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Multi-channel magnetic resonance imaging methods utilize multiple receiving coils to simultaneously under-sample k-space for fast magnetic resonance imaging. Post-processing algorithms were often used to restore the missing information for under-sampled images. However, the quality of reconstructed images is far from satisfying, especially at higher acceleration factor. In this backdrop, a fast multi-channel magnetic resonance imaging method based on parallel complex asymmetric U-Net (PCAU-Net) was proposed, which extends single-channel real-valued U-shaped convolutional neural network to multi-channel complex convolutional neural network. A U-shaped network with an asymmetric structure was designed to reduce the model complexity by reducing the network size in decoding. A 1×1 convolution block was added before skip-connection for PCAU-Net to share cross-channel information. The residual connection between the input and output of the network facilitates loss backpropagation. The experimental results show that by using regular and random sampling templates, the proposed PCAU-Net method can reconstruct the complex magnetic resonance images with high quality compared with the conventional generalized auto-calibrating partially parallel acquisitions (GRAPPA) reconstruction algorithm and iterative self-consistent parallel imaging reconstruction (SPIRiT) algorithm at different acceleration factors. Moreover, compared with the parallel complex U-Net (PCU-Net) method, PCAU-Net reduces model parameters and shortens the training time.

Integration of the geological context, core analysis, and petrographic investigation, together with data from wireline logs, resulted in the recognition of petrofacies types and the representation of facies models characterizing the X-XII sand groups of the K2qn3 Formation in the Daqingzijing area of the Songliao Basin, China. The results show that the lithology of the reservoir’s X-XII sand groups includes shale calcium-bearing siltstone and sandstone, calcareous siltstone and silty sandstone. The petrofacies consist mainly of quartz, feldspar and rock fragments cemented by clay, and some samples include calcite. The studied interval was deposited onto a delta front. Four types of petrofacies were recognized: subaqueous distributary channel, mouth bar, distal bar and subaqueous interdistributary bay. According to background investigation, the study area’s X-XII sand groups have experienced a large-scale decline in lake level. There are many subaqueous distributary channels in layers 36-40, while other layers were mainly deposited in a subaqueous interdistributary bay. [ABSTRACT FROM AUTHOR]

The BCR/ABL p210 fusion gene is a classic biomarker of chronic myeloid leukemia, which can be divided into e13a2 and e14a2 isoforms according to different breakpoints. These two isoforms showed distinct differences in clinical manifestation, treatment effect, and prognosis risk. Herein, a strategy based on nanocluster beacon (NCB) fluorescence was developed to identify the e13a2 and e14a2 isoforms in one-pot. Because the fluorescence of AgNCs can be activated when they are placed in proximity to the corresponding enhancer sequences, thymine-rich (T-rich) or guanine-rich (G-rich). In this work, we explored an ideal DNA-AgNCs template as an excellent molecular reporter with a high signal-to-noise ratio. After recognition with the corresponding isoforms, the AgNCs can be pulled closer to the T-rich or G-rich sequences to form a three-way junction structure and generate fluorescence with corresponding wavelengths. Therefore, by distinguishing the corresponding wavelengths of AgNCs, we successfully identified two isoforms in one tube with the limitation of 16 pM for e13a2 and 9 pM for e14a2. Moreover, this strategy also realized isoform identification in leukemia cells and newly diagnosed CML patients within 40 min, which provides a powerful tool to distinguish fusion gene subtypes at the same time.

The expression and clinical significance of insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), and insulin-like growth factor binding protein 7 (IGFBP-7) were investigated in serum and lung cancer tissues from 57 patients with non-small cell lung cancer (NSCLC). Lung cancer tissues at different pathologic stages (27 patients at stages I-II and 30 patients at stages III-IV), normal lung tissues from 17 patients with benign pulmonary disease, and serum samples from both lung cancer and benign pulmonary disease patients were collected during surgery. Enzyme-linked immunosorbent assay and avidin-biotin-peroxidase complex immunohistochemical staining were used to detect IGF-1, IGFBP-3, and IGFBP-7 expression in serum and tissues, respectively. The results show that expression of IGF-1 in lung cancer tissues and serum from NSCLC patients were significantly higher than in the control (P < 0.05). However, expression of IGFBP-3 and IGFBP-7 in cancer tissues and serum from NSCLC patients was significantly lower than in the control (P < 0.05). These results suggest that upregulation of IGF-1 and downregulation of IGFBP-3 and IGFBP-7 may be potential diagnostic biomarkers for NSCLC.