PADI4 and tumourigenesis

PADI4 post-translationally converts peptidylarginine to citrulline, a process called citrullination. Studies have demonstrated the high expression of PADI4 in various malignant tumour tissues. PADI4 is also expressed at high levels in the blood of patients with some malignant tumours. Thus far, citrullination of histone, cytokeratin, antithrombin and fibronectin have been confirmed to be involved in abnormal apoptosis, high coagulation, and disordered cell proliferation and differentiation, all of which are main features of malignant tumours. PADI4 is expressed in CD34+ stem cells in normal tissues, and many more CD34+ cells expressing PADI4 are present in tumour tissues. These findings suggest that PADI4 may play an important role in tumourigenesis

Inhibition of antithrombin by hyaluronic acid may be involved in the pathogenesis of rheumatoid arthritis

Thrombin is a key factor in the stimulation of fibrin deposition, angiogenesis, proinflammatory processes, and proliferation of fibroblast-like cells. Abnormalities in these processes are primary features of rheumatoid arthritis (RA) in synovial tissues. Tissue destruction in joints causes the accumulation of large quantities of free hyaluronic acid (HA) in RA synovial fluid. The present study was conducted to investigate the effects of HA and several other glycosaminoglycans on antithrombin, a plasma inhibitor of thrombin. Various glycosaminoglycans, including HA, chondroitin sulfate, keratan sulfate, heparin, and heparan, were incubated with human antithrombin III in vitro. The residual activity of antithrombin was determined using a thrombin-specific chromogenic assay. HA concentrations ranging from 250 to 1000 μg/ml significantly blocked the ability of antithrombin to inhibit thrombin in the presence of Ca(2+ )or Fe(3+), and chondroitin A, B and C also reduced this ability under the same conditions but to a lesser extent. Our study suggests that the high concentration of free HA in RA synovium may block antithrombin locally, thereby deregulating thrombin activity to drive the pathogenic process of RA under physiological conditions. The study also helps to explain why RA occurs and develops in joint tissue, because the inflamed RA synovium is uniquely rich in free HA along with extracellular matrix degeneration. Our findings are consistent with those of others regarding increased coagulation activity in RA synovium

Distilling Representations from GAN Generator via Squeeze and Span

In recent years, generative adversarial networks (GANs) have been an actively studied topic and shown to successfully produce high-quality realistic images in various domains. The controllable synthesis ability of GAN generators suggests that they maintain informative, disentangled, and explainable image representations, but leveraging and transferring their representations to downstream tasks is largely unexplored. In this paper, we propose to distill knowledge from GAN generators by squeezing and spanning their representations. We squeeze the generator features into representations that are invariant to semantic-preserving transformations through a network before they are distilled into the student network. We span the distilled representation of the synthetic domain to the real domain by also using real training data to remedy the mode collapse of GANs and boost the student network performance in a real domain. Experiments justify the efficacy of our method and reveal its great significance in self-supervised representation learning. Code is available at https://github.com/yangyu12/squeeze-and-span.Comment: 16 pages, NeurIPS 202

Transgenic mice over-expressing carbonic anhydrase I showed aggravated joint inflammation and tissue destruction

BACKGROUND: Studies have demonstrated that carbonic anhydrase I (CA1) stimulates calcium salt precipitation and cell calcification, which is an essential step in new bone formation. Our study had reported that CA1 encoding gene has a strong association with rheumatoid arthritis (RA) and ankylosing spondylitis (AS), two rheumatic diseases with abnormal new bone formation and bone resorption in joints. This study investigated the effect of CA1 on joint inflammation and tissue destruction in transgenic mice that over-express CA1 (CA1-Tg). METHODS: CA1-Tg was generated with C57BL/6J mice by conventional methods. CA1-Tg was treated with collagen-II to induce arthritis (CIA). Wild-type mice, CA1-Tg treated with bovine serum albumin (BSA) and transgenic mice over-expressing PADI4 (PADI4-Tg), a gene known to be involved in rheumatoid arthritis, were used as controls. Histochemistry and X-ray radiographic assay were used to examine joint destruction. Western blotting and real time-PCR were used to examine CA1 expression. RESULTS: CIA was observed in 60% of CA1-Tg, 20% of PADI4-Tg and 20% of wild-type mice after collagen injections. No CIA was found in CA1-Tg mice that received injections of BSA. The arthritic score was 5.5 ± 0.84 in the CA1-Tgs but the score was less than 2 in the injected wild-type mice and the PADI4-Tgs. The thickness of the hind paws in the CA1-Tgs was 3.46 ± 0.11 mm, which was thicker than that of PADI4-Tgs (2.23 ± 0.08 mm), wild-type mice (2.08 ± 0.06 mm) and BSA-treated CA1-Tgs (2.04 ± 0.07 mm). Histochemistry showed obvious inflammation, synovial hyperplasia and bone destruction in the joints of CA1-Tg that was not detected in PADI4-Tgs or wild-type mice. X-ray assays showed bone fusion in the paws and spines of CA1-Tg mice. CONCLUSION: Over-expression of CA1 may aggravate joint inflammation and tissue destruction in the transgenic mice

Gaussian Differential Privacy on Riemannian Manifolds

We develop an advanced approach for extending Gaussian Differential Privacy (GDP) to general Riemannian manifolds. The concept of GDP stands out as a prominent privacy definition that strongly warrants extension to manifold settings, due to its central limit properties. By harnessing the power of the renowned Bishop-Gromov theorem in geometric analysis, we propose a Riemannian Gaussian distribution that integrates the Riemannian distance, allowing us to achieve GDP in Riemannian manifolds with bounded Ricci curvature. To the best of our knowledge, this work marks the first instance of extending the GDP framework to accommodate general Riemannian manifolds, encompassing curved spaces, and circumventing the reliance on tangent space summaries. We provide a simple algorithm to evaluate the privacy budget $\mu$ on any one-dimensional manifold and introduce a versatile Markov Chain Monte Carlo (MCMC)-based algorithm to calculate $\mu$ on any Riemannian manifold with constant curvature. Through simulations on one of the most prevalent manifolds in statistics, the unit sphere $S^d$, we demonstrate the superior utility of our Riemannian Gaussian mechanism in comparison to the previously proposed Riemannian Laplace mechanism for implementing GDP