Colon cancer is one of the most frequent and lethal neoplasias. Altered metabolic activity is a well-known hallmark for cancer. The present study is aiming to screen key genes associated with tumor ...metabolism and construct a prognostic signature of colon cancer patients.
Glutamine- and UC- metabolism related genes were downloaded from GSEA MsigDB. Three key genes were screened by Cox regression analysis with data samples downloaded from TCGA and GSE29623 database. Consistent clustering based on the prognostic genes identified was employed to divide the colon cancer samples into two clusters with significant OS differences. The mRNA and protein expression of the key genes in colon tissues and matched adjacent noncancerous tissues of 16 patients were detected by IHC, qPCR, and Western blot to validate the constructed clustering model. GO, GSVA, and IPA were used to predict the relevant metabolic pathways.
According to the three key genes identified, i.e., ASNS, CEBPA, and CAD, the cohort can be divided into two clusters with prognosis differences. Clinical specimen results confirmed that the risk model established was effective, and the different expression pattern of ASNS and CEBPA was correlated with TNM stage and lymph node metastasis, whilst that of CAD was correlated with post-operative tumor metastasis and recurrence. Molecular mechanism prediction indicated that CREB, insulin, and RNA Pol II were the key nodes affecting CEBPA and ASNS expression. Moreover, TIDE algorithm reflected the better immune response of the cluster with shorter OS. Further immune infiltration and checkpoints analyses provided important reference for clinicians to perform individualized immunotherapy.
Differential expression profile of three aspartic acid metabolic-associated genes, ASNS, CEBPA, and CAD, can be considered as a risk model with a good evaluation effect on the prognosis of colon cancer patients.
To address the problem of detecting point-like targets in a partially homogeneous Gaussian cluttered environment, we developed a modified Generalized Likelihood Ratio Test (GLRT) detection method ...based on a symmetrically spaced linear array that relies on a GLRT design criterion. Considering the target energy spillover during sampling, we use a spillover model of the target energy to decrease spillover loss. To establish the discrete-time signal mode, we use a persymmetric structure of the disturbance covariance matrix to reduce the requirement for auxiliary signals. Lastly, we estimate all of the unknown parameters based on a consideration of both primary and secondary data to derive the persymmetric modified GLRT detector, which has good target detection and range estimation performance. The performance assessment shows that the proposed method not only performs as a constant false-alarm-rate receiver in partially homogeneous environments but also guarantees superior detection performance relative to that of its competitors. In sample-starved environments, compared with other detection methods of the same type, it realizes a detection performance advantage greater than 1 dB.
Purpose
Cancer testis antigens (CTAs) are optimal tumor diagnostic markers and involved in carcinogenesis. However, colorectal cancer (CRC) related CTAs are less reported with impressive diagnostic ...capability or relevance with tumor metabolism rewiring. Herein, we demonstrated CRC-related CTA, Protamine 1 (PRM1), as a promising diagnostic marker and involved in regulation of cellular growth under nutrient deficiency.
Methods
Transcriptomics of five paired CRC tissues was used to screen CRC-related CTAs. Capability of PRM1 to distinguish CRC was studied by detection of clinical samples through enzyme linked immunosorbent assay (ELISA). Cellular functions were investigated in CRC cell lines through in vivo and in vitro assays.
Results
By RNA-seq and detection in 824 clinical samples from two centers, PRM1 expression were upregulated in CRC tissues and patients` serum. Serum PRM1 showed impressive accuracy to diagnose CRC from healthy controls and benign gastrointestinal disease patients, particularly more sensitive for early-staged CRC. Furthermore, we reported that when cells were cultured in serum-reduced medium, PRM1 secretion was upregulated, and secreted PRM1 promoted CRC growth in culture and in mice. Additionally, G1/S phase transition of CRC cells was facilitated by PRM1 protein supplementation and overexpression via activation of PI3K/AKT/mTOR pathway in serum deficient medium.
Conclusions
In general, our research presented PRM1 as a specific CRC antigen and illustrated the importance of PRM1 in CRC metabolism rewiring. The new vulnerability of CRC cells was also provided with the potential to be targeted in future.
Graphical abstract
Diagnostic value and grow factor-like biofunction of PRM1 A represents the secretion process of PRM1 regulated by nutrient deficiency. B represents activation of PI3K/AKT/mTOR pathway of secreted PRM1.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Based on proportion mixing, a thrust vector/aerodynamics compound control method for solid rocket is studied. First, the model of thrust vector /aerodynamics compound control is established, and the ...compound control method is provided based on proportion mixing in pitch channel. Then, the stability criterions are derived based on the compound control model, and the stable state of rocket is judged based on stability criterions. When the stability criterions are not satisfied, the compound control is opened, which can increase control moment. At last, the numerical simulation is performed, and the simulation results show the validity of the proposed method.
Spatiotemporal fusion (STF) is considered an effective way to address the mutual constraints of the spatiotemporal resolutions of the remote sensing images from a single satellite sensor. Although ...the deep learning (DL)-based STF methods have shown great potential so far, there are still some deficiencies. Supervised DL-based methods usually train the network on the original scale data with richer spatial information, but they utilize only the data at auxiliary dates to generate the fusion data at prediction dates, which may perform poorly when significant spatiotemporal changes occur between the auxiliary and prediction dates. For self-supervised DL-based methods, the training can focus more on the data at prediction dates, but the network is generally trained on the down-sampled data with less spatial information, causing insufficient spatial structures of the fusion results. Based on the above, we innovatively combine supervised and self-supervised learning and propose a dual-stage cascade STF framework. In the first stage, a model based on supervised learning is trained on the data at auxiliary dates to extract abundant spatial features and obtain the initial fusion results. In the second stage, we utilize a self-supervised strategy to excavate the spatiotemporal features of prediction dates based on the initial fusion results and the observed data at prediction dates. In addition, to alleviate the insufficient consideration of the temporal correlation in existing STF methods, we design a temporal consistency loss function to fully utilize the temporal correlation information between multiple prediction dates to generate more accurate fusion results. The proposed framework can not only realize the STF of remote sensing images but also be well applied to the STF of remote sensing products such as land surface temperature (LST). Based on the quantitative results of three datasets, the proposed method improves the quantitative indices of root mean square error (RMSE), structural similarity (SSIM), erreur relative global adimensionnelle de synthese (ERGAS), peak signal to noise ratio (PSNR), and spectral angle mapper (SAM) by up to 0.2014, 0.0279, 0.6797, 0.7629, and 0.2006 at most compared with the best comparison method, which fully shows the superiority of our method.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In the field of remote sensing image pansharpening, deep learning-based methods have shown impressive performances recently. However, most deep learning-based pansharpening methods are based on ...supervised learning, which requires a large number of training images. In addition, obtaining large amounts of images with a high spatial and spectral resolution for training may be difficult in practice. In this letter, a novel self-supervised learning method based on a cycle-consistent generative adversarial network (CycleGAN) is proposed for remote sensing image pansharpening, without requiring large volumes of data for training. The framework contains two generators and two discriminators, and applies a residual neural network to the first generator. The panchromatic (PAN) image and multispectral (MS) image are input into the first generator to obtain the fused image, and then the fused image is input into the second generator to obtain a PAN image, which should be consistent with the input PAN image. The experimental results show that the proposed method performs better than the state-of-the-art unsupervised pansharpening method, and also achieves a competitive performance when compared with a supervised method.
Background
Uveal melanoma (UM) is an intraocular malignant tumor characterized by rapid progression and recurrence. The current conventional treatments are unsatisfactory. Histone acetylation at H3 ...lysine 56 (H3K56ac) has been reported to be a tumor suppressor in breast cancer. However, whether H3K56ac prevents the occurrence and development of UM remains uninvestigated. The study aimed to explore the regulatory effect of H3K56ac on Ras‐PI3K‐AKT induced UM cells proliferation and migration.
Methods
The vectors of pEGFP‐RasWT, pEGFP‐K‐Ras
G12V/Y40C, and pEGFP‐N1 were transfected into MP46 cells, and protein levels of phosphorylated AKT
Ser473 and H3K56ac were examined using western blot analysis. The effect of H3K56ac on cell proliferation and migration were studied using 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5 diphenyl tetrazolium bromide, colony formation, and Transwell assays. Reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR) and chromatin immunoprecipitation assays were performed to determine the phosphoinositide 3‐kinase/protein kinase B (PI3K/AKT) downstream genes. Further, the regulatory effects of silent mating type information regulation 2 homolog‐1 (SIRT1), general control nonderepressible 5 (GCN5), and mouse double minute 2 homolog (MDM2) on Ras‐PI3K‐AKT affected H3K56ac expression were also investigated.
Results
H3K56ac expression was specifically downregulated by Ras‐PI3K‐AKT activation pathway. H3K56ac inhibited the tumorigenic effect of Ras‐PI3K‐AKT on MP46 cells viability, colony formation, and migration, as well as participated in regulating the transcription of PI3K/AKT downstream genes. SIRT1 silence recovered H3K56ac expression, and reversed the tumorigenic effect of Ras‐PI3K‐AKT activation on MP46 cells. Downregulation of H3K56ac induced by Ras‐PI3K‐AKT activation was found to be associated with MDM2‐mediated the degradation of GCN5.
Conclusions
The results demonstrated that Ras‐PI3K‐AKT signaling promoted UM cells proliferation and migration via downregulation of H3K56ac expression, which might be related to MDM2‐mediated the degradation of GCN5.
The results demonstrated that Ras‐PI3K‐AKT signaling promoted UM cells proliferation and migration via downregulation of histone acetylation at H3 lysine 56 (H3K56ac) expression, which might be related to MDM2‐mediated the degradation of GCN5.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Vision transformers have shown great success on numerous computer vision tasks. However, their central component, softmax attention, prohibits vision transformers from scaling up to high-resolution ...images, due to both the computational complexity and memory footprint being quadratic. Linear attention was introduced in natural language processing (NLP) which reorders the self-attention mechanism to mitigate a similar issue, but directly applying existing linear attention to vision may not lead to satisfactory results. We investigate this problem and point out that existing linear attention methods ignore an inductive bias in vision tasks, i.e., 2D locality. In this article, we propose Vicinity Attention, which is a type of linear attention that integrates 2D locality. Specifically, for each image patch, we adjust its attention weight based on its 2D Manhattan distance from its neighbouring patches. In this case, we achieve 2D locality in a linear complexity where the neighbouring image patches receive stronger attention than far away patches. In addition, we propose a novel Vicinity Attention Block that is comprised of Feature Reduction Attention (FRA) and Feature Preserving Connection (FPC) in order to address the computational bottleneck of linear attention approaches, including our Vicinity Attention, whose complexity grows quadratically with respect to the feature dimension. The Vicinity Attention Block computes attention in a compressed feature space with an extra skip connection to retrieve the original feature distribution. We experimentally validate that the block further reduces computation without degenerating the accuracy. Finally, to validate the proposed methods, we build a linear vision transformer backbone named Vicinity Vision Transformer (VVT). Targeting general vision tasks, we build VVT in a pyramid structure with progressively reduced sequence length. We perform extensive experiments on CIFAR-100, ImageNet-1 k, and ADE20 K datasets to validate the effectiveness of our method. Our method has a slower growth rate in terms of computational overhead than previous transformer-based and convolution-based networks when the input resolution increases. In particular, our approach achieves state-of-the-art image classification accuracy with 50% fewer parameters than previous approaches.
Ras–extracellular signal‐regulated protein kinases 1 and 2 (ERK1/2) signaling has been proposed as the crucial regulators in the development of various cancers. Histone acetylation at H3 lysine 14 ...(H3K14ac) is closely associated with gene expression and DNA damage. However, whether H3K14ac participates in mediating Ras–ERK1/2‐induced cell proliferation and migration in uveal melanoma cells remains unknown. The purpose of this study is to investigate the effect of H3K14ac on Ras–ERK1/2 affected uveal melanoma cell phenotypes. MP65 cells were transfected with Ras
WT and Ras
G12V/T35S, the unloaded plasmid of pEGFP‐N1 served as a negative control. Protein levels of phosphorylated ERK1/2
Thr202 and H3K14ac were assessed by western blot assay. Cell viability, number of colonies, migration, and the downstream genes of ERK1/2 were analyzed by 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyl‐2‐H‐tetrazolium bromide, soft‐agar colony formation, transwell, and chromatin immunoprecipitation assays. HA‐tag vectors of CLR3 and TIP60 and the small interfering RNAs that specific for CLR3 and MDM2 were transfected into MP65 cells to uncover the effects of CLR3, TIP60, and MDM2 on Ras–ERK1/2 mediated H3K14ac expression and MP65 cell phenotypes. We found that, Ras–ERK1/2 decreased H3K14ac expression in MP65 cells, and H3K14ac significantly suppressed Ras–ERK1/2‐induced cell viability, colony formation, and migration in MP65 cells. Moreover, the transcription of CYR61, IGFBP3, WNT16B, NT5E, GDF15, and CARD16 was regulated by H3K14ac. Additionally, CLR3 silence recovered H3K14ac expression and reversed the effect of Ras–ERK1/2 on MP65 cell proliferation, migration and the mRNAs of ERK1/2 downstream genes. Besides, Ras–ERK1/2 decreased H3K14ac expression by MDM2‐mediated TIP60 degradation. In conclusion, Ras–ERK1/2 promoted uveal melanoma cells growth and migration by downregulating H3K14ac via MDM2‐mediated TIP60 degradation.
Ras–extracellular signal‐regulated protein kinases 1 and 2 promoted uveal melanoma cells growth and migration by downregulating histone H3 acetylated on lysine 14 via MDM2‐mediated TIP60 degradation.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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