Ixazomib enhances parathyroid hormone-induced β-catenin/T-cell factor signaling by dissociating β-catenin from the parathyroid hormone receptor.

The anabolic action of PTH in bone is mostly mediated by cAMP/PKA and Wnt-independent activation of β-catenin/T-cell factor (TCF) signaling. β-Catenin switches the PTH receptor (PTHR) signaling from cAMP/PKA to PLC/PKC activation by binding to the PTHR. Ixazomib (Izb) was recently approved as the first orally administered proteasome inhibitor for the treatment of multiple myeloma; it acts in part by inhibition of pathological bone destruction. Proteasome inhibitors were reported to stabilize β-catenin by the ubiquitin-proteasome pathway. However, how Izb affects PTHR activation to regulate β-catenin/TCF signaling is poorly understood. In the present study, using CRISPR/Cas9 genome-editing technology, we show that Izb reverses β-catenin-mediated PTHR signaling switch and enhances PTH-induced cAMP generation and cAMP response element-luciferase activity in osteoblasts. Izb increases active forms of β-catenin and promotes β-catenin translocation, thereby dissociating β-catenin from the PTHR at the plasma membrane. Furthermore, Izb facilitates PTH-stimulated GSK3β phosphorylation and β-catenin phosphorylation. Thus Izb enhances PTH stimulation of β-catenin/TCF signaling via cAMP-dependent activation, and this effect is due to its separating β-catenin from the PTHR. These findings provide evidence that Izb may be used to improve the therapeutic efficacy of PTH for the treatment of osteoporosis and other resorptive bone diseases

Probing dark particles indirectly at the CEPC

When dark matter candidate and its parent particles are nearly degenerate, it would be difficult to probe them at the Large Hadron Collider directly. We propose to explore their quantum loop effects at the CEPC through the golden channel process $e^+e^-\to \mu^+\mu^-$. We use a renormalizable toy model consisting of a new scalar and a fermion to describe new physics beyond the Standard Model. The new scalar and fermion are general multiplets of the $SU(2)_L\times U(1)_Y$ symmetry, and couple to the muon lepton through Yukawa interaction. We calculate their loop contributions to anomalous $\gamma\mu^+\mu^-$ and $Z\mu^+\mu^-$ couplings which can be applied to many new physics models. The prospects of their effects at the CEPC are also examined assuming a 0.002 accuracy in the cross section measurement

Flat Currents of the Green-Schwarz Superstrings in AdS_5 x S^1 and AdS_3 x S^3 backgrounds

We construct a one-parameter family of flat currents in AdS_5 x S^1 and AdS_3 x S^3 Green-Schwarz superstrings, which would naturally lead to a hierarchy of classical conserved nonlocal charges. In the former case we rewrite the AdS_5 x S^1 string using a new Z_4-graded base of the superalgebra su(2,2|2). In both cases the existence of the Z_4 grading in the superalgebras plays a key role in the construction. As a result, we find that the flat currents, when formally written in terms of the G_0-gauge invariant lowercase 1-forms, take the same form as the one in AdS_5 x S^5 case.Comment: 18 pages, LaTeX file. References added and typos correcte

Linear Convergence of ISTA and FISTA

In this paper, we revisit the class of iterative shrinkage-thresholding algorithms (ISTA) for solving the linear inverse problem with sparse representation, which arises in signal and image processing. It is shown in the numerical experiment to deblur an image that the convergence behavior in the logarithmic-scale ordinate tends to be linear instead of logarithmic, approximating to be flat. Making meticulous observations, we find that the previous assumption for the smooth part to be convex weakens the least-square model. Specifically, assuming the smooth part to be strongly convex is more reasonable for the least-square model, even though the image matrix is probably ill-conditioned. Furthermore, we improve the pivotal inequality tighter for composite optimization with the smooth part to be strongly convex instead of general convex, which is first found in [Li et al., 2022]. Based on this pivotal inequality, we generalize the linear convergence to composite optimization in both the objective value and the squared proximal subgradient norm. Meanwhile, we set a simple ill-conditioned matrix which is easy to compute the singular values instead of the original blur matrix. The new numerical experiment shows the proximal generalization of Nesterov's accelerated gradient descent (NAG) for the strongly convex function has a faster linear convergence rate than ISTA. Based on the tighter pivotal inequality, we also generalize the faster linear convergence rate to composite optimization, in both the objective value and the squared proximal subgradient norm, by taking advantage of the well-constructed Lyapunov function with a slight modification and the phase-space representation based on the high-resolution differential equation framework from the implicit-velocity scheme.Comment: 16 pages, 4 figure

Riemannian preconditioned algorithms for tensor completion via tensor ring decomposition

We propose Riemannian preconditioned algorithms for the tensor completion problem via tensor ring decomposition. A new Riemannian metric is developed on the product space of the mode-2 unfolding matrices of the core tensors in tensor ring decomposition. The construction of this metric aims to approximate the Hessian of the cost function by its diagonal blocks, paving the way for various Riemannian optimization methods. Specifically, we propose the Riemannian gradient descent and Riemannian conjugate gradient algorithms. We prove that both algorithms globally converge to a stationary point. In the implementation, we exploit the tensor structure and adopt an economical procedure to avoid large matrix formulation and computation in gradients, which significantly reduces the computational cost. Numerical experiments on various synthetic and real-world datasets -- movie ratings, hyperspectral images, and high-dimensional functions -- suggest that the proposed algorithms are more efficient and have better reconstruction ability than other candidates.Comment: 25 pages, 7 figures, 5 table