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•·We realize a novel piezoresistive sensor with rectification characteristic by doping rGO powder into GO film, whose rectification ratio is regulatable by the pressure below the ...threshold.•·Experimental results show that the sensor achieves a resistance change rate up to 99.9 % when pressure exceeds the threshold value (23.9 kPa) and a peak sensitivity of 9.65 kPa−1.•·We further apply this sensor in the rectification circuit for low-frequency (∼1 Hz) alternating current (AC) signals with the better rectification effect than commercial diode IN5399, as well as to recognize the airflow pressures caused by counting numbers.
Flexible piezoresistive sensors with high sensitivity, low cost, and good durability have been studied for widely use in automatic testing, control technology, and wearable devices. Most piezoresistive sensors can be regarded as varying resistances under different pressures, which do not have current directionality. Here, we report a novel piezoresistive sensor with rectification characteristic by doping reduced graphene oxide (rGO) powder into graphene oxide (GO) film. This piezoresistive sensor exhibits good rectification characteristic for rectifying low-frequency alternating current (AC) signals, coupled with an increase in resistance change rate in response to increased pressure within approximately 24 kPa. When the applied pressure exceeds the threshold, the resistance change rate tends to saturation, reaching up to 99.9 %. The sensor has a high peak sensitivity of 9.65 kPa−1, and a great stability in durability, remaining stable piezoresistive performance under 5500 cycles of pressure test. The piezoresistive sensor also has a fast response time of 72 ms and recovery time of 26 ms. Our work provides a simple way to fabricate a novel piezoresistive sensor with rectification characteristic for next-generation diode and high performance sensor.
Metal-organic frameworks (MOF) have been wildly synthesised and studied as electrode materials for supercapacitors, and bimetallic MOF of Ni and Co has been broadly studied to enhance both specific ...capacitance and stability of supercapacitors. Herein, a best performance (about 320 F/g) of Ni–Co bimetallic MOF was found in a uniform preparation condition by adjusting the ratio of Ni to Co. Then tiny third metal ion was introduced, and we found that the morphology of material has a significant change on the original basis. Furthermore, certain ions (Zn, Fe, Mn) introduced make a huge improvement in capacitance based on Ni–Co MOF of 320 F/g. The result shows that Zn–Ni–Co MOF, Fe–Ni–Co MOF and Mn–Ni–Co MOF perform specific capacitance of 1135 F/g, 870 F/g and 760F/g at 1 A/g, respectively. Meanwhile, the asymmetric supercapacitor (ASC) was constructed by Zn–Ni–Co MOF as positive electrode and active carbon (AC) as negative electrode. The Zn–Ni–Co MOF//AC ASC possesses a energy density of 58 Wh/kg at a power density of 775 W/kg. This research provides a new methods to regulate the morphology of MOF and a novel viewpoint for assembling high-performance, low-price, and eco-friendly green energy storage devices.
The combination of a PD-L1 inhibitor and an anti-angiogenic agent has become the new reference standard in the first-line treatment of non-excisable hepatocellular carcinoma (HCC) due to the survival ...advantage, but its objective response rate remains low at 36%. Evidence shows that PD-L1 inhibitor resistance is attributed to hypoxic tumor microenvironment. In this study, we performed bioinformatics analysis to identify genes and the underlying mechanisms that improve the efficacy of PD-L1 inhibition. Two public datasets of gene expression profiles, (1) HCC tumor versus adjacent normal tissue (
= 214) and (2) normoxia versus anoxia of HepG2 cells (
= 6), were collected from Gene Expression Omnibus (GEO) database. We identified HCC-signature and hypoxia-related genes, using differential expression analysis, and their 52 overlapping genes. Of these 52 genes, 14 PD-L1 regulator genes were further identified through the multiple regression analysis of TCGA-LIHC dataset (
= 371), and 10 hub genes were indicated in the protein-protein interaction (PPI) network. It was found that
,
,
,
, and
play critical roles in the response and overall survival in cancer patients under PD-L1 inhibitor treatment. Our study provides new insights and potential biomarkers to enhance the immunotherapeutic role of PD-L1 inhibitors in HCC, which can help in exploring new therapeutic strategies.
Medical imaging serves as a crucial tool in current cancer diagnosis. However, the quality of medical images is often compromised to minimize the potential risks associated with patient image ...acquisition. Computer-aided diagnosis systems have made significant advancements in recent years. These systems utilize computer algorithms to identify abnormal features in medical images, assisting radiologists in improving diagnostic accuracy and achieving consistency in image and disease interpretation. Importantly, the quality of medical images, as the target data, determines the achievable level of performance by artificial intelligence algorithms. However, the pixel value range of medical images differs from that of the digital images typically processed via artificial intelligence algorithms, and blindly incorporating such data for training can result in suboptimal algorithm performance. In this study, we propose a medical image-enhancement scheme that integrates generic digital image processing and medical image processing modules. This scheme aims to enhance medical image data by endowing them with high-contrast and smooth characteristics. We conducted experimental testing to demonstrate the effectiveness of this scheme in improving the performance of a medical image segmentation algorithm.
Schematic descriptions for the formation of CoSx/Ni-Co LDH composites.
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•The hollow rhombic dodecahedral structure CoSx/Ni-Co LDH composites were prepared.•The CoSx/Ni-Co LDH ...composites exhibited excellent electrochemical performance.•The effects of composition and morphology on electrochemical properties were found.•The asymmetric supercapacitor had excellent energy density and cycling stability.
In this paper, two-component nanocages containing CoSx and nickel-cobalt layered double hydroxides (Ni-Co LDH) were facilely synthesized via a multistep transformation approach. The zeolitic imidazolate framework-67 (ZIF-67) nanocrystals were firstly synthesized, and then after partial sulfuration, the CoSx/Ni-Co LDH nanocages were achieved by adding nickel ions for etching and precipitation. The prepared CoSx/Ni-Co LDH nanocages consisted of the hollow rhombic dodecahedral morphology with many nanosheets arrays on the shell. When used as electrode materials for electrochemical capacitors, this CoSx/Ni-Co LDH nanocages deliver a specific capacitance of 1562 F g−1 at a current density of 1 A g−1. In addition, an asymmetric supercapacitor assembled with CoSx/Ni-Co LDH as cathode and active carbon (AC) as anode shows a high energy density of 35.8 Wh kg−1 at a power density of 800 W kg−1 and has an excellent cycling performance with the retention rate of 94.56% after 10,000 cycles, suggesting their potential application in high-performance electrochemical capacitors. These exceptional electrochemical properties can be attributed to the unique structure and synergistic effects between the metal sulfide and the bimetallic hydroxide, which also indicate the potential application of CoSx/Ni-Co LDH nanocages in high-performance supercapacitors.
In recent years, van der Waals heterostructures (vdWHs) of two-dimensional (2D) materials have attracted extensive research interest. By stacking various 2D materials together to form vdWHs, it is ...interesting to see that new and fascinating properties are formed beyond single 2D materials; thus, 2D heterostructures-based nanodevices, especially for potential optoelectronic applications, were successfully constructed in the past few decades. With the dramatically increased demand for well-controlled heterostructures for nanodevices with desired performance in recent years, various interfacial modulation methods have been carried out to regulate the interfacial coupling of such heterostructures. Here, the research progress in the study of interfacial coupling of vdWHs (investigated by Photoluminescence, Raman, and Pump–probe spectroscopies as well as other techniques), the modulation of interfacial coupling by applying various external fields (including electrical, optical, mechanical fields), as well as the related applications for future electrics and optoelectronics, have been briefly reviewed. By summarizing the recent progress, discussing the recent advances, and looking forward to future trends and existing challenges, this review is aimed at providing an overall picture of the importance of interfacial modulation in vdWHs for possible strategies to optimize the device’s performance.
e16261 Background: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality globally, where treatment and prognostic assessment have important implications in clinical ...practice. Hypoxia, as a common feature within solid tumors, can directly change the tumor microenvironment, which affects the efficacy of cancer treatment and prognosis. In this study, we constructed and validated a hypoxia-based prognostic model using bioinformatics and machine learning. Methods: Two public datasets, GSE14520 and GSE41666, were collected from the Gene Expression Omnibus: (1) HCC tumor tissues compared to adjacent normal tissues (N = 214) and (2) HepG2 cells under normoxic and hypoxic conditions (N = 6). Differential expression analysis was performed to identify HCC characteristic genes and hypoxia-related genes, including their common genes (HCC-Hypoxia Overlap genes, HHOs). Using RNA-seq data of HCC patients (N = 367) from the TCGA Liver Cancer (LIHC) database, univariate Cox regression models were identified, and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm selected hypoxia-characteristic genes for the multivariate survival model. A hypoxia-related risk score was calculated based on the model of these characteristic genes and dichotomized cases into high-risk (HR) and low-risk (LR) groups. The model was validated using liver cancer cases (N = 232) from the International Cancer Genome Consortium database (ICGC-LIRI-JP). Results: Through differential expression analysis of the two datasets, we identified 52 HHOs. Univariate Cox analysis of these HHOs indicated that 21 genes were significantly associated with HCC patient survival. Through LASSO regression analysis, a total of 9 characteristic genes, including CENPA, KIF20A, DLGAP5, HMMR, UPB1, AFM, CABYR, PHLDA2, and N4BP2L1 were ultimately retained in the survival model. Based on these 9 genes, TCGA-LIHC samples were classified into HR and LR groups, and Kaplan-Meier (KM) analysis revealed significant differences in survival outcomes (p < 0.032). Risk scoring of the ICGC-LIRI-JP validation set classified samples into HR and LR. KM analysis showed that the survival times of patients in the HR group were significantly shorter than those in the LR group (p < 0.0001). Receiver Operating Characteristic Analysis analysis of the survival model showed area under the curve values of 0.815, 0.774, and 0.771 at 1, 2, and 3 years, respectively, demonstrating high performance in risk stratification. Conclusions: This study established a prognostic risk-scoring model based on 9 characteristic genes associated with hypoxia. This model can effectively stratify risks among HCC patients and demonstrate excellent performance in predicting survival. These findings may offer new biomarkers and therapeutic targets for the personalized treatment of HCC.
Owing to the cytotoxic effect, it is challenging for clinicians to decide whether post-operative adjuvant therapy is appropriate for a non-small cell lung cancer (NSCLC) patient. Radiomics has proven ...its promising ability in predicting survival but research on its actionable model, particularly for supporting the decision of adjuvant therapy, is limited.
Pre-operative contrast-enhanced CT images of 123 NSCLC cases were collected, including 76, 13, 16, and 18 cases from R01 and AMC cohorts of The Cancer Imaging Archive (TCIA), Jiangxi Cancer Hospital and Guangdong Provincial People's Hospital respectively. From each tumor region, 851 radiomic features were extracted and two augmented features were derived therewith to estimate the likelihood of adjuvant therapy. Both Cox regression and machine learning models with the selected main and interaction effects of 853 features were trained using 76 cases from R01 cohort, and their test performances on survival prediction were compared using 47 cases from the AMC cohort and two hospitals. For those cases where adjuvant therapy was unnecessary, recommendations on adjuvant therapy were made again by the outperforming model and compared with those by IBM Watson for Oncology (WFO).
The Cox model outperformed the machine learning model in predicting survival on the test set (C-Index: 0.765 vs. 0.675). The Cox model consists of 5 predictors, interestingly 4 of which are interactions with augmented features facilitating the modulation of adjuvant therapy option. While WFO recommended no adjuvant therapy for only 13.6% of cases that received unnecessary adjuvant therapy, the same recommendations by the identified Cox model were extended to 54.5% of cases (McNemar's test
= 0.0003).
A Cox model with radiomic and augmented features could predict survival accurately and support the decision of adjuvant therapy for bettering the benefit of NSCLC patients.
This study aimed to identify radiomic features of primary tumor and develop a model for indicating extrahepatic metastasis of hepatocellular carcinoma (HCC). Contrast-enhanced computed tomographic ...(CT) images of 177 HCC cases, including 26 metastatic (MET) and 151 non-metastatic (non-MET), were retrospectively collected and analyzed. For each case, 851 radiomic features, which quantify shape, intensity, texture, and heterogeneity within the segmented volume of the largest HCC tumor in arterial phase, were extracted using Pyradiomics. The dataset was randomly split into training and test sets. Synthetic Minority Oversampling Technique (SMOTE) was performed to augment the training set to 145 MET and 145 non-MET cases. The test set consists of six MET and six non-MET cases. The external validation set is comprised of 20 MET and 25 non-MET cases collected from an independent clinical unit. Logistic regression and support vector machine (SVM) models were identified based on the features selected using the stepwise forward method while the deep convolution neural network, visual geometry group 16 (VGG16), was trained using CT images directly. Grey-level size zone matrix (GLSZM) features constitute four of eight selected predictors of metastasis due to their perceptiveness to the tumor heterogeneity. The radiomic logistic regression model yielded an area under receiver operating characteristic curve (AUROC) of 0.944 on the test set and an AUROC of 0.744 on the external validation set. Logistic regression revealed no significant difference with SVM in the performance and outperformed VGG16 significantly. As extrahepatic metastasis workups, such as chest CT and bone scintigraphy, are standard but exhaustive, radiomic model facilitates a cost-effective method for stratifying HCC patients into eligibility groups of these workups.
Transition metal sulfide has been regarded as an ideal electrode material for supercapacitors due to its high energy density. However, the poor cyclic stability caused by low electroconductivity ...seriously limits its practical application. Herein, carbon nanotubes and nickel–cobalt bimetallic organic framework composites were prepared by the in situ growth method and used as precursors to prepare carbon nanotubes/nickel–cobalt bimetallic sulfide (CNTs/Ni–Co–S-3) composites. Benefits from the synergy between the components, CNTs/Ni–Co–S-3, as a positive electrode material, presented an extremely high specific capacity of 734 C g–1 at 1 A g–1 and an improved rate capability. Furthermore, when CNTs/Ni–Co–S served as the positive electrode of the hybrid supercapacitor (CNTs/Ni–Co–S-3//AC HSC), the device provided a competitive energy density of 42.15 Wh kg–1 at the power density of 852 W kg–1 and long-term stability (88.46% of specific capacitance retention for 10000 cycles at 8 A g–1). This synthesis strategy provides a new pathway for further improving the energy density and cyclic stability of metallic sulfide group composite electrodes.
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