Development or absence of conjugate fractures in low-permeability sandstones

Natural fractures are ubiquitous in rocks. The Coulomb law of Mohr’s failure theory predicts that the angle between conjugate failure surfaces is a constant. In the Ordos Basin, observing the development of two groups of conjugate fractures in the field, cores and imaging logging is very difficult. In this paper, the directions of paleocurrents in the Upper Triassic Yanchang Formation of the Ordos Basin are determined by measuring the orientations of field bedding. Through the correlation analysis of paleocurrent and natural fracture orientations, when the sediment comes from a single source, a group of fractures with a large angle between conjugate fractures and the paleocurrent direction is found not to develop. When the sediments in the study area have two provenances, both provenance directions affect the development of conjugate fractures. In the southern Ordos Basin, influenced by the direction of paleocurrent flow in the near-north direction, fractures in the near N‒S direction develop. Through rock mechanics experiments in different directions, the planar anisotropy in rock mechanics parameters caused by the direction of paleocurrent flow is found to be the geological factor leading to various degrees of fracture development in different directions within the Ordos Basin

Krüppel-like factor 12 decreases progestin sensitivity in endometrial cancer by inhibiting the progesterone receptor signaling pathway.

OBJECTIVE: This study aimed to clarify the mechanism by which Krüppel-like factor 12 (KLF12) affects progesterone sensitivity in endometrial cancer (EC) through the progesterone receptor PGR signaling pathway. METHODS: The relationship of KLF12 with PGR in EC patients was examined by immunohistochemistry, and the expression of KLF12 and PGR in EC cell lines was detected by real-time PCR and western blotting. Cell proliferation assay, plate clone formation, cell apoptosis assay, and cell cycle analysis were conducted to determine the impact of KLF12 intervention on progesterone therapy. CUT&Tag analysis and the dual-luciferase reporter experiment were used to determine the underlying regulatory effect of KLF12 on the PGR DNA sequence. A subcutaneous xenograft nude mouse model was established to validate the in vivo effect of KLF12 on progesterone sensitivity via PGR expression modulation. RESULTS: KLF12 demonstrated decreased progesterone sensitivity and a negative correlation with PGR expression in EC tissues. Progesterone sensitivity was increased by KLF12 deficiency through PGR overexpression, a result that could be significantly reversed by PGR downregulation. PGR was identified as a target gene of KLF12, which could directly bind to the PGR promotor region and inhibit its expression. CONCLUSION: This study is the first to investigate the effect of KLF12 expression on EC cell resistance to progesterone. Our results offer important mechanistic insight into the direct regulation of the PGR promoter region, demonstrating that KLF12 expression strongly suppressed the PGR signaling pathway and, as a result, reduced progesterone sensitivity in EC patients

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Enhancement of aminoacylase activity by sodium citrate

Kidney and other tissues of animals and humans have a high concentration of citrate which is an important intermediate substance in the citrate cycle. Citrate may play an important physiological role in metabolism. In this paper, we studied the interaction of the sodium salt of citrate with aminoacylase which is an important enzyme in metabolism and found sodium citrate can enhance the activity of aminoacylase. The maximum enzyme activity induced by sodium citrate increased approximately 3 folds over the enzyme activity without sodium citrate. The initial reaction rates for different concentrations of sodium citrate were obtained, showing that sodium citrate is a non-competitive activator. The result of the ANS binding fluorescence measurements for aminoacylase indicated that increasing sodium citrate concentrations markedly increased the ANS binding fluorescence with a blue shift of the emission spectra peak. This suggests the formation of more hydrophobic regions. Aggregates formed quickly when aminoacylase was incubated with sodium citrate (0.3 mol/L) and guanidinium chloride (0-3.5 mol/L). Aminoacylase lost enzyme activity in the guanidinium chloride more quickly in the presence of sodium citrate than in the absence of sodium citrate. The intrinsic fluorescence emission intensity decreased more quickly and the red shift of the emission spectra peak was larger than that without sodium citrat

Does digitalization mitigate regional inequalities? Evidence from China

Regional inequality significantly influences sustainable development and human well-being. In China, there exists pronounced regional disparities in economic and digital advancements; however, scant research delves into the interplay between them. By analyzing the economic development and digitalization gaps at regional and city levels in China, extending the original Cobb-Douglas production function, this study aims to evaluate the impact of digitalization on China’s regional inequality using seemingly unrelated regression. The results indicate a greater emphasis on digital inequality compared to economic disparity, with variable coefficients of 0.59 for GDP per capita and 0.92 for the digitalization index over the past four years. However, GDP per capita demonstrates higher spatial concentration than digitalization. Notably, both disparities have shown a gradual reduction in recent years. The southeastern region of the Hu Huanyong Line exhibits superior levels and rates of economic and digital advancement in contrast to the northwestern region. While digitalization propels economic growth, it yields a nuanced impact on achieving balanced regional development, encompassing both positive and negative facets. Our study highlights that the marginal utility of advancing digitalization is more pronounced in less developed regions, but only if the government invests in the digital infrastructure and education in these areas. This study’s methodology can be utilized for subsequent research, and our findings hold the potential to the government’s regional investment and policy-making

Visualized Failure Prediction for the Masonry Great Wall

The cultural, architectural, and historical heritage value of the Great Wall of China drives the need to maintain, rehabilitate, and restore its structural integrity from artificial and natural damage. In this study, a hybrid architectural visualization and structural collapse simulation of the Ming Great Wall (1368–1644 AD) are conducted in Blender based on the unit blocks and a physics engine (i.e., Bullet Constraint Builder). Visualized failure predictions caused by four damages, i.e., stone layer collapse, step collapse, parapet walls inward tilting, and stone layer bulge, are developed and performed on a strength basis. The main input parameters are brick dimensions, friction coefficient, and adhesive/glue strength, while the primary output includes collapse, and global and local stabilities. Finally, the results show that the combination of unit blocks and a physical engine can visually simulate the occurrence process of the Great Wall’s failures with preliminary engineering outcome, especially those related to collapse, and can also predict the adverse consequences of the precipitating factors

The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation

Urban agglomerations have become the core areas for carbon reduction in China since they account for around 75% of its total emissions. Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and the Pearl River Delta (PRD), which are its most important poles of regional development and technological innovation, are key to achieving China’s carbon peak emissions target. Based on the panel data of these three major urban agglomerations from 2003 to 2017, this study estimated the carbon emission efficiency (CEE) by the super-efficiency slacks-based measure (super-SBM) model and analyzed its spatiotemporal distribution pattern. The Dagum Gini coefficient was used to evaluate the difference in CEE between the three major agglomerations, while panel data models were established to analyze the impact of technological innovation on the three agglomerations. The overall CEE showed an upward trend during the study period, with significant spatial and temporal variations. Additionally, the main source of urban agglomeration difference in CEE evolved from inter-regional net differences to intensity of transvariation. While technological innovations are expected to significantly improve CEE, their effect varies among urban agglomerations. These results provide policymakers with insights on the collaborative planning of urban agglomerations and the low-carbon economy

Visualized Failure Prediction for the Masonry Great Wall

The cultural, architectural, and historical heritage value of the Great Wall of China drives the need to maintain, rehabilitate, and restore its structural integrity from artificial and natural damage. In this study, a hybrid architectural visualization and structural collapse simulation of the Ming Great Wall (1368–1644 AD) are conducted in Blender based on the unit blocks and a physics engine (i.e., Bullet Constraint Builder). Visualized failure predictions caused by four damages, i.e., stone layer collapse, step collapse, parapet walls inward tilting, and stone layer bulge, are developed and performed on a strength basis. The main input parameters are brick dimensions, friction coefficient, and adhesive/glue strength, while the primary output includes collapse, and global and local stabilities. Finally, the results show that the combination of unit blocks and a physical engine can visually simulate the occurrence process of the Great Wall’s failures with preliminary engineering outcome, especially those related to collapse, and can also predict the adverse consequences of the precipitating factors