Fabrication and Repair of Cartilage Defects with a Novel Acellular Cartilage Matrix Scaffold

The objectives of this study were to develop a three-dimensional acellular cartilage matrix (ACM) and investigate its possibility for use as a scaffold in cartilage tissue engineering. Bovine articular cartilage was decellularized sequentially with trypsin, nuclease solution, hypotonic buffer, and Triton x 100 solution; molded with freeze-drying process; and cross-linked by ultraviolet irradiation. Histological and biochemical analysis showed that the ACM was devoid of cells and still maintained the collagen and glycosaminoglycan components of cartilage. Scanning electronic microscopy and mercury intrusion porosimetry showed that the ACM had a sponge-like structure of high porosity. The ACM scaffold had good biocompatibility with cultured rabbit bone marrow mesenchymal stem cells with no indication of cytotoxicity both in contact and in extraction assays. The cartilage defects repair in rabbit knees with the mesenchymal stem cell-ACM constructs had a significant improvement of histological scores when compared to the control groups at 6 and 12 weeks. In summary, the ACM possessed the characteristics that afford it as a potential scaffold for cartilage tissue engineering.

The complex effects of the slow-releasing hydrogen sulfide donor GYY4137 in a model of acute joint inflammation and in human cartilage cells

The role of hydrogen sulfide (H2 S) in inflammation remains unclear with both pro- and anti-inflammatory actions of this gas described. We have now assessed the effect of GYY4137 (a slow-releasing H2 S donor) on lipopolysaccharide (LPS)-evoked release of inflammatory mediators from human synoviocytes (HFLS) and articular chondrocytes (HAC) in vitro. We have also examined the effect of GYY4137 in a complete Freund's adjuvant (CFA) model of acute joint inflammation in the mouse. GYY4137 (0.1-0.5 mM) decreased LPS-induced production of nitrite (NO2 (-) ), PGE2 , TNF-a and IL-6 from HFLS and HAC, reduced the levels and catalytic activity of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) and reduced LPS-induced NF-?B activation in vitro. Using recombinant human enzymes, GYY4137 inhibited the activity of COX-2, iNOS and TNF-a converting enzyme (TACE). In the CFA-treated mouse, GYY4137 (50 mg/kg, i.p.) injected 1 hr prior to CFA increased knee joint swelling while an anti-inflammatory effect, as demonstrated by reduced synovial fluid myeloperoxidase (MPO) and N-acetyl-ß-D-glucosaminidase (NAG) activity and decreased TNF-a, IL-1ß, IL-6 and IL-8 concentration, was apparent when GYY4137 was injected 6 hrs after CFA. GYY4137 was also anti-inflammatory when given 18 hrs after CFA. Thus, although GYY4137 consistently reduced the generation of pro-inflammatory mediators from human joint cells in vitro, its effect on acute joint inflammation in vivo depended on the timing of administration.

Toward Unconstrained Ear Recognition From Two-Dimensional Images

Ear recognition, as a biometric, has several advantages. In particular, ears can be measured remotely and are also relatively static in size and structure for each individual. Unfortunately, at present, good recognition rates require controlled conditions. For commercial use, these systems need to be much more robust. In particular, ears have to be recognized from different angles ( poses), under different lighting conditions, and with different cameras. It must also be possible to distinguish ears from background clutter and identify them when partly occluded by hair, hats, or other objects. The purpose of this paper is to suggest how progress toward such robustness might be achieved through a technique that improves ear registration. The approach focuses on 2-D images, treating the ear as a planar surface that is registered to a gallery using a homography transform calculated from scale-invariant feature-transform feature matches. The feature matches reduce the gallery size and enable a precise ranking using a simple 2-D distance algorithm. Analysis on a range of data sets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees, and up to 18% occlusion. In addition, recognition remains accurate with masked ear images as small as 20 x 35 pixels.

3D Morphable Model Construction for Robust Ear and Face Recognition

Recent work suggests that the human ear varies significantly between different subjects and can be used for identification. In principle, therefore, using ears in addition to the face within a recognition system could improve accuracy and robustness, particularly for non-frontal views. The paper describes work that investigates this hypothesis using an approach based on the construction of a 3D morphable model of the head and ear. One issue with creating a model that includes the ear is that existing training datasets contain noise and partial occlusion. Rather than exclude these regions manually, a classifier has been developed which automates this process. When combined with a robust registration algorithm the resulting system enables full head morphable models to be constructed efficiently using less constrained datasets. The algorithm has been evaluated using registration consistency, model coverage and minimalism metrics, which together demonstrate the accuracy of the approach. To make it easier to build on this work, the source code has been made available online.

Robust 2D Ear Registration and Recognition Based on SIFT Point Matching

Significant recent progress has shown ear recognition to be a viable biometric. Good recognition rates have been demonstrated under controlled conditions, using manual registration or with specialised equipment. This paper describes a new technique which improves the robustness of ear registration and recognition, addressing issues of pose variation, background clutter and occlusion. By treating the ear as a planar surface and creating a homography transform using SIFT feature matches, ears can be registered accurately. The feature matches reduce the gallery size and enable a precise ranking using a simple 2D distance algorithm. When applied to the XM2VTS database it gives results comparable to PCA with manual registration. Further analysis on more challenging datasets demonstrates the technique to be robust to background clutter, viewing angles up to +/- 13 degrees and with over 20% occlusion.