (MTC) can improve patient prognosis, because histological stage and patient age at diagnosis are highly relevant prognostic factors. As a consequence, delay in the diagnosis and/or incomplete surgical treatment should correlate with a poorer prognosis for patients. Few papers have evaluated the specific capability of fine-needle aspiration cytology (FNAC) to detect MTC, and small series have been reported. This study conducts a meta-analysis of published data on the diagnostic performance of FNAC in MTC to provide more robust estimates. RESEARCH DESIGN AND METHODS: A comprehensive computer literature search of the PubMed/MEDLINE, Embase and Scopus databases was conducted by searching for the terms 'medullary thyroid' AND 'cytology', 'FNA', 'FNAB', 'FNAC', 'fine needle' or 'fine-needle'. The search was updated until 21 March 2014, and no language restrictions were used. RESULTS: Fifteen relevant studies and 641 MTC lesions that had undergone FNAC were included. The detection rate (DR) of FNAC in patients with MTC (diagnosed as 'MTC' or 'suspicious for MTC') on a per lesion-based analysis ranged from 12·5% to 88·2%, with a pooled estimate of 56·4% (95% CI: 52·6-60·1%). The included studies were statistically heterogeneous in their estimates of DR (I-square >50%). Egger's regression intercept for DR pooling was 0·03 (95% CI: -3·1 to 3·2, P = 0·9). The study that reported the largest MTC series had a DR of 45%. Data on immunohistochemistry for calcitonin in diagnosing MTC were inconsistent for the meta-analysis. CONCLUSIONS: The presented meta-analysis demonstrates that FNAC is able to detect approximately one-half of MTC lesions. These findings suggest that other techniques may be needed in combination with FNAC to diagnose MTC and avoid false negative results.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Melan-A-specific cytotoxic T cells are associated with tumor regression and autoimmunity following treatment with anti-CTLA-4.

PURPOSE: Ipilimumab is a monoclonal antibody that blocks the immune-inhibitory interaction between CTL antigen 4 (CTLA-4) and its ligands on T cells. Clinical trials in cancer patients with ipilimumab have shown promising antitumor activity, particularly in patients with advanced melanoma. Often, tumor regressions in these patients are correlated with immune-related side effects such as dermatitis, enterocolitis, and hypophysitis. Although these reactions are believed to be immune-mediated, the antigenic targets for the cellular or humoral immune response are not known. EXPERIMENTAL DESIGN: We enrolled patients with advanced melanoma in a phase II study with ipilimumab. One of these patients experienced a complete remission of his tumor. The specificity and functional properties of CD8-positive T cells in his peripheral blood, in regressing tumor tissue, and at the site of an immune-mediated skin rash were investigated. RESULTS: Regressing tumor tissue was infiltrated with CD8-positive T cells, a high proportion of which were specific for Melan-A. The skin rash was similarly infiltrated with Melan-A-specific CD8-positive T cells, and a dramatic (>30-fold) increase in Melan-A-specific CD8-positive T cells was apparent in peripheral blood. These cells had an effector phenotype and lysed Melan-A-expressing tumor cells. CONCLUSIONS: Our results show that Melan-A may be a major target for both the autoimmune and antitumor reactions in patients treated with anti-CTLA-4, and describe for the first time the antigen specificity of CD8-positive T cells that mediate tumor rejection in a patient undergoing treatment with an anti-CTLA-4 antibody. These findings may allow a better integration of ipilimumab into other forms of immunotherapy.

Do brief alcohol motivational interventions work like we think they do?

BACKGROUND: Questions remain about how brief motivational interventions (BMIs) for unhealthy alcohol use work, and addressing these questions may be important for improving their efficacy. Therefore, we assessed the effects of various characteristics of BMIs on drinking outcomes across 3 randomized controlled trials (RCTs). METHODS: Audio recordings of 314 BMIs were coded. We used the global rating scales of the Motivational Interviewing Skills Code (MISC) 2.1: counselor's acceptance, empathy, and motivational interviewing (MI) spirit, and patient's self-exploration were rated. MI proficiency was defined as counselor's rating scale scores ≥5. We also used the structure, confrontation, and advice subscale scores of the Therapy Process Rating Scale and the Working Alliance Inventory. We examined these process characteristics in interventions across 1 U.S. RCT of middle-aged medical inpatients with unhealthy alcohol use (n = 124) and 2 Swiss RCTs of young men with binge drinking in a nonclinical setting: Swiss-one (n = 62) and Swiss-two (n = 128). We assessed the associations between these characteristics and drinks/d reported by participants 3 to 6 months after study entry. RESULTS: In all 3 RCTs, mean MISC counselor's rating scales scores were consistent with MI proficiency. In overdispersed Poisson regression models, most BMI characteristics were not significantly associated with drinks/d in follow-up. In the U.S. RCT, confrontation and self-exploration were associated with more drinking. Giving advice was significantly associated with less drinking in the Swiss-one RCT. Contrary to expectations, MI spirit was not consistently associated with drinking across studies. CONCLUSIONS: Across different populations and settings, intervention characteristics viewed as central to efficacious BMIs were neither robust nor consistent predictors of drinking outcome. Although there may be alternative reasons why the level of MI processes was not predictive of outcomes in these studies (limited variability in scores), efforts to understand what makes BMIs efficacious may require attention to factors beyond intervention process characteristics typically examined.

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Validation of Logistic Regression Models for Landslide Susceptibility Maps

A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed and documented during the field studies. The validation analysis is exploited to investigate the quality of mapping.

Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity.

Pulse wave velocity (PWV) is a surrogate of arterial stiffness and represents a non-invasive marker of cardiovascular risk. The non-invasive measurement of PWV requires tracking the arrival time of pressure pulses recorded in vivo, commonly referred to as pulse arrival time (PAT). In the state of the art, PAT is estimated by identifying a characteristic point of the pressure pulse waveform. This paper demonstrates that for ambulatory scenarios, where signal-to-noise ratios are below 10 dB, the performance in terms of repeatability of PAT measurements through characteristic points identification degrades drastically. Hence, we introduce a novel family of PAT estimators based on the parametric modeling of the anacrotic phase of a pressure pulse. In particular, we propose a parametric PAT estimator (TANH) that depicts high correlation with the Complior(R) characteristic point D1 (CC = 0.99), increases noise robustness and reduces by a five-fold factor the number of heartbeats required to obtain reliable PAT measurements.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Online Robust 3D Mapping Using Structure from Motion Cues

This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene

Robust decoupled visual servoing based on structured light

This paper focuses on the problem of realizing a plane-to-plane virtual link between a camera attached to the end-effector of a robot and a planar object. In order to do the system independent to the object surface appearance, a structured light emitter is linked to the camera so that 4 laser pointers are projected onto the object. In a previous paper we showed that such a system has good performance and nice characteristics like partial decoupling near the desired state and robustness against misalignment of the emitter and the camera (J. Pages et al., 2004). However, no analytical results concerning the global asymptotic stability of the system were obtained due to the high complexity of the visual features utilized. In this work we present a better set of visual features which improves the properties of the features in (J. Pages et al., 2004) and for which it is possible to prove the global asymptotic stability

Implementation of a robust coded structured light technique for dynamic 3D measurements

This paper presents the implementation details of a coded structured light system for rapid shape acquisition of unknown surfaces. Such techniques are based on the projection of patterns onto a measuring surface and grabbing images of every projection with a camera. Analyzing the pattern deformations that appear in the images, 3D information of the surface can be calculated. The implemented technique projects a unique pattern so that it can be used to measure moving surfaces. The structure of the pattern is a grid where the color of the slits are selected using a De Bruijn sequence. Moreover, since both axis of the pattern are coded, the cross points of the grid have two codewords (which permits to reconstruct them very precisely), while pixels belonging to horizontal and vertical slits have also a codeword. Different sets of colors are used for horizontal and vertical slits, so the resulting pattern is invariant to rotation. Therefore, the alignment constraint between camera and projector considered by a lot of authors is not necessary

Necessary and sufficient conditions for robust stability using modal intervals

In this paper, robustness of parametric systems is analyzed using a new approach to interval mathematics called Modal Interval Analysis. Modal Intervals are an interval extension that, instead of classic intervals, recovers some of the properties required by a numerical system. Modal Interval Analysis not only simplifies the computation of interval functions but allows semantic interpretation of their results. Necessary, sufficient and, in some cases, necessary and sufficient conditions for robust performance are presented

Leprosy reactions: the effect of gender and household contacts

Various host-related factors have been reported as relevant risk factors for leprosy reactions. To support a new hypothesis that an antigenic load in local tissues that is sufficient to trigger the immune response may come from an external supply of Mycobacterium leprae organisms, the prevalence of reactional leprosy was assessed against the number of household contacts. The number of contacts was ascertained at diagnosis in leprosy patients coming from an endemic area of Brazil. The prevalence of reactions (patients with reactions/total patients) was fitted by binomial regression and the risk difference (RD) was estimated with a semi-robust estimation of variance as a measure of effect. Five regression models were fitted. Model 1 included only the main exposure variable "number of household contacts"; model 2 included all four explanatory variables ("contacts", "fertile age", "number of skin lesions" and "bacillary index") that were found to be associated with the outcome upon univariate analysis; models 3-5 contained various combinations of three predictors. Male and female patients were analyzed separately. In females, household contacts were a significant predictor for leprosy reactions in model 1 [crude RD = 0.06; 95% confidence interval (CI) = 0.01; 0.12] and model 5 (RD = 0.05; CI = 0.02; 0.09), which included contacts, bacillary index and skin lesions as predictors. Other models were unsatisfactory because the joint presence of fertile age and bacillary index was a likely source of multicollinearity. No significant results were obtained for males. The likely interpretation of our findings might suggest that in female patients, leprosy reactions may be triggered by an external spreading of M. leprae by healthy carrier family members. The small number of observations is an obvious limitation of our study which requires larger confirmatory studies.