Large detection range and high strain sensitivity fiber SPR sensor based on wave structure.

To achieve a fiber strain sensor with a large detection range and high sensitivity, this paper proposes a wave structured fiber SPR strain sensor. When subjected to axial strain, the wave structured fiber is stretched axially, increasing the stretchability of the sensor and achieving a large detection range strain sensing. Meanwhile, axial strain reduces the longitudinal amplitude of the fiber wave structure, effectively changing the total reflection angle of the transmitted beam at the peak and valley (SPR incidence angle) to achieve high sensitivity SPR strain sensing. The experiment indicates that the strain detection range of the sensor can reach 0-1800µÎµ, with a maximum strain sensitivity of 36.25pm/µÎµ. The wave structured fiber SPR strain sensor designed in this article provides a new approach to improve the range and sensitivity of strain detection.

High sensitivity fiber cladding SPR strain sensor based on V-groove structure.

How to couple the light in the fiber core to the cladding is an urgent issue that need to be done for the fabrication of the fiber-cladding SPR sensor, and there is no report about the fiber SPR strain sensor. Hereby, we propose and demonstrate a high sensitivity fiber cladding SPR strain sensor based on V-groove structure. By CO2 laser, the V-groove is fabricated on the single-mode fiber, and the light in the fiber core is effectively coupled to the cladding. The cladding 2cm behind the V-groove is coated with sensing gold film, and a multimode fiber is spliced with the sensing probe to construct the novel fiber cladding SPR sensor. On the basis of the investigation of the effects of different V-groove depth, number and period on the performance of fiber SPR refractive index sensor, a high sensitivity strain SPR sensor is designed and fabricated by employing the characteristic that the V-groove will deform with strain. The testing results indicate that the average refractive index sensitivity of the sensor is 2896.4nm/RIU, and the strain wavelength sensitivity is 25.92pm/µÎµ which is much higher than that of the fiber interference and grating strain sensors, and the strain light intensity sensitivity is -4.4×10-4 a.u./µÎµ. The proposed fiber cladding SPR strain sensor has the advantages of simple structure and convenient manufacture, and can be used for working in a narrow space.

Fiber SPR two-dimensional micro displacement sensor based on the coaxial double waveguide with a conical structure.

Fiber SPR micro displacement sensor cannot be used for two-dimensional displacement sensing at present. In this paper, we proposed and demonstrated a fiber SPR two-dimensional micro displacement sensor based on the coaxial double waveguide with a conical structure. The coaxial double waveguide is fused into a cone as the light injection fiber, and two different forms of outgoing light fields can be obtained through two cores of the fiber. The horn shaped light field emitted by the ring core of the coaxial double waveguide can cooperate with the sensing fiber to realize the micro displacement sensing in the x-axis direction. And the straight beam emitted by the middle core of the coaxial double waveguide can cooperate with the sensing fiber to realize the micro displacement sensing in the y-axis direction. Through simulation analysis and experimental test, its average wavelength sensitivity and light intensity sensitivity of the x-axis displacement are 0.0537nm/µm and 0.000124a.u./µm, respectively. And that of the y-axis displacement are 0.315nm/µm and 0.00277a.u./µm, respectively. The proposed fiber sensor realizes the two-dimensional displacement sensing based on SPR, which can be widely used in the fields of two-dimensional micro displacement measurement and two-dimensional position precision positioning.

Prediction of long-term mortality by using machine learning models in Chinese patients with connective tissue disease-associated interstitial lung disease.

BACKGROUND: The exact risk assessment is crucial for the management of connective tissue disease-associated interstitial lung disease (CTD-ILD) patients. In the present study, we develop a nomogram to predict 3­ and 5-year mortality by using machine learning approach and test the ILD-GAP model in Chinese CTD-ILD patients. METHODS: CTD-ILD patients who were diagnosed and treated at the First Affiliated Hospital of Zhengzhou University were enrolled based on a prior well-designed criterion between February 2011 and July 2018. Cox regression with the least absolute shrinkage and selection operator (LASSO) was used to screen out the predictors and generate a nomogram. Internal validation was performed using bootstrap resampling. Then, the nomogram and ILD-GAP model were assessed via likelihood ratio testing, Harrell's C index, integrated discrimination improvement (IDI), the net reclassification improvement (NRI) and decision curve analysis. RESULTS: A total of 675 consecutive CTD-ILD patients were enrolled in this study, during the median follow-up period of 50 (interquartile range, 38-65) months, 158 patients died (mortality rate 23.4%). After feature selection, 9 variables were identified: age, rheumatoid arthritis, lung diffusing capacity for carbon monoxide, right ventricular diameter, right atrial area, honeycombing, immunosuppressive agents, aspartate transaminase and albumin. A predictive nomogram was generated by integrating these variables, which provided better mortality estimates than ILD-GAP model based on the likelihood ratio testing, Harrell's C index (0.767 and 0.652 respectively) and calibration plots. Application of the nomogram resulted in an improved IDI (3- and 5-year, 0.137 and 0.136 respectively) and NRI (3- and 5-year, 0.294 and 0.325 respectively) compared with ILD-GAP model. In addition, the nomogram was more clinically useful revealed by decision curve analysis. CONCLUSIONS: The results from our study prove that the ILD-GAP model may exhibit an inapplicable role in predicting mortality risk in Chinese CTD-ILD patients. The nomogram we developed performed well in predicting 3­ and 5-year mortality risk of Chinese CTD-ILD patients, but further studies and external validation will be required to determine the clinical usefulness of the nomogram.

Bioinformatic analysis and preliminary validation of potential therapeutic targets for COVID-19 infection in asthma patients.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 causes coronavirus disease 19 (COVID-19). The number of confirmed cases of COVID-19 is also rapidly increasing worldwide, posing a significant challenge to human safety. Asthma is a risk factor for COVID-19, but the underlying molecular mechanisms of the asthma-COVID-19 interaction remain unclear. METHODS: We used transcriptome analysis to discover molecular biomarkers common to asthma and COVID-19. Gene Expression Omnibus database RNA-seq datasets (GSE195599 and GSE196822) were used to identify differentially expressed genes (DEGs) in asthma and COVID-19 patients. After intersecting the differentially expressed mRNAs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to identify the common pathogenic molecular mechanism. Bioinformatic methods were used to construct protein-protein interaction (PPI) networks and identify key genes from the networks. An online database was used to predict interactions between transcription factors and key genes. The differentially expressed long noncoding RNAs (lncRNAs) in the GSE195599 and GSE196822 datasets were intersected to construct a competing endogenous RNA (ceRNA) regulatory network. Interaction networks were constructed for key genes with RNA-binding proteins (RBPs) and oxidative stress-related proteins. The diagnostic efficacy of key genes in COVID-19 was verified with the GSE171110 dataset. The differential expression of key genes in asthma was verified with the GSE69683 dataset. An asthma cell model was established with interleukins (IL-4, IL-13 and IL-17A) and transfected with siRNA-CXCR1. The role of CXCR1 in asthma development was preliminarily confirmed. RESULTS: By intersecting the differentially expressed genes for COVID-19 and asthma, 393 common DEGs were obtained. GO and KEGG enrichment analyses of the DEGs showed that they mainly affected inflammation-, cytokine- and immune-related functions and inflammation-related signaling pathways. By analyzing the PPI network, we obtained 10 key genes: TLR4, TLR2, MMP9, EGF, HCK, FCGR2A, SELP, NFKBIA, CXCR1, and SELL. By intersecting the differentially expressed lncRNAs for COVID-19 and asthma, 13 common differentially expressed lncRNAs were obtained. LncRNAs that regulated microRNAs (miRNAs) were mainly concentrated in intercellular signal transduction, apoptosis, immunity and other related functional pathways. The ceRNA network suggested that there were a variety of regulatory miRNAs and lncRNAs upstream of the key genes. The key genes could also bind a variety of RBPs and oxidative stress-related genes. The key genes also had good diagnostic value in the verification set. In the validation set, the expression of key genes was statistically significant in both the COVID-19 group and the asthma group compared with the healthy control group. CXCR1 expression was upregulated in asthma cell models, and interference with CXCR1 expression significantly reduced cell viability. CONCLUSIONS: Key genes may become diagnostic and predictive biomarkers of outcomes in COVID-19 and asthma. Video Abstract.

Single-mode fiber curvature sensor based on SPR.

A fiber surface plasmon resonance (SPR) sensor is widely used in high-sensitivity refractive index measurement, but there is less research on curvature measurement. In this paper, a single-mode fiber curvature sensor based on SPR is designed and fabricated. By employing bending, the transmitted light in the fiber core leaks into the cladding. A 50 nm gold film is coated outside the cladding, and the evanescent field of the cladding after bending contacts the gold film to cause SPR. When the curvature changes, the coupled cladding mode and intensity are different; that is, the SPR incident angle and evanescent field intensity are different, so as to realize the dual parameters of SPR resonance wavelength and depth of the resonance valley changing with curvature. By experiments, the influence of different cutoff wavelengths of single-mode fiber on the performance of the sensor is studied. The testing results indicate that with the decrease in cutoff wavelength of the single-mode fiber, the valley depth sensitivity of the sensor increases, and the half height width (FWHM) decreases. When the cutoff wavelength of the single-mode fiber is 630 nm, the valley depth sensitivity of the sensor is 0.0088a.u/m-1, the wavelength sensitivity is 0.26nm/m-1, and the average FWHM is only 21 nm. The proposed single-mode fiber curvature sensor based on SPR has a narrow FWHM and an opening threshold. It can also realize no opening threshold by introducing a coreless fiber, which provides a new solution, to the best of our knowledge, for the diversified detection of fiber SPR sensors.

Use of machine learning models to predict prognosis of combined pulmonary fibrosis and emphysema in a Chinese population.

BACKGROUND: Combined pulmonary fibrosis and emphysema (CPFE) is a novel clinical entity with a poor prognosis. This study aimed to develop a clinical nomogram model to predict the 1-, 2- and 3-year mortality of patients with CPFE by using the machine learning approach, and to validate the predictive ability of the interstitial lung disease-gender-age-lung physiology (ILD-GAP) model in CPFE. METHODS: The data of CPFE patients from January 2015 to October 2021 who met the inclusion criteria were retrospectively collected. We utilized LASSO regression and multivariable Cox regression analysis to identify the variables associated with the prognosis of CPFE and generate a nomogram. The Harrell's C index, the calibration curve and the area under the receiver operating characteristic (ROC) curve (AUC) were used to evaluate the performance of the nomogram. Then, we performed likelihood ratio test, net reclassification improvement (NRI), integrated discrimination improvement (IDI) and decision curve analysis (DCA) to compare the performance of the nomogram with that of the ILD-GAP model. RESULTS: A total of 184 patients with CPFE were enrolled. During the follow-up, 90 patients died. After screening out, diffusing lung capacity for carbon monoxide (DLCO), right ventricular diameter (RVD), C-reactive protein (CRP), and globulin were found to be associated with the prognosis of CPFE. The nomogram was then developed by incorporating the above five variables, and it showed a good performance, with a Harrell's C index of 0.757 and an AUC of 0.800 (95% CI 0.736-0.863). Moreover, the calibration plot of the nomogram showed good concordance between the prediction probabilities and the actual observations. The nomogram also improved the discrimination ability of the ILD-GAP model compared to that of the ILD-GAP model alone, and this was substantiated by the likelihood ratio test, NRI and IDI. The significant clinical utility of the nomogram was demonstrated by DCA. CONCLUSION: Age, DLCO, RVD, CRP and globulin were identified as being significantly associated with the prognosis of CPFE in our cohort. The nomogram incorporating the 5 variables showed good performance in predicting the mortality of CPFE. In addition, although the nomogram was superior to the ILD-GAP model in the present cohort, further validation is needed to determine the clinical utility of the nomogram.

Laser Curve Extraction of Wheelset Based on Deep Learning Skeleton Extraction Network.

In this paper, a new algorithm for extracting the laser fringe center is proposed. Based on a deep learning skeleton extraction network, the laser stripe center can be extracted quickly and accurately. Skeleton extraction is the process of reducing the shape image to its approximate central axis representation while maintaining the image's topological and geometric shape. Skeleton extraction is an important step in topological and geometric shape analysis. According to the characteristics of the wheelset laser curve dataset, a new skeleton extraction network, a hierarchical skeleton network (LuoNet), is proposed. The proposed architecture has three levels of the encoder-decoder network, and YE Module interconnection is designed between each level of the encoder and decoder network. In the wheelset laser curve dataset, the F1_score can reach 0.714. Compared with the traditional laser curve center extraction algorithm, the proposed LuoNet algorithm has the advantages of short running time, high accuracy, and stable extraction results.

Laser curve extraction of a train wheelset based on an encoder-decoder network.

An algorithm of laser curve segmentation for a train wheelset based on an encoder- decoder network is proposed. Aiming at the rich local features and simple semantic features of the train wheelset laser curve image, a neural network with shallow depth, high resolution, and good detail performance was designed. The proposed neural network makes full use of the dense connection mechanism and the upsampling module to enhance feature reuse and feature propagation. It can extract context semantic information at multiple scales with fewer parameters. Experimental results show that the encoder-decoder network has better performance than other neural networks in laser curve extraction of train wheelset. Based on the encoder-decoder neural network, mIOU, Recall, Accuracy, and F1_score of the laser curve dataset of the train wheelset, the score index reached 86.5%, 89.2%, 99.9%, and 85.0%, which can accurately extract the laser stripe of the train wheelset. Additionally, the encoder-decoder network can diminish the influence of noise on the extraction of laser fringes of a train wheelset to a certain extent. Therefore, it has good application in railway safety.

Hypoxia-induced autophagy activation through NF-κB pathway regulates cell proliferation and migration to induce pulmonary vascular remodeling.

OBJECTIVES: This study aimed to investigate whether autophagy mediated cell proliferation and migration of pulmonary arterial smooth muscle cells (PASMCs) under hypoxia and to validate the underlying mechanism. METHODS: The rat model of chronic hypoxia-induced pulmonary vascular remodeling was established. Rat primary PASMCs were isolated and cultured in vitro in hypoxia or normoxia to explore the underlying mechanism. RESULTS: Hypoxia exposure for 21 days induced pulmonary vascular remodeling in rats, accompanied by enhanced proliferation and decreased apoptosis, as well as induced expression of autophagic marker LC3II in their lungs. Furthermore, in vitro assays revealed that hypoxia exposure significantly promoted cell proliferation and migration, but inhibited apoptosis of PASMCs compared with normoxia treatment. Besides, hypoxia exposure led to an increase of cell fractions in S phase and a decrease in G0/G1 of PASMCs, whereas had no significant effect on cell population in G2/M phase. Moreover, the autophagy inhibitor 3-MA significantly decreased the hypoxia-induced upregulated expression of LC3II in PASMCs and abrogated the effect of hypoxia on cell proliferation, cell apoptosis, cell cycle, and cell migration of PASMCs. Additionally, inhibition of NF-κB pathway by PDTC suppressed the hypoxia-induced upregulation of NF-κB activity, LC3II, and cell cycle regulators (cyclin D1, CDK4, and CDK6) in PASMCs, and abolished the hypoxia-mediated regulation of cell proliferation, apoptosis, cycle, and migration of PASMCs. CONCLUSION: In summary, hypoxia could induce autophagy activation through NF-κB pathway, and thereby regulate cell proliferation and migration to induce pulmonary vascular remodeling.

Knockdown of LncRNA MALAT1 contributes to the suppression of inflammatory responses by up-regulating miR-146a in LPS-induced acute lung injury.

BACKGROUND: Acute lung injury (ALI) is a type of severe pulmonary inflammatory disease with high rates of morbidity and mortality. Now, an increasing number of studies suggest that lncRNAs may act as key regulators of the inflammatory response and play a crucial role in the pathogenesis of many inflammatory diseases. Our study firstly explored the function and underlying mechanism of lncRNA metastasis-associated lung adenocarcinoma transcription 1 (MALAT1) in regulating the inflammatory response of lipopolysaccharide (LPS)-induced ALI in rats. METHODS: The ALI rats were constructed by intratracheal instillation with LPS. Hematoxylin and eosin (HE) for histological examination were performed to detect histopathological changes in the lung tissues. Enzyme-linked immunosorbent assay (ELISA) was used to determine the concentrations of cytokines TNF-α, IL-6, and IL-1ß in the supernatants of the bronchoalveolar lavage fluid (BALF). Quantitative real-time PCR (qRT-PCR) analysis was employed to assess the expression of MALAT1, miR-146a, TNF-α, IL-6, and IL-1ß in lung tissues. Luciferase reporter assay and RNA immunoprecipitation (RIP) assay were used to detect the relationship between MALAT1 and miR-146a. RESULTS: The results revealed that MALAT1 knockdown played a protective role in the LPS-induced ALI rat model. In addition, knockdown of MALAT1 in vitro inhibited LPS-induced inflammatory response in murine alveolar macrophages cell line MH-S and murine alveolar epithelial cell line MLE-12. This study found that MALAT1 acts as a molecular sponge for miR-146a and MALAT1 negatively regulated miR-146a expression. Mechanistically, MALAT1 overexpression alleviated the inhibitory effect of miR-146a on LPS-induced inflammatory response in MH-S. CONCLUSIONS: Together, our study provided the first evidence that MALAT1 knockdown could suppress inflammatory response by up-regulating miR-146a in LPS-induced ALI, which provided a potential therapeutic target for the treatment of ALI.

[Influencing factors of anxiety and depression in asthmatics].

OBJECTIVE: To explore the major influencing factors for asthmatics with anxiety and depression. METHODS: A total of 176 physician-diagnosed asthmatics were confirmed from March 2011 to March 2012 at First Affiliated Hospital of Zhengzhou University. And 144 were finally screened to examine their demographic characteristics and clinical features. Their status of anxiety and depression and the levels of control were evaluated with the scores of self-rating anxiety scale (SAS), self-rating depressive scale (SDS) and asthma control test (ACT). Firstly, asthma with anxiety and asthma with depression as a dependent variable, general demographics and clinical characteristics as independent variables, single-factor analysis revealed the relevant factors of asthma with anxiety and depression; secondly, multi-variable Logistic regression analysis was performed to examine the major influencing factors of anxiety and depression in asthmatics based on the relevant factors as independent variables. RESULTS: Multiple variables Logistic regression showed that residing place (rural vs city/town, OR = 0.28); control levels (partly controlled vs uncontrolled, OR = 0.22; control vs non-control, OR = 0.10); severity (secondary vs first level, OR = 1.42; third vs first level, OR = 2.32; forth vs first level, OR = 3.12) were the major influencing factors of anxiety (all P < 0.05). Meanwhile, age (31-45 vs ≤ 30 years, OR = 11.35; >45 vs ≤ 30 years, OR = 18.73); level of education (junior high vs primary school and below, OR = 3.30; high/secondary vs primary school and below, OR = 3.52; college and above vs primary school and below, OR = 3.60), medical history (1-3 years vs <1 year, OR = 2.68; >3 years vs <1 year, OR = 3.01); control levels (partial control vs uncontrolled, OR = 0.25; controlled vs uncontrol, OR = 0.18) were the major influencing factors of depression (all P < 0.05). CONCLUSIONS: Rural dwelling, poorly controlled and severe asthmatics are more likely to associate with anxiety. And depression moods are more common in those with an elder age, a long course of disease, higher education and poor control.

Photooxidation triggered ultralong afterglow in carbon nanodots.

It remains a challenge to obtain biocompatible afterglow materials with long emission wavelengths, durable lifetimes, and good water solubility. Herein we develop a photooxidation strategy to construct near-infrared afterglow carbon nanodots with an extra-long lifetime of up to 5.9 h, comparable to that of the well-known rare-earth or organic long-persistent luminescent materials. Intriguingly, size-dependent afterglow lifetime evolution from 3.4 to 5.9 h has been observed from the carbon nanodots systems in aqueous solution. With structural/ultrafast dynamics analysis and density functional theory simulations, we reveal that the persistent luminescence in carbon nanodots is activated by a photooxidation-induced dioxetane intermediate, which can slowly release and convert energy into luminous emission via the steric hindrance effect of nanoparticles. With the persistent near-infrared luminescence, tissue penetration depth of 20 mm can be achieved. Thanks to the high signal-to-background ratio, biological safety and cancer-specific targeting ability of carbon nanodots, ultralong-afterglow guided surgery has been successfully performed on mice model to remove tumor tissues accurately, demonstrating potential clinical applications. These results may facilitate the development of long-lasting luminescent materials for precision tumor resection.

[Detection of anxiety and depression status of BALB/c asthmatic mice model].

OBJECTIVE: To detect the anxiety and depression status of BALB/c asthmatic model in mice. METHODS: A total of 20 mice were randomly divided into asthma and control groups (n = 10 each). The animals were sensitized and challenged with ovalbumin for asthmatic model. Phosphate buffer solution was used in the control group. The mice were challenged with increasing concentrations of methacholine aerosol and the airway resistance was measuring non-invasively by enhanced pause (Penh). And elevated plus maze test system and forced swim were employed to evaluate their anxiety and depression status. Then bronchoalveolar lavage cytology was detected for evaluating the airway inflammation. RESULTS: In both groups, Penh value increased with the rising concentration of methacholine. The Penh values of asthmatic mice exciting with normal saline and methacholine concentration of 0, 5 g/L were 0.43 ± 0.04, 0.41 ± 0.05 and 0.44 ± 0.04 versus 0.42 ± 0.03, 0.39 ± 0.03,0.43 ± 0.04 in control group. The difference had no statistical significance (P = 0.290,0.652,0.723). At the concentration of methacholine 10, 15, 20 g/L, the Penh values of asthmatic mice were 0.57 ± 0.03,0.85 ± 0.04, 1.57 ± 0.08 and they were significantly higher than those of control group (0.45 ± 0.08,0.57 ± 0.06,0.82 ± 0.09) (P = 0.001,0.000,0.000). Asthmatic mice in the elevated plus maze on a behavioral test and found that asthmatic mice open arm entries sum closed arm entries (OE+CE), percent of open arm/total entries (OE%) and percent of open arm/total time (OT%) was (18.3 ± 3.6) times, (22.2 ± 3.1)%, (16.7 ± 4.2)%. They were significantly lower than those of control group ((24.0 ± 2.9) times,(28.0 ± 3.4)%, (21.8 ± 4.6)%) (P = 0.001,0.001,0.019). Asthmatic mice swimming time was significantly higher than that of control group (147 ± 12) vs (133 ± 10) s (P = 0.010). The total number of cells and eosinophil ratio in asthma group was (10.0 ± 4.0)×10(5)/ml and (68.18 ± 3.76)%. And they were significantly larger than those of control group ((1.7 ± 0.4)× 10(5)/ml, (0.12 ± 0.07)%) (both P = 0.000). CONCLUSION: Asthmatic mice with concurrent anxiety and depression may be a model for elucidating the molecular mechanisms of asthma with anxiety and depression.

Metal-Halide Perovskite Nanocrystal Superlattice: Self-Assembly and Optical Fingerprints.

Self-assembly of nanocrystals into superlattices is a fascinating process that not only changes geometric morphology, but also creates unique properties that considerably enrich the material toolbox for new applications. Numerous studies have driven the blossoming of superlattices from various aspects. These include precise control of size and morphology, enhancement of properties, exploitation of functions, and integration of the material into miniature devices. The effective synthesis of metal-halide perovskite nanocrystals has advanced research on self-assembly of building blocks into micrometer-sized superlattices. More importantly, these materials exhibit abundant optical features, including highly coherent superfluorescence, amplified spontaneous laser emission, and adjustable spectral redshift, facilitating basic research and state-of-the-art applications. This review summarizes recent advances in the field of metal-halide perovskite superlattices. It begins with basic packing models and introduces various stacking configurations of superlattices. The potential of multiple capping ligands is also discussed and their crucial role in superlattice growth is highlighted, followed by detailed reviews of synthesis and characterization methods. How these optical features can be distinguished and present contemporary applications is then considered. This review concludes with a list of unanswered questions and an outlook on their potential use in quantum computing and quantum communications to stimulate further research in this area.

Epidermal growth factor receptor in asthma: A promising therapeutic target?

Activation of the epidermal growth factor receptor (EGFR) pathway is involved in the pathogenesis of asthma. Although decades of intensive research have focused on the role of EGFR in asthma, the specific mechanisms and pathways of EGFR signaling remain unclear. Various reports have indicated that inhibition of EGFR improves the pathological features in asthma models. However, extending these experimental findings to clinical applications is difficult. Several measures can be adopted to promote clinical application of EGFR inhibitors. This review focuses on the role of EGFR in the pathogenesis of asthma and the development of a potentially novel therapeutic target for asthma.

Fiber SPR biosensor sensitized by MOFs for MUC1 protein detection.

The concentration of tumor markers is low, which needs a highly sensitive, stable and fast detection method. In this paper, we proposed and demonstrated a U-shape fiber SPR biosensor sensitized by MOFs materials. The surface of the U-shape SPR sensor was modified with MOFs materials to enhance the sensitivity, and the nucleic acid aptamer was immobilized on the sensor surface because of the biocompatibility of MOFs materials. By the high specificity of the nucleic acid aptamer, the MUC1 protein was recognized and detected. The testing results indicate that the sensor has a logarithmic linear response in the MUC1 protein concentration detection range of 1 pg/ml-100 µg/ml, its sensitivity and detection limit are 5.33 nm/log(µg/ml) and 0.16 pg/ml respectively. After being sensitized by MOFs, the detection sensitivity of the sensor can be increased by 1.62 times，the LOD can be decreased by 0.75 times. The sensor has high sensitivity and specificity, which has broad application prospects in clinical detection of tumor markers.

Multiphoton excited singlet/triplet mixed self-trapped exciton emission.

Multiphoton excited luminescence is of paramount importance in the field of optical detection and biological photonics. Self-trapped exciton (STE) emission with self-absorption-free advantages provide a choice for multiphoton excited luminescence. Herein, multiphoton excited singlet/triplet mixed STE emission with a large full width at half-maximum (617 meV) and Stokes shift (1.29 eV) has been demonstrated in single-crystalline ZnO nanocrystals. Temperature dependent steady state, transient state and time-resolved electron spin resonance spectra demonstrate a mixture of singlet (63%) and triplet (37%) mixed STE emission, which contributes to a high photoluminescence quantum yield (60.5%). First-principles calculations suggest 48.34 meV energy per exciton stored by phonons in the distorted lattice of excited states, and 58 meV singlet-triplet splitting energy for the nanocrystals being consistent with the experimental measurements. The model clarifies long and controversial debates on ZnO emission in visible region, and the multiphoton excited singlet/triplet mixed STE emission is also observed.

A novel O2- (2,4-dinitrophenyl) diazeniumdiolate inhibits hepatocellular carcinoma migration, invasion, and EMT through the Wnt/ß-catenin pathway.

Targeted Wnt/ß-catenin pathway is considered to be a promising therapy for cancer metastasis. The novel O2 -(2,4-dinitrophenyl) diazeniumdiolate (JS-K) plays a potent inhibitory role in the proliferation of cancers. In this study, HepG2 and SMMC7721 were used to clarify the efficacy of JS-K inhibition of HCC metastasis. JS-K significantly inhibited cell motility through a wound-healing assay and restrained cell migration and invasion at noncytotoxic concentrations. However, the inhibitory effects of migration and invasion were abolished after the addition of NO scavenger, Carboxy-PTIO. In addition, JS-K inhibited the Wnt/ß-catenin pathway by a decrease of p-GSK-3ß at Ser9, cytosolic ß-catenin, and nuclear ß-catenin accumulation whereas an increase of p-ß-catenin. Furthermore, the transcription regulators c-Myc, survivin, and Cyclin D1 were down-regulated after treating with JS-K. The inhibitory of the Wnt/ß-catenin pathway was reversed after the addition of Carboxy-PTIO or LiCl. Meanwhile, JS-K also inhibited the epithelial-mesenchymal transition (EMT)-mediated cell migration and invasion. The characteristics of the inhibition were reflected by the upregulation of E-cadherin whereas the downregulation of Vimentin, Snail, and Slug. Taking together, these results demonstrated that JS-K inhibited HepG2 and SMMC7721 cells migration and invasion by reversing EMT via the Wnt/ß-catenin pathway.

All-fiber biological detection microfluidic chip based on space division and wavelength division multiplexing technologies.

To further reduce the size of a microfluidic detection chip and the sample consumption and to shorten the chip manufacturing cycle, an all-fiber SPR detection multichannel microfluidic chip was proposed and demonstrated in this paper. The microfluidic channel of the proposed chip was provided by the air channel of a double side-hole fiber, the detection unit was fabricated using a dumbbell fiber with a fiber core exposed to air, and the sensing probe was composed and packaged by fiber micro-processing technology. The internal double channels of the fiber constructed from double side-hole and dumbbell fibers can realize dual channel detection based on space division multiplexing. 30 nm silver and 50 nm gold films were respectively coated on the left and right sides of the dumbbell fiber, which can realize the dual channel simultaneous detection based on wavelength division multiplexing. We employed the proposed microfluidic chip to detect immunoglobulin G and dopamine molecules, where the average sensitivity is 0.252 nm (mg mL-1)-1 and 0.061 nm (µg mL-1)-1, and the LOD is 0.397 mg mL-1 and 1.639 µg mL-1, respectively. The microfluidic channel and detection unit of all-fiber multi-channel SPR detection microfluidic chip are provided by a soft and flexible fiber, which is compact in structure, flexible in fabrication and short in manufacturing cycle, making it possible for the microfluidic chip to enter the human body for detection and enabling a new approach for the fabrication of wearable detection microfluidic devices. This provides a new idea for the development of microfluidic chips.