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Three dimensional (3D) bioprinting, which involves depositing bioinks (mixed biomaterials) layer by layer to form computer-aided designs, is an ideal method for fabricating complex 3D biological structures. However, it remains challenging to prepare biomaterials with micro-nanostructures that accurately mimic the nanostructural features of natural tissues. A novel nanotechnological tool, electrospinning, permits the processing and modification of proper nanoscale biomaterials to enhance neural cell adhesion, migration, proliferation, differentiation, and subsequent nerve regeneration. The composite scaffold was prepared by combining 3D bioprinting with subsequent electrochemical deposition of polypyrrole and electrospinning of silk fibroin to form a composite polypyrrole/silk fibroin scaffold. Fourier transform infrared spectroscopy was used to analyze scaffold composition. The surface morphology of the scaffold was observed by light microscopy and scanning electron microscopy. A digital multimeter was used to measure the resistivity of prepared scaffolds. Light microscopy was applied to observe the surface morphology of scaffolds immersed in water or Dulbecco's Modified Eagle's Medium at 37°C for 30 days to assess stability. Results showed characteristic peaks of polypyrrole and silk fibroin in the synthesized conductive polypyrrole/silk fibroin scaffold, as well as the structure of the electrospun nanofiber layer on the surface. The electrical conductivity was 1 × 10−5-1 × 10−3 S/cm, while stability was 66.67%. A 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay was employed to measure scaffold cytotoxicity in vitro. Fluorescence microscopy was used to observe EdU-labeled Schwann cells to quantify cell proliferation. Immunohistochemistry was utilized to detect S100β immunoreactivity, while scanning electron microscopy was applied to observe the morphology of adherent Schwann cells. Results demonstrated that the polypyrrole/silk fibroin scaffold was not cytotoxic and did not affect Schwann cell proliferation. Moreover, filopodia formed on the scaffold and Schwann cells were regularly arranged. Our findings verified that the composite polypyrrole/silk fibroin scaffold has good biocompatibility and may be a suitable material for neural tissue engineering.

Pulmonary vascular endothelial cells (VECs) are the main damaged cells in the pathogenesis of various respiratory diseases and they mediate the development and regulation of the diseases. Effective intervention targeting pulmonary VECs is of great significance for the treatment of respiratory diseases. A variety of cell markers are expressed on the surface of VECs, some of which can be specifically combined with the drugs or carriers modified by corresponding ligands such as ICAM-1, PECAM-1, and P-selectin, to achieve effective delivery of drugs in lung tissues. In addition, the great endothelial surface area of the pulmonary vessels, the “first pass effect” of venous blood in lung tissues, and the high volume and relatively slow blood perfusion rate of pulmonary capillaries further promote the drug distribution in lung tissues. This review summarizes the representative markers at the onset of respiratory diseases, drug delivery systems designed to target these markers and their therapeutic effects.

Background/Aims: This study is aimed at identification of miR-195-5p/MMP14 expression in cervical cancer (CC) and their roles on cell proliferation and invasion profile of CC cells through TNF signaling pathway in CC. Methods: Microarray analysis, gene set enrichment analysis (GSEA) and DAVID were used to analyze differentially expressed miRNAs, mRNAs and signaling pathways. MiR-195-5p and MMP14 expression levels in CC cell were determined by qRT-PCR. Western blot was employed to measure MMP14 and TNF signaling pathway-relating protein level. Luciferase reporter system was used to confirm the targeting relationship between MMP14 and miR-195-5p. Cell proliferation and invasion was respectively deeded by CCK8, transwell. In vivo experiment was carried out to study the impact of MMP14 and miR-195-5p on CC development in mice. Results: The microarray analysis and the results of qRT-PCR determined that miR-195-5p was under-expressed and MMP14 was over-expressed in CC cells. GSEA and DAVID analysis showed that TNF signaling pathway was regulated by miR-195-5p/MMP14 and activated in cervical carcinoma cells. The miR-195-5p and MMP14 have a negative regulation relation. In vivo experiment found that down-regulated MMP14 and up-regulated miR-195-5p suppressed the tumor development. Conclusion: Our results suggest that MMP14 is a direct target of miR-195-5p, and down-regulated MMP14 and up-regulated miR-195-5p suppressed proliferation and invasion of CC cells by inhibiting TNF signaling pathway.

Background Barrier function is essential for the maintenance of normal intestinal function. Dysregulation of the intestinal barrier underlies a wide range of disorders. Aim Previously, we found that sodium butyrate (NaB) decreased the molecular permeability of intestinal barrier in vivo model, but the mechanism by which NaB facilitated the tightness of tight junctions (TJs) in small intestinal epithelium needed further studies. Methods In vitro culture of the cdx2-IEC monolayer was used to mimic barrier function. The TJs were assessed by transepithelial electrical resistance (TEER) and paracellular flux of fluorescein isothiocyanate-conjugated dextran 40,000 (FD-40), Western blot, Q-RT-PCR, and immunofluorescence. Promoter and chromatin immunoprecipitation (ChIP) assays were also done to analyze the Claudin-1 gene. Results NaB decreased FD-40 flux, increased TEER and TJ protein Claudin-1 expression, induced ZO-1 and Occludin redistribution in cellular membrane, and reversed the damage effect after calcium (Ca 2+ ) switch assay. Silencing Claudin-1 prevented protective function of NaB from enhancing intestinal barrier integrity. Further studies demonstrated that NaB increased Claudin-1 transcription by facilitating the interaction between transcription factor SP1 and a specific motif within the promoter region of Claudin-1. This SP1 binding motif was located upstream of the coding region (−138 to −76 bp) and indispensable for the transcription of Claudin-1 following NaB treatment. ChIP assay confirmed the association between SP1 and Claudin-1 promoter, and the elimination of the SP1 binding site by point mutation resulted in a significant loss of Claudin-1 transcription after NaB dealing. Conclusions NaB enhanced intestinal barrier function through increasing Claudin-1 transcription via facilitating the association between SP1 and Claudin-1 promoter.

Epstein–Barr virus (EBV) is causally associated with nasopharyngeal carcinoma, 10% of gastric carcinoma and various B cell lymphomas 1 . EBV infects both B cells and epithelial cells 2 . Recently, we reported that epidermal growth factor and Neuropilin 1 markedly enhanced EBV entry into nasopharyngeal epithelial cells 3 . However, knowledge of how EBV infects epithelial cells remains incomplete. To understand the mechanisms through which EBV infects epithelial cells, we integrated microarray and RNA interference screen analyses and found that Ephrin receptor A2 (EphA2) is important for EBV entry into the epithelial cells. EphA2 short interfering RNA knockdown or CRISPR–Cas9 knockout markedly reduced EBV epithelial cell infection, which was mostly restored by EphA2 complementary DNA rescue. EphA2 overexpression increased epithelial cell EBV infection. Soluble EphA2 protein, antibodies against EphA2, soluble EphA2 ligand EphrinA1, or the EphA2 inhibitor 2,5-dimethylpyrrolyl benzoic acid derivative efficiently blocked EBV epithelial cell infection. Mechanistically, EphA2 interacted with EBV entry proteins gH/gL and gB to facilitate EBV internalization and fusion. The EphA2 Ephrin-binding domain and fibronectin type III repeats domain were essential for EphA2-mediated EBV infection, while the intracellular domain was dispensable. This is distinct from Kaposi’s sarcoma-associated herpesvirus infection through EphA2 4 . Taken together, our results identify EphA2 as a critical player for EBV epithelial cell entry. The receptor tyrosine kinase EphA2 is found to be an important determinant of EBV entry and fusion in epithelial cells. EphA2 depletion or absence, or the use of anti-EphA2 antibodies, inhibits oropharyngeal epithelial cell infection.

Solving the problem of ship weather routing has been always a goal of nautical navigation research and has been investigated by many scientists. The operation schedule of an oceangoing ship can be influenced by wave or wind disturbances, which complicate route planning. In this paper, we present a real-coded genetic algorithm to determine the minimum voyage route time for point-to-point problems in a dynamic environment. A fitness assignment method based on an individual's position in the sorted population is presented, which greatly simplifies the calculation of fitness value. A hybrid mutation operator is proposed to enhance the search for the optimal solution and maintain population diversity. Multi-population techniques and an elite retention strategy are employed to increase population diversity and accelerate convergence rates. The effectiveness of the algorithm is demonstrated by numerical simulation experiments.

Background To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. Methods The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. Results The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost ( p  = 0.0017). The p -value of the other two models was < 0.01. Conclusion In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method.

Ischemic stroke is the most common type of cerebrovascular disease with high disability rate and mortality. The blood-brain barrier (BBB) protects the homeostasis of the brain’s microenvironment and impedes the penetration of 98% of drugs. Therefore, effective treatment requires the better drug transport across membranes and increased drug distribution. Nanoparticles are a good choice for drugs to cross BBB. The main pathways of nano delivery systems through BBB include passive diffusion, adsorption-mediated endocytosis, receptor-mediated transport, carrier-mediated transport, etc. At present, the materials used in brain-targeted delivery can be divided into natural polymer, synthetic polymers, inorganic materials and phospholipid. In this review, we first introduced several ways of nano delivery systems crossing the BBB, and then summarized their applications in ischemic stroke. Based on their potential and challenges in the treatment of ischemic stroke, new ideas and prospects are proposed for designing feasible and effective nano delivery systems.

Subarachnoid hemorrhage (SAH), a severe cerebrovascular disorder, is principally instigated by the rupture of an aneurysm. Early brain injury (EBI), which gives rise to neuronal demise, microcirculation impairments, disruption of the blood-brain barrier, cerebral edema, and the activation of oxidative cascades, has been established as the predominant cause of mortality among patients with SAH. These pathophysiological processes hinge on the activation of inflammasomes, specifically the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3)and absent in melanoma 2 (AIM2) inflammasomes. These inflammasomes assume a crucial role in downstream intracellular signaling pathways and hold particular significance within the nervous system. The activation of inflammasomes can be modulated, either by independently regulating these two entities or by influencing their engagement at specific target loci within the pathway, thereby attenuating EBI subsequent to SAH. Although certain clinical instances lend credence to this perspective, more in-depth investigations are essential to ascertain the optimal treatment regimen, encompassing dosage, timing, administration route, and frequency. Consequently, targeting the ensuing early brain injury following SAH represents a potentially efficacious therapeutic approach.

Hydraulic support plays a key role in ground control of longwall mining. The smart prediction methods of support load are important for achieving intelligent mining. In this paper, the hydraulic support load data is decomposed into trend term, cycle term, and residual term, and it is found that the data has clear trend and period features, which can be called time series data. Based on the autoregression theory and weighted moving average method, the time series model is built to analyze the load data and predict its evolution trend, and the prediction accuracy of the sliding window model, ARIMA (Autoregressive Integrated Moving Average) model, and SARIMA (Seasonal Autoregressive Integrated Moving Average) model to the hydraulic support load under different parameters are evaluated, respectively. The results of single-point and multipoint prediction test with various sliding window values indicate that the sliding window method has no advantage in predicting the trend of the support load. The ARIMA model shows a better short-term trend prediction than the sliding window model. To some extent, increasing the length of the autoregressive term can improve the long-term prediction accuracy of the model, but it also increases the sensitivity of the model to support load fluctuation, and it is still difficult to predict the load trend in one support cycle. The SARIMA model has better prediction results than the sliding window model and the ARIMA model, which reveals the load evolution trend accurately during the whole support cycle. However, there are many external factors affecting the support load, such as overburden properties, hydraulic support moving speed, and worker’s operation. The smarter model of SARIMA considering these factors should be developed to be more suitable in predicting the hydraulic support load.