Tailored design of NKT-stimulatory glycolipids for polarization of immune responses.

Natural killer T (NKT) cell is a distinct population of T lymphocytes that can rapidly release massive amount of Th1 and Th2 cytokines upon the engagement of their T cell receptor with glycolipids presented by CD1d. The secreted cytokines can promote cell-mediated immunity to kill tumor cells and intracellular pathogens, or suppress autoreactive immune cells in autoimmune diseases. Thus, NKT cell is an attractive target for developing new therapeutics to manipulate immune system. The best-known glycolipid to activate NKT cells is α-galactosylceramide (α-GalCer), which has been used as a prototype for designing new NKT stimulatory glycolipids. Many analogues have been generated by modification of the galactosyl moiety, the acyl chain or the phytosphingosine chain of α-GalCer. Some of the analogues showed greater abilities than α-GalCer in polarizing immune responses toward Th1 or Th2 dominance. Among them, several analogues containing phenyl groups in the lipid tails were more potent in inducing Th1-skewed cytokines and exhibited greater anticancer efficacy than α-GalCer. Analyses of the correlation between structure and activity of various α-GalCer analogues on the activation of iNKT cell revealed that CD1d-glycolipid complexes interacted with the same population of iNKT cell expressing similar T-cell receptor Vβ as α-GalCer. On the other hand, those phenyl glycolipids with propensity for Th1 dominant responses showed greater binding avidity and stability than α-GalCer for iNKT T-cell receptor when complexed with CD1d. Thus, it is the avidity and stability of the ternary complexes of CD1d-glycolipid-iNKT TCR that dictate the polarity and potency of immune responses. These findings provide a key to the rationale design of immune modulating glycolipids with desirable Th1/Th2 polarity for clinical application. In addition, elucidation of α-GalCer-induced anergy, liver damage and accumulation of myeloid derived suppressor cells has offered explanation for its lacklustre anti-cancer activities in clinical trials. On other hand, the lack of such drawbacks in glycolipid analogues containing phenyl groups in the lipid tails of α-GalCer coupled with the greater binding avidity and stability of CD1d-glycolipid complex for iNKT T-cell receptor, account for their superior anti-cancer efficacy in tumor bearing mice. Further clinical development of these phenyl glycolipids is warranted

Fine structures of solar radio type III bursts and their possible relationship with coronal density turbulence

Solar radio type III bursts are believed to be the most sensitive signatures of near-relativistic electron beam propagation in the corona. A solar radio type IIIb-III pair burst with fine frequency structures, observed by the Low Frequency Array (LOFAR) with high temporal (~10 ms) and spectral (12.5 kHz) resolutions at 30–80 MHz, is presented. The observations show that the type III burst consists of many striae, which have a frequency scale of about 0.1 MHz in both the fundamental (plasma) and the harmonic (double plasma) emission. We investigate the effects of background density fluctuations based on the observation of striae structure to estimate the density perturbation in the solar corona. It is found that the spectral index of the density fluctuation spectrum is about −1.7, and the characteristic spatial scale of the density perturbation is around 700 km. This spectral index is very close to a Kolmogorov turbulence spectral index of −5/3, consistent with a turbulent cascade. This fact indicates that the coronal turbulence may play the important role of modulating the time structures of solar radio type III bursts, and the fine structure of radio type III bursts could provide a useful and unique tool to diagnose the turbulence in the solar corona

Interaction of RNA-binding protein HuR and miR-466i regulates GM-CSF expression.

Granulocyte-macrophage colony-stimulating factor (GM-CSF) produced by T helper 17 (Th17) cells plays an essential role in autoimmune diseases. Transcriptional regulation of Th17 cell differentiation has been extensively studied, but post-transcriptional regulation of Th17 cell differentiation has remained less well characterized. The RNA-binding protein HuR functions to promote the stability of target mRNAs via binding the AU-rich elements of the 3\u27 untranslated region (3\u27UTR) of numerous pro-inflammatory cytokines including IL-4, IL-13, IL-17 and TNF-α. However, whether HuR regulates GM-CSF expression in Th17 cells has not been fully investigated. Here we showed that HuR conditional knockout (KO) Th17 cells have decreased GM-CSF mRNA in comparison with wild-type (WT) Th17 cells, and that HuR binds directly to GM-CSF mRNA 3\u27UTR. Interestingly, HuR deficiency increased the levels of certain microRNA expression in Th17 cells; for example, miR-466i functioned to mediate GM-CSF and IL-17 mRNA decay, which was confirmed by in vitro luciferase assay. Furthermore, we found that HuR promoted Mxi1 expression to inhibit certain miRNA expression. Taken together, these findings indicate that interaction of HuR and miR-466i orchestrates GM-CSF expression in Th17 cells

Unconventional Superconducting Symmetry in a Checkerboard Antiferromagnet

We use a renormalized mean field theory to study the Gutzwiller projected BCS states of the extended Hubbard model in the large $U$ limit, or the $t$-$t'$-$J$-$J'$ model on a two-dimensional checkerboard lattice. At small $t'/t$, the frustration due to the diagonal terms of $t'$ and $J'$ does not alter the $d_{x^2-y^2}$-wave pairing symmetry, and the negative (positive) $t'/t$ enhances (suppresses) the pairing order parameter. At large $t'/t$, the ground state has an extended s-wave symmetry. At the intermediate $t'/t$, the ground state is $d+id$ or $d+is$-wave with time reversal symmetry broken.Comment: 6 pages, 6 figure

Two-stage Denoising Diffusion Model for Source Localization in Graph Inverse Problems

Source localization is the inverse problem of graph information dissemination and has broad practical applications. However, the inherent intricacy and uncertainty in information dissemination pose significant challenges, and the ill-posed nature of the source localization problem further exacerbates these challenges. Recently, deep generative models, particularly diffusion models inspired by classical non-equilibrium thermodynamics, have made significant progress. While diffusion models have proven to be powerful in solving inverse problems and producing high-quality reconstructions, applying them directly to the source localization is infeasible for two reasons. Firstly, it is impossible to calculate the posterior disseminated results on a large-scale network for iterative denoising sampling, which would incur enormous computational costs. Secondly, in the existing methods for this field, the training data itself are ill-posed (many-to-one); thus simply transferring the diffusion model would only lead to local optima. To address these challenges, we propose a two-stage optimization framework, the source localization denoising diffusion model (SL-Diff). In the coarse stage, we devise the source proximity degrees as the supervised signals to generate coarse-grained source predictions. This aims to efficiently initialize the next stage, significantly reducing its convergence time and calibrating the convergence process. Furthermore, the introduction of cascade temporal information in this training method transforms the many-to-one mapping relationship into a one-to-one relationship, perfectly addressing the ill-posed problem. In the fine stage, we design a diffusion model for the graph inverse problem that can quantify the uncertainty in the dissemination. The proposed SL-Diff yields excellent prediction results within a reasonable sampling time at extensive experiments