Antibody Epitope of Human α‐Galactosidase A Revealed by Affinity Mass Spectrometry: A Basis for Reversing Immunoreactivity in Enzyme Replacement Therapy of Fabry Disease

α‐Galactosidase (αGal) is a lysosomal enzyme that hydrolyses the terminal α‐galactosyl moiety from glycosphingolipids. Mutations in the encoding genes for αGal lead to defective or misfolded enzyme, which results in substrate accumulation and subsequent organ dysfunction. The metabolic disease caused by a deficiency of human α‐galactosidase A is known as Fabry disease or Fabry–Anderson disease, and it belongs to a larger group known as lysosomal storage diseases. An effective treatment for Fabry disease has been developed by enzyme replacement therapy (ERT), which involves infusions of purified recombinant enzyme in order to increase enzyme levels and decrease the amounts of accumulated substrate. However, immunoreactivity and IgG antibody formation are major, therapy‐limiting, and eventually life‐threatening complications of ERT. The present study focused on the epitope determination of human α‐galactosidase A against its antibody formed. Here we report the identification of the epitope of human αGal(309–332) recognized by a human monoclonal anti‐αGal antibody, using a combination of proteolytic excision of the immobilized immune complex and surface plasmon resonance biosensing mass spectrometry. The epitope peptide, αGal(309–332), was synthesized by solid‐phase peptide synthesis. Determination of its affinity by surface plasmon resonance analysis revealed a high binding affinity for the antibody (K_D=39×10^?9 m ), which is nearly identical to that of the full‐length enzyme (K_D=16×10^?9 m ). The proteolytic excision affinity mass spectrometry method is shown here to be an efficient tool for epitope identification of an immunogenic lysosomal enzyme. Because the full‐length αGal and the antibody epitope showed similar binding affinities, this provides a basis for reversing immunogenicity upon ERT by: 1) treatment of patients with the epitope peptide to neutralize antibodies, or 2) removal of antibodies by apheresis, and thus significantly improving the response to ERT.     

Phenol degradation in water through a heterogeneous photo-Fenton process catalyzed by Fe-treated laponite

New photo-Fenton catalysts have been prepared from synthetic layered clay laponite (laponite RD). Two series of Fe-laponite catalysts were synthesised, with or without thermal treatment of the mixture Fe polycations-laponite in the intercalation procedure. In each series, the intercalated solids underwent calcination at four temperatures, 250, 350, 450, and 550 °C. The catalysts were used for photo-assisted Fenton conversion of phenol, analyzing the influence of five operating factors: the wavelength of the light source (254 nm UV-C and 360 UV-A radiation), the amount of the catalyst (between 0 and 2 g/L), the initial phenol concentration (between 0.5 and 1.5 mmol/L), the initial concentration of hydrogen peroxide (between 20 and 100 mmol/L), and the initial pH of the solution (between 2.5 and 3.5). In all experiments, the temperature was kept constant at 30 °C. The results have shown that the almost complete conversion of phenol was possible, after only 5 min, under the following operating conditions: UV-C radiation; a pH of the aqueous solution of 3; a dose of 1 g_catalyst/L, and a hydrogen peroxide concentration of 50 mmol/L for a solution containing 1 mmol/L of phenol. The catalyst prepared under thermal treatment and calcined at 350 °C showed the best catalytic performance. A kinetic model was proposed for the process, testing its validity and estimating the rate constants.     

Finding the maximally inscribed rectangle in a robot’s workspace

In this paper we formulate an optimization based approach to determining the maximally inscribed rectangle in a robot’s workspace. The size and location of the maximally inscribed rectangle is an effective index for evaluating the size and quality of a robot’s workspace. Such information is useful for, e. g., optimal worktable placement, and the placement of cooperating robots. For general robot workspaces we show how the problem can be formulated as a constrained nonlinear optimization problem possessing a special structure, to which standard numerical algorithms can be applied. Key to the rapid convergence of these algorithms is the choice of a starting point; in this paper we develop an efficient computational geometric algorithm for rapidly obtaining an approximate solution suitable as an initial starting point. We also develop an improved version of the algorithm of Haug et al. for calculating a robot’s workspace boundary.