Research on DCE-MRI Images Based on Deep Transfer Learning in Breast Cancer Adjuvant Curative Effect Prediction.

Breast cancer is a serious threat to women's physical and mental health. In recent years, its incidence has been on the rise and it has become the top female malignant tumor in China. At present, adjuvant chemotherapy for breast cancer has become the standard mode of breast cancer treatment, but the response results usually need to be completed after the implementation of adjuvant chemotherapy, and the optimization of the treatment plan and the implementation of breast-conserving therapy need to be based on accurate estimation of the pathological response. Therefore, to predict the efficacy of adjuvant chemotherapy for breast cancer patients is to find a predictive method that is conducive to individualized choice of chemotherapy regimens. This article introduces the research of DCE-MRI images based on deep transfer learning in breast cancer adjuvant curative effect prediction. Deep transfer learning algorithms are used to process images, and then, the features of breast cancer after adjuvant chemotherapy are collected through image feature collection. Predictions are made, and the research results show that the accuracy of the prediction reaches 70%.

circ_0041732 Promotes Breast Cancer Progression.

Breast cancer is quite a prevalent cancer worldwide, and it is the leading cause of cancer-related deaths among female populations worldwide. Increasingly more efforts have been made in exploration of circular RNA functions in various malignancies. In this study, the primary target was to verify the putative influences of circ_0041732 on breast cancer progression and the corresponding regulatory mechanism. In addition to measurement of RNAs and proteins, functional assays were done to examine the changes in cell proliferation and cell cycle, and the potential association among genes was investigated by mechanism assays. According to experimental results, significant upregulation of circ_0041732 was confirmed in breast cancer tissues and cell lines. E2F4 was proved to transcriptionally modulate circ_0041732. Moreover, circ_0041732 was validated to accelerate breast cancer cell proliferation and impede G2-M arrest and cell apoptosis, and the oncogenic role of circ_0041732 in breast cancer was further verified via in vivo experiments. circ_0041732 could sponge miR-541-3p to enhance expression levels of RelA and GLI4, thus activating NFκB and Hedgehog pathways and affecting breast cancer cell proliferation, cell cycle, and apoptosis. In all, E2F4-mediated circ_0041732 could activate RelA/NFκB and GLI4/Hedgehog signaling pathways via modulation on miR-541-3p/RelA/GLI4 to promote breast cancer progression. IMPLICATIONS: E2F4-mediated circ_0041732 upregulation resulted in the activation of NFκB and Hedgehog pathways via sponging miR-541-3p and enhancing expression levels of RelA and GLI4, thus affecting breast cancer cell proliferation, cell cycle, and cell apoptosis.

High-Quality de novo Chromosome-Level Genome Assembly of a Single Bombyx mori With BmNPV Resistance by a Combination of PacBio Long-Read Sequencing, Illumina Short-Read Sequencing, and Hi-C Sequencing.

The reference genomes of Bombyx mori (B. mori), Silkworm Knowledge-based database (SilkDB) and SilkBase, have served as the gold standard for nearly two decades. Their use has fundamentally shaped model organisms and accelerated relevant studies on lepidoptera. However, the current reference genomes of B. mori do not accurately represent the full set of genes for any single strain. As new genome-wide sequencing technologies have emerged and the cost of high-throughput sequencing technology has fallen, it is now possible for standard laboratories to perform full-genome assembly for specific strains. Here we present a high-quality de novo chromosome-level genome assembly of a single B. mori with nuclear polyhedrosis virus (BmNPV) resistance through the integration of PacBio long-read sequencing, Illumina short-read sequencing, and Hi-C sequencing. In addition, regular bioinformatics analyses, such as gene family, phylogenetic, and divergence analyses, were performed. The sample was from our unique B. mori species (NB), which has strong inborn resistance to BmNPV. Our genome assembly showed good collinearity with SilkDB and SilkBase and particular regions. To the best of our knowledge, this is the first genome assembly with BmNPV resistance, which should be a more accurate insect model for resistance studies.

Optimization of ultrasonic-assisted extraction conditions for bioactive components from coffee leaves using the Taguchi design and response surface methodology.

Coffee leaves contain various bioactive compounds that are beneficial for human health. However, there are very limited researches related to the extraction of the bioactive phytochemicals from coffee leaves. In the present study, the extraction conditions for bioactive components from coffee leaves were optimized using Taguchi design and response surface methodology (RSM). Taguchi design was used to screen significant factors that affected the yield of phytochemicals including trigonelline, caffeine, chlorogenic acids, mangiferin, and rutin, total phenolic content (TPC) and antioxidant activity. Sequentially, a Box-Behnken design (BBD) was used to optimize the extraction conditions. Three factors including Liquid-to-solid (L:S) ratio, ethanol concentration, and extraction temperature that significantly affected most of the phytochemical yields and antioxidant activity were selected from the six variables using Taguchi design. The optimal extraction conditions obtained from RSM were 30.3:1 L:S ratio, 54.5% ethanol, and 80 °C when simultaneously considered four responses, including TPC, the yields of mangiferin and 5-CQA and DPPH scavenging capacity. Under the optimal conditions, the experimental results for the above four responses were 62.1 mg gallic acid/g, 4.1 mg/g, 11.4 mg/g, and 356.9 µmol Trolox/g, respectively, which were close to the predicted values. About 97% of phytochemicals can be extracted in the first two times of extraction. In conclusion, the combination of Taguchi design and response surface methodology can be successfully used to screen and optimize the significant factors that affected the bioactive components extracted from coffee leaves. PRACTICAL APPLICATION: Coffee leaves, the byproducts of coffee plants, are considered no- or low-value although it has a long history for using them as tea-like beverage and ethnomedicine by locals in the coffee plant growing countries. Bioactive components extracted from coffee leaves can be used as ingredients in functional beverages, functional food, and natural health products. These applications will add values to coffee leaves as well as increase the incomes of coffee farmers and workers.

Transcriptomics and proteomics-based analysis of heterosis on main economic traits of silkworm, Bombyx mori.

The application of silkworm hybrids have promoted the innovation and development of agricultural technology, but the mechanism of heterosis in silkworm has not been explained clearly. In this study, the heterosis of silkworm in the aspects of body weight, silk gland and cocoon weight was investigated by means of silkworm hybridization and multi-omics approaches, including transcriptome and proteome. The results showed that heterosis of silkworm body weight, silk gland and cocoon weight was overdominant, but only part of genes and proteins were overdominant, and most of genes and proteins were non-additive. Combined analysis obtained six up-regulated genes and four down-regulated genes that were consistent both in transcriptome and proteome. Gene functional enrichment analysis indicated that most up-regulated genes and proteins were mostly related to metabolism, which led to accelerated metabolism and protein synthesis and contributing to improved heterosis. The up-regulation of 6-phosphate glucose dehydrogenase (G6PDH), phosphatidylethanolamine-binding protein (PEBP) and sHSP20.4, which are involved in metabolism, might be related to silk gland heterosis. SIGNIFICANCE: A combination of transcriptomic and proteomic analysis was used to understand the molecular mechanism of silkworm heterosis. We found that the phenotypic traits of silkworm are overdominant, while the analysis of transcriptome and proteome showed that only part of genes and proteins were overdominant, and most of genes and proteins were non-additive. Some of the genes had unique expression in F1, which was speculated that genes under heterozygous condition may result in rearrangement and cause metabolic changes in the hybrids. Those both up-regulated in transcriptomic and proteomic analysis were found to be involved in various metabolic processes, so as to accelerate metabolism and protein synthesis, thus exhibiting heterosis.