Expression of Novel Kinase MAP3K19 in Various Cancers and Survival Correlations.

Mitogen Activated Protein (MAP) kinases are a category of serine/threonine kinases that have been demonstrated to regulate intracellular events including stress responses, developmental processes, and cancer progression Although many MAP kinases have been extensively studied in various disease processes, MAP3K19 is an understudied kinase whose activities have been linked to lung disease and fibroblast development. In this manuscript, we use bioinformatics databases starBase, GEPIA, and KMPlotter, to establish baseline expressions of MAP3K19 in different tissue types and its correlation with patient survival in different cancers.

Evaluation of Extracellular Matrix Composition to Improve Breast Cancer Modeling.

The development of resistance to therapy is a significant obstacle to effective therapeutic regimens. Evaluating the effects of oncology drugs in the laboratory setting is limited by the lack of translational models that accurately recapitulate cell-microenvironment interactions present in tumors. Acquisition of resistance to therapy is facilitated, in part, by the composition of the tumor extracellular matrix (ECM), with the primary current in vitro model using collagen I (COL I). Here we seek to identify the prevalence of COL I-enhanced expression in the triple-negative breast cancer (TNBC) subtype. Furthermore, we identify if methods of response to therapy are altered depending on matrix composition. We demonstrated that collagen content varies in patient tumor samples across subtypes, with COL I expression dramatically increased in typically less aggressive estrogen receptor (ER)-positive(ER+)/progesterone receptor (PGR)-positive (PGR+) cancers irrespective of patient age or race. These findings are of significance considering how frequently COL I is implicated in tumor progression. In vitro analyses of ER+ and ER-negative (ER-) cell lines were used to determine the effects of ECM content (collagen I, collagen IV, fibronectin, and laminin) on proliferation, cellular phenotype, and survival. Neither ER+ nor ER- cells demonstrated significant increases in proliferation when cultured on these ECM substrates. ER- cells cultured on these substrates were sensitized to both chemotherapy and targeted therapy. In addition, MDA-MB-231 cells expressed different morphologies, binding affinities, and stiffness across these substrates. We also demonstrated that ECM composition significantly alters transcription of senescence-associated pathways across ER+ and ER- cell lines. Together, these results suggest that complex matrix composites should be incorporated into in vitro tumor models, especially for the drug-resistant TNBC subtype. Impact statement The importance of tumor extracellular matrix (ECM) in disease progression is often inadequately represented in models of breast cancer that rely heavily on collagen I and Matrigel. Through immunohistochemistry analysis of patient breast tumors, we show a wide variation in collagen content based on subtype, specifically a repression of fibril collagens in the receptor negative subtype, irrespective of age and race. We also demonstrated that tumor ECM composition alters cellular elasticity and oncogenic pathway activation demonstrating that physiologically relevant three-dimensional models of breast cancer should include an ECM that is subtype specific.

Resolution enhancement of imaging small-scale portions in a compactly supported function.

The ambiguity involved in reconstructing an image from limited Fourier data is removed using a new technique that incorporates prior knowledge of the location of regions containing small-scale features of interest. The prior discrete Fourier transform (PDFT) method for image reconstruction incorporates prior knowledge of the support, and perhaps general shape, of the object function being reconstructed through the use of a weight function. The new approach extends the PDFT by allowing different weight functions to modulate the different spatial frequency components of the reconstructed image. The effectiveness of the new method is tested on one- and two-dimensional simulations.

Quantifying the spatial risk of Avian Influenza introduction into British poultry by wild birds.

The transmission of pathogens across the interface between wildlife and livestock presents a challenge to the development of effective surveillance and control measures. Wild birds, especially waterbirds such as the Anseriformes and Charadriiformes are considered to be the natural hosts of Avian Influenza (AI), and are presumed to pose one of the most likely vectors for incursion of AI into European poultry flocks. We have developed a generic quantitative risk map, derived from the classical epidemiological risk equation, to describe the relative, spatial risk of disease incursion into poultry flocks via wild birds. We then assessed the risk for AI incursion into British flocks. The risk map suggests that the majority of AI incursion risk is highly clustered within certain areas of Britain, including in the east, the south west and the coastal north-west of England. The clustering of high risk areas concentrates total risk in a relatively small land area; the top 33% of cells contribute over 80% of total incursion risk. This suggests that targeted risk-based sampling in a relatively small geographical area could be a much more effective and cost-efficient approach than representative sampling. The generic nature of the risk map method, allows rapid updating and application to other diseases transmissible between wild birds and poultry.

Resolution enhancement in computerized tomographic imaging.

We consider the problem of reconstructing an object function f(r) from finitely many linear functional values. In our main application, the function f(r) is a tomographic image, and the data are integrals of f(r) along thin strips. Because the data are limited, resolution can be enhanced through the inclusion of prior knowledge. One way to do that, a generalization of the prior discrete Fourier transform (PDFT) method, was suggested in 1982 [SIAM J. Appl. Math.42,933 (1982)] but was found to be difficult to implement for the tomography problem, and that application was not pursued. Recent advances in approximating the PDFT make it possible to achieve the desired resolution enhancement in an easily implemented procedure.

Reconstruction of 2D PET data with Monte Carlo generated system matrix for generalized natural pixels.

In discrete detector PET, natural pixels are image basis functions calculated from the response of detector pairs. By using reconstruction with natural pixel basis functions, the discretization of the object into a predefined grid can be avoided. Here, we propose to use generalized natural pixel reconstruction. Using this approach, the basis functions are not the detector sensitivity functions as in the natural pixel case but uniform parallel strips. The backprojection of the strip coefficients results in the reconstructed image. This paper proposes an easy and efficient way to generate the matrix M directly by Monte Carlo simulation. Elements of the generalized natural pixel system matrix are formed by calculating the intersection of a parallel strip with the detector sensitivity function. These generalized natural pixels are easier to use than conventional natural pixels because the final step from solution to a square pixel representation is done by simple backprojection. Due to rotational symmetry in the PET scanner, the matrix M is block circulant and only the first blockrow needs to be stored. Data were generated using a fast Monte Carlo simulator using ray tracing. The proposed method was compared to a listmode MLEM algorithm, which used ray tracing for doing forward and backprojection. Comparison of the algorithms with different phantoms showed that an improved resolution can be obtained using generalized natural pixel reconstruction with accurate system modelling. In addition, it was noted that for the same resolution a lower noise level is present in this reconstruction. A numerical observer study showed the proposed method exhibited increased performance as compared to a standard listmode EM algorithm. In another study, more realistic data were generated using the GATE Monte Carlo simulator. For these data, a more uniform contrast recovery and a better contrast-to-noise performance were observed. It was observed that major improvements in contrast recovery were obtained with MLEM when the correct system matrix was used instead of simple ray tracing. The correct modelling was the major cause of improved contrast for the same background noise. Less important factors were the choice of the algorithm (MLEM performed better than ART) and the basis functions (generalized natural pixels gave better results than pixels).

Choosing parameters in block-iterative or ordered subset reconstruction algorithms.

Viewed abstractly, all the algorithms considered here are designed to provide a nonnegative solution x to the system of linear equations y = Px, where y is a vector with positive entries and P a matrix whose entries are nonnegative and with no purely zero columns. The expectation maximization maximum likelihood method, as it occurs in emission tomography, and the simultaneous multiplicative algebraic reconstruction technique are slow to converge on large data sets; accelerating convergence through the use of block-iterative or ordered subset versions of these algorithms is a topic of considerable interest. These block-iterative versions involve relaxation and normalization parameters, the correct selection of which may not be obvious to all users. The algorithms are not faster merely by virtue of being block-iterative; the correct choice of the parameters is crucial. Through a detailed discussion of the theoretical foundations of these methods, we come to a better understanding of the precise roles these parameters play.

Childhood trauma levels in individuals attending adult mental health services: An evaluation of clinical records and structured measurement of childhood trauma.

Despite an increased awareness regarding the prevalence and impact of childhood trauma, especially childhood sexual abuse (CSA), few studies examine the clinical reporting of such childhood experiences. This study compared the prevalence of childhood trauma recorded in individual's clinical notes to those ascertained with a structured validated questionnaire, examined which forms of childhood trauma were less likely to be reported to the treating mental health team and established which demographic or clinical factors were associated with reporting of childhood trauma. The prevalence of childhood trauma was ascertained using both the Childhood Trauma Questionnaire (CTQ) and a lifetime retrospective clinical note review in 129 individuals attending a general adult mental health service. Individuals were evaluated for the presence of mental health disorders, impulsivity, symptom severity and disability. Using the CTQ, childhood trauma was noted in 77% of individuals and recorded in 38% of individual's clinical notes (p<0.001). The greatest differences between CTQ reporting and clinical note documentation were noted for emotional neglect (62% versus 13.2%), physical neglect (48.1% versus 5.4%) and CSA (24.8% versus 8.5%). Childhood trauma was associated with increased psychopathology and greater symptom severity, and was particularly prevalent for individuals with personality disorders. This study demonstrated high rates of childhood trauma amongst adults attending a general adult mental health service. Furthermore, we demonstrated high rates of either non-enquiry from mental health professionals and/or high rates of non-documentation of childhood trauma by mental health professionals. Given the disparity between reporting of childhood trauma in clinical notes and findings with the CTQ, the use of a standardised questionnaire for the assessment of childhood trauma should be considered when performing a comprehensive mental health history.

An iterative transmission algorithm incorporating cross-talk correction for SPECT.

Simultaneous emission/transmission acquisitions in cardiac SPECT with a Tc99m/Gd153 source combination offer the capability for nonuniform attenuation correction. However, cross-talk of Tc99m photons downscattered into the Gd153 energy window contaminates the reconstructed transmission map used for attenuation correction. The estimated cross-talk contribution can be subtracted prior to transmission reconstruction or incorporated in the reconstruction algorithm itself. In this work, we propose an iterative transmission algorithm (MLTG-S) based on the maximum-likelihood gradient algorithm (MLTG) that explicitly accounts for this cross-talk estimate. Clinical images were acquired on a three-headed SPECT camera, acquiring Tc99m emission and Gd153 transmission images simultaneously. Subtracting the cross-talk estimate prior to transmission reconstruction can result in negative and zero values if the estimate is larger than or equal to the count in the transmission projection bin, especially with increased attenuator size or amount of cross-talk. This results in inaccurate attenuation coefficients for MLTG reconstructions with cross-talk subtraction. MLTG-S reconstructions on the other hand, yield better estimates of attenuation maps, by avoiding the subtraction of the cross-talk estimate. Comparison of emission slices corrected for nonuniform attenuation reveals that inaccuracies in the reconstructed attenuation map caused by cross-talk can artificially enhance the extra-cardiac activity, confounding the ability to visualize the left-ventricular walls.

Improving the uptake of systematic reviews: a systematic review of intervention effectiveness and relevance.

OBJECTIVE: Little is known about the barriers, facilitators and interventions that impact on systematic review uptake. The objective of this study was to identify how uptake of systematic reviews can be improved. SELECTION CRITERIA: Studies were included if they addressed interventions enhancing the uptake of systematic reviews. Reports in any language were included. All decisionmakers were eligible. Studies could be randomised trials, cluster-randomised trials, controlled-clinical trials and before-and-after studies. DATA SOURCES: We searched 19 databases including PubMed, EMBASE and The Cochrane Library, covering the full range of publication years from inception to December 2010. Two reviewers independently extracted data and assessed quality according to the Effective Practice and Organisation of Care criteria. RESULTS: 10 studies from 11 countries, containing 12 interventions met our criteria. Settings included a hospital, a government department and a medical school. Doctors, nurses, mid-wives, patients and programme managers were targeted. Six of the studies were geared to improving knowledge and attitudes while four targeted clinical practice. SYNTHESIS OF RESULTS: Three studies of low-to-moderate risk of bias, identified interventions that showed a statistically significant improvement: educational visits, short summaries of systematic reviews and targeted messaging. Promising interventions include e-learning, computer-based learning, inactive workshops, use of knowledge brokers and an e-registry of reviews. Juxtaposing barriers and facilitators alongside the identified interventions, it was clear that the three effective approaches addressed a wide range of barriers and facilitators. DISCUSSION: A limited number of studies were found for inclusion. However, the extensive literature search is one of the strengths of this review. CONCLUSIONS: Targeted messaging, educational visits and summaries are recommended to enhance systematic review uptake. Identified promising approaches need to be developed further. New strategies are required to encompass neglected barriers and facilitators. This review addressed effectiveness and also appropriateness of knowledge uptake strategies.

Making evidence more wanted: a systematic review of facilitators to enhance the uptake of evidence from systematic reviews and meta-analyses.

CONTEXT: The increased uptake of evidence from systematic reviews is advocated because of their potential to improve the quality of decision making for patient care. Systematic reviews can do this by decreasing inappropriate clinical variation and quickly expediting the application of current, effective advances to everyday practice. However, research suggests that evidence from systematic reviews has not been widely adopted by health professionals. Little is known about the facilitators to uptake of research evidence from systematic reviews and meta-analyses. OBJECTIVE: To review the facilitators to the uptake by decision makers, of evidence from systematic, meta-analyses and the databases containing them. SEARCH STRATEGY: We searched 19 databases covering the full range of publication years, utilised three search engines and also personally contacted investigators. Grey literature and knowledge translation research was particularly sought. Reference lists of primary studies and related reviews were also searched. SELECTION CRITERIA: Studies were included if they reported on the views and perceptions of decision makers on the uptake of evidence from systematic reviews, meta-analyses and the databases associated with them. One investigator screened titles to identify candidate articles, and then two reviewers independently assessed the relevance of retrieved articles to exclude studies that did not meet the inclusion criteria. Quality of the included studies was also assessed. DATA EXTRACTION: Using a pre-established taxonomy, two reviewers described the methods of included studies and extracted data that were summarised in tables and then analysed. Differences were resolved by consensus. RESULTS: Of articles initially identified, we selected unique published studies describing at least one facilitator to the uptake of evidence from systematic reviews. The 15 unique studies reported 10 surveys, three qualitative investigations and two mixed studies that addressed potential facilitators. Five studies were from Canada, four from the UK, three from Australia, one from Iran and one from South-east Asia (Indonesia, Malaysia, Thailand and the Philippines), with one study covering both Canada and UK. In total, the 15 studies covered eight countries from four continents. Of 2495 participants in the 15 studies, at least 1343 (53.8%) were physicians. Perceived facilitators to the use of evidence from systematic reviews varied. The 15 studies yielded 54 potential facilitators to systematic review uptake. The five most commonly reported perceived facilitators to uptake of evidence from systematic reviews were the following: the perception that systematic reviews have multiple uses for improving knowledge, research, clinical protocols and evidence-based medicine skills (6/15); a content that included benefits, harms and costs and is current, transparent and timely (6/15); a format with a 1:3:25 staged access and executive summary (5/15); training in use (4/15); and peer-group support (4/15). CONCLUSION: The results expand our understanding of how multiple factors act as facilitators to optimal clinical practice. This systematic review reveals that interventions to foster uptake of evidence from systematic reviews, meta-analyses and The Cochrane Library can build on a broad range of facilitators.

The Influence of Photon Attenuation on Tumor-to-Background and Signal-to-Noise Ratios for SPECT Imaging.

Expanding on the work of Nuyts et. al [1], Bai et. al. [2], and Bai and Shao [3], who all studied the effects of attenuation and attenuation correction on tumor-to-background ratios and signal detection, we have derived a general expression for the tumor-to-background ratio (TBR) for SPECT attenuated data that have been reconstructed with a linear, non-iterative reconstruction operator O. A special case of this is when O represents discrete filtered back-projection (FBP). The TBR of the reconstructed, uncorrected attenuated data (TBR(no-AC)) can be written as a weighted sum of the TBR of the FBP-reconstructed unattenuated data (TBR(FBP)) and the TBR of the FBP-reconstructed "difference" projection data (TBR(diff)). We evaluated the expression for TBR(no-AC) for a variety of objects and attenuation conditions. The ideal observer signal-to-noise ratio (SNR(ideal)) was also computed in projection space, in order to obtain an upper bound on signal detectability for a signal-known-exactly/background-known-exactly (SKE/BKE) detection task. The results generally show that SNR(ideal) is lower for tumors located deeper within the attenuating medium and increases for tumors nearer the edge of the object. In addition, larger values for the uniform attenuation coefficient µ lead to lower values for SNR(ideal). The TBR for FBP-reconstructed, uncorrected attenuated data can both under- and over-estimate the true TBR, depending on several properties of the attenuating medium, including the shape of the attenuator, the uniformity of the attenuator, and the degree to which the data are attenuated.

Image reconstruction from limited Fourier data.

We consider the problem of reconstructing a function f with bounded support S from finitely many values of its Fourier transform F. Although f cannot be band limited since it has bounded support, it is typically the case that f can be modeled as the restriction to S of a sigma-band-limited function, say g. Our reconstruction method is based on such a model for f. Of particular interest is the effect of the choice of sigma > 0 on the resolution.

Image reconstruction: a unifying model for resolution enhancement and data extrapolation. Tutorial.

In reconstructing an object function F(r) from finitely many noisy linear-functional values integral of F(r)Gn(r)dr we face the problem that finite data, noisy or not, are insufficient to specify F(r) uniquely. Estimates based on the finite data may succeed in recovering broad features of F(r), but may fail to resolve important detail. Linear and nonlinear, model-based data extrapolation procedures can be used to improve resolution, but at the cost of sensitivity to noise. To estimate linear-functional values of F(r) that have not been measured from those that have been, we need to employ prior information about the object F(r), such as support information or, more generally, estimates of the overall profile of F(r). One way to do this is through minimum-weighted-norm (MWN) estimation, with the prior information used to determine the weights. The MWN approach extends the Gerchberg-Papoulis band-limited extrapolation method and is closely related to matched-filter linear detection, the approximation of the Wiener filter, and to iterative Shannon-entropy-maximization algorithms. Non-linear versions of the MWN method extend the noniterative, Burg, maximum-entropy spectral-estimation procedure.

Iterative image reconstruction using prior knowledge.

A method is proposed to reconstruct signals from incomplete data. The method, which can be interpreted both as a discrete implementation of the so-called prior discrete Fourier transform (PDFT) spectral estimation technique and as a variant of the algebraic reconstruction technique, allows one to incorporate prior information about the reconstructed signal to improve the resolution of the signal estimated. The context of diffraction tomography and image reconstruction from samples of the far-field scattering amplitude are used to explore the performance of the method. On the basis of numerical computations, the optimum choice of parameters is determined empirically by comparing image reconstructions of the noniterative PDFT algorithm and the proposed iterative scheme.