Application and Exploration of FLUENT Software in the Teaching of Engineering Thermophysics

Engineering thermophysics is a basic discipline for energy majors, but this course emphasizes the theoretical level and is difficult to understand. Students\u27 enthusiasm and participation in the learning process are low, and it is difficult to understand the course. Accordingly, the research team attempts to introduce Fluent software into the course teaching exploration. Specifically, Fluent software is adopted to provide a reliable physics teaching model, and to change the traditional teaching mode, so as to improve students\u27 daily learning ability and practical ability, and ultimately enable students to learn and practice

A Text Recognition Algorithm Based on a Dual-Attention Mechanism in Complex Driving Environment

In response to many problems such as complex background of text recognition environment, perspective distortion, shallow handwriting, and mixed Chinese and English characters, we have designed an OCR algorithm framework with features such as landmark extraction and correction, image enhancement, text detection, and text recognition. We have designed a DBNet based on dual attention mechanism and content-aware upsampling. We have also designed a text recognition module incorporating the central loss CRNN + CTC to improve content awareness. Experimental results show that the improved text detection network in this paper has increased accuracy by 5.09%, recall by 2.12%, and F-score by 3.46% on the ICDAR2015 dataset. The text recognition network has improved the accuracy of recognizing Chinese and English characters by 1.2%

Modulating fast skeletal muscle contraction protects skeletal muscle in animal models of Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a lethal muscle disease caused by absence of the protein dystrophin, which acts as a structural link between the basal lamina and contractile machinery to stabilize muscle membranes in response to mechanical stress. In DMD, mechanical stress leads to exaggerated membrane injury and fiber breakdown, with fast fibers being the most susceptible to damage. A major contributor to this injury is muscle contraction, controlled by the motor protein myosin. However, how muscle contraction and fast muscle fiber damage contribute to the pathophysiology of DMD has not been well characterized. We explored the role of fast skeletal muscle contraction in DMD with a potentially novel, selective, orally active inhibitor of fast skeletal muscle myosin, EDG-5506. Surprisingly, even modest decreases of contraction (\u3c15%) were sufficient to protect skeletal muscles in dystrophic mdx mice from stress injury. Longer-term treatment also decreased muscle fibrosis in key disease-implicated tissues. Importantly, therapeutic levels of myosin inhibition with EDG-5506 did not detrimentally affect strength or coordination. Finally, in dystrophic dogs, EDG-5506 reversibly reduced circulating muscle injury biomarkers and increased habitual activity. This unexpected biology may represent an important alternative treatment strategy for Duchenne and related myopathies

MicroRNA Profiling and Head and Neck Cancer

Head and neck/oral cancer (HNOC) is a devastating disease. Despite advances in diagnosis and treatment, mortality rates have not improved significantly over the past three decades. Improvement in patient survival requires a better understanding of the disease progression so that HNOC can be detected early in the disease process and targeted therapeutic interventions can be deployed. Accumulating evidence suggests that microRNAs play important roles in many human cancers. They are pivotal regulators of diverse cellular processes including proliferation, differentiation, apoptosis, survival, motility, and morphogenesis. MicroRNA expression patterns may become powerful biomarkers for diagnosis and prognosis of HNOC. In addition, microRNA therapy could be a novel strategy for HNOC prevention and therapeutics. Recent advances in microRNA expression profiling have led to a better understanding of the cancer pathogenesis. In this review, we will survey recent technological advances in microRNA profiling and their applications in defining microRNA markers/targets for cancer prediction, diagnostics, treatment, and prognostics. MicroRNA alterations that consistently identified in HNOC will be discussed, such as upregulation of miR-21, miR-31, miR-155, and downregulation of miR-26b, miR-107, miR-133b, miR-138, and miR-139

RNA expression of the molecular signature genes for metastasis in colorectal cancer

Colorectal cancer is an endemic disease in the Western world. Search for molecular signatures present in primary tumors that predict tumor metastasis potential has been proposed and in particular, a 17-gene molecular signature is associated with poor survival in breast cancer, prostate cancer, meduloblastoma and lymphoma in a recent study. Using quantitative real-time PCR assay (qPCR), our study observed tumor-normal differential RNA expression in 15 of these 17 genes in a cohort of 52 stage III colorectal cancer patients (all P0.05), two distinct groups among these genes were observed with Spearman correlation scores >0.6 (P0.05), but the recurrence group had more patients with mucinous tumors (9/12 vs. 7/25, P<0.05) and more lymph node involvement (median 7.2 vs. 2.5, P<0.05) compared to the non-recurrence group. Moreover, survival analysis revealed a significant difference in patient overall survival time between low and high tumor RNA levels for 1 of the 17 genes (PTTG1, P=0.024). Our qPCR validation study confirms the importance of most 17-gene molecular signature genes with differential RNA expression and suggests the relevance of PTTG1 for survival in colorectal cancers