Predicting One-year Recurrence of HCC based on Gadoxetic Acid-enhanced MRI by Machine Learning Models.

OBJECTIVE: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection. METHODS: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed. All patients underwent preoperative gadoxetic acidenhanced MRI examination. Preoperative clinical factors and MRI characteristics were collected for feature selection. Least Absolute Shrinkage and Selection Operator (LASSO) was applied to select the optimal features for predicting postoperative 1-year recurrence of HCC. Four machine learning algorithms, Multilayer Perception (MLP), random forest, support vector machine, and k-nearest neighbor, were used to construct the predictive models based on the selected features. A Receiver Operating Characteristic (ROC) curve was used to assess the performance of each model. RESULTS: Among the enrolled patients, 32 patients experienced recurrences within one year, while 50 did not. Tumor size, peritumoral hypointensity, decreasing ratio of liver parenchyma T1 value (ΔT1), and α-fetoprotein (AFP) levels were selected by using LASSO to develop the machine learning models. The area under the curve (AUC) of each model exceeded 0.72. Among the models, the MLP model showed the best performance with an AUC, accuracy, sensitivity, and specificity of 0.813, 0.742, 0.570, and 0.853, respectively. CONCLUSION: Machine learning models can accurately predict postoperative 1-year recurrence in patients with HCC, which may help to provide individualized treatment.

Deep learning for differentiation of osteolytic osteosarcoma and giant cell tumor around the knee joint on radiographs: a multicenter study.

OBJECTIVES: To develop a deep learning (DL) model for differentiating between osteolytic osteosarcoma (OS) and giant cell tumor (GCT) on radiographs. METHODS: Patients with osteolytic OS and GCT proven by postoperative pathology were retrospectively recruited from four centers (center A, training and internal testing; centers B, C, and D, external testing). Sixteen radiologists with different experiences in musculoskeletal imaging diagnosis were divided into three groups and participated with or without the DL model's assistance. DL model was generated using EfficientNet-B6 architecture, and the clinical model was trained using clinical variables. The performance of various models was compared using McNemar's test. RESULTS: Three hundred thirty-three patients were included (mean age, 27 years ± 12 [SD]; 186 men). Compared to the clinical model, the DL model achieved a higher area under the curve (AUC) in both the internal (0.97 vs. 0.77, p = 0.008) and external test set (0.97 vs. 0.64, p < 0.001). In the total test set (including the internal and external test sets), the DL model achieved higher accuracy than the junior expert committee (93.1% vs. 72.4%; p < 0.001) and was comparable to the intermediate and senior expert committee (93.1% vs. 88.8%, p = 0.25; 87.1%, p = 0.35). With DL model assistance, the accuracy of the junior expert committee was improved from 72.4% to 91.4% (p = 0.051). CONCLUSION: The DL model accurately distinguished osteolytic OS and GCT with better performance than the junior radiologists, whose own diagnostic performances were significantly improved with the aid of the model, indicating the potential for the differential diagnosis of the two bone tumors on radiographs. CRITICAL RELEVANCE STATEMENT: The deep learning model can accurately distinguish osteolytic osteosarcoma and giant cell tumor on radiographs, which may help radiologists improve the diagnostic accuracy of two types of tumors. KEY POINTS: • The DL model shows robust performance in distinguishing osteolytic osteosarcoma and giant cell tumor. • The diagnosis performance of the DL model is better than junior radiologists'. • The DL model shows potential for differentiating osteolytic osteosarcoma and giant cell tumor.

Gelatin-mediated gallium-doped SrHA composite coatings with sequential antimicrobial and osteogenic functions for infected bone defect repair.

In this study, gallium- and gelatin-modified strontium-doped hydroxyapatite (SrHA-Gel-Ga) bilayer coatings were prepared on titanium substrates by electrodeposition and spin-coating techniques. The results showed that gallium and gelatin were uniformly doped into the SrHA coatings, which exhibited good hydrophilicity and bioactivity. Furthermore, SrHA-Gel-Ga demonstrated good antimicrobial properties against E. coli and S. aureus, especially S. aureus. The co-doping of Sr and gelatin in the coatings was effective in mitigating the cytotoxicity of Ga. SrHA-Gel-Ga was better able to promote the adhesion, proliferation and early differentiation of MC3T3-E1 cells. This study provides a new strategy for the development of anti-infective bone repair coatings.

Preoperative assessment of peripheral vascular invasion of pancreatic ductal adenocarcinoma based on high-resolution MRI.

OBJECTIVES: Preoperative imaging of vascular invasion is important for surgical resection of pancreatic ductal adenocarcinoma (PDAC). However, whether MRI and CT share the same evaluation criteria remains unclear. This study aimed to compare the diagnostic accuracy of high-resolution MRI (HR-MRI), conventional MRI (non-HR-MRI) and CT for PDAC vascular invasion. METHODS: Pathologically proven PDAC with preoperative HR-MRI (79 cases, 58 with CT) and non-HR-MRI (77 cases, 59 with CT) were retrospectively collected. Vascular invasion was confirmed surgically or pathologically. The degree of tumour-vascular contact, vessel narrowing and contour irregularity were reviewed respectively. Diagnostic criteria 1 (C1) was the presence of all three characteristics, and criteria 2 (C2) was the presence of any one of them. The diagnostic efficacies of different examination methods and criteria were evaluated and compared. RESULTS: HR-MRI showed satisfactory performance in assessing vascular invasion (AUC: 0.87-0.92), especially better sensitivity (0.79-0.86 vs. 0.40-0.79) than that with non-HR-MRI and CT. HR-MRI was superior to non-HR-MRI. C2 was superior to C1 on CT evaluation (0.85 vs. 0.79, P = 0.03). C1 was superior to C2 in the venous assessment using HR-MRI (0.90 vs. 0.87, P = 0.04) and in the arterial assessment using non-HR-MRI (0.69 vs. 0.68, P = 0.04). The combination of C1-assessed HR-MRI and C2-assessed CT was significantly better than that of CT alone (0.96 vs. 0.86, P = 0.04). CONCLUSIONS: HR-MRI more accurately assessed PDAC vascular invasion than conventional MRI and may contribute to operative decision-making. C1 was more applicable to MRI scans, and C2 to CT scans. The combination of C1-assessed HR-MRI and C2-assessed CT outperformed CT alone and showed the best efficacy in preoperative examination of PDAC.

The phosphoproteome is a first responder in tiered cellular adaptation to chemical stress followed by proteomics and transcriptomics alteration.

Next-generation risk assessment (NGRA) for environmental chemicals involves a weight of evidence (WoE) framework integrating a suite of new approach methodologies (NAMs) based on points of departure (PoD) obtained from in vitro assays. Among existing NAMs, the omic-based technologies are of particular importance based on the premise that any apical endpoint change indicative of impaired health must be underpinned by some alterations at the omics level, such as transcriptome, proteome, metabolome, epigenome and genome. Transcriptomic assay plays a leading role in providing relatively conservative PoDs compared with apical endpoints. However, it is unclear whether and how parameters measured with other omics techniques predict the cellular response to chemical perturbations, especially at exposure levels below the transcriptomically defined PoD. Multi-omics coverage may provide additional sensitive or confirmative biomarkers to complement and reduce the uncertainty in safety decisions made using targeted and transcriptomics assays. In the present study, we conducted multi-omics studies of transcriptomics, proteomics and phosphoproteomics on two prototype compounds, coumarin and 2,4-dichlorophenoxyacetic acid (2,4-D), with multiple chemical concentrations and time points, to understand the sensitivity of the three omics techniques in response to chemically-induced changes in HepG2. We demonstrated that, phosphoproteomics alterations occur not only earlier in time, but also more sensitive to lower concentrations than proteomics and transcriptomics when the HepG2 cells were exposed to various chemical treatments. The phosphoproteomics changes appear to approach maximum when the transcriptomics alterations begin to initiate. Therefore, it is proximal to the very early effects induced by chemical exposure. We concluded that phosphoproteomics can be utilized to provide a more complete coverage of chemical-induced cellular alteration and supplement transcriptomics-based health safety decision making.

GPS 6.0: an updated server for prediction of kinase-specific phosphorylation sites in proteins.

Protein phosphorylation, catalyzed by protein kinases (PKs), is one of the most important post-translational modifications (PTMs), and involved in regulating almost all of biological processes. Here, we report an updated server, Group-based Prediction System (GPS) 6.0, for prediction of PK-specific phosphorylation sites (p-sites) in eukaryotes. First, we pre-trained a general model using penalized logistic regression (PLR), deep neural network (DNN), and Light Gradient Boosting Machine (LightGMB) on 490 762 non-redundant p-sites in 71 407 proteins. Then, transfer learning was conducted to obtain 577 PK-specific predictors at the group, family and single PK levels, using a well-curated data set of 30 043 known site-specific kinase-substrate relations in 7041 proteins. Together with the evolutionary information, GPS 6.0 could hierarchically predict PK-specific p-sites for 44046 PKs in 185 species. Besides the basic statistics, we also offered the knowledge from 22 public resources to annotate the prediction results, including the experimental evidence, physical interactions, sequence logos, and p-sites in sequences and 3D structures. The GPS 6.0 server is freely available at https://gps.biocuckoo.cn. We believe that GPS 6.0 could be a highly useful service for further analysis of phosphorylation.

Interferon regulatory factor 3 mediates effective antiviral responses to human coronavirus 229E and OC43 infection.

Interferon regulatory factors (IRFs) are key elements of antiviral innate responses that regulate the transcription of interferons (IFNs) and IFN-stimulated genes (ISGs). While the sensitivity of human coronaviruses to IFNs has been characterized, antiviral roles of IRFs during human coronavirus infection are not fully understood. Type I or II IFN treatment protected MRC5 cells from human coronavirus 229E infection, but not OC43. Cells infected with 229E or OC43 upregulated ISGs, indicating that antiviral transcription is not suppressed. Antiviral IRFs, IRF1, IRF3 and IRF7, were activated in cells infected with 229E, OC43 or severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2). RNAi knockdown and overexpression of IRFs demonstrated that IRF1 and IRF3 have antiviral properties against OC43, while IRF3 and IRF7 are effective in restricting 229E infection. IRF3 activation effectively promotes transcription of antiviral genes during OC43 or 229E infection. Our study suggests that IRFs may be effective antiviral regulators against human coronavirus infection.

Recent advances in lanthanide-doped up-conversion probes for theranostics.

Up-conversion (or anti-Stokes) luminescence refers to the phenomenon whereby materials emit high energy, short-wavelength light upon excitation at longer wavelengths. Lanthanide-doped up-conversion nanoparticles (Ln-UCNPs) are widely used in biomedicine due to their excellent physical and chemical properties such as high penetration depth, low damage threshold and light conversion ability. Here, the latest developments in the synthesis and application of Ln-UCNPs are reviewed. First, methods used to synthesize Ln-UCNPs are introduced, and four strategies for enhancing up-conversion luminescence are analyzed, followed by an overview of the applications in phototherapy, bioimaging and biosensing. Finally, the challenges and future prospects of Ln-UCNPs are summarized.

Scorpion Venom Polypeptide Inhibits Pulmonary Epithelial-Mesenchymal Transition in Systemic Sclerosis-Interstitial Lung Disease Model Mice by Intervening TGF-ß1/Smad Signaling Pathway.

Objective: Interstitial lung disease (ILD) is an important complication of systemic sclerosis (SSc). The aim of this study was to investigate the effect and possible mechanism of polypeptide extract of scorpion venom (PESV) on SSc-ILD. Methods: C57/BL6 mice were injected with bleomycin to establish a SSc-ILD model. Different concentrations of PESV solution were administered to SSc-ILD mice, and dexamethasone was used as a positive control. H&E staining and Masson staining were used to observe the pathological changes. The TGF-ß1 expression level was detected by immunohistochemistry. The expression of epithelial-mesenchymal transition (EMT)-related proteins was detected by Western blot, and the expression of TGF-ß1/Smad pathway-related proteins was also detected. The content of inflammatory cytokines in serum and BALF was determined by ELISA. Results: Pathological analysis showed that PESV could alleviate SSc-ILD-induced pulmonary inflammation and fibrosis. Compared with the model group, the content of inflammatory cytokines IL-6 and TNF-α significantly decreased after PESV treatment. PESV could increase the expression of epithelial marker (E-cadherin) and reduce the expression of interstitial markers (collagen I, vimentin, N-cadherin, and a-SMA). In addition, PESV could reduce the expression level of TGF-ß1/Smad pathway-related protein. Conclusion: PESV can attenuate SSc-ILD by regulating EMT, and the effect was linked to the TGF-ß1/Smad signaling pathway, which indicated that PESV may serve as a candidate drug for SSc-ILD.

Terahertz Broadband Absorber Based on a Combined Circular Disc Structure.

To solve the problem of complex structure and narrow absorption band of most of today's terahertz absorbers, this paper proposes and utilizes the finite element (COMSOL) method to numerically simulate a broadband absorber based on a straightforward periodic structure consisting of a disk and concentric ring. The final results show that our designed absorber has an absorption rate of over 99% in the broadband range of 9.06 THz to 9.8 THz and an average of over 97.7% in the ultra-broadband range of 8.62 THz to 10 THz. The reason for the high absorption is explained by the depiction of the electric field on the absorber surface at different frequencies. In addition, the materials for the top pattern of the absorber are replaced by Cu, Ag, or Al, and the absorber still achieves perfect absorption with different metal materials. Due to the perfect symmetry of the absorber structure, the absorber is very polarization-insensitive. The overall design is simple, easy to process and production. Therefore, our research will offer great potential for applications in areas such as terahertz electromagnetic stealth, sensing, and thermal imaging.

NIR II Luminescence Imaging for Sentinel Lymph Node and Enhanced Chemo-/Photothermal Therapy for Breast Cancer.

In this research, a NIR II luminescence imaging and enhanced chemo-/photothermal therapy system of CuS-DOX-Nd/FA NPs for breast cancer and lymph node tracing under single 808 nm irradiation is proposed. Nd-DTPA molecular cluster with the NIR II imaging effect as the carrier was designed to load the ultrasmall CuS nanoparticles and chemotherapeutic drug doxorubicin hydrochloride (DOX). The composite probe is used for tumor lesion imaging and tracking the breast cancer sentinel lymph nodes with simultaneous chemo-/photothermal therapy (PTT) for breast cancer under the single 808 nm laser. This designed probe not only has high permeability and retention (EPR) targeting effect but also can respond to the tumor microenvironment (TME), realizing more precise and efficient release of DOX at the cancer focus. At the same time, CuS as a drug carrier has a good photothermal therapy effect (photothermal conversion efficiency: 27.9%). The serialized released chemotherapy DOX and synergistic PTT effect can be used to the treat the in situ breast cancer land and simultaneously kill the metastasis cancer. The system made the combined molecular clusters Nd-DTPA achieve NIR II imaging of tumor lesions of breast cancer and lymph node to obtain the integration of diagnosis of the transferred disease for better prognosis. The feasibility of the system had obvious tumor growth inhibition effect with NIR II imaging guided is verified by a series of in vitro and in vivo experiments.

Ultra-Wideband and Wide-Angle Perfect Solar Energy Absorber Based on Titanium and Silicon Dioxide Colloidal Nanoarray Structure.

In this paper, we designed an ultra-wideband solar energy absorber and approved it numerically by the finite-difference time-domain simulation. The designed solar energy absorber can achieve a high absorption of more than 90% of light in a continuous 3.506 µm (0.596 µm-4.102 µm) wavelength range. The basic structure of the absorber is based on silicon dioxide colloidal crystal and Ti. Since the materials have a high melting point, the designed solar energy absorber can work normally under high temperature, and the structure of this solar energy absorber is simpler than most solar energy absorbers fabricated with traditional metal. In the entire wavelength band researched, the average absorption of the colloidal crystal-based solar energy absorber is as high as 94.3%, demonstrating an excellent performance under the incidence light of AM 1.5 solar spectrum. In the meantime, the absorption spectrum of the solar energy absorber is insensitive to the polarization of light. In comparison to other similar structures, our designed solar energy absorber has various advantages, such as its high absorption in a wide spectrum range and that it is low cost and easy to make.

MEK reduces cancer-specific PpIX accumulation through the RSK-ABCB1 and HIF-1α-FECH axes.

The efficacy of aminolevulinic acid (5-ALA)-based photodynamic diagnosis (5-ALA-PDD) and photodynamic therapy (5-ALA-PDT) is dependent on 5-ALA-induced cancer-specific accumulation of protoporphyrin IX (PpIX). We previously reported that inhibition of oncogenic Ras/MEK increases PpIX accumulation in cancer cells by reducing PpIX efflux through ATP-binding cassette sub-family B member 1 (ABCB1) and ferrochelatase (FECH)-catalysed PpIX conversion to haem. Here, we sought to identify the downstream pathways of Ras/MEK involved in the regulation of PpIX accumulation via ABCB1 and FECH. First, we demonstrated that Ras/MEK activation reduced PpIX accumulation in RasV12-transformed NIH3T3 cells and HRAS transgenic mice. Knockdown of p90 ribosomal S6 kinases (RSK) 2, 3, or 4 increased PpIX accumulation in RasV12-transformed NIH3T3 cells. Further, treatment with an RSK inhibitor reduced ABCB1 expression and increased PpIX accumulation. Moreover, HIF-1α expression was reduced when RasV12-transformed NIH3T3 cells were treated with a MEK inhibitor, demonstrating that HIF-1α is a downstream element of MEK. HIF-1α inhibition decreased FECH activity and increased PpIX accumulation. Finally, we demonstrated the involvement of RSKs and HIF-1α in the regulation of PpIX accumulation in human cancer cell lines. These results demonstrate that the RSK-ABCB1 and HIF-1α-FECH axes are the downstream pathways of Ras/MEK involved in the regulation of PpIX accumulation.

Transferred Photothermal to Photodynamic Therapy Based on the Marriage of Ultrathin Titanium Carbide and Up-Conversion Nanoparticles.

In this research, upconversion nanoparticles (UCNPs) are used as a light conversion carrier, and their deep light source penetrability is closely combined with ultrathin two-dimensional (2D) Ti3C2Tx to explore the application efficiency of the complex in phototherapy. Due to the advantages of 2D Ti3C2Tx with its high absorbance to ultraviolet/visible light, rich atomic defects to load the drugs, and adjustable thinner structure, this 2D material is beneficially applied as the energy donor. UCNPs@Ti3C2Tx with a photothermal conversion efficiency of 20.7% is proven with the ability to generate reactive oxygen species under a 980 nm laser at the cellular level. Importantly, the main photothermal therapy method can be changed to a photodynamic therapy method due to the degradation of Ti3C2Tx to TiO2 under the oxygen-bearing environment. The in vivo experiment was continued to verify that UCNPs@Ti3C2Tx can kill tumor cells and inhibit tumor growth within a certain period. In addition, in vivo treatment with a combination of immunotherapy and phototherapy of UCNPs@ Ti3C2Tx is carried out to achieve stronger tumor inhibition over the prolonged time points.

Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study.

BACKGROUND: Response evaluation of neoadjuvant chemotherapy (NACT) in patients with osteosarcoma is significant for the termination of ineffective treatment, the development of postoperative chemotherapy regimens, and the prediction of prognosis. However, histological response and tumour necrosis rate can currently be evaluated only in resected specimens after NACT. A preoperatively accurate, noninvasive, and reproducible method of response assessment to NACT is required. In this study, the value of multi-parametric magnetic resonance imaging (MRI) combined with machine learning for assessment of tumour necrosis after NACT for osteosarcoma was investigated. METHODS: Twelve patients with primary osteosarcoma of limbs underwent NACT and received MRI examination before surgery. Postoperative tumour specimens were made corresponding to the transverse image of MRI. One hundred and two tissue samples were obtained and pathologically divided into tumour survival areas (non-cartilaginous and cartilaginous tumour viable areas) and tumour-nonviable areas (non-cartilaginous tumour necrosis areas, post-necrotic tumour collagen areas, and tumour necrotic cystic/haemorrhagic and secondary aneurismal bone cyst areas). The MRI parameters, including standardised apparent diffusion coefficient (ADC) values, signal intensity values of T2-weighted imaging (T2WI) and subtract-enhanced T1-weighted imaging (ST1WI) were used to train machine learning models based on the random forest algorithm. Three classification tasks of distinguishing tumour survival, non-cartilaginous tumour survival, and cartilaginous tumour survival from tumour nonviable were evaluated by five-fold cross-validation. RESULTS: For distinguishing non-cartilaginous tumour survival from tumour nonviable, the classifier constructed with ADC achieved an AUC of 0.93, while the classifier with multi-parametric MRI improved to 0.97 (P = 0.0933). For distinguishing tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.83, while the classifier with multi-parametric MRI improved to 0.90 (P < 0.05). For distinguishing cartilaginous tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.61, while the classifier with multi-parametric MRI parameters improved to 0.81(P < 0.05). CONCLUSIONS: The combination of multi-parametric MRI and machine learning significantly improved the discriminating ability of viable cartilaginous tumour components. Our study suggests that this method may provide an objective and accurate basis for NACT response evaluation in osteosarcoma.

Lanthanide-Based Nanocomposites for Photothermal Therapy under Near-Infrared Laser: Relationship between Light and Heat, Biostability, and Reaction Temperature.

In this research, typical organic/inorganic photothermal therapy (PTT) agents were designed with a combination of upconversion luminescent (UCL) or near-infrared (NIR) II imaging rare-earth nanomaterials for photo-acoustic (PA)/UCL/NIR II imaging-guided PTT under NIR laser irradiation. The results show the following: (1) The PTT effect mainly comes from NIR absorption and partly from UCL light conversion. (2) Visible UCL emission is mainly quenched by NIR absorption of the coated PTT agent and partly quenched by visible absorption, indicating that excitation may play a more important role than in the UCL emission process. (3) The biostability of the composite might be decided by the synthesis reaction temperature. Among the five inorganic/organic nanocomposites, UCNP@MnO2 is the most suitable candidate for cancer diagnosis and treatment because of its stimuli-response ability to the micro-acid environment of tumor cells and highest biostability. The composites generate heat for PTT after entering the tumor cells, and then, the visible light emission gradually regains as MnO2 is reduced to colorless Mn2+ ions, thereby illuminating the cancer cells after the therapy.

Fabrication of ZnO@MoS2 Nanocomposite Heterojunction Arrays and Their Photoelectric Properties.

In this paper, ZnO@MoS2 core-shell heterojunction arrays were successfully prepared by the two-step hydrothermal method, and the growth mechanism was systematically studied. We found that the growth process of molybdenum disulfide (MoS2) was sensitively dependent on the reaction temperature and time. Through an X-ray diffractometry (XRD) component test, we determined that we prepared a 2H phase MoS2 with a direct bandgap semiconductor of 1.2 eV. Then, the photoelectric properties of the samples were studied on the electrochemical workstation. The results show that the ZnO@MoS2 heterojunction acts as a photoanode, and the photocurrent reaches 2.566 mA under the conditions of 1000 W/m2 sunshine and 0.6 V bias. The i-t curve also illustrates the perfect cycle stability. Under the condition of illumination and external bias, the electrons flow to the conduction band of MoS2 and flow out through the external electrode of MoS2. The holes migrate from the MoS2 to the zinc oxide (ZnO) valence band. It is transferred to the external circuit through the glass with fluorine-doped tin oxide (FTO) together with the holes on the ZnO valence band. The ZnO@MoS2 nanocomposite heterostructure provides a reference for the development of ultra-high-speed photoelectric switching devices, photodetector(PD) devices, and photoelectrocatalytic technologies.

A Narrow Dual-Band Monolayer Unpatterned Graphene-Based Perfect Absorber with Critical Coupling in the Near Infrared.

The combination of critical coupling and coupled mode theory in this study elevated the absorption performance of a graphene-based absorber in the near-infrared band, achieving perfect absorption in the double bands (98.96% and 98.22%), owing to the guided mode resonance (the coupling of the leak mode and guided mode under the condition of phase matching, which revealed 100% transmission or reflection efficiency in the wavelet band), and a third high-efficiency absorption (91.34%) emerged. During the evaluation of the single-structure, cross-circle-shaped absorber via simulation and theoretical analysis, the cross-circle shaped absorber assumed a conspicuous preponderance through exploring the correlation between absorption and tunable parameters (period, geometric measure, and incident angle of the cross-circle absorber), and by briefly analyzing the quality factors and universal applicability. Hence, the cross-circle resonance structure provides novel potential for the design of a dual-band unpatterned graphene perfect absorber in the near-infrared band, and possesses practical application significance in photoelectric detectors, modulators, optical switching, and numerous other photoelectric devices.

High Quality Factor, High Sensitivity Metamaterial Graphene-Perfect Absorber Based on Critical Coupling Theory and Impedance Matching.

By means of critical coupling and impedance matching theory, we have numerically simulated the perfect absorption of monolayer graphene. Through the critical coupling effect and impedance matching, we studied a perfect single-band absorption of the monolayer graphene and obtained high quality factor (Q-factor = 664.2) absorption spectrum which has an absorbance close to 100% in the near infrared region. The position of the absorption spectrum can be adjusted by changing the ratio between the radii of the elliptic cylinder air hole and the structural period. The sensitivity of the absorber can be achieved S = 342.7 nm/RIU (RIU is the per refractive index unit) and FOM = 199.2 (FOM is the figure of merit), which has great potential for development on biosensors. We believe that our research will have good application prospects in graphene photonic devices and optoelectronic devices.