Pectic Galactan Polysaccharide-Based Gene Delivery System for Targeting Neuroinflammation

Treating neuroinflammation-related injuries and disorders through manipulation of neuroinflammation functions is being heralded as a new therapeutic strategy. In this study, a novel pectic galactan (PG) polysaccharide based gene therapy approach is developed for targeting reactive gliosis in neuroinflammation. Galectin-3 (Gal-3) is a cell protein with a high affinity to β-galactoside sugars and is highly expressed in reactive gliosis. Since PG carries galactans, it can target reactive gliosis via specific carbohydrate interaction between galactan and Gal-3 on the cell membrane, and therefore can be utilized as a carrier for delivering genes to these cells. The carrier is synthesized by modifying quaternary ammonium groups on the PG. The resulting quaternized PG (QPG) is found to form complexes with plasmid DNA with a mean diameter of 100 nm and have the characteristics required for targeted gene therapy. The complexes efficiently condense large amounts of plasmid per particle and successfully bind to Gal-3. The in vivo study shows that the complexes are biocompatible and safe for administration and can selectively transfect reactive glial cells of an induced cortical lesion. The results confirm that this PG-based delivery system is a promising platform for targeting Gal-3 overexpressing neuroinflammation cells for treating neuroinflammation-related injuries and neurodegenerative diseases.     

Mixture model for face-color modeling and segmentation

In this paper, we propose a general methodology for face-color modeling and segmentation. One of the major difficulties in face detection and retrieval is partial face extraction due to highlights, shadows and lighting variations. We show that a mixture-of-Gaussians modeling of the color space, provides a robust representation that can accommodate large color variations, as well as highlights and shadows. Our method enables to segment within-face regions, and associate semantic meaning to them, and provides statistical analysis and evaluation of the dominant variability within a given archive.     

Raman microprobe investigation of the calcium phosphate phases of three commercially available plasma-flame-sprayed hydroxyapatite-coated dental implants

The purpose of the current study was to evaluate the crystallographic properties of three commercially plasma-flame-sprayed hydroxyapatite (HAp) coatings on dental implants. For this purpose a Raman microprobe (MOLE U1000) was used. No preparation of the surfaces was necessary to examine the thin ceramic surface layers. Microspectra (5 µm) and macrospectra (100 µm) have been measured and compared to the spectra of crystalline and amorphous HAp as well as to the spectra of tricalciumphosphate. All implants showed spectra that were more like that of the amorphous phase of HAp than any of the other examined reference materials. However, the implant spectra exhibited an extra band that as yet has not been identified. This band is probably indicative of some structure within the sprayed amorphous phase. Such structural effects would result either directly from quenching from the plasma state or by incorporation of titanium into the lattice during plasma treatment.     

Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users

The increasing demand for video streaming services with a high Quality of Experience (QoE) has prompted considerable research on client-side adaptation logic approaches. However, most algorithms use the client’s previous download experience and do not use a crowd knowledge database generated by users of a professional service. We propose a new crowd algorithm that maximizes the QoE. We evaluate our algorithm against state-of-the-art algorithms on large, real-life, crowdsourcing datasets. There are six datasets, each of which contains samples of a single operator (T-Mobile, AT&T or Verizon) from a single road (I100 or I405). All measurements were from Android cellphones. The datasets were provided by WeFi LTD and are public for academic users. Our new algorithm outperforms all other methods in terms of QoE (eMOS).     

Optimizing depth resolution in confocal Raman microscopy: a comparison of metallurgical, dry corrected, and oil immersion objectives

Spherical aberration is probably the most important factor limiting the practical performance of a confocal Raman microscope. This paper suggests some simple samples that can be readily fabricated in any laboratory to test the performance of a confocal Raman microscope under realistic operating conditions (i.e., a deeply buried interface, rather than the often-selected alternative of a bare silicon wafer or a thin film in air). The samples chosen were silicon wafers buried beneath transparent polymeric or glass overlayers, and a polymer laminate buried beneath a cover glass. These samples were used to compare the performance of three types of objectives (metallurgical, oil immersion, and dry corrected) in terms of depth resolution and signal throughput. The oil immersion objective gave the best depth resolution and intensity, followed by a dry corrected (60x, 0.9 numerical aperture) objective. The 100x metallurgical objective was the worst choice, with degradations of approximately 5x and 8x in the depth resolution and signal from a silicon wafer, comparing a bare wafer with one buried under a 150 microm cover glass. In particular, the high signal level obtained makes the immersion objective an attractive choice. Results from the buried laminate were even more impressive; a 30x improvement in spectral contrast was obtained using the oil immersion objective to analyze a thin (19 microm) coating on a PET substrate, buried beneath a 150 microm cover glass, compared with the metallurgical objective.