HpGAN: Sequence Search with Generative Adversarial Networks

Sequences play an important role in many engineering applications and systems. Searching sequences with desired properties has long been an interesting but also challenging research topic. This article proposes a novel method, called HpGAN, to search desired sequences algorithmically using generative adversarial networks (GAN). HpGAN is based on the idea of zero-sum game to train a generative model, which can generate sequences with characteristics similar to the training sequences. In HpGAN, we design the Hopfield network as an encoder to avoid the limitations of GAN in generating discrete data. Compared with traditional sequence construction by algebraic tools, HpGAN is particularly suitable for intractable problems with complex objectives which prevent mathematical analysis. We demonstrate the search capabilities of HpGAN in two applications: 1) HpGAN successfully found many different mutually orthogonal complementary code sets (MOCCS) and optimal odd-length Z-complementary pairs (OB-ZCPs) which are not part of the training set. In the literature, both MOCSSs and OB-ZCPs have found wide applications in wireless communications. 2) HpGAN found new sequences which achieve four-times increase of signal-to-interference ratio--benchmarked against the well-known Legendre sequence--of a mismatched filter (MMF) estimator in pulse compression radar systems. These sequences outperform those found by AlphaSeq.Comment: 12 pages, 16 figure

Synergistic Catalysis of Ruthenium Nanoparticles and Polyoxometalate Integrated Within Single UiO−66 Microcrystals for Boosting the Efficiency of Methyl Levulinate to γ-Valerolactone

The synthesis of heterogeneous cooperative catalysts in which two or more catalytically active components are spatially separated within a single material has generated considerable research efforts. The multiple functionalities of catalysts can significantly improve the efficiency of existing organic chemical transformations. Herein, we introduce ruthenium (Ru) nanoparticles (NPs) on the surfaces of a metal–organic framework pre-encapsulated with polyoxometalate silicotungstic acid (SiW) UiO−66 (University of Oslo [UiO]) and prepared a 2.0% Ru/11.7% SiW@UiO−66 porous hybrid using the impregnation method. The close synergistic effect of metal Ru NPs, SiW, and UiO-66 endow 2.0% Ru/11.7% SiW@UiO-66 with increased activity and stability for complete methyl levulinate (ML) conversion and exclusive γ-valerolactone (GVL) selectivity at mild conditions of 80°C and at a H2 pressure of 0.5 MPa. Effectively, this serves as a model reaction for the upgrading of biomass and outperforms the performances of the constituent parts and that of the physical mixture (SiW + Ru/UiO−66). The highly dispersed Ru NPs act as active centers for hydrogenation, while the SiW molecules possess Brønsted acidic sites that cooperatively promote the subsequent lactonization of MHV to generate GVL, and the UiO−66 crystal accelerates the mass transportation facilitated by its own porous structure with a large surface area

The connection between tricarboxylic acid cycle enzyme mutations and pseudohypoxic signaling in pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from chromaffin cells, holding significant clinical importance due to their capacity for excessive catecholamine secretion and associated cardiovascular complications. Roughly 80% of cases are associated with genetic mutations. Based on the functionality of these mutated genes, PPGLs can be categorized into distinct molecular clusters: the pseudohypoxia signaling cluster (Cluster-1), the kinase signaling cluster (Cluster-2), and the WNT signaling cluster (Cluster-3). A pivotal factor in the pathogenesis of PPGLs is hypoxia-inducible factor-2α (HIF2α), which becomes upregulated even under normoxic conditions, activating downstream transcriptional processes associated with pseudohypoxia. This adaptation provides tumor cells with a growth advantage and enhances their ability to thrive in adverse microenvironments. Moreover, pseudohypoxia disrupts immune cell communication, leading to the development of an immunosuppressive tumor microenvironment. Within Cluster-1a, metabolic perturbations are particularly pronounced. Mutations in enzymes associated with the tricarboxylic acid (TCA) cycle, such as succinate dehydrogenase (SDHx), fumarate hydratase (FH), isocitrate dehydrogenase (IDH), and malate dehydrogenase type 2 (MDH2), result in the accumulation of critical oncogenic metabolic intermediates. Notable among these intermediates are succinate, fumarate, and 2-hydroxyglutarate (2-HG), which promote activation of the HIFs signaling pathway through various mechanisms, thus inducing pseudohypoxia and facilitating tumorigenesis. SDHx mutations are prevalent in PPGLs, disrupting mitochondrial function and causing succinate accumulation, which competitively inhibits α-ketoglutarate-dependent dioxygenases. Consequently, this leads to global hypermethylation, epigenetic changes, and activation of HIFs. In FH-deficient cells, fumarate accumulation leads to protein succination, impacting cell function. FH mutations also trigger metabolic reprogramming towards glycolysis and lactate synthesis. IDH1/2 mutations generate D-2HG, inhibiting α-ketoglutarate-dependent dioxygenases and stabilizing HIFs. Similarly, MDH2 mutations are associated with HIF stability and pseudohypoxic response. Understanding the intricate relationship between metabolic enzyme mutations in the TCA cycle and pseudohypoxic signaling is crucial for unraveling the pathogenesis of PPGLs and developing targeted therapies. This knowledge enhances our comprehension of the pivotal role of cellular metabolism in PPGLs and holds implications for potential therapeutic advancements

On-chip topological transport of optical frequency combs in silicon-based valley photonic crystals

The generation and control of optical frequency combs in integrated photonic systems enables complex, high-controllable, and large-scale devices. In parallel, harnessing topological physics in multipartite systems has allowed them with compelling features such as robustness against fabrication imperfections. Here we experimentally demonstrate on-chip topological transport for optical frequency combs at telecommunication wavelengths, both in classical and nonclassical domains. We access both the quantum frequency combs and dissipative Kerr soliton combs with a micro-resonator. The quantum frequency comb, that is, a coherent superposition of multiple frequency modes, is proven to be a frequency-entangled qudit state. We also show that dissipative Kerr soliton combs are highly coherent and mode-locked due to the collective coherence or self-organization of solitons. Moreover, the valley kink states allow both quantum frequency combs and dissipative Kerr soliton combs with robustness against sharp bends. Our topologically protected optical frequency combs could enable the inherent robustness in integrated complex photonic systems.Comment: 20 pages,12 figure

Fenofibrate Improved Interstitial Fibrosis of Renal Allograft through Inhibited Epithelial-Mesenchymal Transition Induced by Oxidative Stress

The best treatment for end-stage renal disease is renal transplantation. However, it is often difficult to maintain a renal allograft healthy for a long time following transplantation. Interstitial fibrosis and tubular atrophy (IF/TA) are significant histopathologic characteristics of a compromised renal allograft. There is no effective therapy to improve renal allograft function once IF/TA sets in. Although there are many underlying factors that can induce IF/TA, the pathogenesis of IF/TA has not been fully elucidated. It has been found that epithelial-mesenchymal transition (EMT) significantly contributes to the development of IF/TA. Oxidative stress is one of the main causes that induce EMT in renal allografts. In this study, we have used H2O2 to induce oxidative stress in renal tubular epithelial cells (NRK-52e) of rats. We also pretreated NRK-52e cells with an antioxidant (N-acetyl L-cysteine (NAC)) 1 h prior to the treatment with H2O2. Furthermore, we used fenofibrate (a peroxisome proliferator-activated receptor α agonist) to treat NRK-52e cells and a renal transplant rat model. Our results reveal that oxidative stress induces EMT in NRK-52e cells, and pretreatment with NAC can suppress EMT in these cells. Moreover, fenofibrate suppresses fibrosis by ameliorating oxidative stress-induced EMT in a rat model. Thus, fenofibrate may effectively prevent the development of fibrosis in renal allograft and improve the outcome

HpGAN: Sequence Search With Generative Adversarial Networks.

Sequences play an important role in many engineering applications. Searching sequences with desired properties has long been an intriguing but also challenging research topic. This article proposes a novel method, called HpGAN, to search desired sequences algorithmically using generative adversarial networks (GANs). HpGAN is based on the idea of zero-sum game to train a generative model, which can generate sequences with characteristics similar to the training sequences. In HpGAN, we design the Hopfield network as an encoder to avoid the limitations of GAN in generating discrete data. Compared with traditional sequence construction by algebraic tools, HpGAN is particularly suitable for complex problems which are intractable by mathematical analysis. We demonstrate the search capabilities of HpGAN in two applications: 1) HpGAN successfully found many different mutually orthogonal complementary sequence sets (MOCSSs) and optimal odd-length binary Z-complementary pairs (OB-ZCPs) which are not part of the training set. In the literature, both MOCSSs and OB-ZCPs have found wide applications in wireless communications and 2) HpGAN found new sequences which achieve a four-times increase of signal-to-interference ratio--benchmarked against the well-known Legendre sequences--of a mismatched filter (MMF) estimator in pulse compression radar systems. These sequences outperform those found by AlphaSeq