Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

The SM protein Vps33 and the t-SNARE H(abc) domain promote fusion pore opening.

Intracellular membrane fusion proceeds via distinct stages of membrane docking, hemifusion and fusion pore opening and depends on interacting families of Rab, SNARE and SM proteins. Trans-SNARE complexes dock the membranes in close apposition. Efficient fusion requires further SNARE-associated proteins. They might increase the number of trans-SNARE complexes or the fusogenic potential of a single SNARE complex. We investigated the contributions of the SM protein Vps33 to hemifusion and pore opening between yeast vacuoles. Mutations in Vps33 that weaken its interactions with the SNARE complex allowed normal trans-SNARE pairing and lipid mixing but retarded content mixing. Deleting the H(abc) domain of the vacuolar t-SNARE Vam3, which interacts with Vps33, had the same effect. This suggests that SM proteins promote fusion pore opening by enhancing the fusogenic activity of a SNARE complex. They should thus be considered integral parts of the fusion machinery.

Hyperpolarized lithium-6 as a sensor of nanomolar contrast agents.

Lithium is widely used in psychotherapy. The (6)Li isotope has a long intrinsic longitudinal relaxation time T(1) on the order of minutes, making it an ideal candidate for hyperpolarization experiments. In the present study we demonstrated that lithium-6 can be readily hyperpolarized within 30 min, while retaining a long polarization decay time on the order of a minute. We used the intrinsically long relaxation time for the detection of 500 nM contrast agent in vitro. Hyperpolarized lithium-6 was administered to the rat and its signal retained a decay time on the order of 70 sec in vivo. Localization experiments imply that the lithium signal originated from within the brain and that it was detectable up to 5 min after administration. We conclude that the detection of submicromolar contrast agents using hyperpolarized NMR nuclei such as (6)Li may provide a novel avenue for molecular imaging.

Pretargeted radioimmunotherapy using genetically engineered antibody-streptavidin fusion proteins for treatment of non-hodgkin lymphoma.

Purpose: Pretargeted radioimmunotherapy (PRIT) using streptavidin (SAv)-biotin technology can deliver higher therapeutic doses of radioactivity to tumors than conventional RIT. However, "endogenous" biotin can interfere with the effectiveness of this approach by blocking binding of radiolabeled biotin to SAv. We engineered a series of SAv FPs that downmodulate the affinity of SAv for biotin, while retaining high avidity for divalent DOTA-bis-biotin to circumvent this problem.Experimental Design: The single-chain variable region gene of the murine 1F5 anti-CD20 antibody was fused to the wild-type (WT) SAv gene and to mutant SAv genes, Y43A-SAv and S45A-SAv. FPs were expressed, purified, and compared in studies using athymic mice bearing Ramos lymphoma xenografts.Results: Biodistribution studies showed delivery of more radioactivity to tumors of mice pretargeted with mutant SAv FPs followed by (111)In-DOTA-bis-biotin [6.2 +/- 1.7% of the injected dose per gram (%ID/gm) of tumor 24 hours after Y43A-SAv FP and 5.6 +/- 2.2%ID/g with S45A-SAv FP] than in mice on normal diets pretargeted with WT-SAv FP (2.5 +/- 1.6%ID/g; P = 0.01). These superior biodistributions translated into superior antitumor efficacy in mice treated with mutant FPs and (90)Y-DOTA-bis-biotin [tumor volumes after 11 days: 237 +/- 66 mm(3) with Y43A-SAv, 543 +/- 320 mm(3) with S45A-SAv, 1129 +/- 322 mm(3) with WT-SAv, and 1435 +/- 212 mm(3) with control FP (P < 0.0001)].Conclusions: Genetically engineered mutant-SAv FPs and bis-biotin reagents provide an attractive alternative to current SAv-biotin PRIT methods in settings where endogenous biotin levels are high. Clin Cancer Res; 17(23); 7373-82. (C)2011 AACR.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Reconeixement de gestos de la mà amb el sensor Kinect

El reconeixement dels gestos de la mà (HGR, Hand Gesture Recognition) és actualment un camp important de recerca degut a la varietat de situacions en les quals és necessari comunicar-se mitjançant signes, com pot ser la comunicació entre persones que utilitzen la llengua de signes i les que no. En aquest projecte es presenta un mètode de reconeixement de gestos de la mà a temps real utilitzant el sensor Kinect per Microsoft Xbox, implementat en un entorn Linux (Ubuntu) amb llenguatge de programació Python i utilitzant la llibreria de visió artifical OpenCV per a processar les dades sobre un ordinador portàtil convencional. Gràcies a la capacitat del sensor Kinect de capturar dades de profunditat d’una escena es poden determinar les posicions i trajectòries dels objectes en 3 dimensions, el que implica poder realitzar una anàlisi complerta a temps real d’una imatge o d’una seqüencia d’imatges. El procediment de reconeixement que es planteja es basa en la segmentació de la imatge per poder treballar únicament amb la mà, en la detecció dels contorns, per després obtenir l’envolupant convexa i els defectes convexos, que finalment han de servir per determinar el nombre de dits i concloure en la interpretació del gest; el resultat final és la transcripció del seu significat en una finestra que serveix d’interfície amb l’interlocutor. L’aplicació permet reconèixer els números del 0 al 5, ja que s’analitza únicament una mà, alguns gestos populars i algunes de les lletres de l’alfabet dactilològic de la llengua de signes catalana. El projecte és doncs, la porta d’entrada al camp del reconeixement de gestos i la base d’un futur sistema de reconeixement de la llengua de signes capaç de transcriure tant els signes dinàmics com l’alfabet dactilològic.

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

Report on a special investigation of the Region 4 Fusion Office in Atlantic, Iowa for the period March 1, 2006 through August 31, 2009

Report on a special investigation of the Region 4 Fusion Office in Atlantic, Iowa for the period March 1, 2006 through August 31, 2009

An Adeno-Associated Virus-Based Intracellular Sensor of Pathological Nuclear Factor-κB Activation for Disease-Inducible Gene Transfer.

Stimulation of resident cells by NF-κB activating cytokines is a central element of inflammatory and degenerative disorders of the central nervous system (CNS). This disease-mediated NF-κB activation could be used to drive transgene expression selectively in affected cells, using adeno-associated virus (AAV)-mediated gene transfer. We have constructed a series of AAV vectors expressing GFP under the control of different promoters including NF-κB -responsive elements. As an initial screen, the vectors were tested in vitro in HEK-293T cells treated with TNF-α. The best profile of GFP induction was obtained with a promoter containing two blocks of four NF-κB -responsive sequences from the human JCV neurotropic polyoma virus promoter, fused to a new tight minimal CMV promoter, optimally distant from each other. A therapeutical gene, glial cell line-derived neurotrophic factor (GDNF) cDNA under the control of serotype 1-encapsidated NF-κB -responsive AAV vector (AAV-NF) was protective in senescent cultures of mouse cortical neurons. AAV-NF was then evaluated in vivo in the kainic acid (KA)-induced status epilepticus rat model for temporal lobe epilepsy, a major neurological disorder with a central pathophysiological role for NF-κB activation. We demonstrate that AAV-NF, injected in the hippocampus, responded to disease induction by mediating GFP expression, preferentially in CA1 and CA3 neurons and astrocytes, specifically in regions where inflammatory markers were also induced. Altogether, these data demonstrate the feasibility to use disease-activated transcription factor-responsive elements in order to drive transgene expression specifically in affected cells in inflammatory CNS disorders using AAV-mediated gene transfer.

Peroxisome proliferator-activated receptor beta/delta (PPARbeta/delta) but not PPARalpha serves as a plasma free fatty acid sensor in liver.

Peroxisome proliferator-activated receptor alpha (PPARalpha) is an important transcription factor in liver that can be activated physiologically by fasting or pharmacologically by using high-affinity synthetic agonists. Here we initially set out to elucidate the similarities in gene induction between Wy14643 and fasting. Numerous genes were commonly regulated in liver between the two treatments, including many classical PPARalpha target genes, such as Aldh3a2 and Cpt2. Remarkably, several genes induced by Wy14643 were upregulated by fasting independently of PPARalpha, including Lpin2 and St3gal5, suggesting involvement of another transcription factor. Using chromatin immunoprecipitation, Lpin2 and St3gal5 were shown to be direct targets of PPARbeta/delta during fasting, whereas Aldh3a2 and Cpt2 were exclusive targets of PPARalpha. Binding of PPARbeta/delta to the Lpin2 and St3gal5 genes followed the plasma free fatty acid (FFA) concentration, consistent with activation of PPARbeta/delta by plasma FFAs. Subsequent experiments using transgenic and knockout mice for Angptl4, a potent stimulant of adipose tissue lipolysis, confirmed the stimulatory effect of plasma FFAs on Lpin2 and St3gal5 expression levels via PPARbeta/delta. In contrast, the data did not support activation of PPARalpha by plasma FFAs. The results identify Lpin2 and St3gal5 as novel PPARbeta/delta target genes and show that upregulation of gene expression by PPARbeta/delta is sensitive to plasma FFA levels. In contrast, this is not the case for PPARalpha, revealing a novel mechanism for functional differentiation between PPARs.

Multicopy suppression of a gacA mutation by the infC operon in Pseudomonas fluorescens CHA0: competition with the global translational regulator RsmA.

The gacA gene of the biocontrol strain Pseudomonas fluorescens CHA0 codes for a response regulator which, together with the sensor kinase GacS (=LemA), is required for the production of exoenzymes and secondary metabolites involved in biocontrol, including hydrogen cyanide (HCN). A gacA multicopy suppressor was isolated from a cosmid library of strain CHA0 and identified as the infC-rpmI-rplT operon, which encodes the translation initiation factor IF3 and the ribosomal proteins L35 and L20. The efficiency of suppression was about 30%, as determined by the use of a GacA-controlled reporter construct, i.e. a translational hcnA'-'lacZ fusion. Overexpression of the rsmA gene (coding for a global translational repressor) reversed the suppressive effect of the amplified infC operon. This finding suggests that some product(s) of the infC operon can compete with RsmA at the level of translation in P. fluorescens CHA0 and that important biocontrol traits can be regulated at this level.

Avoiding sensor blindness in Geiger mode avalanche photodiode arrays fabricated in a conventional CMOS process

The need to move forward in the knowledge of the subatomic world has stimulated the development of new particle colliders. However, the objectives of the next generation of colliders sets unprecedented challenges to the detector performance. The purpose of this contribution is to present a bidimensional array based on avalanche photodiodes operated in the Geiger mode to track high energy particles in future linear colliders. The bidimensional array can function in a gated mode to reduce the probability to detect noise counts interfering with real events. Low reverse overvoltages are used to lessen the dark count rate. Experimental results demonstrate that the prototype fabricated with a standard HV-CMOS process presents an increased efficiency and avoids sensor blindness by applying the proposed techniques.

A reusable smart interface for gas sensor resistance measurement

The advances of the semiconductor industry enable microelectromechanical systems sensors, signal conditioning logic and network access to be integrated into a smart sensor node. In this framework, a mixed-mode interface circuit for monolithically integrated gas sensor arrays was developed with high-level design techniques. This interface system includes analog electronics for inspection of up to four sensor arrays and digital logic for smart control and data communication. Although different design methodologies were used in the conception of the complete circuit, high-level synthesis tools and methodologies were crucial in speeding up the whole design cycle, enhancing reusability for future applications and producing a flexible and robust component.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.