Broadband lens and graphene/silicon photodiode for wide spectral imaging.

We designed a broadband lens along with a graphene/silicon photodiode for wide spectral imaging ranging from ultraviolet to near-infrared wavelengths. By using five spherical glass lenses, the broadband lens, with the modulation transfer function of 0.38 at 100 lp/mm, corrects aberrations ranging from 340 to 1700 nm. Our design also includes a broadband graphene/silicon Schottky photodiode with the highest responsivity of 0.63 A/W ranging from ultraviolet to near-infrared. By using the proposed broadband lens and the broadband graphene/silicon photodiode, several single-pixel imaging designs in ultraviolet, visible, and near-infrared wavelengths are demonstrated. Experimental results show the advantages of integrating the lens with the photodiode and the potential to realize broadband imaging with a single set of lens and a detector.

Development of a CT radiomics nomogram for preoperative prediction of Ki-67 index in pancreatic ductal adenocarcinoma: a two-center retrospective study.

OBJECTIVES: To develop and validate a contrast-enhanced computed tomography (CECT)-based radiomics nomogram for the preoperative evaluation of Ki-67 proliferation status in pancreatic ductal adenocarcinoma (PDAC). METHODS: In this two-center retrospective study, a total of 181 patients (95 in the training cohort; 42 in the testing cohort, and 44 in the external validation cohort) with PDAC who underwent CECT examination were included. Radiomic features were extracted from portal venous phase images. The radiomics signatures were built by using two feature-selecting methods (relief and recursive feature elimination) and four classifiers (support vector machine, naive Bayes, linear discriminant analysis (LDA), and logistic regression (LR)). Multivariate LR was used to build a clinical model and radiomics-clinical nomogram. The predictive performances of the models were evaluated using area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). RESULTS: The relief selector and LDA classifier using twelve features built the optimal radiomics signature, with AUCs of 0.948, 0.927, and 0.824 in the training, testing, and external validation cohorts, respectively. The radiomics-clinical nomogram incorporating the optimal radiomics signature, CT-reported lymph node status, and CA19-9 showed better predictive performance with AUCs of 0.976, 0.955, and 0.882 in the training, testing, and external validation cohorts, respectively. The calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice of the nomogram. CONCLUSIONS: The radiomics-clinical nomogram is an effective and non-invasive computer-aided tool to predict the Ki-67 expression status in patients with PDAC. CLINICAL RELEVANCE STATEMENT: The radiomics-clinical nomogram is an effective and non-invasive computer-aided tool to predict the Ki-67 expression status in patients with pancreatic ductal adenocarcinoma. KEY POINTS: The radiomics analysis could be helpful to predict Ki-67 expression status in patients with pancreatic ductal adenocarcinoma (PDAC). The radiomics-clinical nomogram integrated with the radiomics signature, clinical data, and CT radiological features could significantly improve the differential diagnosis of Ki-67 expression status. The radiomics-clinical nomogram showed satisfactory calibration and net benefit for discriminating high and low Ki-67 expression status in PDAC.

Comprehensive variation discovery and recovery of missing sequence in the pig genome using multiple de novo assemblies.

Uncovering genetic variation through resequencing is limited by the fact that only sequences with similarity to the reference genome are examined. Reference genomes are often incomplete and cannot represent the full range of genetic diversity as a result of geographical divergence and independent demographic events. To more comprehensively characterize genetic variation of pigs (Sus scrofa), we generated de novo assemblies of nine geographically and phenotypically representative pigs from Eurasia. By comparing them to the reference pig assembly, we uncovered a substantial number of novel SNPs and structural variants, as well as 137.02-Mb sequences harboring 1737 protein-coding genes that were absent in the reference assembly, revealing variants left by selection. Our results illustrate the power of whole-genome de novo sequencing relative to resequencing and provide valuable genetic resources that enable effective use of pigs in both agricultural production and biomedical research.

Graphene-based ultrasensitive optical microfluidic sensor for the real-time and label-free monitoring of simulated arterial blood flow.

Highly sensitive, real-time and label-free sensing of liquid flow in microfluidic environments remains challenging. Here, by growing high-quality graphene directly on a glass substrate, we designed a microfluidic-integrated graphene-based flow sensor (GFS) capable of detecting complex, weak, and transient flow velocity and pressure signals in a microfluidic environment. This device was used to study weak and transient liquid flows, especially blood flow, which is closely related to heart and artery functions. By simulating cardiac peristalsis and arterial flow using peristaltic pumps and microfluidic systems, we monitored simulated arterial blood flow. This ultrasensitive graphene-based flow sensor accurately detected a flow velocity limit as low as 0.7 mm/s, a pumping frequency range of 0.04 Hz to 2.5 Hz, and a pressure range from 0.6 kPa to 14 kPa. By measuring the blood flow velocities and pressures, pathological blood flow signals were distinguished and captured by the corresponding flow velocities or pressures, which can reflect vascular occlusion and heart functions. This sensor may be used for the real-time and label-free monitoring of patients' basic vital signs using their blood flow and provide a possible new method for the care of critically ill patients.

Review of Polarization Optical Devices Based on Graphene Materials.

Graphene has received extensive scholarly attention for its extraordinary optical, electrical, and physicochemical properties, as well as its compatibility with silicon-based semiconductor processes. As a unique two-dimensional atomic crystal material, graphene has excellent mechanical properties, ultra-high carrier mobility, ultra-wide optical response spectrum, and strong polarization dependence effect, which make it have great potential in new optical and polarization devices. A series of new optical devices that are based on graphene have been developed, showing excellent performance and broad application prospects. In this paper, the recent research progress of polarizers, sensors, modulators, and detectors that are based on the polarization characteristics of graphene is reviewed. In particular, the polarization dependence effect and broadband absorption enhancement of graphene under total reflection structure are emphasized, which enhance the interaction between graphene and light and then provide a new direction for research of graphene polarization devices.

Graphene Optical Biosensors.

Graphene shows great potential in biosensing owing to its extraordinary optical, electrical and physical properties. In particular, graphene possesses unique optical properties, such as broadband and tunable absorption, and strong polarization-dependent effects. This lays a foundation for building graphene-based optical sensors. This paper selectively reviews recent advances in graphene-based optical sensors and biosensors. Graphene-based optical biosensors can be used for single cell detection, cell line, and anticancer drug detection, protein and antigen-antibody detection. These new high-performance graphene-based optical sensors are able to detect surface structural changes and biomolecular interactions. In all these cases, the optical biosensors perform well with ultra-fast detection, high sensitivities, unmarked, and are able to respond in real time. The future of the field of graphene applications is also discussed.

The miRNA Transcriptome Directly Reflects the Physiological and Biochemical Differences between Red, White, and Intermediate Muscle Fiber Types.

MicroRNAs (miRNAs) are small non-coding RNAs that can regulate their target genes at the post-transcriptional level. Skeletal muscle comprises different fiber types that can be broadly classified as red, intermediate, and white. Recently, a set of miRNAs was found expressed in a fiber type-specific manner in red and white fiber types. However, an in-depth analysis of the miRNA transcriptome differences between all three fiber types has not been undertaken. Herein, we collected 15 porcine skeletal muscles from different anatomical locations, which were then clearly divided into red, white, and intermediate fiber type based on the ratios of myosin heavy chain isoforms. We further illustrated that three muscles, which typically represented each muscle fiber type (i.e., red: peroneal longus (PL), intermediate: psoas major muscle (PMM), white: longissimus dorsi muscle (LDM)), have distinct metabolic patterns of mitochondrial and glycolytic enzyme levels. Furthermore, we constructed small RNA libraries for PL, PMM, and LDM using a deep sequencing approach. Results showed that the differentially expressed miRNAs were mainly enriched in PL and played a vital role in myogenesis and energy metabolism. Overall, this comprehensive analysis will contribute to a better understanding of the miRNA regulatory mechanism that achieves the phenotypic diversity of skeletal muscles.

A nomogram based on dual-layer detector spectral computed tomography quantitative parameters and morphological quantitative indicator for distinguishing metastatic and nonmetastatic regional lymph nodes in pancreatic ductal adenocarcinoma.

Background: There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete regional LN dissection can lead to postoperative recurrence, while blind expansion of the scope of regional LN dissection significantly increases the perioperative risk without significantly prolonging overall survival. We aimed to establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) to predict the probability of regional LN metastasis in patients with PDAC. Methods: A total of 163 regional LNs were reviewed and divided into a metastatic cohort (n=58 LNs) and nonmetastatic cohort (n=105 LNs). The DLCT quantitative parameters and the nodal ratio of the longest axis to the shortest axis (L/S) of the regional LNs were compared between the two cohorts. The DLCT quantitative parameters included the iodine concentration in the arterial phase (APIC), normalized iodine concentration in the arterial phase (APNIC), effective atomic number in the arterial phase (APZeff), normalized effective atomic number in the arterial phase (APNZeff), slope of the spectral attenuation curves in the arterial phase (APλHU), iodine concentration in the portal venous phase (PVPIC), normalized iodine concentration in the portal venous phase (PVPNIC), effective atomic number in the portal venous phase (PVPZeff), normalized effective atomic number in the portal venous phase (PVPNZeff), and slope of the spectral attenuation curves in the portal venous phase (PVPλHU). Logistic regression analysis based on area under the curve (AUC) was used to analyze the diagnostic performance of significant DLCT quantitative parameters, L/S, and the models combining significant DLCT quantitative parameters and L/S. A nomogram based on the models with highest diagnostic performance was developed as a predictor. The goodness of fit and clinical applicability of the nomogram were assessed through calibration curve and decision curve analysis (DCA). Results: The combined model of APNIC + L/S (APNIC + L/S) had the highest diagnostic performance among all models, yielding an AUC, sensitivity, and specificity of 0.878 [95% confidence interval (CI): 0.825-0.931], 0.707, and 0.886, respectively. The calibration curve indicated that the APNIC-L/S nomogram had good agreement between the predicted probability and the actual probability. Meanwhile, the decision curve indicated that the APNIC-L/S nomogram could produce a greater net benefit than could the all- or-no-intervention strategy, with threshold probabilities ranging from 0.0 to 0.75. Conclusions: As a valid and visual noninvasive prediction tool, the APNIC-L/S nomogram demonstrated favorable predictive efficacy for identifying metastatic LNs in patients with PDAC.

Detection of malignant lesions in cytologically indeterminate thyroid nodules using a dual-layer spectral detector CT-clinical nomogram.

Purpose: To evaluate the capability of dual-layer detector spectral CT (DLCT) quantitative parameters in conjunction with clinical variables to detect malignant lesions in cytologically indeterminate thyroid nodules (TNs). Materials and methods: Data from 107 patients with cytologically indeterminate TNs who underwent DLCT scans were retrospectively reviewed and randomly divided into training and validation sets (7:3 ratio). DLCT quantitative parameters (iodine concentration (IC), NICP (IC nodule/IC thyroid parenchyma), NICA (IC nodule/IC ipsilateral carotid artery), attenuation on the slope of spectral HU curve and effective atomic number), along with clinical variables, were compared between benign and malignant cohorts through univariate analysis. Multivariable logistic regression analysis was employed to identify independent predictors which were used to construct the clinical model, DLCT model, and combined model. A nomogram was formulated based on optimal performing model, and its performance was assessed using receiver operating characteristic curve, calibration curve, and decision curve analysis. The nomogram was subsequently tested in the validation set. Results: Independent predictors associated with malignant TNs with indeterminate cytology included NICP in the arterial phase, Hashimoto's Thyroiditis (HT), and BRAF V600E (all p < 0.05). The DLCT-clinical nomogram, incorporating the aforementioned variables, exhibited superior performance than the clinical model or DLCT model in both training set (AUC: 0.875 vs 0.792 vs 0.824) and validation set (AUC: 0.874 vs 0.792 vs 0.779). The DLCT-clinical nomogram demonstrated satisfactory calibration and clinical utility in both training set and validation set. Conclusion: The DLCT-clinical nomogram emerges as an effective tool to detect malignant lesions in cytologically indeterminate TNs.

Development and validation of a model for predicting the expression of Ki-67 in pancreatic ductal adenocarcinoma with radiological features and dual-energy computed tomography quantitative parameters.

OBJECTIVE: To construct and validate a model based on the dual-energy computed tomography (DECT) quantitative parameters and radiological features to predict Ki-67 expression levels in pancreatic ductal adenocarcinoma (PDAC). MATERIALS AND METHODS: Data from 143 PDAC patients were analysed. The variables of clinic, radiology and DECT were evaluated. In the arterial phase and portal venous phase (PVP), the normalized iodine concentration (NIC), normalized effective atomic number and slope of the spectral attenuation curves were measured. The extracellular volume fraction (ECVf) was measured in the equilibrium phase. Univariate analysis was used to screen independent risk factors to predict Ki-67 expression. The Radiology, DECT and DECT-Radiology models were constructed, and their diagnostic effectiveness and clinical applicability were obtained through area under the curve (AUC) and decision curve analysis, respectively. The nomogram was established based on the optimal model, and its goodness-of-fit was assessed by a calibration curve. RESULTS: Computed tomography reported regional lymph node status, NIC of PVP, and ECVf were independent predictors for Ki-67 expression prediction. The AUCs of the Radiology, DECT, and DECT-Radiology models were 0.705, 0.884, and 0.905, respectively, in the training cohort, and 0.669, 0.835, and 0.865, respectively, in the validation cohort. The DECT-Radiology nomogram was established based on the DECT-Radiology model, which showed the highest net benefit and satisfactory consistency. CONCLUSIONS: The DECT-Radiology model shows favourable predictive efficacy for Ki-67 expression, which may be of value for clinical decision-making in PDAC patients. CRITICAL RELEVANCE STATEMENT: The DECT-Radiology model could contribute to the preoperative and non-invasive assessment of Ki-67 expression of PDAC, which may help clinicians to screen out PDAC patients with high Ki-67 expression. KEY POINTS: • Dual-energy computed tomography (DECT) can predict Ki-67 in pancreatic ductal adenocarcinoma (PDAC). • The DECT-Radiology model facilitates preoperative and non-invasive assessment of PDAC Ki-67 expression. • The nomogram may help screen out PDAC patients with high Ki-67 expression.

Human chorionic gonadotropin ß induces cell motility via ERK1/2 and MMP-2 activation in human glioblastoma U87MG cells.

Human chorionic gonadotropin ß (hCGß) promotes tumorigenesis in a variety of tumors including glioblastoma, breast and prostate cancer cells, etc. However, the involved mechanisms remain elusive. Distinct from the other tumors, glioblastoma is a highly invasive brain tumor; invasion causes high recurrence and mortality. Characterization of hCGß signaling is to determine therapeutic targets to inhibit invasion and lower recurrence. Through both a stable cell line over-expressing hCGß and hCGß standards, we tested hCGß signaling, migration and invasion in human glioblastoma U87MG cells. ELISA showed that hCGß secreted into culture medium at an amount of 237.8 ± 7.8 ng/10(7) cells in hCGß transfected stable cells after the cells were grown for 24 h. Through Western blot and Gelatin zymography, we found that hCGß standards phosphorylated ERK1/2 and upregulated MMP-2 expression in dose- and time-dependent manners. Meanwhile, overexpressed hCGß phosphorylated ERK1/2, and upregulated MMP-2 expression and activity, whereas ERK1/2 blocker PD98059 (25 µM) significantly decreased both ERK1/2 and MMP-2 expression and activity. In addition, in the same conditions as the signaling test, hCGß promoted cell migration and invasion, whereas the PD98059 diminished these effects. These findings demonstrated that hCGß phosphorylated ERK1/2 upregulating MMP-2 expression and activity leading to cell migration and invasion, suggesting that hCGß, ERK1/2 and MMP-2 are the potential targets to inhibit glioblastoma invasion.

Preparation, properties and applications of two-dimensional superlattices.

As a combination concept of a 2D material and a superlattice, two-dimensional superlattices (2DSs) have attracted increasing attention recently. The natural advantages of 2D materials in their properties, dimension, diversity and compatibility, and their gradually improved technologies for preparation and device fabrication serve as solid foundations for the development of 2DSs. Compared with the existing 2D materials and even their heterostructures, 2DSs relate to more materials and elaborate architectures, leading to novel systems with more degrees of freedom to modulate material properties at the nanoscale. Here, three typical types of 2DSs, including the component, strain-induced and moiré superlattices, are reviewed. The preparation methods, properties and state-of-the-art applications of each type are summarized. An outlook of the challenges and future developments is also presented. We hope that this work can provide a reference for the development of 2DS-related research.

Nomogram based on spectral CT quantitative parameters and typical radiological features for distinguishing benign from malignant thyroid micro-nodules.

PURPOSE: To analyse the predictive effect of a nomogram combining dual-layer spectral computed tomography (DSCT) quantitative parameters with typical radiological features in distinguishing benign micro-nodule from thyroid microcarcinoma (TMC). METHODS: Data from 342 instances with thyroid micro-nodules (≤1 cm) who underwent DSCT (benign group: n = 170; malignant group: n = 172) were reviewed. Typical radiological features including micro-calcification and enhanced blurring, and DSCT quantitative parameters including attenuation on virtual monoenergetic images (40 keV, 70 keV and 100 keV), the slope of the spectral HU curve (λHU), normalized iodine concentration (NIC), and normalized effective atomic number (NZeff) in the arterial phase (AP) and venous phase (VP), were measured and compared between the benign and malignant groups. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of significant quantitative DSCT parameters or the models combining DSCT parameters respectively and typical radiological features based on multivariate logistic regression (LR) analysis. A nomogram was developed using predictors with the highest diagnostic performance in the above model, as determined by multivariate LR analysis. RESULTS: The DSCT parameter APλHU showed the greatest diagnostic efficiency in identifying patients with TMC, with an area under the ROC curve (AUC) of 0.829, a sensitivity and specificity of 0.738 and 0.753, respectively. Then, APλHU was combined with the two radiological features to construct the DSCT-Radiological nomogram, which had an AUC of 0.858, a sensitivity of 0.791 and a specificity of 0.800. The calibration curve of the nomogram demonstrated that the prediction result was in good agreement with the actual observation. The decision curve revealed that the nomogram can result in a greater net benefit than the all/none-intervention strategy for all threshold probabilities. CONCLUSION: As a valid and visual noninvasive prediction tool, the DSCT-Radiological nomogram incorporating DSCT quantitative parameters and radiological features shows favourable predictive efficiency for identifying benign and malignant thyroid micro-nodules.

Diagnostic accuracy of dual-energy computed tomography-based nomogram for differentiating papillary thyroid microcarcinomas from micronodular goiters.

Background: The misdiagnosis of papillary thyroid microcarcinoma (PTMC) and micronodular goiter (MNG) may lead to overtreatment and unnecessary medical expenditure by patients. This study developed and validated a dual-energy computed tomography (DECT)-based nomogram for the preoperative differential diagnosis of PTMC and MNG. Methods: This retrospective study analyzed the data of 366 pathologically confirmed thyroid micronodules, of which 183 were PTMCs and 183 were MNGs, from 326 patients who underwent DECT examinations. The cohort was divided into the training (n=256) and validation cohorts (n=110). The conventional radiological features and DECT quantitative parameters were analyzed. The iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number, normalized effective atomic number, and slope of the spectral attenuation curves in the arterial phase (AP) and venous phase (VP) were measured. A univariate analysis and stepwise logistic regression analysis were performed to screen the independent indicators for PTMC. A radiological model, DECT model, and DECT-radiological nomogram were constructed, and the performances of the 3 models were assessed using the receiver operating characteristic curve, DeLong test, and a decision curve analysis (DCA). Results: The IC in the AP [odds ratio (OR) =0.172], NIC in the AP (OR =0.003), punctate calcification (OR =2.163), and enhanced blurring (OR =3.188) were identified as independent predictors in the stepwise-logistic regression. The areas under the curve with 95% confidence intervals (CIs) of the radiological model, DECT model, and DECT-radiological nomogram were 0.661 (95% CI: 0.595-0.728), 0.856 (95% CI: 0.810-0.902), and 0.880 (95% CI: 0.839-0.921), respectively, in the training cohort; and 0.701 (95% CI: 0.601-0.800), 0.791 (95% CI: 0.704-0.877), and 0.836 (95% CI: 0.760-0.911), respectively, in the validation cohort. The diagnostic performance of the DECT-radiological nomogram was better than that of the radiological model (P<0.05). The DECT-radiological nomogram was found to be well calibrated and had a good net benefit. Conclusions: DECT provides valuable information for differentiating between PTMC and MNG. The DECT-radiological nomogram could serve as an easy-to-use, noninvasive, and effective method for differentiating between PTMC and MNG and help clinicians in decision-making.

Silica nanoparticles suppress fibronectin-mediated adhesion and migration in normal human keratinocytes.

Nanotechnology has been increasingly applied to various fields, such as biology, chemistry, physics, medicine and engineering. However, a major concern that has been the topic in nanoscience is whether exposure of humans to engineered nanoparticles might cause toxic effects. In the present in vitro study, the influence of silica nanoparticles on fibronectin-mediated cellular response was assessed in normal human keratinocytes. Our results demonstrated that silica nanoparticles but not silica microparticles significantly suppressed cell adhesion and migration to fibronectin. This phenomenon was not observed in cell response to Poly-L-Lysine, which mediates cell adhesion and migration in a way different from that of fibronectin. Moreover, it seemed that this suppression was not due to cytotoxic effects induced by silica nanoparticles. Subsequently, we also showed that silica nanoparticles impaired the fibronectin-induced activation of FAK and its downstream PI3K, AKT and Src. Taken together, our data suggests that silica nanoparticles may negatively modulate cell response to fibronectin.

Feasibility of a CT-based lymph node radiomics nomogram in detecting lymph node metastasis in PDAC patients.

Objectives: To investigate the potential value of a contrast enhanced computed tomography (CECT)-based radiological-radiomics nomogram combining a lymph node (LN) radiomics signature and LNs' radiological features for preoperative detection of LN metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). Materials and methods: In this retrospective study, 196 LNs in 61 PDAC patients were enrolled and divided into the training (137 LNs) and validation (59 LNs) cohorts. Radiomic features were extracted from portal venous phase images of LNs. The least absolute shrinkage and selection operator (LASSO) regression algorithm with 10-fold cross-validation was used to select optimal features to determine the radiomics score (Rad-score). The radiological-radiomics nomogram was developed by using significant predictors of LN metastasis by multivariate logistic regression (LR) analysis in the training cohort and validated in the validation cohort independently. Its diagnostic performance was assessed by receiver operating characteristic curve (ROC), decision curve (DCA) and calibration curve analyses. Results: The radiological model, including LN size, and margin and enhancement pattern (three significant predictors), exhibited areas under the curves (AUCs) of 0.831 and 0.756 in the training and validation cohorts, respectively. Nine radiomic features were used to construct a radiomics model, which showed AUCs of 0.879 and 0.804 in the training and validation cohorts, respectively. The radiological-radiomics nomogram, which incorporated the LN Rad-score and the three LNs' radiological features, performed better than the Rad-score and radiological models individually, with AUCs of 0.937 and 0.851 in the training and validation cohorts, respectively. Calibration curve analysis and DCA revealed that the radiological-radiomics nomogram showed satisfactory consistency and the highest net benefit for preoperative diagnosis of LN metastasis. Conclusions: The CT-based LN radiological-radiomics nomogram may serve as a valid and convenient computer-aided tool for personalized risk assessment of LN metastasis and help clinicians make appropriate clinical decisions for PADC patients.

Experimental Study on Mechanical Properties of the Sandwich Composite Structure Reinforced by Basalt Fiber and Nomex Honeycomb.

The new sandwich composite structure formed by basalt fiber resin-based sheets and Nomex honeycomb has the advantages of being lightweight and environmentally friendly, as well as having excellent electromagnetic performance. It has very important application prospects in traditional and emerging fields. In this paper, the mechanical properties of this new sandwich composite structure are studied. The results show that, under the condition of flatwise compression, increasing the height of the honeycomb is conducive to improving the compressive capacity of the structure. However, the height should be controlled within a certain range in case of instability and yield of the honeycomb; under the bending conditions, the bending failure mode of the composite structure has gone through five stages. Owing to the honeycomb manufacturing process, the orientation of the honeycomb also has a great influence on the bending strength of the structure. After further analysis, it is found that basalt fiber sheets contribute the most to the bending stiffness of the structure, and the main role of honeycomb is to provide out-of-plane support. In both cases, the failure of specimens is ductile, and the combined structure still has a small amount of bearing capacity and maintains structural integrity. Research on this new type of composite structural material is very beneficial for promoting the application and development of green and lightweight special functional materials.

Recent Advances in the Fabrication and Application of Graphene Microfluidic Sensors.

This review reports the progress of the recent development of graphene-based microfluidic sensors. The introduction of microfluidics technology provides an important possibility for the advance of graphene biosensor devices for a broad series of applications including clinical diagnosis, biological detection, health, and environment monitoring. Compared with traditional (optical, electrochemical, and biological) sensing systems, the combination of graphene and microfluidics produces many advantages, such as achieving miniaturization, decreasing the response time and consumption of chemicals, improving the reproducibility and sensitivity of devices. This article reviews the latest research progress of graphene microfluidic sensors in the fields of electrochemistry, optics, and biology. Here, the latest development trends of graphene-based microfluidic sensors as a new generation of detection tools in material preparation, device assembly, and chip materials are summarized. Special emphasis is placed on the working principles and applications of graphene-based microfluidic biosensors, especially in the detection of nucleic acid molecules, protein molecules, and bacterial cells. This article also discusses the challenges and prospects of graphene microfluidic biosensors.

Broadband and Ultrasensitive Graphene-Based Mechanical Wave Detector with Nanosecond Response Used for Biological Photoacoustic Imaging.

Achieving broadband and sensitive mechanical wave detection with fast time response remains a great challenge. Here, we exploited the polarization-sensitive absorption characteristics and ultrafast photoelectric response of graphene to construct a broadband and ultrasensitive detector with a nanosecond response for mechanical wave detection. The unprecedented performance of the graphene-based detector allowed us to detect high-frequency mechanical waves over 100 MHz with a detection limit of 0.18 kPa. Moreover, we applied the detector in high-contrast photoacoustic imaging of human hairs and a mouse hindlimb to demonstrate its capability in detection of photoacoustic waves. This device could also find application in other areas such as THz detection and modulation.

[Development and verification of an FLP/FRT system for gene editing in Bacillus licheniformis].

Few tools of gene editing have been developed in Bacillus licheniformis at present. In order to enrich the tools, an FLP/FRT gene editing system that can repeatedly use a single selectable marker was constructed in Bacillus licheniformis, and the system was verified by knocking out an alpha amylase gene (amyL), an protease gene (aprE) and knocking in an exogenous Vitreoscilla hemoglobin gene (vgb). First, knock-out plasmids pNZTT-AFKF of amyL and pNZTT-EFKF of aprE were constructed using thermosensitive plasmid pNZT1 as a carrier. The two knock-out plasmids contained respective homology arms, resistance genes and FRT sites. Then the knock-out plasmids were transformed into Bacillus licheniformis and the target genes were replaced by respective deletion cassette via twice homologous exchange. Finally, an expression plasmid containing FLP recombinase reading frane was introduced and mediated the excision of resistance marker. In order to expand the practicability of the system, knock-in plasmid pNZTK-PFTF-vgb was constructed, with which knock-in of vgb at pflB site was carried out successfully. The results showed that amyL and aprE were successfully knocked out and the marker kanamycin cassette exactly excised. The activities of amylase and protease of deletion mutants were reduced by 95.3% and 80.4% respectively. vgb was successfully knocked in at pflB site and the marker tetracycline cassette excised. The expression of integrated vgb was verified via real-time PCR. It is the first time to construct an FLP/FRT system for gene editing in Bacillus licheniformis, which could provide an effective technical means for genetic modification.