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BACKGROUND: The inflammatory response caused by the NLRP3 is closely related to the formation of myocardial ischemia-reperfusion injury. Costimulatory receptor CD137 and its ligand play a crucial role in regulating the inflammatory immune response in atherosclerosis, which is the fundamental cause of cardiovascular diseases. However, the roles of CD137 signaling in the process of myocardial ischaemia-reperfusion (IR) injury remain unknown. METHODS: Genetic ablation was used to determine the functional significance of CD137 in myocardial IR injury. Expression of CD137 was examined by Western-blot, quantitative real-time polymerase chain reaction, and immunohistochemistry in a murine IR model by coronary artery ligation. Even’s blue-TTC staining and echocardiography to evaluate the severity of myocardial IR injury. Furthermore, HL-1 cardiomyocytes treated with agonist-CD137 recombinant protein were used to explore the underlying mechanism in CD137 signaling-induced NLRP3 inflammasome activation in response to hypoxia/reoxygenation or LPS/ATP. RESULTS: We demonstrated that CD137 knockout significantly improved cardiac function, accompanied by a markedly reduced NLRP3-mediated inflammatory response and IA/AAR which were reversed by mitophagy inhibitor Mdivi-1. Activating CD137 signaling significantly inhibited mitophagy and provoked NLRP3-mediated inflammatory response in H/R-injured or LPS-primed and ATP-stimulated HL-1 cardiomyocytes, the effects of which could be abolished by either anti-CD137 or mitophagy activator FCCP. Besides, mitochondrial ROS was augmented by activating CD137 signaling through the suppression of mitophagy. CONCLUSIONS: Our results reveal that activating CD137 signaling aggravates myocardial IR injury by upregulating NLRP3 inflammasome activation via suppressing mitophagy and promoting mtROS generation.

EMUs play an important role in the rapid development of China’s economy, so ensuring the safety of high-speed EMUs has been a research issue for relevant experts and scholars. Because the defect change of the motor car apron will lead to the stability of the whole motor car running on the side, this paper takes the motor car apron defect as the recognition object, and proposes to add feature reasoning module to the typical convolutional network model to improve the ability to identify occlusion defects by solving the problem that the traditional recognition model cannot identify the features of occlusion and stacking and the status quo that cannot be identified under a small number of samples, Then the meta learning mechanism is incorporated into the model to realize the recognition under the condition of few samples in the dataset. Through experimental comparison, it is proved that the performance of the improved recognition network algorithm in recognition accuracy and recognition speed is improved as a whole. &nbsp

In recent years, the research of face age features has achieved rapid development driven by deep learning. The faces generated by the Conditional Adversarial Auto-encoder (CAAE) model are not only highly credible, but also closer to the target age. However, there are many problems, such as low resolution of human face image generation and poor local feature retention effect of human face features. To this end, this paper improves on the CAAE network. Firstly, referring to the LSGAN network structure, the 4 convolution layers of the encoder are added to 5 layers and the 4 convolution layers of the generator are added to 7 layers. Secondly, on the basis of the original loss function, the image gradient difference loss function is added to ensure the output face image quality. Meanwhile, the data set were preprocessed for face correction. Finally, this paper performs face similarity analysis on the Eye-key platform and contrasts the generated image quality using structural similarity and peak signal to noise ratio metrics. In addition, the generated results were tested for their robustness. The experimental results show that the average similarity of faces generated by the Improved Conditional Adversarial Auto-encoder (I-CAAE) network was increased by 3.9. And the average peak signal to noise ratio of the generated pictures was reduced by 1.8. Confirming the superiority of the proposed method. &nbsp

Background: In the treatment of colorectal cancer, laparoscopic surgery has seen a significant amount of success. Reducing the risk of postoperative complications and improving patients’ quality of life can be accomplished by appropriately employing pelvic peritoneal repair and sigmoid colostomy when appropriate. Objective: To compare fusion closure of pelvic peritoneum combined with extraperitoneal colostomy with non-closure of pelvic peritoneum combined with intraperitoneal colostomy in patients with low rectal cancer who had permanent colostomy. Methods: Low rectal cancer patients admitted to Hengshui People’s Hospital for permanent colostomy were evaluated. The participants were divided into two groups: an observation and a control group. All 30 cases in the observation group underwent pelvic peritoneum closure and extraperitoneal colostomy, while the other 30 cases in the control group underwent intraperitoneal colostomy. The C-reactive protein (CRP) levels of the participants in both groups were evaluated for 6 months to 2 years (24 h before, 24 h after, 48 h after, 96 h after surgery). Results: Comparing the colostomy operative time, time to first passage of flatus postoperatively, time to first defecation postoperatively, length of hospital stay, laboratory indicators, stoma-related complications, colostomy function, etc., the colostomy operative time significantly differed between the two groups (P < 0.05); the observation group did considerably better than the control group in terms of stoma-related complications and bowel movement control 6 months after surgery (P < 0.05); and although serum CRP levels increased in both groups 48 h after surgery, the difference was significant (P < 0.05). Conclusion: Extraperitoneal colostomy can improve the quality of life of patients with permanent stoma and reduce the occurrence of stoma-related complications. Thus, this technique is worthy of promotion in clinical practice.

A large body of the literature on automated program repair develops approaches where patches are automatically generated to be validated against an oracle (e.g., a test suite). Because such an oracle can be imperfect, the generated patches, although validated by the oracle, may actually be incorrect. Our empirical work investigates different representation learning approaches for code changes to derive embeddings that are amenable to similarity computations of patch correctness identification, and assess the possibility of accurate classification of correct patch by combining learned embeddings with engineered features. Experimental results demonstrate the potential of learned embeddings to empower Leopard (a patch correctness predicting framework implemented in this work) with learning algorithms in reasoning about patch correctness: a machine learning predictor with BERT transformer-based learned embeddings associated with XGBoost achieves an AUC value of about 0.803 in the prediction of patch correctness on a new dataset of 2,147 labeled patches that we collected for the experiments. Our investigations show that deep learned embeddings can lead to complementary/better performance when comparing against the state-of-the-art, PATCH-SIM, which relies on dynamic information. By combining deep learned embeddings and engineered features, Panther (the upgraded version of Leopard implemented in this work) outperforms Leopard with higher scores in terms of AUC, +Recall and -Recall, and can accurately identify more (in)correct patches that cannot be predicted by the classifiers only with learned embeddings or engineered features. Finally, we use an explainable ML technique, SHAP, to empirically interpret how the learned embeddings and engineered features are contributed to the patch correctness prediction., Comment: arXiv admin note: substantial text overlap with arXiv:2008.02944

Fix pattern-based patch generation is a promising direction in automated program repair (APR). Notably, it has been demonstrated to produce more acceptable and correct patches than the patches obtained with mutation operators through genetic programming. The performance of pattern-based APR systems, however, depends on the fix ingredients mined from fix changes in development histories. Unfortunately, collecting a reliable set of bug fixes in repositories can be challenging. In this article, we propose investigating the possibility in an APR scenario of leveraging fix patterns inferred from code changes that address violations detected by static analysis tools. To that end, we build a fix pattern-based APR tool, Avatar , which exploits fix patterns of static analysis violations as ingredients for the patch generation of repairing semantic bugs. Evaluated on four benchmarks (i.e., Defects4J, Bugs.jar, BEARS, and QuixBugs), Avatar presents the potential feasibility of fixing semantic bugs with the fix patterns inferred from the patches for fixing static analysis violations and can correctly fix 26 semantic bugs when Avatar is implemented with the normal program repair pipeline. We also find that Avatar achieves performance metrics that are comparable to that of the closely related approaches in the literature. Compared with CoCoNut, Avatar can fix 18 new bugs in Defects4J and 3 new bugs in QuixBugs. When compared with HDRepair, JAID, and SketchFix, Avatar can newly fix 14 Defects4J bugs. In terms of the number of correctly fixed bugs, Avatar is also comparable to the program repair tools with the normal fault localization setting and presents better performance than most program repair tools. These results imply that Avatar is complementary to current program repair approaches. We further uncover that Avatar can present different bug-fixing performances when it is configured with different fault localization tools, and the stack trace information from the failed executions of test cases can be exploited to improve the bug-fixing performance of Avatar by fixing more bugs with fewer generated patch candidates. Overall, our study highlights the relevance of static bug-finding tools as indirect contributors of fix ingredients for addressing code defects identified with functional test cases (i.e., dynamic information).

In this study, we explore how to teach mathematics, science and coding through digital tools, design projects, and global competencies. We explore the question: How do upper elementary school children develop an understanding of mathematics and science coupled with coding through digital design? The theoretical framework adopted for this study is Kafai and Burke’s (2014) definition of Computational Participation: a shift from code to actual applications; a shift from tools to communities; a shift from starting from scratch to remixing; and a shift from screens to tangibles. We conducted a qualitative case study interlinked with Design-Based Research. Both STEAM camps were an outreach program for students in grades 4-8 in Ontario, Canada. The two camps were designed and facilitated by a research team from the Faculty of Education. The research team developed the curriculum through an iterative process (design-test-revise-repeat). There were 43 students registered in the STEAM camps, and 34 of them participated in the study. We collected observation, interviews, audio/video recordings, and survey data as well as pictures of the students’ work. Our main findings were that students were provided with opportunities to: 1) develop a deeper understanding of curricular concepts; 2) engage more with the digital tools when they were remixing, improving, and reimaging the design; and 3) apply their knowledge to global competencies. The findings of this research have implications for improvements in researching, designing, and implementing design projects as part of a pedagogical approach to teaching mathematics and science, coupled with coding, in an interdisciplinary context.

Woody oil plants are important economic trees which are widely cultivated and distributed throughout China. Surveys conducted during 2020 and 2021 on several woody oil plantations from five regions of Sichuan Province, China, revealed a high diversity of Botryosphaerialean fungi. The identification of 50 botryosphaeriaceous isolates was carried out based on both morphology and multi-gene phylogenetic analysis of internal transcribed spacer region (ITS), translation elongation factor 1-alpha gene (tef1) and β-tubulin gene (tub2). This allowed the identification of twelve previously known Botryosphaeriales species: Aplosporella prunicola, A. ginkgonis, Barriopsis tectonae, Botryosphaeria dothidea, Bo. fabicerciana, Diplodia mutila, Di. seriata, Dothiorella sarmentorum, Neofusicoccum parvum, Sardiniella guizhouensis, Sphaeropsis citrigena, and Sp. guizhouensis, and four novel species belonging to the genera Diplodia and Dothiorella, viz. Di. acerigena, Di. pistaciicola, Do. camelliae and Do. zanthoxyli. The dominant species isolated across the surveyed regions were Botryosphaeria dothidea, Sardiniella guizhouensis and Diplodia mutila, representing 20%, 14% and 12% of the total isolates, respectively. In addition, most isolates were obtained from Pistacia chinensis (14 isolates), followed by Camellia oleifera (10 isolates). The present study enhances the understanding of Botryosphaeriales species diversity on woody oil plants in Sichuan Province, China.

The rich salt culture resources provide the basic conditions for Zigong City to promote the integration of cultural and tourism development, consolidate the achievements of poverty alleviation, and empower rural revitalization. On the basis of clarifying the mechanism of consolidating poverty alleviation achievements and empowering rural revitalization through the integration of salt culture and tourism in Zigong City, this article explores the practical difficulties of consolidating poverty alleviation achievements and empowering rural revitalization through the integration of cultural and tourism resources, industries, functions, and markets, and explores countermeasures and suggestions to promote the integration of cultural and tourism in Zigong City.

Purpose: The human voice usually contains two types of information: linguistic and identity information. However, whether and how linguistic information interacts with identity information remains controversial. This study aimed to explore the processing of identity and linguistic information during spoken word processing by considering the modulation of attention. Method: We conducted two event-related potentials (ERPs) experiments in the study. Different speakers (self, friend, and unfamiliar speakers) and emotional words (positive, negative, and neutral words) were used to manipulate the identity and linguistic information. With the manipulation, Experiment 1 explored the identity and linguistic information processing with a word decision task that requires participants' explicit attention to linguistic information. Experiment 2 further investigated the issue with a passive oddball paradigm that requires rare attention to either the identity or linguistic information. Results: Experiment 1 revealed an interaction among speaker, word type, and hemisphere in N400 amplitudes but not in N100 and P200, which suggests that identity information interacted with linguistic information at the later stage of spoken word processing. The mismatch negativity results of Experiment 2 showed no significant interaction between speaker and word pair, which indicates that identity and linguistic information were processed independently. Conclusions: The identity information would interact with linguistic information during spoken word processing. However, the interaction was modulated by the task demands on attention involvement. We propose an attention-modulated explanation to explain the mechanism underlying identity and linguistic information processing. Implications of our findings are discussed in light of the integration and independence theories.

Quaternary ammonium compounds (QACs), a large class of chemicals that includes high production volume substances, have been used for decades as antimicrobials, preservatives, and antistatic agents and for other functions in cleaning, disinfecting, personal care products, and durable consumer goods. QAC use has accelerated in response to the COVID-19 pandemic and the banning of 19 antimicrobials from several personal care products by the US Food and Drug Administration in 2016. Studies conducted before and after the onset of the pandemic indicate increased human exposure to QACs. Environmental releases of these chemicals have also increased. Emerging information on adverse environmental and human health impacts of QACs is motivating a reconsideration of the risks and benefits across the life cycle of their production, use, and disposal. This work presents a critical review of the literature and scientific perspective developed by a multidisciplinary, multi-institutional team of authors from academia, governmental, and nonprofit organizations. The review evaluates currently available information on the ecological and human health profile of QACs and identifies multiple areas of potential concern. Adverse ecological effects include acute and chronic toxicity to susceptible aquatic organisms, with concentrations of some QACs approaching levels of concern. Suspected or known adverse health outcomes include dermal and respiratory effects, developmental and reproductive toxicity, disruption of metabolic function such as lipid homeostasis, and impairment of mitochondrial function. QACs' role in antimicrobial resistance has also been demonstrated. In the US regulatory system, how a QAC is managed depends on how it is used, for example in pesticides or personal care products. This can result in the same QACs receiving different degrees of scrutiny depending on the use and the agency regulating it. Further, the US Environmental Protection Agency's current method of grouping QACs based on structure, first proposed in 1988, is insufficient to address the wide range of QAC chemistries, potential toxicities, and exposure scenarios. Consequently, exposures to common mixtures of QACs and from multiple sources remain largely unassessed. Some restrictions on the use of QACs have been implemented in the US and elsewhere, primarily focused on personal care products. Assessing the risks posed by QACs is hampered by their vast structural diversity and a lack of quantitative data on exposure and toxicity for the majority of these compounds. This review identifies important data gaps and provides research and policy recommendations for preserving the utility of QAC chemistries while also seeking to limit adverse environmental and human health effects.