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Manual selection of the distribution target and determination of its spatial location is not only time consuming but also has a serious impact on the polarimetric channel imbalances assessment if the area is incorrect. However, the existing automatic extraction methods are affected by the morphology of the features, and their local feature extraction capability is limited. On the other hand, only local information is considered, while the feature channels and global information are ignored, which in turn leads to the limited application scenarios, especially in some urban areas. The polarimetric channel imbalance estimation accuracy is so low that it exceeds the system tolerance limit. Therefore, in order to more effectively mine the polarimetric features of distributed targets in polarimetric synthetic aperture radar images, we propose an attention-based multipath hybrid convolutional distribution target extraction network for polarimetric channel imbalance assessment. First, in order to develop the local feature extraction capability of the hierarchical network, we design a hybrid convolutional module with adaptive adjustment of the receptive field size. Second, a polarimetric feature channel reconstruction module is constructed in order to utilize the spatial information of the polarimetric feature channels. Then, considering that the polarimetric information of the ground feature is sensitive to the relative geometry of the target attitude to the radar line of sight, the vision transformer architecture is used to capture polarimetric global information and extend it to multipath. Finally, Gaofen-3(GF-3) full-polarimetric data are used for experimental verification. Experimental results demonstrate the effectiveness and reliability of the proposed method.

Abstract Objective Male breast cancer (BC) is a rare disease, having different clinicopathological features and survival outcomes from female patients. The aim of this research was to, combine with molecular subtypes, analyze the metastatic patterns, and prognosis between male and female patients, and to determine whether the gender was the independent prognostic factor for BC. Methods Data used in this study were acquired from the SEER database from 2010 to 2016. The clinicopathology features and metastatic patterns were compared by the Chi‐square test and Fisher's exact test. Kaplan–Meier method was performed to compare overall survival (OS) and factors correlated with OS were determined by Cox regression models. Competing risk models were used to ascertain factors related to breast cancer‐specific death (BCSD). Results Compared with female BC, the incidence of regional LN (HR 1.849, 95% CI 1.674–2.043, p

BackgroundDespite tremendous advances in cancer research, breast cancer (BC) remains a major health concern and is the most common cancer affecting women worldwide. Breast cancer is a highly heterogeneous cancer with potentially aggressive and complex biology, and precision treatment for specific subtypes may improve survival in breast cancer patients. Sphingolipids are important components of lipids that play a key role in the growth and death of tumor cells and are increasingly the subject of new anti-cancer therapies. Key enzymes and intermediates of sphingolipid metabolism (SM) play an important role in regulating tumor cells and further influencing clinical prognosis.MethodsWe downloaded BC data from the TCGA database and GEO database, on which we performed in depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, and transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, and selection operator (Lasso) regression analysis to construct a prognostic model for BC patients. Finally, the expression and function of the key gene PGK1 in the model were verified by in vitro experiments.ResultsThis prognostic model allows for the classification of BC patients into high-risk and low-risk groups, with a statistically significant difference in survival time between the two groups. The model is also able to show high prediction accuracy in both internal and external validation sets. After further analysis of the immune microenvironment and immunotherapy, it was found that this risk grouping could be used as a guide for the immunotherapy of BC. The proliferation, migration, and invasive ability of MDA-MB-231 and MCF-7 cell lines were dramatically reduced after knocking down the key gene PGK1 in the model through cellular experiments.ConclusionThis study suggests that prognostic features based on genes related to SM are associated with clinical outcomes, tumor progression, and immune alterations in BC patients. Our findings may provide insights for the development of new strategies for early intervention and prognostic prediction in BC.

BackgroundAlthough breast cancer (BC) treatment has entered the era of precision therapy, the prognosis is good in the case of comprehensive multimodal treatment such as neoadjuvant, endocrine, and targeted therapy. However, due to its high heterogeneity, some patients still cannot benefit from conventional treatment and have poor survival prognoses. Amino acids and their metabolites affect tumor development, alter the tumor microenvironment, play an increasingly obvious role in immune response and regulation of immune cell function, and are involved in acquired and innate immune regulation; therefore, amino acid metabolism is receiving increasing attention.MethodsBased on public datasets, we carried out a comprehensive transcriptome and single-cell sequencing investigation. Then we used 2.5 Weighted Co-Expression Network Analysis (WGCNA) and Cox to evaluate glutamine metabolism-related genes (GRGs) in BC and constructed a prognostic model for BC patients. Finally, the expression and function of the signature key gene SNX3 were examined by in vitro experiments.ResultsIn this study, we constituted a risk signature to predict overall survival (OS) in BC patients by glutamine-related genes. According to our risk signature, BC patients can obtain a Prognostic Risk Signature (PRS), and the response to immunotherapy can be further stratified according to PRS. Compared with traditional clinicopathological features, PRS demonstrated robust prognostic power and accurate survival prediction. In addition, altered pathways and mutational patterns were analyzed in PRS subgroups. Our study sheds some light on the immune status of BC. In in vitro experiments, the knockdown of SNX3, an essential gene in the signature, resulted in a dramatic reduction in proliferation, invasion, and migration of MDA-MB-231 and MCF-7 cell lines.ConclusionWe established a brand-new PRS consisting of genes associated with glutamine metabolism. It expands unique ideas for the diagnosis, treatment, and prognosis of BC.

Background:CD161 has been identified as a prognostic biomarker in many neoplasms, but its role in breast cancer (BC) has not been fully explained. We aimed to investigate the molecular mechanism and prognostic value of CD161 in BC.Methods:CD161 expression profile was extracted from TIMER, Oncomine, UALCAN databases, and verified by the Gene Expression Omnibus (GEO) database and quantitative real-time polymerase chain reaction (qRT-PCR). The prognostic value of CD161 was assessed via GEPIA, Kaplan–Meier plotter and PrognoScan databases. The Cox regression and nomogram analyses were conducted to further validate the association between CD161 expression and survival. Gene set enrichment analysis (GSEA), Gene Ontology (GO) analysis, and KEGG pathway enrichment analysis were performed to probe the tumor-associated annotations of CD161. CIBERSORT and ssGSEA were employed to investigate the correlation between CD161 expression and immune cell infiltration in BC, and the result was verified by TIMER and TISIDB.Results: Multiple BC cohorts showed that CD161 expression was decreased in BC, and a high CD161 expression was associated with a preferable prognosis. Therefore, we identified the combined model including CD161, age and PR status to predict the survival (C index = 0.78) of BC patients. Functional enrichment analysis indicated that CD161 and its co-expressed genes were closely related to several cancerous and immune signaling pathways, suggesting its involvement in immune response during cancer development. Moreover, immune infiltration analysis revealed that CD161 expression was correlated with immune infiltration.Conclusion: Collectively, our findings revealed that CD161 may serve as a potential biomarker for favorable prognosis and a promising immune therapeutic target in BC.

Breast cancer is the most common malignant tumor worldwide and the leading cause of cancer-related deaths in female. Metabolic reprogramming plays critical roles in breast tumorigenesis and induces enhanced glucose uptake and glycolysis. TRPC5OS is encoded by short transient receptor potential channel 5 opposite strand, and predicted to correlate with tumor metabolic reprogramming. Here we aim to elucidate the function of TRPC5OS in aberrant metabolism mediated tumorigenesis. We detected TRPC5OS expression levels in cell lines and tissues by quantitative real-time polymerase chain reaction and immunohistochemistry. Then we assessed the effects of TRPC5OS on proliferation and cell cycle progression in breast cancer cells by cell counting kit-8, colony-formation, EdU-incorporation assays and flow cytometry. Tumor growth in vivo was observed in a mouse xenograft model. Mass spectrum analyses were performed to identify potential interactors of TRPC5OS in tumor cells, and the interaction between TRPC5OS and interactors was validated by co-immunoprecipitation (CO-IP), western blots, and immunofluorescent staining. Glucose uptake was measured by liquid scintillation spectrometry. TRPC5OS highly expresses both in breast tumors and cell lines, and might be an independent prognostic marker for breast cancer patients. Overexpressed TRPC5OS promotes breast cancer cell proliferation, cell cycle progression, and enhances tumor xenograft growth. Mass spectral and CO-IP data showed that TRPC5OS interacts with ENO1. We also demonstrate that TRPC5OS could enhance ENO1/PI3K/Akt-mediated glucose uptake in breast cancer cells. Our study demonstrated that TRPC5OS promotes breast tumorigenesis by ENO1/PI3K/Akt-mediated glucose uptake. TRPC5OS might be an independent prognostic marker and potential therapeutic target for breast cancer patients.

ObjectiveAxillary lymph node management is an important part of breast cancer surgery and the accuracy of preoperative imaging evaluation can provide adequate information to guide operation. Different molecular subtypes of breast cancer have distinct imaging characteristics. This article was aimed to evaluate the predictive ability of imaging methods in accessing the status of axillary lymph node in different molecular subtypes.MethodsA total of 2,340 patients diagnosed with primary invasive breast cancer after breast surgery from 2013 to 2018 in Jiangsu Breast Disease Center, the First Affiliated Hospital with Nanjing Medical University were included in the study. We collected lymph node assessment results from mammography, ultrasounds, and MRIs, performed receiver operating characteristic (ROC) analysis, and calculated the sensitivity and specificity of each test. The C-statistic among different imaging models were compared in different molecular subtypes to access the predictive abilities of these imaging models in evaluating the lymph node metastasis.ResultsIn Her-2 + patients, the C-statistic of ultrasound was better than that of MRI (0.6883 vs. 0.5935, p=0.0003). The combination of ultrasound and MRI did not raise the predictability compared to ultrasound alone (p=0.492). In ER/PR+HER2- patients, the C-statistic of ultrasound was similar with that of MRI (0.7489 vs. 0.7650, p=0.5619). Ultrasound+MRI raised the prediction accuracy compared to ultrasound alone (p=0.0001). In ER/PR-HER2- patients, the C-statistics of ultrasound was similar with MRI (0.7432 vs. 0.7194, p=0.5579). Combining ultrasound and MRI showed no improvement in the prediction accuracy compared to ultrasound alone (p=0.0532).ConclusionFrom a clinical perspective, for Her-2+ patients, ultrasound was the most recommended examination to assess the status of axillary lymph node metastasis. For ER/PR+HER2- patients, we suggested that the lymph node should be evaluated by ultrasound plus MRI. For ER/PR-Her2- patients, ultrasound or MRI were both optional examinations in lymph node assessment. Furthermore, more new technologies should be explored, especially for Her2+ patients, to further raise the prediction accuracy of lymph node assessment.

Shadow detection is a new method for video synthetic aperture radar moving target indication (ViSAR-GMTI). The shadow formed by the target occlusion will reflect its real position, preventing the defocusing or offset of the moving target from making it difficult to identify the target during imaging. To achieve high-precision shadow detection, this paper proposes a video SAR moving target shadow-detection algorithm based on low-rank sparse decomposition combined with trajectory area extraction. Based on the low-rank sparse decomposition (LRSD) model, the algorithm creates a new decomposition framework combined with total variation (TV) regularization and coherence suppression items to improve the decomposition effect, and a global constraint is constructed to suppress interference using feature operators. In addition, it cooperates with the double threshold trajectory segmentation and error trajectory elimination method to further improve the detection performance. Finally, an experiment was carried out based on the video SAR data released by Sandia National Laboratory (SNL); the results prove the effectiveness of the proposed method, and the detection performance of the method is proved by comparative experiments.

To investigate the disintegration and microstructure characteristics of carbonaceous shale in high-latitude cold regions, indoor, outdoor, initial particle size, and freeze–thaw disintegration experiments were conducted concerning dry–wet cycles. Two tests were performed: sieving and microscopic scanning electron analysis. The carbonaceous shale disintegration, particle size variation rule, disintegration resistance, and fractal characteristics were studied. The microstructure variations of carbonaceous rock before and after water immersion were compared, and the microscopic mechanism of calving in water was discussed. The results show that: (1) the disintegration of carbonaceous shale is basically achieved after eight dry–wet cycles, and the particle size is concentrated at 2 mm~10 mm; (2) the temperature and freeze–thaw cycle conditions accelerated the disintegration rate and shortened the disintegration stability time of carbonaceous shale; (3) there is a negative correlation between the disintegration resistance index and the disintegrating fractal dimension of carbonaceous shale, and the disintegration resistance of disintegrating carbonaceous shale can be indirectly characterized by the fractional dimension; (4) carbonaceous shale contains two hydrophilic clay particles, kaolinite and montmorillonite, and the difference between the lattice expansion of clay particles, the expansion of adsorbed water film, and mineral dissolution are the main factors leading to the disintegration of carbonaceous rock.

Abstract Background The exact pathogenesis of idiopathic choroidal neovascularization (ICNV) remains unclear. Cytokine-mediated inflammation has been thought to be involved in the pathophysiology of ICNV. The purpose of this study was to investigate serum cytokine profiles in patients with ICNV and to explore the relationship between serum cytokine levels and ICNV severity. Methods This case-control study was conducted in 32 ICNV patients and 30 healthy volunteers. Clinical and demographic information was obtained from the medical data platform and the serum was analysed with a multiplex assay to determine the levels of seven cytokines: interleukin (IL)-2, IL-10, IL-15, IL-17, basic fibroblast growth factor (basic FGF), granulocyte-macrophage colony-stimulating factor (GM-CSF), and vascular endothelial growth factor (VEGF). Results Serum levels of IL-2, IL-10, IL-17, basic FGF, and VEGF were elevated in ICNV patients compared to controls. Serum GM-CSF levels were positively related to central retinal thickness, and serum IL-17 levels were positively related to CNV lesion area. Conclusion Serum inflammatory cytokines were significantly elevated in ICNV patients compared to controls. This suggests that systemic inflammation may play a critical role in the physiopathology of ICNV.

As nuclear structural materials, austenitic and ferritic/martensitic (F/M) steels will face inevitable irradiation swelling when fulfilling a role in nuclear reactors, especially under high-dose irradiation. For this work, a coupled machine learning rate theory (ML-RT) model for the swelling of austenitic and F/M steels was developed. In this model, ML was introduced to predict the steady-state irradiation swelling onset dose (Donset), while the improved RT was developed to simulate the swelling behavior after the incubation period. More than 200 series of data on the Donset of different structures of steel were collected for the ML prediction. The coefficient of determination (R) of the results in ML is more than 0.9. In the RT, the evolutions of the dislocation loop and void were described and calculated rather than using the fitting parameters. Cascade efficiency was employed to describe the cascade process. The coupled ML-RT model was verified with the swelling data from neutron irradiation experiments for various steels. The theoretical results of the swelling peak temperatures and swelling behavior are more accurate and reasonable, compared with those from the previous RT model. Using the ML-RT model, the swelling performance of CLAM steel under neutron irradiation of up to 180 dpa was predicted. The differences between the swelling performance of austenitic steels and F/M steels were analyzed and the differences were mainly associated with the bias. These results will be helpful for evaluating the neutron irradiation swelling behavior of candidate structural materials.

Moving targets are usually smeared and imaged at incorrect positions in synthetic aperture radar (SAR) images due to the target motions during the illumination time. Moreover, a moving target will cause multiple artifacts in the reconstructed image since pulse repetition frequency (PRF) operated in high-resolution wide-swath (HRWS) SAR is very low. In order to reliably indicate moving targets, a robust cancellation algorithm is derived in this paper for clutter suppression in multichannel HRWS SAR, which is free by velocity searching and covariance matrix estimation of clutter plus noise. The proposed multilayer channel-cancellation combined with the deramp processing is designed to sequentially suppress the seriously aliased clutter in HRWS SAR. Experimental results show that the proposed algorithm is efficient and robust in tough situations, and have a superior detection ability in weak targets and low-velocity targets. In addition, the radial velocity estimation algorithm combined with the channel cancellation is exploited to relocate moving targets. The effectiveness of the proposed algorithms is validated by actual spaceborne SAR data acquired by a coordination experiment with two controllable vehicles.

This article investigates channel phase mismatch calibration during the application of displaced-phase-center antenna (DPCA) in dual-channel sliding spotlight synthetic aperture radar (SAR) for ground moving target indication (GMTI). In sliding spotlight SAR, the utilization of beam progressive sweeping in azimuth causes antenna phase centers to be misaligned from the sensor path, resulting in the phase mismatch between channels. Then, spatial channel co-registration required in the DPCA cannot be achieved directly by an azimuth time shift. In this study, a calibration method based on scanning geometry of the dual-channel sliding spotlight SAR is developed to address this issue. Moreover, the effect of the phase mismatch calibration on the estimation of azimuth time difference between the two channels is derived and analyzed in depth. The clutter suppression results processed from experimental data acquired by a C-band dual-channel SAR system (Gaofen-3) operated in sliding spotlight mode are shown for the first time to demonstrate the effective phase mismatch calibration.

The neural crest (NC) is a multipotent and temporarily migratory cell population stemming from the dorsal neural tube during vertebrate embryogenesis. Cardiac neural crest cells (NCCs), a specified subpopulation of the NC, are vital for normal cardiovascular development, as they significantly contribute to the pharyngeal arch arteries, the developing cardiac outflow tract (OFT), cardiac valves, and interventricular septum. Various signaling pathways are shown to orchestrate the proper migration, compaction, and differentiation of cardiac NCCs during cardiovascular development. Any loss or dysregulation of signaling pathways in cardiac NCCs can lead to abnormal cardiovascular development during embryogenesis, resulting in abnormalities categorized as congenital heart defects (CHDs). This review focuses on the contributions of cardiac NCCs to cardiovascular formation, discusses cardiac defects caused by a disruption of various regulatory factors, and summarizes the role of multiple signaling pathways during embryonic development. A better understanding of the cardiac NC and its vast regulatory network will provide a deeper insight into the mechanisms of the associated abnormalities, leading to potential therapeutic advancements.

Multi-principal element alloys (MPEAs) have wide promising applications. However, the composition design of MPEAs is challenging due to their vast options and complexity. To narrow down the composition options for MPEAs, a quick screening approach based on a two-parameter method was proposed for the MPEA design. Two thermodynamic parameters of the entropy-enthalpy difference ζ and the entropy-enthalpy quotient Ωmod were defined based on a new enthalpy parameter which was proposed as the summation of the weighted enthalpy modulus |ΔH|sum. The phase selection rules for solid solution MPEAs were statistically summarized from ~200 experimental data. The two-parameter method based on these two parameters and phase selection rules can well classify the conventional steels, high-entropy steels, high-entropy alloys and amorphous alloys. The quick screening approach developed through the two-parameter method together with Monte Carlo sampling method was applied to the alloy systems of (CoCrFeMnNi)random, Fe50(CoCrMnNi)random and Fe50(CoCrMn)random to predict the optimal compositions with stable solid solution phases from millions of options. The theoretical prediction was validated by experimental results. This quick screening approach is applicable to different kinds of MPEAs and can facilitate the research and development of MPEAs as well as other alloys with stable solid solution phases. Keywords: Multi-principal element alloys, Solid solution, Quick screening approach, Composition design

Intractable cardiovascular diseases are leading causes of mortality around the world. Adult mammalian hearts have poor regenerative capacity and are not capable of self-repair after injury. Recent studies of cell-free therapeutics such as those designed to stimulate endogenous cardiac regeneration have uncovered new feasible therapeutic avenues for cardiac repair. The Hippo pathway, a fundamental pathway with pivotal roles in cell proliferation, survival and differentiation, has tremendous potential for therapeutic manipulation in cardiac regeneration. In this review, we summarize the most recent studies that have revealed the function of the Hippo pathway in heart regeneration and homeostasis. In particular, we discuss the molecular mechanisms of how the Hippo pathway maintains cardiac homeostasis by directing cardiomyocyte chromatin remodeling and regulating the cell-cell communication between cardiomyocytes and non-cardiomyocytes in the heart.

In spaceborne synthetic aperture radar (SAR), moving targets are almost buried in ground clutter due to the wide clutter Doppler spectrum and the restricted pulse repetition frequency (PRF), which increases the difficulty of moving target detection. Clutter suppression is one of the key issues in the spaceborne SAR moving target indicator operation. In this paper, we describe the clutter suppression principle and analyze the influence of amplitude and phase error on clutter suppression. In the following, a novel dual-channel SAR clutter suppression algorithm is proposed, which is suitable for the Gaofen-3(GF-3) SAR sensor. The proposed algorithm consists of three technique steps, namely adaptive two-dimensional (2D) channel calibration, refined amplitude error correction and refined phase error correction. After channel error is corrected by these procedures, the clutter component, especially a strong clutter component, can be well suppressed. The validity of the proposed algorithm is verified by GF-3 SAR real data which demonstrates the ground moving-target indication (GMTI) capability of GF-3 SAR sensor.