Deficiency of optineurin enhances osteoclast differentiation by attenuating the NRF2-mediated antioxidant response

Abnormally increased resorption contributes to bone degenerative diseases such as Paget’s disease of bone (PDB) through unclear mechanisms. Recently, the optineurin (OPTN) gene has been implicated in PDB, and global OPTN knockout mice (Optn^−/−) were shown to exhibit increased formation of osteoclasts (osteoclastogenesis). Growing evidence, including our own, has demonstrated that intracellular reactive oxygen species (ROS) stimulated by receptor activator of nuclear factor kappa-B ligand (RANKL) can act as signaling molecules to promote osteoclastogenesis. Here, we report that OPTN interacts with nuclear factor erythroid-derived factor 2-related factor 2 (NRF2), the master regulator of the antioxidant response, defining a pathway through which RANKL-induced ROS could be regulated for osteoclastogenesis. In this study, monocytes from Optn^−/− and wild-type (Optn^+/+) mice were utilized to differentiate into osteoclasts, and both qRT-PCR and tartrate-resistant acid phosphatase (TRAP) staining showed that the Optn^−/− monocytes exhibited enhanced osteoclastogenesis compared to the Optn^+/+ cells. CellROX^® staining, qRT-PCR, and Western blotting indicated that OPTN deficiency reduced the basal expression of Nrf2, inhibited the expression of NRF2-responsive antioxidants, and increased basal and RANKL-induced intracellular ROS levels, leading to enhanced osteoclastogenesis. Coimmunoprecipitation (co-IP) showed direct interaction, and immunofluorescence staining showed perinuclear colocalization of the OPTN-NRF2 granular structures during differentiation. Finally, curcumin and the other NRF2 activators attenuated the hyperactive osteoclastogenesis induced by OPTN deficiency. Collectively, our findings reveal a novel OPTN-mediated mechanism for regulating the NRF2-mediated antioxidant response in osteoclasts and extend the therapeutic potential of OPTN in the aging process resulting from ROS-triggered oxidative stress, which is associated with PDB and many other degenerative diseases.Subject terms: Mechanisms of disease, Stress signalling     

Photoswitchable Composite Polymer Electrolytes Using Spiropyran-Immobilized Nanoporous Templates

Composite polymer electrolytes (CPEs) with smart, stimuli-responsive characteristics have gained considerable attention owing to their noninvasive manipulation and applications in future technologies. To address this potential, in this work, we demonstrate photoresponsive composite polymer electrolytes, consisting of gel polymer electrolyte (GPE) and spiropyran-immobilized nanoporous anodic aluminum oxide (SP-AAO) templates. Under UV irradiation, the close SP form isomerizes to the open merocyanine (MC) form, creating extremely polarized AAO surfaces; whereas, under visible light irradiation, the MC form reverts to the SP form, creating neutral surface conditions. The electrostatic interactions between ions and AAO surfaces are investigated by attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. Moreover, the behavior of ionic conductivity of the GPE@SP-AAO is found to be consistent with the kinetics of isomerization tracked by UV-Vis spectroscopy. This work provides a promising platform for developing next-generation photoelectronic smart devices.     

Sodium Phytate-Incorporated Gelatin-Silicate Nanoplatelet Composites for Enhanced Cohesion and Hemostatic Function of Shear-Thinning Biomaterials

Shear-thinning biomaterials (STBs) based on gelatin-silicate nanoplatelets (SNs) are emerging as an alternative to conventional coiling and clipping techniques in the treatment of vascular anomalies. Improvements in the cohesion of STB hydrogels pave the way toward their translational application in minimally invasive therapies such as endovascular embolization repair. In the present study, sodium phytate (Phyt) additives are used to tune the electrostatic network of SNs-gelatin STBs, thereby promoting their mechanical integrity and facilitating injectability through standard catheters. We show that an optimized amount of Phyt enhances storage modulus by approximately one order of magnitude and reduces injection force by ≈58% without compromising biocompatibility and hydrogel wet stability. The Phyt additives are found to decrease the immune responses induced by SNs. In vitro embolization experiments suggest a significantly lower rate of failure in Phyt-incorporated STBs than in control groups. Furthermore, the addition of Phyt leads to accelerated blood coagulation (reduces clotting time by ≈45% compared to controls) due to the contributions of negatively charged phosphate groups, which aid in the prolonged durability of STB in coagulopathic patients. Therefore, the proposed approach is an effective method for the design of robust and injectable STBs for minimally invasive treatment of vascular malformations.     

Maintenance outsourcing coordination with risk-averse contractors

Under a maintenance outsourcing contract, an external contractor receives a fixed payment from a manufacturer for periodically performing preventive maintenance and for performing minimal repairs whenever process failures occur. If the contractor’s maintenance policy results in a process uptime above a target level specified in the contract, the contractor receives a bonus payment based on the difference between the uptime and the target levels. We study the optimal designs of maintenance outsourcing contracts for achieving channel coordination when the contractor is risk averse towards uncertain repair costs caused by process failures. We find cases in which channel coordination cannot be achieved because of the contractor’s risk preference. Furthermore, the contractor’s risk preference may make channel coordination more difficult or easier, depending on the parameters considered in the model.     

Extracting informative variables in the validation of two-group causal relationship

The validation of causal relationship between two groups of multivariate time series data often requires the precedence knowledge of all variables. However, in practice one finds that some variables may be negligible in describing the underlying causal structure. In this article we provide an explicit definition of “non-informative variables” in a two-group causal relationship and introduce various automatic computer-search algorithms that can be utilized to extract informative variables based on a hypothesis testing procedure. The result allows us to represent a simplified causal relationship by using minimum possible information on two groups of variables.     

The quantum orbifold cohomology of weighted projective spaces

We calculate the small quantum orbifold cohomology of arbitrary weighted projective spaces. We generalize Givental’s heuristic argument, which relates small quantum cohomology to S ¹-equivariant Floer cohomology of loop space, to weighted projective spaces and use this to conjecture an explicit formula for the small J-function, a generating function for certain genus-zero Gromov–Witten invariants. We prove this conjecture using a method due to Bertram. This provides the first non-trivial example of a family of orbifolds of arbitrary dimension for which the small quantum orbifold cohomology is known. In addition we obtain formulas for the small J-functions of weighted projective complete intersections satisfying a combinatorial condition; this condition naturally singles out the class of orbifolds with terminal singularities.     

A hybrid genetic local search algorithm for the permutation flowshop scheduling problem

Traditionally, the permutation flowshop scheduling problem (PFSP) was with the criterion of minimizing makespan. The permutation flowshop scheduling problem to minimize the total flowtime has attracted more attention from researchers in recent years. In this paper, a hybrid genetic local search algorithm is proposed to solve this problem with each of both criteria. The proposed algorithm hybridizes the genetic algorithm and a novel local search scheme that combines two local search methods: the Insertion Search (IS) and the Insertion Search with Cut-and-Repair (ISCR). It employs the genetic algorithm to do the global search and two local search methods to do the local search. Two local search methods play different roles in the search process. The Insertion Search is responsible for searching a small neighborhood while the Insertion Search with Cut-and-Repair is responsible for searching a large neighborhood. Furthermore, the orthogonal-array-based crossover operator is designed to enhance the GA’s capability of intensification. The experimental results show the advantage of combining the two local search methods. The performance of the proposed hybrid genetic algorithm is very competitive. For the PFSP with the total flowtime criterion, it improved 66 out of the 90 current best solutions reported in the literature in short-term search and it also improved all the 20 current best solutions reported in the literature in long-term search. For the PFSP with the makespan criterion, the proposed algorithm also outperforms the other three methods recently reported in the literature.     

Block-Coordinate Gradient Descent Method for?Linearly Constrained Nonsmooth Separable Optimization

We consider the problem of minimizing the weighted sum of a smooth function f and a convex function P of n real variables subject to m linear equality constraints. We propose a block-coordinate gradient descent method for solving this problem, with the coordinate block chosen by a Gauss-Southwell-q rule based on sufficient predicted descent. We establish global convergence to first-order stationarity for this method and, under a local error bound assumption, linear rate of convergence. If f is convex with Lipschitz continuous gradient, then the method terminates in O(n ²/ε) iterations with an ε-optimal solution. If P is separable, then the Gauss-Southwell-q rule is implementable in O(n) operations when m=1 and in O(n ²) operations when m>1. In the special case of support vector machines training, for which f is convex quadratic, P is separable, and m=1, this complexity bound is comparable to the best known bound for decomposition methods. If f is convex, then, by gradually reducing the weight on P to zero, the method can be adapted to solve the bilevel problem of minimizing P over the set of minima of f+δ _X , where X denotes the closure of the feasible set. This has application in the least 1-norm solution of maximum-likelihood estimation. This research was supported by the National Science Foundation, Grant No. DMS-0511283.