Addressing Domain Shift via Knowledge Space Sharing for Generalized Zero-Shot Industrial Fault Diagnosis

Fault diagnosis is a critical aspect of industrial safety, and supervised industrial fault diagnosis has been extensively researched. However, obtaining fault samples of all categories for model training can be challenging due to cost and safety concerns. As a result, the generalized zero-shot industrial fault diagnosis has gained attention as it aims to diagnose both seen and unseen faults. Nevertheless, the lack of unseen fault data for training poses a challenging domain shift problem (DSP), where unseen faults are often identified as seen faults. In this article, we propose a knowledge space sharing (KSS) model to address the DSP in the generalized zero-shot industrial fault diagnosis task. The KSS model includes a generation mechanism (KSS-G) and a discrimination mechanism (KSS-D). KSS-G generates samples for rare faults by recombining transferable attribute features extracted from seen samples under the guidance of auxiliary knowledge. KSS-D is trained in a supervised way with the help of generated samples, which aims to address the DSP by modeling seen categories in the knowledge space. KSS-D avoids misclassifying rare faults as seen faults and identifies seen fault samples. We conduct generalized zero-shot diagnosis experiments on the benchmark Tennessee-Eastman process, and our results show that our approach outperforms state-of-the-art methods for the generalized zero-shot industrial fault diagnosis problem

Solving Expensive Optimization Problems in Dynamic Environments with Meta-learning

Dynamic environments pose great challenges for expensive optimization problems, as the objective functions of these problems change over time and thus require remarkable computational resources to track the optimal solutions. Although data-driven evolutionary optimization and Bayesian optimization (BO) approaches have shown promise in solving expensive optimization problems in static environments, the attempts to develop such approaches in dynamic environments remain rarely unexplored. In this paper, we propose a simple yet effective meta-learning-based optimization framework for solving expensive dynamic optimization problems. This framework is flexible, allowing any off-the-shelf continuously differentiable surrogate model to be used in a plug-in manner, either in data-driven evolutionary optimization or BO approaches. In particular, the framework consists of two unique components: 1) the meta-learning component, in which a gradient-based meta-learning approach is adopted to learn experience (effective model parameters) across different dynamics along the optimization process. 2) the adaptation component, where the learned experience (model parameters) is used as the initial parameters for fast adaptation in the dynamic environment based on few shot samples. By doing so, the optimization process is able to quickly initiate the search in a new environment within a strictly restricted computational budget. Experiments demonstrate the effectiveness of the proposed algorithm framework compared to several state-of-the-art algorithms on common benchmark test problems under different dynamic characteristics

Manometric Measurement of the Sphincter of Oddi in Patients with Common Bile Duct Stones: A Consecutive Study of the Han Population of China

Objective. Role of dysfunction of the sphincter of Oddi (SO) in choledocholithiasis is controversial. This study was to evaluate SO motor activity in patients with common bile duct (CBD) stones in the Han population of China. Patients and Methods. In this study, 76 patients with CBD stones were enrolled in a single tertiary endoscopy center. Data of SO motor activities was prospectively evaluated by endoscopic manometry. Mean basal SO pressure, amplitude, and frequency were collected and analyzed. Results. The mean basal SO pressure, amplitude, and frequency were 52.7±40.0 (1.60–171.1) mmHg, 39.9±19.7 (14.9–115.5) mmHg, and 5.7±3.2 (1.3–13.8)/min, respectively. The basal SO pressure was higher in patients with CBD stones < 10 mm in diameter than that in those with CBD stones larger than 10 mm in diameter (60.7±41.0 mmHg versus 36.8±29.4 mmHg, P=0.043). There was no significant difference in the basal SO pressure, amplitude, and frequency when compared with the CBD diameter, CBD stone number, prior cholecystectomy, periampullary diverticula, and symptoms. Levels of alanine aminotransferase, aspartate transaminase, γ-glutamyl transpeptidase, and alkaline phosphatase showed no significant difference in patients with normal or elevated basal SO pressure. Conclusion. These results identify that, in Chinese Han population, abnormalities of SO motor activity are associated with CBD stones

PDE2 Inhibits PKA-Mediated Phosphorylation of TFAM to Promote Mitochondrial Ca2+-Induced Colorectal Cancer Growth

Growing evidence indicates that the dysregulation of mitochondrial calcium (Ca2+) plays a critical role in the growth of tumor cells, including colorectal cancer (CRC). However, the underling mechanism is not fully elucidated. In this study, the regulatory effects of mitochondrial Ca2+ on phosphodiesterase 2 (PDE2)/cAMP/PKA axis and the phosphorylation of mitochondrial transcription factor A (TFAM) as well as the growth of CRC cells were systematically investigated both in vitro and in vivo. Our findings demonstrated that MCU-induced mitochondrial Ca2+ uptake activated mitochondrial PDE2 in CRC cells. Moreover, overexpression MCU in CRC led to a 1.9-fold increase in Ca2+ uptake compared to control cells. However, knockdown of MCU resulted in 1.5-fould decrease in Ca2+ uptake in mitochondria compared to the controls. Activation of mitochondrial PDE2 significantly inhibited the activity of mitochondrial protein kinase A (PKA), which subsequently leads to decreased phosphorylation of TFAM. Our data further revealed that PKA regulates the phosphorylation of TFAM and promotes the degradation of phosphorylated TFAM. Thus, TFAM protein levels accumulated in mitochondria when the activity of PKA was inhibited. Overall, this study showed that the overexpression of MCU enhanced CRC growth through promoting the accumulation of TFAM proteins in mitochondria. Conversely, knockdown of MCU in CRC cells resulted in decreased CRC growth. Collectively, these data suggest that the mitochondrial Ca2+-activated PDE2/cAMP/PKA axis plays a key role in regulating TFAM stability and the growth of CRC cells

Comparative transcriptome profiling reveals the importance of GmSWEET15 in soybean susceptibility to Sclerotinia sclerotiorum

Soybean sclerotinia stem rot (SSR) is a disease caused by Sclerotinia sclerotiorum that causes incalculable losses in soybean yield each year. Considering the lack of effective resistance resources and the elusive resistance mechanisms, we are urged to develop resistance genes and explore their molecular mechanisms. Here, we found that loss of GmSWEET15 enhanced the resistance to S. sclerotiorum, and we explored the molecular mechanisms by which gmsweet15 mutant exhibit enhanced resistance to S. sclerotiorum by comparing transcriptome. At the early stage of inoculation, the wild type (WT) showed moderate defense response, whereas gmsweet15 mutant exhibited more extensive and intense transcription reprogramming. The gmsweet15 mutant enriched more biological processes, including the secretory pathway and tetrapyrrole metabolism, and it showed stronger changes in defense response, protein ubiquitination, MAPK signaling pathway-plant, plant-pathogen interaction, phenylpropanoid biosynthesis, and photosynthesis. The more intense and abundant transcriptional reprogramming of gmsweet15 mutant may explain how it effectively delayed colonization by S. sclerotiorum. In addition, we identified common and specific differentially expressed genes between WT and gmsweet15 mutant after inoculation with S. sclerotiorum, and gene sets and genes related to gmsweet15_24 h were identified through Gene Set Enrichment Analysis. Moreover, we constructed the protein–protein interaction network and gene co-expression networks and identified several groups of regulatory networks of gmsweet15 mutant in response to S. sclerotiorum, which will be helpful for the discovery of candidate functional genes. Taken together, our results elucidate molecular mechanisms of delayed colonization by S. sclerotiorum after loss of GmSWEET15 in soybean, and we propose novel resources for improving resistance to SSR

Genome-wide identification and analysis of heterotic loci in three maize hybrids

Heterosis, or hybrid vigour, is a predominant phenomenon in plant genetics, serving as the basis of crop hybrid breeding, but the causative loci and genes underlying heterosis remain unclear in many crops. Here, we present a large-scale genetic analysis using 5360 offsprings from three elite maize hybrids, which identifies 628 loci underlying 19 yield-related traits with relatively high mapping resolutions. Heterotic pattern investigations of the 628 loci show that numerous loci, mostly with complete–incomplete dominance (the major one) or overdominance effects (the secondary one) for heterozygous genotypes and nearly equal proportion of advantageous alleles from both parental lines, are the major causes of strong heterosis in these hybrids. Follow-up studies for 17 heterotic loci in an independent experiment using 2225 F2 individuals suggest most heterotic effects are roughly stable between environments with a small variation. Candidate gene analysis for one major heterotic locus (ub3) in maize implies that there may exist some common genes contributing to crop heterosis. These results provide a community resource for genetics studies in maize and new implications for heterosis in plants

Genetic Polymorphism in a VEGF-Independent Angiogenesis Gene ANGPT1 and Overall Survival of Colorectal Cancer Patients after Surgical Resection

Background The VEGF-independent angiogenic signaling plays an important role in the development of colorectal cancer (CRC). However, its implication in the clinical outcome of CRC has not been reported. This study aimed to investigate the association between genetic variations in several major VEGF-independent signaling pathway genes and the overall survival of CRC patients. Methods Seven single nucleotide polymorphisms (SNPs) in four important VEGF-independent angiogenic genes (ANGPT1, AMOT, DLL4 and ENG) were genotyped in a Chinese population with 408 CRC patients. Results One SNP, rs1954727 in ANGPT1, was significantly associated with CRC overall survival. Compared to patients with the homozygous wild-type genotype of rs1954727, those with heterozygous and homozygous variant genotypes exhibited a favorable overall survival with a hazard ratio (HR) of 0.89 (95% confidence interval [CI] 0.55–1.43, P = 0.623), and 0.32 (95% CI 0.15–0.71, P = 0.005), respectively (P trend = 0.008). In stratified analysis, this association remained significant in patients receiving chemotherapy (P trend = 0.012), but not in those without chemotherapy. We further evaluated the effects of chemotherapy on CRC survival that was stratified by rs1954727 genotypes. We found that chemotherapy resulted in a significantly better overall survival in the CRC patients (HR = 0.44, 95% CI 0.26–0.75, P = 0.002), which was especially prominent in those patients with the heterozygous genotype of rs1954727 (HR = 0.45, 95%CI 0.22–0.92, P = 0.028). Conclusion Our data suggest that rs1954727 in ANGPT1 gene might be a prognostic biomarker for the overall survival of CRC patients, especially in those receiving chemotherapy, a finding that warrants validation in larger independent populations

RNA-Seq Analyses Generate Comprehensive Transcriptomic Landscape and Reveal Complex Transcript Patterns in Hepatocellular Carcinoma

RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify >50% of all the annotated genes for each sample. Furthermore, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3–24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels