Sustained activation and tumor targeting of NKT cells using a CD1d-anti-HER2-scFv fusion protein induce antitumor effects in mice

Invariant NKT (iNKT) cells are potent activators of DCs, NK cells, and T cells, and their antitumor activity has been well demonstrated. A single injection of the high-affinity CD1d ligand alpha-galactosylceramide (alphaGalCer) leads to short-lived iNKT cell activation followed, however, by long-term anergy, limiting its therapeutic use. In contrast, we demonstrated here that when alphaGalCer was loaded on a recombinant soluble CD1d molecule (alphaGalCer/sCD1d), repeated injections led to sustained iNKT and NK cell activation associated with IFN-gamma secretion as well as DC maturation in mice. Most importantly, when alphaGalCer/sCD1d was fused to a HER2-specific scFv antibody fragment, potent inhibition of experimental lung metastasis and established s.c. tumors was obtained when systemic treatment was started 2-7 days after the injection of HER2-expressing B16 melanoma cells. In contrast, administration of free alphaGalCer at this time had no effect. The antitumor activity of the CD1d-anti-HER2 fusion protein was associated with HER2-specific tumor localization and accumulation of iNKT, NK, and T cells at the tumor site. Targeting iNKT cells to the tumor site thus may activate a combined innate and adaptive immune response that may prove to be effective in cancer immunotherapy

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.

Sequential analysis of trans-SNARE formation in intracellular membrane fusion.

SNARE complexes are required for membrane fusion in the endomembrane system. They contain coiled-coil bundles of four helices, three (Q(a), Q(b), and Q(c)) from target (t)-SNAREs and one (R) from the vesicular (v)-SNARE. NSF/Sec18 disrupts these cis-SNARE complexes, allowing reassembly of their subunits into trans-SNARE complexes and subsequent fusion. Studying these reactions in native yeast vacuoles, we found that NSF/Sec18 activates the vacuolar cis-SNARE complex by selectively displacing the vacuolar Q(a) SNARE, leaving behind a Q(bc)R subcomplex. This subcomplex serves as an acceptor for a Q(a) SNARE from the opposite membrane, leading to Q(a)-Q(bc)R trans-complexes. Activity tests of vacuoles with diagnostic distributions of inactivating mutations over the two fusion partners confirm that this distribution accounts for a major share of the fusion activity. The persistence of the Q(bc)R cis-complex and the formation of the Q(a)-Q(bc)R trans-complex are both sensitive to the Rab-GTPase inhibitor, GDI, and to mutations in the vacuolar tether complex, HOPS (HOmotypic fusion and vacuolar Protein Sorting complex). This suggests that the vacuolar Rab-GTPase, Ypt7, and HOPS restrict cis-SNARE disassembly and thereby bias trans-SNARE assembly into a preferred topology.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Fusion telomérique de deux chromosomes X par leurs bras courts chez une patiente présentant un syndrome de Turner atypique. [Telomeric fusion of the short arms of both X chromosomes in a patient presenting an atypical Turner syndrome.]

A case of atypical Turner's syndrome with unusual karyotype is reported. The chromosome complements of the patient, studied with different banding techniques, is 45,XO/46,X,dic(X)(Xqter leads to p22::p22 leads to qter). In the literature 8 similar cases have been reported. Short stature and amenorrhea are the most constant findings. The mechanisms by which the observed chromosomal "rearrangement" can be produced are briefly discussed.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

T-cell activation by treatment of cancer patients with EMD 521873 (Selectikine), an IL-2/anti-DNA fusion protein.

ABSTRACT: BACKGROUND: EMD 521873 (Selectikine or NHS-IL2LT) is a fusion protein consisting of modified human IL-2 which binds specifically to the high-affinity IL-2 receptor, and an antibody specific for both single- and double-stranded DNA, designed to facilitate the enrichment of IL-2 in tumor tissue. METHODS: An extensive analysis of pharmacodynamic (PD) markers associated with target modulation was assessed during a first-in-human phase I dose-escalation trial of Selectikine. RESULTS: Thirty-nine patients with metastatic or locally advanced tumors refractory to standard treatments were treated with increasing doses of Selectikine, and nine further patients received additional cyclophosphamide. PD analysis, assessed during the first two treatment cycles, revealed strong activation of both CD4+ and CD8+ T-cells and only weak NK cell activation. No dose response was observed. As expected, Treg cells responded actively to Selectikine but remained at lower frequency than effector CD4+ T-cells. Interestingly, patient survival correlated positively with both high lymphocyte counts and low levels of activated CD8+ T-cells at baseline, the latter of which was associated with enhanced T-cell responses to the treatment. CONCLUSIONS: The results confirm the selectivity of Selectikine with predominant T-cell and low NK cell activation, supporting follow-up studies assessing the clinical efficacy of Selectikine for cancer patients.

Fusion of the human gene for the polyubiquitination co-effector UEV-1 with Kua, a newly identified gene

UEV proteins are enzymatically inactive variants of the E2 ubiquitin-conjugating enzymes that regulate noncanonical elongation of ubiquitin chains. In Saccharomyces cerevisiae, UEV is part of the RAD6-mediated error-free DNA repair pathway. In mammalian cells, UEV proteins can modulate c-FOS transcription and the G2-M transition of the cell cycle. Here we show that the UEV genes from phylogenetically distant organisms present a remarkable conservation in their exon–intron structure. We also show that the human UEV1 gene is fused with the previously unknown gene Kua. In Caenorhabditis elegans and Drosophila melanogaster, Kua and UEV are in separated loci, and are expressed as independent transcripts and proteins. In humans, Kua and UEV1 are adjacent genes, expressed either as separate transcripts encoding independent Kua and UEV1 proteins, or as a hybrid Kua–UEV transcript, encoding a two-domain protein. Kua proteins represent a novel class of conserved proteins with juxtamembrane histidine-rich motifs. Experiments with epitope-tagged proteins show that UEV1A is a nuclear protein, whereas both Kua and Kua–UEV localize to cytoplasmic structures, indicating that the Kua domain determines the cytoplasmic localization of Kua–UEV. Therefore, the addition of a Kua domain to UEV in the fused Kua–UEV protein confers new biological properties to this regulator of variant polyubiquitination.[Kua cDNAs isolated by RT-PCR and described in this paper have been deposited in the GenBank data library under accession nos. AF1155120 (H. sapiens) and AF152361 (D. melanogaster). Genomic clones containing UEV genes: S. cerevisiae, YGL087c (accession no. Z72609); S. pombe, c338 (accession no. AL023781); P. falciparum, MAL3P2 (accession no. AL034558); A. thaliana, F26F24 (accession no. AC005292); C. elegans, F39B2 (accession no. Z92834); D. melanogaster, AC014908; and H. sapiens, 1185N5 (accession no. AL034423). Accession numbers for Kua cDNAs in GenBank dbEST: M. musculus, AA7853; T. cruzi, AI612534. Other Kua-containing sequences: A. thaliana genomic clones F10M23 (accession no. AL035440), F19K23 (accession no. AC000375), and T20K9 (accession no. AC004786).

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

Use of an empty, Plasmapore-covered titanium cage for interbody fusion after anterior cervical microdiscectomy.

The use of cages of different material and shapes for cervical discectomy with fusion (ACDF) has increased during the last few years. The use of additional osteogenic material is controversial. We prospectively evaluated an empty, Plasmapore-covered titanium cage (PCTC) in 45 patients undergoing 58 ACDFs. Patients were evaluated using standard clinical and radiological criteria. Good to excellent outcome was achieved in 93%, 78% and 75% after 3, 12 and 48 months, respectively. Sixty-five percent of patients could resume their prior work after 48 months. Disc space height and lordosis could be preserved in all cases. Two percent of the treated levels showed subsidence and 2% increased segmental motion. There were no procedure-related complications. Implantation of an empty PCTC after microsurgical anterior cervical discectomy is a safe procedure with good results and low incidence of complications. Disc height and lordosis can be preserved with low incidence of subsidence and good fusion rates.

Secondary Accident Data Fusion for Assessing Long-Term Performance of Transportation Systems, 2007

Secondary accident statistics can be useful for studying the impact of traffic incident management strategies. An easy-to-implement methodology is presented for classifying secondary accidents using data fusion of a police accident database with intranet incident reports. A current method for classifying secondary accidents uses a static threshold that represents the spatial and temporal region of influence of the primary accident, such as two miles and one hour. An accident is considered secondary if it occurs upstream from the primary accident and is within the duration and queue of the primary accident. However, using the static threshold may result in both false positives and negatives because accident queues are constantly varying. The methodology presented in this report seeks to improve upon this existing method by making the threshold dynamic. An incident progression curve is used to mark the end of the queue throughout the entire incident. Four steps in the development of incident progression curves are described. Step one is the processing of intranet incident reports. Step two is the filling in of incomplete incident reports. Step three is the nonlinear regression of incident progression curves. Step four is the merging of individual incident progression curves into one master curve. To illustrate this methodology, 5,514 accidents from Missouri freeways were analyzed. The results show that secondary accidents identified by dynamic versus static thresholds can differ by more than 30%.

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.