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Although the effect of the digital economy in promoting high-quality economic development is increasing day by day, research analysing this mechanism from the spatial perspective is very scarce. This study measures the level of the digital economy and high-quality economic development based on the panel data of 31 provinces in China from 2013 to 2020. On this basis, the direct, spillover, and mediating effects of the digital economy and scientific and technological innovation on high-quality economic development are further analysed through the spatial Durbin model and mediating effect model. The main conclusions are as follows: (1) the digital economy, scientific and technological innovation, and high-quality economic development all show significant spatial correlation; (2) the digital economy can directly drive high-quality economic development, the spillover effect of which is obvious; and (3) the mechanism analysis based on the spatial perspective shows that the mediating effect of scientific and technological innovation is significant. The conclusions still hold after robustness tests based on the use of lagged variables, replacement of the weight matrices, and changing of the measurement methods. This study provides theoretical support and empirical evidence for promoting the digital economy and high-quality economic development.

The diagnosis of gastric cancer mainly relies on endoscopy, which is invasive and costly. The aim of this study is to develop a predictive model for the diagnosis of gastric cancer based on noninvasive characteristics. To construct a predictive model for the diagnosis of gastric cancer with high accuracy based on noninvasive characteristics. A retrospective study of 709 patients at Zhejiang Provincial People's Hospital was conducted. Variables of age, gender, blood cell count, liver function, kidney function, blood lipids, tumor markers and pathological results were analyzed. We used gradient boosting decision tree (GBDT), a type of machine learning method, to construct a predictive model for the diagnosis of gastric cancer and evaluate the accuracy of the model. Of the 709 patients, 398 were diagnosed with gastric cancer; 311 were health people or diagnosed with benign gastric disease. Multivariate analysis showed that gender, age, neutrophil lymphocyte ratio, hemoglobin, albumin, carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125) and carbohydrate antigen 199 (CA199) were independent characteristics associated with gastric cancer. We constructed a predictive model using GBDT, and the area under the receiver operating characteristic curve (AUC) of the model was 91%. For the test dataset, sensitivity was 87.0% and specificity 84.1% at the optimal threshold value of 0.56. The overall accuracy was 83.0%. Positive and negative predictive values were 83.0% and 87.8%, respectively. We construct a predictive model to diagnose gastric cancer with high sensitivity and specificity. The model is noninvasive and may reduce the medical cost.

Traditional Chinese medicine (TCM) plays an important role in the global traditional health systems. However, adulterated and counterfeit TCM is on the rise. DNA barcoding is an effective, rapid, and accurate technique for identifying plant species. In this study, we collected manuscripts on DNA barcoding published in the last decade and summarized the use of this technique in identifying 50 common Chinese herbs listed in the Chinese pharmacopoeia. Based on the dataset of the major seven DNA barcodes of plants in the NCBI database, the strengths and limitations of the barcodes and their derivative barcoding technology, including single-locus barcode, multi-locus barcoding, super-barcoding, meta-barcoding, and mini-barcoding, were illustrated. In addition, the advances in DNA barcoding, particularly identifying plant species for TCM using machine learning technology, are also reviewed. Finally, the selection process of an ideal DNA barcoding technique for accurate identification of a given TCM plant species was also outlined.

Non-coding RNAs have attracted considerable attention for their vital role in cancer. The purpose of this study was to determine the effects of non-coding RNAs on hepatocellular carcinoma (HCC) and reveal their regulatory mechanism in the pathophysiological process. We measured the expression of mucin 1 (MUC1) and miR-485-5p in tissues from 15 HCC patients and in liver cancer cell lines by quantitative real-time polymerase chain reaction and Western blot, screened for aberrantly expressed microRNAs (miRNAs) by miRNA microarrays. Bioinformatics tools were used to find the miRNA and circular RNA that regulated MUC1, which were validated by RNA immunoprecipitation assay and luciferase reporter assay. Cell counting kit-8, Transwell assays, and flow cytometry were used to conduct functional experiments. Proteins were examined by western blot and immunohistochemical staining assays. Significant differences between groups were estimated using the one-way analysis of variance. A P < 0.05 was considered statistically significant. MUC1 was overexpressed in HCC tissues compared with that in paratumor tissues (normal vs. tumor, 1.007 ± 0.215 vs. 75.213 ± 18.403, t = 18.401, P < 0.001) while miR-485-5p was down-regulated (normal vs. tumor, 4.894 ± 0.684 vs. 1.586 ± 0.398, t = 16.191, P < 0.001). Inhibition of miR-485-5p promoted cell proliferation (73.33% ± 5.13% vs. 41.33% ± 3.51%, t = 8.913, P < 0.001), migration (102 ± 8 cells vs. 46 ± 8 cells, t = 8.681, P < 0.001), invasion (59 ± 7 cells vs. 28 ± 2 cells, t = 8.034, P < 0.01), and suppressed apoptosis (22.64% ± 6.97% vs. 36.33% ± 3.96%, t = 2.958, P < 0.05) of HepG2 cells with which MUC1 is knocked down. Mechanically, miR-485-5p binds to MUC1, while circHECTD1 binds to miR-485-5p, resulting in the indirect up-regulation of the MUC1 level. Our findings reveal that circHECTD1 facilitates HCC progression by sponging miR-485-5p to up-regulate MUC1.

The fragile ecological environment near mines provide advantageous conditions for the development of landslides. Mine landslide susceptibility mapping is of great importance for mine geo-environment control and restoration planning. In this paper, a total of 493 landslides in Shangli County, China were collected through historical landslide inventory. 16 spectral, geomorphic and hydrological predictive factors, mainly derived from Landsat 8 imagery and Global Digital Elevation Model (ASTER GDEM), were prepared initially for landslide susceptibility assessment. Predictive capability of these factors was evaluated by using the value of variance inflation factor and information gain ratio. Three models, namely artificial neural network (ANN), support vector machine (SVM) and information value model (IVM), were applied to assess the mine landslide sensitivity. The receiver operating characteristic curve (ROC) and rank probability score were used to validate and compare the comprehensive predictive capabilities of three models involving uncertainty. Results showed that ANN model achieved higher prediction capability, proving its advantage of solve nonlinear and complex problems. Comparing the estimated landslide susceptibility map with the ground-truth one, the high-prone area tends to be located in the middle area with multiple fault distributions and the steeply sloped hill.

Characterized by essential complexity, dynamism, and dynamics, streamflow forecasting presents a great challenge to hydrologists. Long short-term memory (LSTM) streamflow forecast model has received a lot of attention in recent years due to its powerful non-linear modeling ability. But probabilistic streamflow forecasting has rarely been addressed by the LSTM approach. In this study, a probabilistic Long Short-Term Memory network coupled with the Gaussian process (GP) is proposed to deal with the probabilistic daily streamflow forecasting. Moreover, considering that changing mean and variance over time exist in the daily streamflow time series, the heteroscedastic Gaussian process regression is adopted to produce a varying prediction interval. The proposed method encapsulates the inductive biases of the LSTM recurrent network and retains the non-parametric, probabilistic property of Gaussian processes. The performance of the proposed model is investigated by predicting the daily streamflow time series collected from the upper Yangtze River and its tributaries. Artificial neuron network, generalized linear model, heteroscedastic GP, and regular LSTM models are also developed for comparison. Results indicated that the performance of the proposed model is satisfying. It improves prediction accuracy as well as provides an adaptive prediction interval, which is of great significance for water resources management and planning.

Mild photothermal therapy (PTT), as a new anticancer therapeutic strategy, faces big challenges of limited therapeutic accuracy and side‐effects due to uneven heat distribution. Here, near infrared triggered nitric oxide (NO) release nanocomposites based on bismuth sulfide (Bi2S3) nanoparticles and bis‐N‐nitroso compounds (BNN) are constructed for NO‐enhanced mild photothermal therapy. Upon 808 nm irradiation, the high photothermal conversion efficiency and on‐demand NO release are realized simultaneously. Due to the unique properties of NO, enhanced antitumor efficacy of mild PTT based on BNN‐Bi2S3 nanocomposites is achieved in vitro and in vivo. Mechanism studies reveal that the exogenous NO from BNN‐Bi2S3 could not only impair the autophagic self‐repairing ability of tumor cells in situ, but also diffuse to the surrounding cells to enhance the therapeutic effect. This work points out a strategy to overcome the difficulties in mild PTT, and has potentials for further exploitation of NO‐sensitized synergistic cancer therapy. Nanocomposites based on bismuth sulfide nanoparticles and nitric oxide (NO) donors are constructed to realize simultaneous near infrared‐controlled NO release and mild photothermal therapy (PTT). The results lead to efficient tumor ablation due to the efficient dispersion of NO and the synergistic effect of NO and heat, which could overcome the drawbacks of mild PTT.

Background The precision of anterior segment biometric measurements in eyes has become increasingly important in refractive surgery. The purpose of this study is to assess the repeatability of the automatic measurements provided by a new spectral-domain optical coherence tomograph (SD-OCT)/Placido topographer (MS-39, CSO) and its agreement with a swept-source OCT (SS-OCT) biometer (CASIA SS-1000, Tomey) in patients with myopia. Methods The right eye of 235 subjects was scanned 3 times with both devices. The evaluated parameters included central corneal radius of the steep meridian, central corneal radius of the flat meridian, mean central corneal radius, thinnest corneal thickness, central corneal thickness, anterior chamber depth, corneal volume and diameter. The intraobserver repeatability of the MS-39 measurements was calculated using intraclass correlation coefficient (ICC), within subject standard deviation, coefficient of repeatability, coefficient of variation and repeated-measures analysis of variance of the 3 repeated measurements. The agreement between the two devices was evaluated by 95% limits of agreement (LoA). Results The majority of the parameters acquired from MS-39 showed high repeatability. The repeatability of corneal diameter was slightly lower than the other measurements, although the ICC remained high. Agreement with the CASIA SS-1000 was good, indicated by the Bland-Altman plots with narrow 95% LoA values for all parameters assessed. Conclusions The high repeatability of automatic measurements by the new device supports its clinical application in eyes with myopia, and the good agreement between the two devices indicates they could be used interchangeably for the parameters evaluated.

The production and application of nanomaterials have grown tremendously during last few decades. The widespread exposure of nanoparticles to the public is provoking great concerns regarding their toxicity to the human body. However, in comparison with the extensive studies carried out to examine nanoparticle toxicity to the human body/organs, one especially vulnerable organ, the eye, is always neglected. Although it is a small part of the body, 90% of outside information is obtained via the ocular system. In addition, eyes usually directly interact with the surrounding environment, which may get severer damage from toxic nanoparticles compared to inner organs. Therefore, the study of assessing the potential nanoparticle toxicity to the eyes is of great importance. Here, the recent advance of some representative manufactured nanomaterials on ocular toxicity is summarized. First, a brief introduction of ocular anatomy and disorders related to particulate matter exposure is presented. Following, the factors that may influence toxicity of nanoparticles to the eye are emphasized. Next, the studies of representative manufactured nanoparticles on eye toxicity are summarized and classified. Finally, the limitations that are associated with current nanoparticle‐eye toxicity research are proposed. This work covers the recent advances of toxicity of nanomaterials to eyes. It starts with an introduction of eye anatomy and disorders related to particulate matter exposure. Next, the factors that may influence toxicity of nanoparticles to the eyes and studies of representative manufactured nanomaterials on eye toxicity are summarized. Finally, the limitations that are associated with this field are proposed.

Carbon fiber reinforced polymer (CFRP) plays an important role in many fields, especially in aviation and civil industries. The electrical conductivity of CFRP is critical for its electrical behavior, such as its lightning strike vulnerability, electromagnetic shielding ability, and potential uses for self-sensing. In addition, the electrical conductivity is related to the mechanical integrity. Therefore, electrical properties can be measured as an indication when detecting delamination and other defects in CFRP. This review provides a comprehensive basis for readers to grasp recent research progresses on electrical behaviors of CFRP.