Feasibility of Passive ECG Bio-sensing and EMA Emotion Reporting Technologies and Acceptability of Just-in-Time Content in a Well-being Intervention, Considerations for Scalability and Improved Uptake.

Researchers increasingly use passive sensing data and frequent self-report to implement personalized mobile health (mHealth) interventions. Yet, we know that certain populations may find these technical protocols burdensome and intervention uptake as well as treatment efficacy may be affected as a result. In the present study, we predicted feasibility (participant adherence to protocol) and acceptability (participant engagement with intervention content) as a function of baseline sociodemographic, mental health, and well-being characteristics of 99 women randomized in the personalized preventive intervention Wellness-for-Two (W-4-2), a randomized trial evaluating stress-related alterations during pregnancy and their effect on infant neurodevelopmental trajectories. The W-4-2 study used ecological momentary assessment (EMA) and wearable electrocardiograph (ECG) sensors to detect physiological stress and personalize the intervention. Participant adherence to protocols was 67% for EMAs and 52% for ECG bio-sensors. Higher baseline negative affect significantly predicted lower adherence to both protocols. Women assigned to the intervention group engaged on average with 42% of content they received. Women with higher annual household income were more likely to engage with more of the intervention content. Researchers should carefully consider tailoring of the intensity of technical intervention protocols to reduce fatigue, especially among participants with higher baseline negative affect, which may improve intervention uptake and efficacy findings at scale.

Maximum likelihood wavelet density estimation with applications to image and shape matching.

Density estimation for observational data plays an integral role in a broad spectrum of applications, e.g., statistical data analysis and information-theoretic image registration. Of late, wavelet-based density estimators have gained in popularity due to their ability to approximate a large class of functions, adapting well to difficult situations such as when densities exhibit abrupt changes. The decision to work with wavelet density estimators brings along with it theoretical considerations (e.g., non-negativity, integrability) and empirical issues (e.g., computation of basis coefficients) that must be addressed in order to obtain a bona fide density. In this paper, we present a new method to accurately estimate a non-negative density which directly addresses many of the problems in practical wavelet density estimation. We cast the estimation procedure in a maximum likelihood framework which estimates the square root of the density radicalp, allowing us to obtain the natural non-negative density representation ( radicalp)(2). Analysis of this method will bring to light a remarkable theoretical connection with the Fisher information of the density and, consequently, lead to an efficient constrained optimization procedure to estimate the wavelet coefficients. We illustrate the effectiveness of the algorithm by evaluating its performance on mutual information-based image registration, shape point set alignment, and empirical comparisons to known densities. The present method is also compared to fixed and variable bandwidth kernel density estimators.

Kernel Fisher discriminant for shape-based classification in epilepsy.

In this paper, we present the application of kernel Fisher discriminant in the statistical analysis of shape deformations that indicate the hemispheric location of an epileptic focus. The scans of two classes of patients with epilepsy, those with a right and those with a left anterior medial temporal lobe focus (RATL and LATL), as validated by clinical consensus and subsequent surgery, were compared to a set of age and sex matched healthy volunteers using both volume and shape based features. Shape-based features are derived from the displacement field characterizing the non-rigid deformation between the left and right hippocampi of a control or a patient as the case may be. Using the shape-based features, the results show a significant improvement in distinguishing between the controls and the rest (RATL and LATL) vis-a-vis volume-based features. Using a novel feature, namely, the normalized histogram of the 3D displacement field, we also achieved significant improvement over the volume-based feature in classifying the patients as belonging to either of the two classes LATL or RATL, respectively. It should be noted that automated identification of hemispherical foci of epilepsy has not been previously reported.

Data-Driven Discovery of Extravasation Pathway in Circulating Tumor Cells.

Circulating tumor cells (CTCs) play a crucial role in cancer dissemination and provide a promising source of blood-based markers. Understanding the spectrum of transcriptional profiles of CTCs and their corresponding regulatory mechanisms will allow for a more robust analysis of CTC phenotypes. The current challenge in CTC research is the acquisition of useful clinical information from the multitude of high-throughput studies. To gain a deeper understanding of CTC heterogeneity and identify genes, pathways and processes that are consistently affected across tumors, we mined the literature for gene expression profiles in CTCs. Through in silico analysis and the integration of CTC-specific genes, we found highly significant biological mechanisms and regulatory processes acting in CTCs across various cancers, with a particular enrichment of the leukocyte extravasation pathway. This pathway appears to play a pivotal role in the migration of CTCs to distant metastatic sites. We find that CTCs from multiple cancers express both epithelial and mesenchymal markers in varying amounts, which is suggestive of dynamic and hybrid states along the epithelial-mesenchymal transition (EMT) spectrum. Targeting the specific molecular nodes to monitor disease and therapeutic control of CTCs in real time will likely improve the clinical management of cancer progression and metastases.

Thrombospondin-1 repression is mediated via distinct mechanisms in fibroblasts and epithelial cells.

Tumor-associated angiogenesis is postulated to be regulated by the balance between pro- and anti-angiogenic factors. We demonstrate here that the critical step in establishing the angiogenic capability of human tumor cells is the repression of a key secreted anti-angiogenic factor, thrombospondin-1 (Tsp-1). This repression is essential for tumor formation by mammary epithelial cells and kidney cells engineered to express SV40 early region proteins, hTERT, and H-RasV12. In transformed epithelial cells, a signaling pathway leading from Ras to Tsp-1 repression induces the sequential activation of PI3 kinase, Rho and ROCK, leading to activation of Myc through phosphorylation, thereby enabling Myc to repress Tsp-1 transcription. In transformed fibroblasts, however, the repression of Tsp-1 can be achieved by an alternative mechanism involving inactivation of both p53 and pRb. We thus describe novel mechanisms by which the activation of oncogenes in epithelial cells and the inactivation of tumor suppressors in fibroblasts permits angiogenesis and, in turn, tumor formation.

Oxidative glucose metabolism in rat brain during single forepaw stimulation: a spatially localized 1H[13C] nuclear magnetic resonance study.

In the alpha-chloralose-anesthetized rat during single forepaw stimulation, a spatially localized 1H[13C] nuclear magnetic resonance spectroscopic method was used to measure the rate of cerebral [C4]-glutamate isotopic turnover from infused [1,6-(13)C]glucose. The glutamate turnover data were analyzed using a mathematical model of cerebral glucose metabolism to evaluate the tricarboxylic acid (TCA) cycle flux (V(TCA)). During stimulation the value of V(TCA) in the sensorimotor region increased from 0.47 +/- 0.06 (at rest) to 1.44 +/- 0.41 micromol x g(-1) x min(-1) (P < 0.01) in the contralateral hemispheric compartment (24 mm3) and to 0.65 +/- 0.10 micromol x g(-1) x min(-1) (P < 0.03) in the ipsilateral side. Each V(TCA) value was converted to the cerebral metabolic rates of glucose oxidation (oxidative-CMR(glc)) and oxygen consumption (CMR(O2)). These rates were corrected for partial-volume based on activation maps obtained by blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI). The percent increase and the absolute value of oxidative-CMR(glc) in the activated regions are similar to values reported previously for total-CMR(glc) using the same activation paradigm. This indicates that the large majority of energy required for brain activation, in going from the resting to an activated state, is supplied by glucose oxidation. The level of activity during stimulation is relevant to awake animals because the oxidative-CMR(glc) (1.05 +/- 0.28 micromol x g(-1) x min(-1); current study) is in the range of total-CMR(glc) previously reported for awake rats undergoing physiologic activation (0.7-1.4 micromol x g(-1) x min(-1)). It is concluded that oxidative glycolysis is the main source of energy for increased brain activity and a positive BOLD fMRI signal-change occurs in conjunction with a large increase in CMR(O2).

Bayesian image reconstruction in SPECT using higher order mechanical models as priors.

While the ML-EM algorithm for reconstruction for emission tomography is unstable due to the ill-posed nature of the problem. Bayesian reconstruction methods overcome this instability by introducing prior information, often in the form of a spatial smoothness regularizer. More elaborate forms of smoothness constraints may be used to extend the role of the prior beyond that of a stabilizer in order to capture actual spatial information about the object. Previously proposed forms of such prior distributions were based on the assumption of a piecewise constant source distribution. Here, the authors propose an extension to a piecewise linear model-the weak plate-which is more expressive than the piecewise constant model. The weak plate prior not only preserves edges but also allows for piecewise ramplike regions in the reconstruction. Indeed, for the authors' application in SPECT, such ramplike regions are observed in ground-truth source distributions in the form of primate autoradiographs of rCBF radionuclides. To incorporate the weak plate prior in a MAP approach, the authors model the prior as a Gibbs distribution and use a GEM formulation for the optimization. They compare quantitative performance of the ML-EM algorithm, a GEM algorithm with a prior favoring piecewise constant regions, and a GEM algorithm with their weak plate prior. Pointwise and regional bias and variance of ensemble image reconstructions are used as indications of image quality. The authors' results show that the weak plate and membrane priors exhibit improved bias and variance relative to ML-EM techniques.

Bayesian reconstruction of functional images using anatomical information as priors.

Proposes a Bayesian method whereby maximum a posteriori (MAP) estimates of functional (PET and SPECT) images may be reconstructed with the aid of prior information derived from registered anatomical MR images of the same slice. The prior information consists of significant anatomical boundaries that are likely to correspond to discontinuities in an otherwise spatially smooth radionuclide distribution. The authors' algorithm, like others proposed recently, seeks smooth solutions with occasional discontinuities; the contribution here is the inclusion of a coupling term that influences the creation of discontinuities in the vicinity of the significant anatomical boundaries. Simulations on anatomically derived mathematical phantoms are presented. Although computationally intense in its current implication, the reconstructions are improved (ROI-RMS error) relative to filtered backprojection and EM-ML reconstructions. The simulations show that the inclusion of position-dependent anatomical prior Information leads to further improvement relative to Bayesian reconstructions without the anatomical prior. The algorithm exhibits a certain degree of robustness with respect to errors in the location of anatomical boundaries.

Rigid point feature registration using mutual information.

We have developed a new mutual information-based registration method for matching unlabeled point features. In contrast to earlier mutual information-based registration methods, which estimate the mutual information using image intensity information, our approach uses the point feature location information. A novel aspect of our approach is the emergence of correspondence (between the two sets of features) as a natural by-product of joint density estimation. We have applied this algorithm to the problem of geometric alignment of primate autoradiographs. We also present preliminary results on three-dimensional robust matching of sulci derived from anatomical magnetic resonance images. Finally, we present an experimental comparison between the mutual information approach and other recent approaches which explicitly parameterize feature correspondence.

A robust point-matching algorithm for autoradiograph alignment.

We present a novel method for the geometric alignment of autoradiographs of the brain. The method is based on finding the spatial mapping and the one-to-one correspondences (or homologies) between point features extracted from the images and rejecting non-homologies as outliers. In this way, we attempt to account for the local, natural and artifactual differences between the autoradiograph slices. We have used the resulting automated algorithm on a set of left prefrontal cortex autoradiograph slices, specifically demonstrated its ability to perform point outlier rejection, validated its robustness property using synthetically generated spatial mappings and provided an anecdotal visual comparison with the well-known iterated closest-point (ICP) algorithm. Visualization of a stack of aligned left prefrontal cortex autoradiograph slices is also provided.

A Lagrangian relaxation network for graph matching.

A Lagrangian relaxation network for graph matching is presented. The problem is formulated as follows: given graphs G and g, find a permutation matrix M that brings the two sets of vertices into correspondence. Permutation matrix constraints are formulated in the framework of deterministic annealing. Our approach is in the same spirit as a Lagrangian decomposition approach in that the row and column constraints are satisfied separately with a Lagrange multiplier used to equate the two "solutions". Due to the unavoidable symmetries in graph isomorphism (resulting in multiple global minima), we add a symmetry-breaking self-amplification term in order to obtain a permutation matrix. With the application of a fixpoint preserving algebraic transformation to both the distance measure and self-amplification terms, we obtain a Lagrangian relaxation network. The network performs minimization with respect to the Lagrange parameters and maximization with respect to the permutation matrix variables. Simulation results are shown on 100 node random graphs and for a wide range of connectivities.

A minimax entropy registration framework for patient setup verification in radiotherapy.

In external beam radiotherapy (EBRT), patient setup verification over the entire course of fractionated treatment is necessary for accurate delivery of a specified dose to the tumor. We are working on the development of a minimax entropy registration framework for patient setup verification using dual portal images and the treatment planning 3D CT dataset. In this paper, we present an overview of our registration framework, where an iteratively and automatically estimated segmentation of the portal image is utilized to more accurately and robustly register the portal image to the 3D treatment-planning CT data. In addition, we describe initial testing of this approach. We note that, due to low resolution and low contrast of the portal images, this registration presents a difficult problem. We also note that the registration of the images in our proposed method is guided by the bony structure visible in the portal and the 3D CT images. However, since the prostate can move with respect to the pelvic bone, we propose using ultrasound images to quantify this movement.

Introduction of SV40ER and hTERT into mammospheres generates breast cancer cells with stem cell properties.

Emerging evidence suggests that cancers arise in stem/progenitor cells. Yet, the requirements for transformation of these primitive cells remains poorly understood. In this study, we have exploited the 'mammosphere' system that selects for primitive mammary stem/progenitor cells to explore their potential and requirements for transformation. Introduction of Simian Virus 40 Early Region and hTERT into mammosphere-derived cells led to the generation of NBLE, an immortalized mammary epithelial cell line. The NBLEs largely comprised of bi-potent progenitors with long-term self-renewal and multi-lineage differentiation potential. Clonal and karyotype analyses revealed the existence of heterogeneous population within NBLEs with varied proliferation, differentiation and sphere-forming potential. Significantly, injection of NBLEs into immunocompromised mice resulted in the generation of invasive ductal adenocarcinomas. Further, these cells harbored a sub-population of CD44(+)/CD24(-) fraction that alone had sphere- and tumor-initiating potential and resembled the breast cancer stem cell gene signature. Interestingly, prolonged in vitro culturing led to their further enrichment. The NBLE cells also showed increased expression of stemness and epithelial to mesenchymal transition markers, deregulated self-renewal pathways, activated DNA-damage response and cancer-associated chromosomal aberrations-all of which are likely to have contributed to their tumorigenic transformation. Thus, unlike previous in vitro transformation studies that used adherent, more differentiated human mammary epithelial cells our study demonstrates that the mammosphere-derived, less-differentiated cells undergo tumorigenic conversion with only two genetic elements, without requiring oncogenic Ras. Moreover, the striking phenotypic and molecular resemblance of the NBLE-generated tumors with naturally arising breast adenocarcinomas supports the notion of a primitive breast cell as the origin for this subtype of breast cancer. Finally, the NBLEs represent a heterogeneous population of cells with striking plasticity, capable of differentiation, self-renewal and tumorigenicity, thus offering a unique model system to study the molecular mechanisms involved with these processes.

Transcription factors that mediate epithelial-mesenchymal transition lead to multidrug resistance by upregulating ABC transporters.

Development of multidrug resistance (MDR) is a major deterrent in the effective treatment of metastatic cancers by chemotherapy. Even though MDR and cancer invasiveness have been correlated, the molecular basis of this link remains obscure. We show here that treatment with chemotherapeutic drugs increases the expression of several ATP binding cassette transporters (ABC transporters) associated with MDR, as well as epithelial-mesenchymal transition (EMT) markers, selectively in invasive breast cancer cells, but not in immortalized or non-invasive cells. Interestingly, the mere induction of an EMT in immortalized and non-invasive cell lines increased their expression of ABC transporters, migration, invasion, and drug resistance. Conversely, reversal of EMT in invasive cells by downregulating EMT-inducing transcription factors reduced their expression of ABC transporters, invasion, and rendered them more chemosensitive. Mechanistically, we demonstrate that the promoters of ABC transporters carry several binding sites for EMT-inducing transcription factors, and overexpression of Twist, Snail, and FOXC2 increases the promoter activity of ABC transporters. Furthermore, chromatin immunoprecipitation studies revealed that Twist binds directly to the E-box elements of ABC transporters. Thus, our study identifies EMT inducers as novel regulators of ABC transporters, thereby providing molecular insights into the long-standing association between invasiveness and MDR. Targeting EMT transcription factors could hence serve as novel strategies to curb both metastasis and the associated drug resistance.

Young unwed fathers of AFDC children: do they provide support?

We examine the support provided by fathers of children born to disadvantaged teenage mothers. Our sample includes the fathers of 6,009 children born over a two-year period to 3,855 teenage mothers receiving AFDC in three economically depressed inner cities. These fathers provide little social and economic support to their children. Support declines as their children age from infants to toddlers and as fathers' relationships with the mothers grow more distant. Fathers' employment status and educational attainment positively affect the amount of economic support that they provide but do not strongly influence the amount of social support they provide.

Convergence properties of the softassign quadratic assignment algorithm.

The softassign quadratic assignment algorithm is a discrete-time, continuous-state, synchronous updating optimizing neural network. While its effectiveness has been shown in the traveling salesman problem, graph matching, and graph partitioning in thousands of simulations, its convergence properties have not been studied. Here, we construct discrete-time Lyapunov functions for the cases of exact and approximate doubly stochastic constraint satisfaction, which show convergence to a fixed point. The combination of good convergence properties and experimental success makes the softassign algorithm an excellent choice for neural quadratic assignment optimization.

Activated Notch1 signaling cooperates with papillomavirus oncogenes in transformation and generates resistance to apoptosis on matrix withdrawal through PKB/Akt.

Invasive cervical tumors, a major subset of human epithelial neoplasms, are characterized by the consistent presence of papillomavirus oncogenes 16 or 18 E6 and E7 products. Cervical tumors also consistently exhibit cytosolic and nuclear forms of Notch1, suggesting the possible persistent activation of the Notch pathway. Here we show that activated Notch1 synergizes with papillomavirus oncogenes in transformation of immortalized epithelial cells and leads to the generation of resistance to anoikis, an apoptotic response induced on matrix withdrawal. This resistance to anoikis by activated Notch1 is mediated through the activation of PKB/Akt, a key effector of activated Ras in transformation. We suggest that activated Notch signaling may serve to substitute for the lack of activated Ras mutations in the majority of human cervical neoplasms.

The human transcription enhancer factor-1, TEF-1, can substitute for Drosophila scalloped during wingblade development.

The human transcription enhancer factor-1 (TEF-1) belongs to a family of evolutionarily conserved proteins that have a DNA binding TEA domain. TEF-1 shares a 98% homology with Drosophila scalloped (sd) in the DNA binding domain and a 50% similarity in the activation domain. We have expressed human TEF-1 in Drosophila under the hsp-70 promoter and find that it can substitute for Sd function. The transformants rescue the wingblade defects as well as the lethality of loss-of-function alleles. Observation of reporter activity in the imaginal wing discs of the enhancer-trap alleles suggests that TEF-1 is capable of promoting sd gene regulation. The functional capability of the TEF-1 product was assessed by comparing the extent of rescue by heat shock (hs)-TEF-1 with that of hs-sd. The finding that TEF-1 can function in vivo during wingblade development offers a potent genetic system for the analysis of its function and in the identification of the molecular partners of TEF-1.

The link between integration and expression of human papillomavirus type 16 genomes and cellular changes in the evolution of cervical intraepithelial neoplastic lesions.

We have matched a PCR assay which detects disruptions in the E2 reading frame of human papillomavirus type 16, with RNA in situ hybridization patterns and shown that in 15 out of 16 cervical intraepithelial neoplastic (CIN) III lesions and in 19 out of 19 tumours, the E2 gene is disrupted with no detectable E2 transcripts. Varying levels of E6-E7 transcripts are detected in CIN III lesions, with stronger signals in tumours. The cytokeratin profile of most tumours: cytokeratin 10-, 14- and 19-positive and 4-, 13- and 18-negative, is also detected in CIN III lesions. The changes in levels of alpha 2, beta 1 and beta 4 integrins, CD44 and E-cadherin occur during the evolution of high-grade CIN lesions. Increases in the levels of expression of CD44 and E6-E7 transcripts, coupled with changes in the cellular localization of the Notch protein, define the transition from CIN III lesions to tumours.