Growth and morphogenetic factors in bone induction: role of osteogenin and related bone morphogenetic proteins in craniofacial and periodontal bone repair.

Bone has considerable potential for repair as illustrated by the phenomenon of fracture healing. Repair and regeneration of bone recapitulate the sequential stages of development. It is well known that demineralized bone matrix has the potential to induce new bone formation locally at a heterotopic site of implantation. The sequential development of bone is reminiscent of endochondral bone differentiation during bone development. The collagenous matrix-induced bone formation is a prototype model for matrix-cell interactions in vivo. The developmental cascade includes migration of progenitor cells by chemotaxis, attachment of cells through fibronectin, proliferation of mesenchymal cells, and differentiation of bone. The bone inductive protein, osteogenin, was isolated by heparin affinity chromatography. Osteogenin initiates new bone formation and is promoted by other growth factors. Recently, the genes for osteogenin and related bone morphogenetic proteins were cloned and expressed. Recombinant osteogenin is osteogenic in vivo. The future prospects for bone induction are bright, and this is an exciting frontier with applications in oral and orthopaedic surgery.TS2016

Noise-robust method for image segmentation

Segmentation of noisy images is one of the most challenging problems in image analysis and any improvement of segmentation methods can highly influence the performance of many image processing applications. In automated image segmentation, the fuzzy c-means (FCM) clustering has been widely used because of its ability to model uncertainty within the data, applicability to multi-modal data and fairly robust behaviour. However, the standard FCM algorithm does not consider any information about the spatial linage context and is highly sensitive to noise and other imaging artefacts. Considering above mentioned problems, we developed a new FCM-based approach for the noise-robust fuzzy clustering and we present it in this paper. In this new iterative algorithm we incorporated both spatial and feature space information into the similarity measure and the membership function. We considered that spatial information depends on the relative location and features of the neighbouring pixels. The performance of the proposed algorithm is tested on synthetic image with different noise levels and real images. Experimental quantitative and qualitative segmentation results show that our method efficiently preserves the homogeneity of the regions and is more robust to noise than other FCM-based methods

Recent Progress in Bone Induction by Osteogenin and Bone Morphogenetic Proteins: Challenges for Biomechanical and Tissue Engineering

Implantation of demineralized bone matrix results in local bon

Differentially Private Adaptive Optimization with Delayed Preconditioners

Privacy noise may negate the benefits of using adaptive optimizers in differentially private model training. Prior works typically address this issue by using auxiliary information (e.g., public data) to boost the effectiveness of adaptive optimization. In this work, we explore techniques to estimate and efficiently adapt to gradient geometry in private adaptive optimization without auxiliary data. Motivated by the observation that adaptive methods can tolerate stale preconditioners, we propose differentially private adaptive training with delayed preconditioners (DP^2), a simple method that constructs delayed but less noisy preconditioners to better realize the benefits of adaptivity. Theoretically, we provide convergence guarantees for our method for both convex and non-convex problems, and analyze trade-offs between delay and privacy noise reduction. Empirically, we explore DP^2 across several real-world datasets, demonstrating that it can improve convergence speed by as much as 4x relative to non-adaptive baselines and match the performance of state-of-the-art optimization methods that require auxiliary data.Comment: Accepted by ICLR 202

Experience and signaling value in technology licensing contract payment structures

Singapore MOE Academic Research Fund Tier