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RING finger (RNF) proteins are frequently dysregulated in human malignancies and are tightly associated with tumorigenesis. However, the expression profiles of RNF genes in hepatocellular carcinoma (HCC) and their relations with prognosis remain undetermined. Here, we aimed at constructing a prognostic model according to RNF genes for forecasting the outcomes of HCC patients using the data from The Cancer Genome Atlas (TCGA) program. We collected HCC datasets to validate the values of our model in predicting prognosis of HCC patients from International Cancer Genome Consortium (ICGC) platform. Then, functional experiments were carried out to explore the roles of the representative RNF in HCC progression. A total of 107 differentially expressed RNFs were obtained between TCGA-HCC tumor and normal tissues. After comprehensive evaluation, a prognostic signature composed of 11 RNFs (RNF220, RNF25, TRIM25, BMI1, RNF216P1, RNF115, RNF2, TRAIP, RNF157, RNF145, and RNF19B) was constructed based on TCGA cohort. Then, the Kaplan-Meier (KM) curves and the receiver operating characteristic curve (ROC) were employed to evaluate predictive power of the prognostic model in testing cohort (TCGA) and validation cohort (ICGC). The KM and ROC curves illustrated the good predictive power in testing and validation cohort. The areas under the ROC curve are 0.77 and 0.76 in these two cohorts, respectively. Among the prognostic signature genes, BMI1 was selected as a representative for functional study. We found that BMI1 protein level was significantly upregulated in HCC tissues. Moreover, the inhibitor of BMI1, PTC-209, displayed an excellent anti-HCC effect in vitro. Enrichment analysis of BMI1 downstream targets showed that BMI1 might be involved in tumor immunotherapy. Together, our overall analyses revealed that the 11-RNFs prognostic signature might provide us latent chances for evaluating HCC prognosis and developing novel HCC therapy.

Critical size of droplet on metal fiber is an important parameter during the dehumidifying process, as it determines the drainage performance of metal foam heat exchangers. In the present study, the droplet shedding characteristics on metal fibers with various fiber diameters, surface wettability and inclined angles were investigated experimentally. The results show that, the critical size of droplet on metal fibers is increased by 69%-213% as the receding contact angle reduces from 132.8° to 17.2°, and it is increased by 93%-292% as the fiber diameter increases from 0.3 mm to 2.0 mm. As the inclined angle of metal fiber increases from 0° to 90°, the critical droplet size is decreased by 78%-86%. Based on the equilibrium of gravity and capillary force, a predictive correlation for the critical droplet size on metal fibers with different wettability and inclined angles was developed, and it agrees with 90% of the experimental data within a deviation of ±15%.

Spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) obtains three-dimensional (3D) hyperspectral information with two-dimensional (2D) compressive measurements in a single shot, which has attracted much attention in recent years. However, its imaging quality and real-time performance of reconstruction still need to be further improved. Recently, deep learning has shown great potential in improving the reconstruction quality and reconstruction speed for computational imaging. When applying deep learning into GISC spectral camera, there are several challenges need to be solved: 1) how to deal with the large amount of 3D hyperspectral data, 2) how to reduce the influence caused by the uncertainty of the random reference measurements, 3) how to improve the reconstructed image quality as far as possible. In this paper, we present an end-to-end V-DUnet for the reconstruction of 3D hyperspectral data in GISC spectral camera. To reduce the influence caused by the uncertainty of the measurement matrix and enhance the reconstructed image quality, both differential ghost imaging results and the detected measurements are sent into the network's inputs. Compared with compressive sensing algorithm, such as PICHCS and TwIST, it not only significantly improves the imaging quality with high noise immunity, but also speeds up the reconstruction time by more than two orders of magnitude.

Background Cancer stem cell (CSC)-related chemoresistance leads to poor outcome of the patients with colorectal cancer (CRC). In this study, we identified the chemoresistance-relevant molecules and decipher the involved mechanisms to provide potential therapeutic target for CRC. We focused on Sec62, a novel target with significantly increased expression in chemoresistant CRC tissues, and further investigated its role in the progression of CRC. Methods Through analyzing the differentially-expressed genes between chemoresistant and chemosensitive CRCs, we selected Sec62 as a novel chemoresistance-related target in CRC. The expression and clinical significance of Sec62 were determined by immunoblotting and immunohistochemistry in tissues and cell lines of CRC. The roles of Sec62 in drug resistance, stemness and tumorigenesis were evaluated in vitro and in vivo using functional experiments. GST pull-down, western blot, coimmunoprecipitation and Me-RIP assays were performed to further explore the downstream molecular mechanisms. Results Sec62 upregulation was associated with the chemoresistance of CRC and poor outcome of CRC patients. Depletion of Sec62 sensitized CRC cells to chemotherapeutic drugs. Sec62 promoted the stemness of CRC cells through activating Wnt/β-catenin signaling. Mechanistically, Sec62 bound to β-catenin and inhibited the degradation of β-catenin. Sec62 competitively disrupted the interaction between β-catenin and APC to inhibit the β-catenin destruction complex assembly. Moreover, Sec62 expression was upregulated by the m6A-mediated stabilization of Sec62 mRNA. Conclusions Sec62 upregulated by the METTL3-mediated m6A modification promotes the stemness and chemoresistance of CRC by binding to β-catenin and enhancing Wnt signalling. Thus, m6A modification-Sec62-β-catenin molecular axis might act as therapeutic targets in improving treatment of CRC.

Continuous hBN films have been grown by means of a radio-frequency-sputtering technology, and their material properties have been investigated. The prepared hBN films can achieve good smoothness in a large area. The surface morphologies and compositions of the hBN films on Si substrate and Al film have been characterized, indicating that there is no difference. The 101-phase peak of hBN film is the strongest, and the optical band gap of the fabricated film is 5.84 eV. An attempt on the fabrication of the hBN based resistive switching (RS) device has been made by using an Ag/hBN/Al structure, leading to the observation of a clear and stable RS behavior. The device exhibits a resistance window (high-resistivity state/low-resistivity state) of around 102, and the RS behaviors of hBN film prepared by sputtering were first observed. It has been found that the opening voltage for the device is changed when a different cycle voltage is applied because of the built-in electric field increasing with the increase of applied cycle voltage. The mechanism of the RS behavior has been analyzed, which lay a foundation for the application of hBN as RS material in resistive random access memory to improve the storage density.

Recently, compressed sensing (CS) has aroused much attention for that sparse signals can be retrieved from a small set of linear samples. Algorithms for CS reconstruction can be roughly classified into two categories: (1) optimization-based algorithms and (2) greedy search ones. In this paper, we propose an algorithm called the preconditioned generalized orthogonal matching pursuit (Pre-gOMP) to promote the recovery performance. We provide a sufficient condition for exact recovery via the Pre-gOMP algorithm, which says that if the mutual coherence of the preconditioned sampling matrix Φ satisfies $ \mu ({\Phi }) < \frac {1}{SK -S + 1}, $μ(Φ)<1SK−S+1, then the Pre-gOMP algorithm exactly recovers any K-sparse signals from the compressed samples, where S (>1) is the number of indices selected in each iteration of Pre-gOMP. We also apply the Pre-gOMP algorithm to the application of ghost imaging. Our experimental results demonstrate that the Pre-gOMP can largely improve the imaging quality of ghost imaging, while boosting the imaging speed.

Herein, we present a high-performance NO2 sensor operating at room temperature based on ZnO nanorods functionalized by nonplasmonic Pd nanoparticles. Optoelectronic measurements revealed that the ZnO/Pd hybrids exhibited high photocurrent with ultrafast rise/decay rates under visible light with optimal wavelength (λ = 475 nm), which was related to the photoexcited nonplasmonic electron injection from Pd nanoparticles to ZnO nanorods. Characterization of the visible-light-activated gas sensing performance is pursued at ppb-level of NO2 resulting in high responses, fast response/recovery rate, low detection limit as well as full reversibility. The enhanced optoelectronic NO2 sensing performance of the ZnO/Pd hybrid was attributed to the photoexcited nonplasmonic electrons. Here, we designed and demonstrated a high-performance NO2 sensing material utilizing the photoexcited nonplasmonic electrons from transition metal nanoparticles. This concept can also be extended to other metal oxide/transition metal nanoparticle heterostructures for optoelectronic devices.

Transition metal dichalcogenide nanostructures especially MoS2 have emerged as novel gas sensing materials. Particularly, MoS2-based optoelectronic devices activated by UV or visible light have bee...

Recent cancer studies have found that the thrombospondin (THBS) family, including THBS1, THBS2, THBS3, THBS4, and THBS5, play vital roles in the development and progression of human cancers. However, their relationships with tumor stage, prognosis, and tumor immunity in pan-cancer have not been systematically reported. In the present study, we employed versatile public databases to assess the expression and mutations of different THBSs in pan-cancer and performed functional experiments to analyze the roles of THBS2 in gastrointestinal cancer metastasis. Our findings indicate that THBS genes are frequently mutated in various cancers and the dysregulation of THBS family members is associated with the progression of some cancers such as gastric cancer, colon cancer, and lung cancer. Further analyses indicate that THBS genes are associated with cancer hallmarks such as cell cycle and epithelial-mesenchymal transition (EMT). Importantly, thrombospondins, especially THBS1 and THBS2, are correlated with the immune cell infiltration level in gastrointestinal cancers. Our experiments further verified that THBS2 participates in tumor metastasis by enhancing EMT. Therefore, the overall analyses reveal that THBSs might offer us potential chances for tumor diagnosis and therapy.

A spectral polarization camera based on ghost imaging via sparsity constraints (GISC) is presented. The proposed imager modulates three-dimensional spatial and spectral information of the target into two-dimensional speckle patterns using a spatial random phase modulator and then acquires the speckle patterns at four linear polarization channels through a polarized CCD. The experimental results verify the feasibility of the system structure and reconstruction algorithm. The GISC spectral polarization camera, which has a simple structure and achieves compressive sampling during the imaging acquisition process, provides a simple scheme for obtaining multi-dimensional information of the light field.

Considering prior statistical information about multi-scale of a target scene, a multi-scale ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed in this work. This method significantly improves the imaging efficiency. Simulation and experimental results demonstrate that it has higher imaging quality at low sampling rate than using single-scale speckle pattern.

Fourier-transform ghost imaging (FGI) enables us to realize diffraction imaging within the Fresnel region by calculating the second-order correlations of light fields. Existing FGI schemes reconstruct the Fourier frequency spectrum via correlation or sparsity constraints, which generally require object-arm detection values with relatively high signal-to-noise ratio. In this paper, we propose a correspondence FGI scheme, which reconstructs the object's Fourier spectrum by averaging partial reference patterns corresponding to object-arm detection values of high fluctuations. This conditional-averaging method is theoretically demonstrated and then explored and verified by both simulation and experiment. Moreover, an information-theory-based explanation of the simulation results is performed by studying the Fisher information of detection signals. The proposed scheme improves the sampling efficiency and is expected to expand the application of FGI by combining it with other reconstruction techniques.

Additional file 1: Figure S1. Sec62 is involved in maintaining the stemness of CRC cells. a, Scatter plots of mRNA level of Sec62 versus mRNA levels of CD44, CD133, EPCAM, ITGB1, and BMI1 in colon adenocarcinoma from TCGA dataset were plotted. b, The control cells or Sec62 depleted cells were seeded in unattached 96-well plates and cultured for 7 day. The percentage of wells with spheres was evaluated and calculated with limiting dilution analysis (LDA) to determine the sphere-initiating cell frequency. Frequency and probability estimates were computed using the ELDA software. ***, P

TiN coating plays a positive role in improving the abrasion resistance and impact resistance of aero-engines in sand and dust environments. However, little research has been done on the laser cleaning of TiN coatings that failed on aircraft engines. In this paper, TiN coatings are deposited on Ti6Al4V alloys by magnetic filtered cathodic vacuum arc (MFCVA). The TiN coating was laser cleaned with different parameters. By analyzing coating morphology, surface composition and sample profile, the research reveals the morphological change of the TiN coating after cleaning and the laser cleaning mechanism. The results show that for TiN&ndash, Ti6Al4V structure, when the laser average power density is 2.54 &times, 103 W/cm2, the cleaning mechanism of the coating is thermal expansion, The laser average power density is increased to 5.08 &times, 103 W/cm2, the cleaning mechanism is thermal expansion, accompanied by the thermal melting of the substrate, a small amount of molten substrate overflows from the crack. When the laser average power density is 5.08 &times, 103 W/cm2 and the number of cleanings doubles, the cleaning direction is perpendicular to each other, the cleaning mechanism is thermal expansion and thermal melting, both the substrate and the coating are melted, and the cleaning is obviously effective.

Introduction: Pulmonary artery intimal sarcoma (PAIS) is a rare and highly aggressive tumor, and approximately 80% of pulmonary cases occur in the pulmonary trunk. We report herein a case of retrograde extension of the sarcoma to the pulmonary valve and right ventricle, which is an uncommon manifestation of this lethal tumor. Patient concerns: A 41-year-old woman was initially diagnosed with pulmonary thromboembolism (PTE) and transferred to our hospital. Diagnosis: Computed tomographic pulmonary angiography (CTPA) showed that there are low-density filling defects in both pulmonary arteries, and the patient was diagnosed with PTE. However, the ultrasonographers considered that the lesion is a space-occupying type that involves the right ventricular outflow tract and pulmonary valve instead of PTE. Postoperative pathology confirmed the diagnosis of PAIS. Interventions: The patient underwent resection of pulmonary artery sarcoma and endarterectomy. Outcomes: During the follow-up via telephone 1 month after discharge, the patient reported to have been feeling well. Conclusion: Owing to the rarity of the disease and its non-specific clinical manifestations, approximately half of the PAIS cases are misdiagnosed or have a delayed diagnosis. Thus, improving our understanding of the disease and facilitating its early diagnosis are essential.

During the operation of AC/DC interconnected power grids, small signal instability of low frequency oscillation between regions is prone to occur. In this paper, distributed power flow controller is applied to improve the small signal stability of the power system. In order to ensure the distributed power flow controller to control the flow of the target line in the small signal stability range, a method for determining target parameters of distributed power flow controller is presented. This method combines power flow calculation model with active power optimal dispatch and small signal calculation. And an integrated scheduling equation with small signal stability constraints will be formed. Solve this equation to get the control target parameters of distributed power flow controller. Meanwhile, the PSASP is used to simulate and verify CEPRI7V7 system with the distributed power flow controller. The results show that the proposed method can improve the stability of small signal in the system.

The spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) is a phase modulated compressive snapshot spectral imager. It makes use of the second-order intensity correlation of the light field to resolve the spatial and spectral information. In this paper, an optical design for GISC spectral camera which aims to obtain the desired spatial and spectral resolution is presented. A system calibration strategy based on few-mode optical fiber and monochrometer is developed. The snapshot spectral imaging experiments for the test targets and natural scenes are conducted using the prototype of GISC spectral camera loaded on the tethered balloon. The result of the spatial resolution, linearity, and spectra reconstruction error of the prototype is quantitatively evaluated. The distinguishable size at the distance of 1 km is around 0.34 m. The linearity is higher than 0.99 among the wavelength channels from 410 to 640 nm. The reconstructed spectra of eight color targets are compared with those measured by a commercial spectroradiometer. The average relative root mean squared error of the reconstructed spectra is 0.65.

In the present study, the nucleate pool boiling heat transfer characteristics of water on the hydrophilic and uncoated metal foam covers were experimentally investigated, and were compared with those on hydrophobic metal foam covers to analyze the influence of surface wettability on pool boiling heat transfer on metal foam covers. The experimental conditions cover pore densities of 5–50 PPI (pores per inch), porosities of 85%–95%, average contact angles of 0°–148.1°, heat fluxes of 0-2 × 106 W/m2. As the pore density increases from 5 PPI to 40 PPI, the pool boiling heat transfer coefficient in hydrophilic metal foam is increased by 10%–25%, and the critical heat flux is increased by 40%. As the porosity decreases from 95% to 85%, both the critical heat flux and the pool boiling heat transfer performance in hydrophilic metal foams are deteriorated. The surface modification effect factor EFsm for hydrophilic metal foam varies within 1.01–1.38; EFsm increases with the increasing heat flux, which is contrary to that for hydrophobic metal foam. The critical heat flux on hydrophilic metal foam covers with 5 PPI and 20 PPI are 1.2 × 106 W/m2 and 1.36 × 106 W/m2, respectively, which are larger than those on hydrophobic ones. A new correlation for pool boiling heat transfer coefficient on metal foam covers with different wettability was developed with an average deviation of 14.1%.

Ghost imaging (GI) is a novel imaging technique based on the second-order correlation of light fields. Due to limited number of samplings in practice, traditional GI methods often reconstruct objects with unsatisfactory quality. To improve the imaging results, many reconstruction methods have been developed, yet the reconstruction quality is still fundamentally restricted by the modulated light fields. In this paper, we propose to improve the imaging quality of GI by optimizing the light fields, which is realized via matrix optimization for a learned dictionary incorporating the sparsity prior of objects. A closed-form solution of the sampling matrix, which enables successive sampling, is derived. Through simulation and experimental results, it is shown that the proposed scheme leads to better imaging quality compared to the state-of-the-art optimization methods for light fields, especially at a low sampling rate., Comment: 14 pages, 6 figures

Ghost imaging (GI) can nonlocally image objects by exploiting the fluctuation characteristics of light fields, where the spatial resolution is determined by the normalized second-order correlation function g ( 2 ) . However, the spatial shift-invariant property of g ( 2 ) is distorted when the number of samples is limited, which hinders the deconvolution methods from improving the spatial resolution of GI. In this paper, based on prior imaging systems, we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in GI. Our theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging system. The imaging resolution of GI after preconditioning is restricted to the detection noise. Both simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution method. In the experiment, 1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned deconvolution. Our results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems, and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands.

Photoactivation is a promising approach for room-temperature gas sensing with metal oxide semiconductors. For room-temperature methane (CH4) gas sensors, it is highly desirable to develop sensing materials with high photocatalytic CH4 oxidation activity so as to improve their UV-activated CH4 sensing performance. Herein, we reported that mesoporous ZnO nanosheets with rich surface oxygen vacancies (VO) exhibited enhanced CH4-sensing properties under UV illumination at room temperature. The VO-enriched mesoporous ZnO nanosheets were fabricated via a low-temperature thermal phase transformation route. Under UV irradiation, the VO-rich ZnO nanosheets demonstrated a response of 62 % to 0.1 % CH4, about 4.7 times higher than that of VO-deficient commercial ZnO nanoparticles. The improved CH4 sensing capacity of the porous ZnO nanosheets under UV illumination was correlated to their enhanced photocatalytic oxidation activity of CH4 induced by surface VO. The in-situelectron paramagnetic resonance and O2 temperature programmed desorption analysis indicated that the generation of Zn+/O− active centers and active oxygen species could be promoted by the rich surface VO on mesoporous ZnO nanosheets. Furthermore, the density functional theory calculations suggested that VO could improve the surface charge density of ZnO and lower the Gibbs free energy for the CH4 activation on the ZnO surface.

Speckle autocorrelation is a popular method for imaging through scattering media. Currently, most proposed methods in literature can only recognize the pattern and the relative movement ratio of a hidden object. Position and size quantification, the other content of imaging, is just as important as object recognition. Here, we propose a non-invasive method to estimate the axial position and size of a hidden object based on speckle autocorrelation imaging. A unique geometry setup for bi-directional exposure is applied to extract the position and size information. The image of the object can be reconstructed from the recorded speckle pattern via phase retrieval techniques. According to the geometry relationship, we calculate the size and axial position of the object, and further, obtain the lateral or axial displacements when the object is shifted in both simulation and experiment. This method opens a door for noninvasive imaging and positioning through scattering media, will impact the fields of biomedical imaging, object tracking, etc.

The effect of Nb addition on the microstructure and magnetic properties of nanocrystalline Sm(CobalNbxZr0.02)7 permanent magnet were investigated. The magnetization reversal behavior for ball milled Sm(CobalNbxZr0.02)7 samples with high coercivity was investigated by analyzing hysteresis curves and recoil loops of demagnetization curves. Nb addition proved to result in relevant improvement in the magnetic properties, especially in the coercivity Hc. It was shown that the magnetic properties of Sm(CobalNbx- Zr0.02)7 nanocrystalline magnets were improved by an additional 0.06 at.% Nb. In particular, Hc was improved from 602 to 786 kA/m at room temperature. The maximum value of the integrated recoil loops area for 0.06 at.% Nb-doped samples of 1.81 kJ/m3 was much lower than that of the Nb-free sample, which could be explained by a smaller recoverable portion of the magnetization remaining in the Nb-doped sample when the applied field was below the coercivity Hc. The nucleation field Hn for irreversible magnetization reversal of the magnetically hard phase were calculated by analyzed in terms of the ΔMirrev-H curve and the Kondorsky model.

Hydrophobic metal foam has a great potential for improving the boiling characteristics. In the present study, the nucleate pool boiling heat transfer characteristics of water on the hydrophobic metal foam covers were experimentally investigated. The experimental conditions cover the metal foam pore density of 5–40 PPI (pores per inch), the porosity of 85%-95%, and the heat flux of 0–2 × 106 W/m2. The experimental results show that, at heat flux smaller than 1.3 × 106 W/m2, the pool boiling heat transfer coefficient is increased maximally by 36% and the incipient boiling superheated degree is decreased by 0.4–1.4 K through hydrophobic modification on metal fibers; with the increasing heat flux, the increment of heat transfer coefficient decreases; at high heat flux, the heat transfer coefficient of hydrophobic metal foams is smaller than that of uncoated ones. The hydrophobic modification effect factor EFHy varies within 0.88–1.36. A new correlation for pool boiling on uncoated and hydrophobic metal foam covers was developed with an average deviation of 10.2%.

Objective: To investigate diseases associated with amyotrophic lateral sclerosis (ALS) by using a total population-based medical database. Methods: This study included 705 ALS patients aged older than 15 years diagnosed from January 1, 2007, to December 31, 2013, along with 14,100 controls matching in sex, age, residence, and insurance premium. Data from the National Health Insurance Research Database (NHIRD) and Serious Disabling Diseases (SDD) database in Taiwan were used to conduct a total population-based case–control study. Prior diseases were categorized as being diagnosed 1, 3, 5, 7, or 9 years before first ALS diagnosis. Chi-square or t test was used to examine differences in demographic characteristics between the new patients with ALS and controls. Previous diseases were screened using a conditional logistic regression model. Multivariate analysis was performed using stepwise selection to evaluate the association between these diseases and the risk of ALS. The path analysis was conducted to analyze the pathway between prior diseases and ALS. Results: In total, 28 diseases were associated with ALS, including 17 positive associations and 11 negative associations. The path analysis revealed that the 11 negatively associated diseases could be attributed to diabetes mellitus and its comorbidities. The 17 positively associated diseases could be categorized as metabolic syndrome, neuroinflammation, head trauma, sports injuries, infections, and their comorbidities. Conclusions: Our results support the hypothesis that diseases developing prior to ALS diagnoses are hypermetabolic disorders. Hypometabolic disorders may have a beneficial effect on ALS incidence. Defective energy metabolism may play a role in ALS pathogenesis.

We propose a scheme of optimization in ghost imaging by minimizing the mutual coherence between measurement matrix and an overcomplete dictionary. Simulation results show the effectiveness of the optimization.