RESUMEN
As mechanized open-pit coal mining intensifies, assessing and predicting slope stability has become increasingly important. To address the limitations of traditional mechanical calculations, numerical simulations, and physical experiments, this paper identifies the key factors impacting slope stability in open-pit mines and develops a multi-parameter sample data set. The study employs hyperparameters optimized using a Bayesian algorithm, introduces additional convolutional layers, and combines the Adam optimizer with dropout techniques to enhance the feature extraction and performance of one-dimensional convolutional neural networks (1D-CNN). This leads to a Bayesian-optimized one-dimensional convolutional neural network (B-1D MCNN) model for predicting slope stability.The study evaluates the classification performance and accuracy of various models for slope stability, including BP neural networks, genetic algorithm-optimized convolutional neural networks, 1D-CNN, and B-1D MCNN, using accuracy, precision, and F1-score as metrics. The analysis also examines the influence of factor indicators and training set length on the model's output to assess its generalization capabilities.The research findings suggest that: (1) the B-1D MCNN model for evaluating slope stability demonstrates the capability to accurately depict the nonlinear correlation between influencing factors and slope stability. (2) Compared with other models, the B-1D MCNN model has shown enhancements of 10.96% to 27.85%, 10.26% to 28.55%, and 8.98% to 25.05% in terms of Accuracy, F1-Score, and Precision, respectively. (3) As the length of the training dataset increases, the performance of the model improves accordingly. (4) The B-1D MCNN model shows a generalization power of 87.5%.
RESUMEN
To minimize the global pandemic COVID-19 spread, understanding the possible transmission routes of SARS-CoV-2 and discovery of novel antiviral drugs are necessary. We describe here that the virus can infect ocular surface limbal epithelial, but not other regions. Limbal supports wild type and mutant SARS-CoV-2 entry and replication depending on ACE2, TMPRSS2 and possibly other receptors, resulting in slight CPE and arising IL-6 secretion, which symbolizes conjunctivitis in clinical symptoms. With this limbal model, we have screened two natural product libraries and discovered several unreported drugs. Our data reveal important commonalities between COVID-19 and ocular infection with SARS-CoV-2, and establish an ideal cell model for drug screening and mechanism research.
RESUMEN
CLINICAL RELEVANCE: The pathogenesis of chronic dacryocystitis (CDC) is associated with a variety of bacteria. Investigating microflora has the potential to provide a theoretical basis for preventing and treating CDC. BACKGROUND: 16S rRNA sequencing is a sequence-based bacterial analysis. The application of 16S rRNA sequencing in CDC is rarely reported. METHODS: A case-control study of infected and healthy eyes diagnosed as CDC patients was conducted. Seventy-eight patients were divided into A (conjunctival sac secretions from healthy eyes), B (conjunctival sac secretions from affected eyes), and C (lacrimal sac secretions from affected eyes) groups. The flora of samples was analysed with 16S rRNA sequencing, and the data was analysed using QIIME, R, LefSE and other software. The potential functions were analysed by PICRUSt. RESULTS: A total of 1440 operational taxonomic units (OTUs) were obtained, 139 specific to group A, 220 specific to group B, and 239 specific to group C. There was no significant difference in α index between the three groups. The beta diversity and grouping analysis data indicated that the three groups of flora were similar in species richness and diversity, but there were some differences in composition. In group A, the abundance of Pseudomonadaceae, Chlorobacteria, Moraceae, Staphylococcaceae, Bacillariophyceae, Immunobacterium spp. and Bacillus spp. was higher; in group B, the abundance of Burkholderiaceae, Sphingomonas, Rhizobia, Stalked Bacteria, Sphingomonadaceae, Enterobacteriaceae, Shortwaveomonas spp. was higher; in group C, the abundance of Streptococcus digestiveis, Propionibacterium, Enterobacteriaceae, Anaerobacteriaceae, Propionibacteriaceae, Bacillus spp. Neisseria spp. and Shortactomonas spp. was higher. Six pathways were identified to assess the potential microbial functions. CONCLUSION: Alterations in the microbiota of the conjunctiva and lacrimal sac are associated with the pathogenesis of CDC, which may provide certain guidance for antibiotic treatment of CDC.
RESUMEN
Monitoring and preventing coal-rock dynamic disasters are vital for safe mining. To investigate the time-frequency features of induced charge signals with coal damage and failure of roadways, the generation mechanism of free charge in loaded coal is analyzed and the induced charge monitoring test is conducted. According to the stress-induced charge-time curves, the time-domain features of charge signals at each loading stage are obtained. The wavelet threshold denoising approach and generalized Morse wavelet transform method are applied to denoise the raw signals and study the frequency-domain features. Further, the quantitative relationship between the de-noised induced charge signals and the degree of coal damage is established. The results show that the event number, amplitude and fluctuation degree of available induced charge signals are all at a low level in the compaction and elastic stages of the coal, which are mainly generated by the piezoelectric effect and predominantly represent discreteness. When entering the plastic and failure stages, the available signals are primarily produced by the crack propagation and triboelectric effects, with a significant increase in the event number, amplitude, and fluctuation degree. Then the induced charge signals gradually transit from discrete to continuous. Generally, the dominant frequency of the available induced charge signals during the coal damage process is concentrated at 0 ~ 11 Hz. The available induced charge is positively correlated with the degree of coal damage, which can perform the damage degree of coal mass, providing a new approach to evaluate the stability of roadway surrounding rocks.
RESUMEN
Aqueous-deficient dry eye (ADDE) is a type of dry eye disease that can result in the reduction of tear secretion quantity and quality. Prolonged abnormal tear production can lead to a disturbance in the ocular surface environment, including corneal damage and inflammation. In severe cases, ADDE can cause vision loss or even blindness. Currently, dry eye treatment is limited to eye drops or physical therapy, which can only alleviate eye discomfort symptoms and cannot fundamentally cure dry eye syndrome. To restore the function of the lacrimal gland in dry eye, we have created an animal model of lacrimal gland dysfunction in rats induced by scopolamine. Through the comprehensive evaluation of the lacrimal gland, corneas, conjunctivas, and other factors, we aim to provide a full understanding of the pathological changes of ADDE. Compared with the current dry eye mouse model, this ADDE animal model includes a functional evaluation of the lacrimal gland, providing a better platform for studying lacrimal gland dysfunction in ADDE.
Asunto(s)
Síndromes de Ojo Seco , Aparato Lagrimal , Ratones , Animales , Ratas , Escopolamina , Síndromes de Ojo Seco/inducido químicamente , Síndromes de Ojo Seco/tratamiento farmacológico , Ceguera , Modelos Animales de EnfermedadRESUMEN
BACKGROUND AND OBJECTIVE: Literature has reported that circular RNAs (circRNAs) are crucially associated with diabetic retinopathy (DR). Furthermore, circEHMT1 has been identified to maintain endothelial cell barrier function. This study aimed to investigate the mechanisms that regulate aberrant circEHMT1 expression and its role in the pathogenesis of DR. METHODS: In this study, retinal microvascular endothelial cells were exposed to a high glucose (HG) environment, and subsequently, tube formation and intercellular junction proteins were evaluated. Furthermore, the biological functions of circEHMT1 and its potential regulatory factor, eIF4A3, in microvascular endothelial cells under HG conditions were also assessed. In addition, the regulatory role of eIF4A3 on circEHMT1 expression was confirmed. Moreover, to elucidate the in vivo functions of eIF4A3 and circEHMT1, streptozotocin (STZ) was used to establish a DR model in rats. RESULTS: It was revealed that HG condition decreased circEHMT1 and eIF4A3 expressions and reduced ZO-1, Claudin-5, and Occludin levels in retinal microvascular endothelial cells. Furthermore, it was observed that eIF4A3 could regulate the expression of circEHMT1. Overexpression of eIF4A3 or circEHMT1 under HG conditions improved endothelial cell injury and decreased tube-formation ability. Additionally, in the DR rat model, eIF4A3 overexpression restored circEHMT1 levels and ameliorated retinal vasculature changes. CONCLUSION: Altogether, eIF4A3 regulates circEHMT1 expression, thereby affecting microvascular endothelial cell injury and tube formation. Further understanding the regulatory effect of eIF4A3 on circEHMT1 may provide novel therapeutic targets for DR.