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Ferroptosis, as a form of cell death different from apoptosis, is very promising for the treatment of cancer in nonapoptotic systems. Since iron is a key component in the induction of ferroptosis in cells, the use of iron-based nanomaterials in treating cancer through ferroptosis is of great significance. Therefore, in this study, magnetic nanoparticles (MNP) were coated with the zwitterionic polymer poly(2-methacryloyloxyethyl phosphorylcholine) (PMPC), and then loaded with sorafenib (SRF) to obtain drug-loaded composite nanoparticles MNP@PMPC-SRF. Fe3O4 provided a large number of ferric/ferrous ions as an iron source, releasing Fe2+ for the regulation of the ferroptosis process and enhancing the effect of the induced cellular ferroptosis on the treatment of colon cancer with SRF. The zwitterionic polymer PMPC effectively extended the blood circulation time, resulting in an enhanced tumor accumulation of the nanodrug. MNP@PMPC-SRF exhibited good biocompatibility for in vivo application and showed an excellent tumor inhibitory effect on HCT116 tumor-bearing nude mice. [ABSTRACT FROM AUTHOR]

Copper(I)‐catalyzed radical 1,2‐benzylarylation of N‐phenethylenamides was developed and 1,1‐disubstituted N‐acyl tetrahydroisoquinolines were obtained in moderate to good yields. In this process, two new C–C bonds were formed in one‐step fashion with high atom economy. A possible reaction pathway for the formation of the products is also discussed. [ABSTRACT FROM AUTHOR]

In a linear approximation, an arbitrary axial-symmetric source can be expressed as the linear superposition of a set of Gaussian sources and the corresponding radiated sound field can be represented as the superposition of this set of Gaussian beams. The analysis is extended to the second harmonic generation due to nonlinear effects under a quasilinear approximation, then the second harmonic sound field could be considered as a sum of self- and cross-interaction terms produced by a series of Gaussian beams. Therefore, the calculation of the second harmonic sound field of an axial-symmetric source can be reduced to a simple linear combination of a set of exponential integral functions, instead of a complicated triple integral. In order to verify this calculation approach, the second harmonic generation of a focused and a simple piston source is examined, and the result is in good agreement with that in earlier paper by complicated computation. © 1996 Acoustical Society of America. [ABSTRACT FROM AUTHOR]

The segmentation of high-resolution (HR) remote sensing images is very important in modern society, especially in the fields of industry, agriculture and urban modelling. Through the neural network, the machine can effectively and accurately extract the surface feature information. However, using the traditional deep learning methods requires plentiful efforts in order to find a robust architecture. In this paper, we introduce a neural network architecture search (NAS) method, called NAS-HRIS, which can automatically search neural network architecture on the dataset. The proposed method embeds a directed acyclic graph (DAG) into the search space and designs the differentiable searching process, which enables it to learn an end-to-end searching rule by using gradient descent optimization. It uses the Gumbel-Max trick to provide an efficient way when drawing samples from a non-continuous probability distribution, and it improves the efficiency of searching and reduces the memory consumption. Compared with other NAS, NAS-HRIS consumes less GPU memory without reducing the accuracy, which corresponds to a large amount of HR remote sensing imagery data. We have carried out experiments on the WHUBuilding dataset and achieved 90.44% MIoU. In order to fully demonstrate the feasibility of the method, we made a new urban Beijing Building dataset, and conducted experiments on satellite images and non-single source images, achieving better results than SegNet, U-Net and Deeplab v3+ models, while the computational complexity of our network architecture is much smaller. [ABSTRACT FROM AUTHOR]

Deforestation in the Amazon rainforest results in reduced biodiversity, habitat loss, climate change, and other destructive impacts. Hence obtaining location information on human activities is essential for scientists and governments working to protect the Amazon rainforest. We propose a novel remote sensing image classification framework that provides us with the key data needed to more effectively manage deforestation and its consequences. We introduce the attention module to separate the features which are extracted from CNN(Convolutional Neural Network) by channel, then further send the separated features to the LSTM(Long-Short Term Memory) network to predict labels sequentially. Moreover, we propose a loss function by calculating the co-occurrence matrix of all labels in the dataset and assigning different weights to each label. Experimental results on the satellite image dataset of the Amazon rainforest show that our model obtains a better F 2 score compared to other methods, which indicates that our model is effective in utilizing label dependencies to improve the performance of multi-label image classification. [ABSTRACT FROM AUTHOR]

Voltage-gated chloride ion channels (CLCs) are transmembrane proteins that maintain chloride ion homeostasis in various cells. Accumulating studies indicated CLCs were related to cell growth, proliferation, and cell cycle. Nevertheless, the role of CLCs in prostate cancer (PCa) has not been systematically profiled. The purpose of this study was to investigate the expression profiles and biofunctions of CLCs genes, and construct a novel risk signature to predict biochemical recurrence (BCR) of PCa patients. We identified five differentially expressed CLCs genes in our cohort and then constructed a signature composed of CLCN2 and CLCN6 through Lasso-Cox regression analysis in the training cohort from the Cancer Genome Atlas (TCGA). The testing and entire cohorts from TCGA and the GSE21034 from the Gene Expression Omnibus (GEO) were used as internal and independent external validation datasets. This signature could divide PCa patients into the high and low risk groups with different prognoses, was apparently correlated with clinical features, and was an independent excellent prognostic indicator. Enrichment analysis indicated our signature was primarily concentrated in cellular process and metabolic process. The expression patterns of CLCN2 and CLCN6 were detected in our own cohort based immunohistochemistry staining, and we found CLCN2 and CLCN6 were highly expressed in PCa tissues compared with benign tissues and positively associated with higher Gleason score and shorter BCR-free time. Functional experiments revealed that CLCN2 and CLCN6 downregulation inhibited cell proliferation, colony formation, invasion, and migration, but prolonged cell cycle and promoted apoptosis. Furthermore, Seahorse assay showed that silencing CLCN2 or CLCN6 exerted potential inhibitory effects on energy metabolism in PCa. Collectively, our signature could provide a novel and robust strategy for the prognostic evaluation and improve treatment decision making for PCa patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Luo, Liu, Li, Zhong, Lin and Chen.)

The aim of this study is to construct an inflammatory response-related genes (IRRGs) signature to monitor biochemical recurrence (BCR) and treatment effects in prostate cancer patients (PCa). A gene signature for inflammatory responses was constructed on the basis of the data from the Cancer Genome Atlas (TCGA) database, and validated in external datasets. It was analyzed using receiver operating characteristic curve, BCR-free survival, Cox regression, and nomogram. Distribution analysis and external model comparison were utilized. Then, enrichment analysis, tumor mutation burden, tumor immune microenvironment, and immune cell infiltration signatures were investigated. The role of the signature in immunotherapy was evaluated. The expression patterns of core genes were verified by RNA sequencing. We identified an IRRGs signature in the TCGA-PRAD cohort and verified it well in two other independent external datasets. The signature was a robust and independent prognostic index for predicting the BCR of PCa. The high-risk group of our signature predicted a shortened BCR time and an aggressive disease progression. A nomogram was constructed to predict BCR-free time in clinical practices. Neutrophils and CD8+ T cells were in higher abundance among the low-risk individuals. Immune functions varied significantly between the two groups and immune checkpoint therapy worked better for the low-risk patients. The expression of four IRRGs showed significant differences between PCa and surrounding benign tissues, and were validated in BPH-1 and DU145 cell lines by RNA sequencing. Our signature served as a reliable and promising biomarker for predicting the prognosis and evaluating the efficacy of immunotherapy, facilitating a better outcome for PCa patients.

Ferroptosis, as a form of cell death different from apoptosis, is very promising for the treatment of cancer in nonapoptotic systems. Since iron is a key component in the induction of ferroptosis in cells, the use of iron-based nanomaterials in treating cancer through ferroptosis is of great significance. Therefore, in this study, magnetic nanoparticles (MNP) were coated with the zwitterionic polymer poly(2-methacryloyloxyethyl phosphorylcholine) (PMPC), and then loaded with sorafenib (SRF) to obtain drug-loaded composite nanoparticles MNP@PMPC-SRF. Fe 3 O 4 provided a large number of ferric/ferrous ions as an iron source, releasing Fe 2+ for the regulation of the ferroptosis process and enhancing the effect of the induced cellular ferroptosis on the treatment of colon cancer with SRF. The zwitterionic polymer PMPC effectively extended the blood circulation time, resulting in an enhanced tumor accumulation of the nanodrug. MNP@PMPC-SRF exhibited good biocompatibility for in vivo application and showed an excellent tumor inhibitory effect on HCT116 tumor-bearing nude mice.

Tumor mutation burden (TMB), an emerging molecular determinant, is accompanied by microsatellite instability and immune infiltrates in various malignancies. However, whether TMB is related to the prognosis or immune responsiveness of adrenocortical carcinoma (ACC) remains to be elucidated. This paper aims to investigate the impact of TMB on the prognosis and immune microenvironment infiltration in ACC. The somatic mutation data, gene expression profile, and corresponding clinicopathological information were retrieved from TCGA. The mutation landscape was summarized and visualized with the waterfall diagram. The ACC patients were divided into low and high TMB groups based on the median TMB value and differentially expressed genes (DEGs) between the two groups were identified. Diverse functional analyses were conducted to determine the functionality of the DEGs. The immune cell infiltration signatures were evaluated based on multiple algorithms. Eventually, a TMB Prognostic Signature (TMBPS) was established and its predictive accuracy for ACC was evaluated. Single nucleotide polymorphism and C > T were found to be more common than other missense mutations. In addition, lower TMB levels indicated improved survival outcomes and were correlated with younger age and earlier clinical stage. Functional analysis suggested that DEGs were primarily related to the cell cycle, DNA replication, and cancer progression. Additionally, significant differences in infiltration levels of activated CD4+ T cells, naive B cells, and activated NK cells were observed in two TMB groups. We also found that patients with higher TMBPS showed worse survival outcomes, which was validated in the Gene Expression Omnibus database. Our study systematically analyzed the mutation and identified a TMBPS combined with immune microenvironment infiltration in ACC. It is expected that this paper can promote the development of ACC treatment strategies.