Chemical Synthesis and Biological Applications of O-GlcNAcylated Peptides and Proteins

All human cells use O-GlcNAc protein modifications (O-linked N-acetylglucosamine) to rapidly adapt to changing nutrient and stress conditions through signaling, epigenetic, and proteostasis mechanisms. A key challenge for biologists in defining precise roles for specific O-GlcNAc sites is synthetic access to homogenous isoforms of O-GlcNAc proteins, a result of the non-genetically templated, transient, and heterogeneous nature of O-GlcNAc modifications. Toward a solution, this review details the state of the art of two strategies for O-GlcNAc protein modification: advances in “bottom-up” O-GlcNAc peptide synthesis and direct “top-down” installation of O-GlcNAc on full proteins. We also describe key applications of synthetic O-GlcNAc peptide and protein tools as therapeutics, biophysical structure–function studies, biomarkers, and as disease mechanistic probes to advance translational O-GlcNAc biology.     

Entrepreneurship and the carbon market: opportunities and challenges for South African entrepreneurs

The Kyoto Protocol and its implementation brought forward issues of climate change and its mitigation strategy by national measures through the creation of market mechanisms in carbon trading. The trading of emission certificates has become an important trade commodity worldwide, and its markets have diversified. While this opportunity has created new markets for entrepreneurs and actors that range from farmers to brokers, unequal involvement in most developing countries is noted. This has been mostly observed in those countries where entrepreneurship is often regarded as the cornerstone of economic growth and social improvement. South Africa has spearheaded other African countries in its implementation of Clean Development Mechanism (CDM) projects leading to carbon trading. Based on our research on South African entrepreneurship and its involvement in the carbon market, we conclude that albeit a number of opportunities, the biggest challenge for entrepreneurial participation in the carbon market remains in the nature and processes of CDM project implementation, the lack of a clear supportive system, limited access to financing and—more importantly—general ignorance of the trading opportunities by entrepreneurs. The complex nature of CDM projects themselves limits participation due to lack of the necessary skills on the national level leading to uneven distribution of CDM projects on provincial levels in South Africa. Recommendations are provided to overcome the obstacles and to promote entrepreneurial activity in the carbon market.     

Distribution of Matrix Cracks in a Uniaxial Ceramic Composite

Conventional shear-lag analyses of matrix cracking and debonding in uniaxial composites loaded in tension predict that the matrix stress varies only very slowly with position except near existing cracks. It therefore follows that the location of subsequent cracks is very sensitive to minor local variations in matrix strength, leading to significant statistical variation in crack spacing. This question is investigated using a discrete random process model of a composite and by direct experimental measurements of crack spacing. In the limit of a completely homogeneous composite, it is shown that the crack spacing distribution tends to an inverse square distribution between the theoretical maximum spacing and half that value. The random process model recovers this behavior in the limit and exhibits an approximately Weibull distribution of crack spacings when the matrix strength has significant variance. The theoretical predictions are compared with experimental results obtained for a unidirectional ceramic-matrix composite (SiC fibers in a calcium aluminosilicate matrix). The experimental results exhibit features similar to those predicted by the model and are compatible with a matrix strength whose standard deviation is of the order of 40% of the mean strength. An important point is that, with this magnitude of strength variation, the material exhibits a significant size effect and it is essential to take this into account in estimating the mean crack spacing from the corresponding mean matrix properties.     

Root growth and phosphorus and potassium uptake by two corn genotypes in the field

In a field study P and K uptake by two corn (Zea mays L.) genotypes which differed in root growth was investigated. The effect of differences in root growth on P and K uptake was assessed using a mechanistic-mathematical model which describes nutrient uptake by growing plant roots in soil. Nitrogen was applied at 0 and 227 kg ha^–1 to Pioneer 3732 and B73xMo17 corn grown on Raub silt loam (fine-silty, mixed, mesic Aquic Argiudoll) and at 227 kg N ha^–1 to these two genotypes on Chalmers silt loam (finesilty, mixed, mesic, Typic Haplaquoll). Root growth and P and K uptake by the two corn genotypes was measured 31, 47, 75 and 91 d after planting on the Raub and 31, 47, 61 and 75 d after planting on the Chalmers soil.Root growth and P and K uptake by B73xMo17 was greater than that of Pioneer 3732 on N-fertilized Raub soil. On Chalmers soil the difference in root growth between the two genotypes resulted in an increase in K but not P uptake. The higher soil P level of the Chalmers appears to have offset possible differences in P uptake due to root size. There were no differences between the two genotypes in either the percentage of roots with root hairs, or the density or length of root hairs. Phosphorus and K uptake calculated with the simulation models for both corn genotypes on both soils over each of three growth periods agreed with observed P (Y = 0.68X + 1.71; r = 0.944^**) and K (Y = 0.88X + 15.52; r = 0.928^**) uptake. Differences in P and K uptake between B73xMo17 and Pioneer 3732 resulted primarily from the difference in root growth in the topsoil. A high correlation was found between root surface area and P (r = 0.893^**) and K (r = 0.928^**) uptake by both corn genotypes on both the soils.Journal paper No. 10,316 Purdue Univ. Agric. Exp. Stn., W. Lafayette, In 47906. Contribution from the Dep. of Agron. This paper was supported in part by a grant from the Tennessee Valley Authority.     

Intraoperative tumor detection: relative performance of single-element, dual-element, and imaging probes with various collimators

Accurate tumor staging depends on finding all tumor sites, and curative surgery requires the removal of ail cancerous tissue from those sites. One technique for locating tumors is to inject patients before surgery with a radiotracer that is preferentially taken up by cancerous tissue. Then, an intraoperative gamma-sensitive probe is used to locate the tumors. Small (<1-cm diameter) tumors, often undetectable by external imaging and by the standard surgical inspection with sight and touch, can be found with probes, Simple calculations and measurements with radioactive tumor models show that small tumors should be detected by single-element probes, but often such probes fail to detect these small tumors in practice. This discrepancy is often caused by the use of a uniform background to predict probe performance, Real backgrounds are nonuniform and can decrease probe performance dramatically. Dual-element, coincidence, or imaging probes may solve the background problem. The authors devised a method to predict probe performance in a realistic background which includes variations in normal organ uptakes. They predict the relative performance of both existing probes and those in the design stage so that optimal detector and collimator configurations can be determined. The procedure includes a Monte-Carlo-calculated point-response function, a numerical torso phantom, and measured biodistributions of a monoclonal antibody. The Hotelling Trace Value, a measure of tumor-detection performance, is computed from the probe responses in simulated studies.     

Photoacoustic‐Guided Surgery with Indocyanine Green‐Coated Superparamagnetic Iron Oxide Nanoparticle Clusters

A common cause of local tumor recurrence in brain tumor surgery results from incomplete surgical resection. Adjunctive technologies meant to facilitate gross total resection have had limited efficacy to date. Contrast agents used to delineate tumors preoperatively cannot be easily or accurately used in the real‐time operative setting. Although multimodal imaging contrast agents are developed to help the surgeon discern tumor from normal tissue in the operating room, these contrast agents are not readily translatable. This study has developed a novel contrast agent comprised solely of two Food and Drug Administration approved components, indocyanine green (ICG) and superparamagnetic iron oxide (SPIO) nanoparticles—with no additional amphiphiles or carrier materials, to enable preoperative detection by magnetic resonance (MR) imaging and intraoperative photoacoustic (PA) imaging. The encapsulation efficiency of both ICG and SPIO within the formulated clusters is ≈100%, and the total ICG payload is 20–30% of the total weight (ICG + SPIO). The ICG–SPIO clusters are stable in physiologic conditions; can be taken up within tumors by enhanced permeability and retention; and are detectable by MR. In a preclinical surgical resection model in mice, following injection of ICG–SPIO clusters, animals undergoing PA‐guided surgery demonstrate increased progression‐free survival compared to animals undergoing microscopic surgery.     

NK cells can recognize different forms of class I MHC

NK recognition and lysis of targets are mediated by activation receptor(s) whose effects may be over-ridden by inhibitory receptors recognizing class I MHC on the target. Incubation of normal lymphoblasts with a peptide that can bind to their class I MHC renders them sensitive to lysis by syngeneic NK cells. By binding to class I MHC, the peptide alters or masks the target structure recognized by an inhibitory NK receptor(s). This target structure is most likely an "empty" dimer of class I heavy chain and beta2m as opposed to a "full" class I trimer formed by binding of specific peptide that is recognized by CTL.     

Adaptive discrete neural observer design for nonlinear systems with unknown time‐delay

This paper focuses on the adaptive observer design for nonlinear discrete‐time MIMO systems with unknown time‐delay and nonlinear dynamics. The delayed states involved in the system are arguments of a nonlinear function and only the estimated delay is utilized. By constructing an appropriate Lyapunov–Krasovskii function, the delay estimation error is considered in the observer parameter design. The proposed method is then extended to the system with a nonlinear output measurement equation and the delayed dynamics. With the help of a high‐order neural network (HONN), the requirement for a precise system model, the linear‐in‐the‐parameters (LIP) assumption of the delayed states, the Lipschitz or norm‐boundedness assumption of unknown nonlinearities are removed. A novel converse Lyapunov technical lemma is also developed and used to prove the uniform ultimate boundedness of the proposed observer. The effectiveness of the proposed results is verified by simulations. Copyright © 2010 John Wiley & Sons, Ltd.     

A Data‐driven Segmentation for the Shoulder Complex

The human shoulder complex is perhaps the most complicated joint in the human body being comprised of a set of three bones, muscles, tendons, and ligaments. Despite this anatomical complexity, computer graphics models for motion capture most often represent this joint as a simple ball and socket. In this paper, we present a method to determine a shoulder skeletal model that, when combined with standard skinning algorithms, generates a more visually pleasing animation that is a closer approximation to the actual skin deformations of the human body. We use a data‐driven approach and collect ground truth skin deformation data with an optical motion capture system with a large number of markers (200 markers on the shoulder complex alone). We cluster these markers during movement sequences and discover that adding one extra joint around the shoulder improves the resulting animation qualitatively and quantitatively yielding a marker set of approximately 70 markers for the complete skeleton. We demonstrate the effectiveness of our skeletal model by comparing it with ground truth data as well as with recorded video. We show its practicality by integrating it with the conventional rendering/animation pipeline.