Adaptive tempered reversible jump algorithm for Bayesian curve fitting

Bayesian curve fitting plays an important role in inverse problems, and is often addressed using the reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. However, this algorithm can be computationally inefficient without appropriately tuned proposals. As a remedy, we present an adaptive RJMCMC algorithm for the curve fitting problems by extending the adaptive Metropolis sampler from a fixed-dimensional to a trans-dimensional case. In this presented algorithm, both the size and orientation of the proposal function can be automatically adjusted in the sampling process. Specifically, the curve fitting setting allows for the approximation of the posterior covariance of the a priori unknown function on a representative grid of points. This approximation facilitates the definition of efficient proposals. In addition, we introduce an auxiliary-tempered version of this algorithm via non-reversible parallel tempering. To evaluate the algorithms, we conduct numerical tests involving a series of controlled experiments. The results demonstrate that the adaptive algorithms exhibit significantly higher efficiency compared to the conventional ones. Even in cases where the posterior distribution is highly complex, leading to ineffective convergence in the auxiliary-tempered conventional RJMCMC, the proposed auxiliary-tempered adaptive RJMCMC performs satisfactorily. Furthermore, we present a realistic inverse example to test the algorithms. The successful application of the adaptive algorithm distinguishes it again from the conventional one that fails to converge effectively even after millions of iterations.<br/

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

Graph Neural Networks (GNNs) have emerged as the de facto standard for representation learning on graphs, owing to their ability to effectively integrate graph topology and node attributes. However, the inherent suboptimal nature of node connections, resulting from the complex and contingent formation process of graphs, presents significant challenges in modeling them effectively. To tackle this issue, Graph Structure Learning (GSL), a family of data-centric learning approaches, has garnered substantial attention in recent years. The core concept behind GSL is to jointly optimize the graph structure and the corresponding GNN models. Despite the proposal of numerous GSL methods, the progress in this field remains unclear due to inconsistent experimental protocols, including variations in datasets, data processing techniques, and splitting strategies. In this paper, we introduce OpenGSL, the first comprehensive benchmark for GSL, aimed at addressing this gap. OpenGSL enables a fair comparison among state-of-the-art GSL methods by evaluating them across various popular datasets using uniform data processing and splitting strategies. Through extensive experiments, we observe that existing GSL methods do not consistently outperform vanilla GNN counterparts. However, we do observe that the learned graph structure demonstrates a strong generalization ability across different GNN backbones, despite its high computational and space requirements. We hope that our open-sourced library will facilitate rapid and equitable evaluation and inspire further innovative research in the field of GSL. The code of the benchmark can be found in https://github.com/OpenGSL/OpenGSL.Comment: 9 pages, 4 figure

Effects of Chinese Medicine Tong xinluo on Diabetic Nephropathy via Inhibiting TGF- β

Diabetic nephropathy (DN) is a major cause of chronic kidney failure and characterized by interstitial and glomeruli fibrosis. Epithelial-to-mesenchymal transition (EMT) plays an important role in the pathogenesis of DN. Tong xinluo (TXL), a Chinese herbal compound, has been used in China with established therapeutic efficacy in patients with DN. To investigate the molecular mechanism of TXL improving DN, KK-Ay mice were selected as models for the evaluation of pathogenesis and treatment in DN. In vitro, TGF-β1 was used to induce EMT. Western blot (WB), immunofluorescence staining, and real-time polymerase chain reaction (RT-PCR) were applied to detect the changes of EMT markers in vivo and in vitro, respectively. Results showed the expressions of TGF-β1 and its downstream proteins smad3/p-smad3 were greatly reduced in TXL group; meantime, TXL restored the expression of smad7. As a result, the expressions of collagen IV (Col IV) and fibronectin (FN) were significantly decreased in TXL group. In vivo, 24 h-UAER (24-hour urine albumin excretion ratio) and BUN (blood urea nitrogen) were decreased and Ccr (creatinine clearance ratio) was increased in TXL group compared with DN group. In summary, the present study demonstrates that TXL successfully inhibits TGF-β1-induced epithelial-to-mesenchymal transition in DN, which may account for the therapeutic efficacy in TXL-mediated renoprotection

Longitudinal morphological and functional characterization of human heart organoids using optical coherence tomography

Organoids play an increasingly important role as in vitro models for studying organ development, disease mechanisms, and drug discovery. Organoids are self-organizing, organ-like three-dimensional (3D) cell cultures developing organ-specific cell types and functions. Recently, three groups independently developed self-assembling human heart organoids (hHOs) from human pluripotent stem cells (hPSCs). In this study, we utilized a customized spectral-domain optical coherence tomography (SD-OCT) system to characterize the growth of hHOs. Development of chamber structures and beating patterns of the hHOs were observed via OCT and calcium imaging. We demonstrated the capability of OCT to produce 3D images in a fast, label-free, and non-destructive manner. The hHOs formed cavities of various sizes, and complex interconnections were observed as early as on day 4 of differentiation. The hHOs models and the OCT imaging system showed promising insights as an in vitro platform for investigating heart development and disease mechanisms

A novel method for determining the neutral axis position of the asymmetric cross section and its application in the simplified progressive collapse method for damaged ships

Ultimate strength is an important design consideration for the safety of intact or damaged ship structures. The simplified progressive collapse method is a commonly used iterative method to obtain the accurate ultimate strength of ships. Since the accuracy of the neutral axis position directly affects the accuracy of the ultimate strength, the force equilibrium criterion and the force vector equilibrium criterion are adopted to search for the height and angle of the neutral axis, especially for damaged ships. However, the search for the neutral axis position based on the two criteria requires iterative computation which decreases the calculation efficiency. In this paper, the relationship between the results of the iterative process and the neutral axis position is studied, and it is found that the relationship is approximately linear. Then a new iterative method based on the linear equation is proposed to obtain the neutral axis position and is adopted to improve the simplified progressive collapse method. Finally, the new method is used to calculate the neutral axis position of a damaged VLCC. The comparison of the ultimate strength results shows that the improved simplified progressive collapse method based on the linear equation has improved efficiency and good accuracy

Enhanced multiclass SVM with thresholding fusion for speech-based emotion classification

As an essential approach to understanding human interactions, emotion classification is a vital component of behavioral studies as well as being important in the design of context-aware systems. Recent studies have shown that speech contains rich information about emotion, and numerous speech-based emotion classification methods have been proposed. However, the classification performance is still short of what is desired for the algorithms to be used in real systems. We present an emotion classification system using several one-against-all support vector machines with a thresholding fusion mechanism to combine the individual outputs, which provides the functionality to effectively increase the emotion classification accuracy at the expense of rejecting some samples as unclassified. Results show that the proposed system outperforms three state-of-the-art methods and that the thresholding fusion mechanism can effectively improve the emotion classification, which is important for applications that require very high accuracy but do not require that all samples be classified. We evaluate the system performance for several challenging scenarios including speaker-independent tests, tests on noisy speech signals, and tests using non-professional acted recordings, in order to demonstrate the performance of the system and the effectiveness of the thresholding fusion mechanism in real scenarios.Peer ReviewedPreprin

The complete reference genome for grapevine (Vitis vinifera L.) genetics and breeding

Grapevine is one of the most economically important crops worldwide. However, the previous versions of the grapevine reference genome consisted of thousands of fragments with missing centromeres and telomeres, which limited the accessibility of the repetitive sequences, the centromeric and telomeric regions, and the inheritance of important agronomic traits in these regions. Here, we assembled a telomere-to-telomere (T2T) gap-free reference genome for the pinot noir cultivar (PN40024) using the PacBio HiFi long reads. The T2T reference genome (PN_T2T) was 69 Mb longer with 9026 more genes identified than the 12X.v2 version (Canaguier et al., 2017). We annotated 67% repetitive sequences, 19 centromeres and 36 telomeres, and incorporated gene annotations of previous versions into the PN_T2T. We detected a total of 377 gene clusters, which showed associations with complex traits, such as aroma and disease resistance. Even though the PN40024 sample had been selfed for nine generations, we still found nine genomic hotspots of heterozygous sites associated with biological processes, such as the oxidation-reduction process and protein phosphorylation. The fully annotated complete reference genome, therefore, provides important resources for grapevine genetics and breeding.This work was supported by the National Natural Science Fund for Excellent Young Scientists Fund Program (Overseas) to Yongfeng Zhou, the National Key Research and Development Program of China(grant2019YFA0906200), the Agricultural Science and Technology Innovation Program (CAAS-ZDRW202101), the Shenzhen Science and Technology Program (grant KQTD2016113010482651), the BMBF funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI). We thank Bianca Frommer, Marie Lahaye, David Navarro-Payá, Marcela K. Tello-Ruiz and Kapeel Chougule for their help in analyzing the RNA-Seq data and in running the gene annotation pipeline. This study is also based upon work from COST Action CA17111 INTEGRAPE and form COST Innovators Grant IG17111 GRAPEDIA, supported by COST (European Cooperation in Science and Technology).ViticultureT2Tgap-fregene clustercentromeretelomerePublishe

The “Golden Apple”: Gold Catalysis in the Synthesis of Caged Indole Alkaloids, Strictamine and Arborisidine, and Harziane Diterpenes

Chapter 1 Gold Catalysis: Strategic Advantages in the Total Syntheses of Complex Natural Products Since its early use in the late 1980 and 1990, homogeneous gold catalysis has emerged as a powerful tool in the field of natural product synthesis. Herein, we illustrated with recent examples that the incorporation of gold catalysis in total synthesis has benefited tremendously in the rapid construction of challenging all-carbon quaternary centers and medium-sized ring. Chapter 2 Formal Synthesis of (+)-Strictamine Strictamine is a pentacyclic Akuammiline alkaloid isolated in 1966 bearing a unique methanoquinolizidine core and its total synthesis puzzle has not been solved for 50 years. While a number of total and formal syntheses of strictamine were discloses by other labs in recent years, all of them required no less than 14 steps of chemical transformations. We developed a gold-catalyzed 6-endo-dig cyclization with “protonation as traceless protection” strategy to access the key intermediate towards strictamine and accomplished a concise formal synthesis of strictamine (6 step racemic, 7 step asymmetric). The application of an enantioselective propargylation developed during the course of our research was also demonstrated in the catalytic asymmetric synthesis of other indole alkaloids. Chapter 3 Total Synthesis of (+)-Arborisidine Arborisidine is a pentacyclic indole alkaloid isolated in 2016 containing a rare fully substituted cyclohexanone moiety, with promising in vitro inhibition activity of gastric cancer in combination of pimelautide. The presence of aza-quaternary center and dense substitutions raised significant synthetic challenges. Herein, we discussed our elaborations of 6-endo-dig cyclization reactions and detours to access the intriguing core of arborisidine, and additional efforts in the regioselective functionalization of dienes as well as late-stage one-pot redox manipulations, which ultimately led to the first total synthesis of arborisidine (7 steps racemic, 9 steps asymmetric). The development of chemoselective decyanation reaction also provided alternative entry to the enantioenriched 1-acyl tetrahydro-β-carboline building blocks. Chapter 4 Studies toward Total Synthesis of Harziane Diterpenes Harziane diterpenes, mostly isolated from Trichoderma fungi species, constitute of a considerable number of members sharing a complicated tetracyclic scaffold with four-, five-, six- and seven membered rings, at least five stereocenters and three all-carbon quaternary centers, in which two are vicinal. We designed a unified approach taking advantage of the gold-catalyzed [2+2] cycloaddition reaction to access the unique 7-4 fused bicyclic system with different types of ring tethers. A ring reorganization strategy was also devised, complementary to the innate selectivity of Favorskii-type ring contraction. These establishments allowed access to a key ketoaldehyde intermediate in 10 steps that contains the major stereocenters in the right half of harziane diterpenes. With the aid of versatile diene functionalizations, we would hopefully complete the collective total synthesis of harziane diterpene natural products in the near future