Protective effect of alcohol extract of Yulangsan leaf on chemically-induced liver injury in mice

Purpose: To investigate the protective effect of Millettia pulchra Kurz var. Laxior (Dunn) Z. Wei (Yulangsan) leaf (YLSL) on chemically-induced liver injury in mice.Methods: Models of carbon tetrachloride (CCl4) and D-galactosamine (D-GalN)-induced liver injury in Kunming mice were prepared by intraperitoneal injection. Sixty mice were randomly divided into normal saline (NS) group, liver-injury group, low-, medium- and high-dose YLSL groups (7.5, 15 and 30 g/kg dose, respectively), and biphenyldicarboxylate (BPDC) group, with 10 animals per group. Indices for liver, spleen and thymus were assessed. Serum aspartate transaminase (AST) and alanine aminotransferase (ALT) activities, levels of malondialdehyde (MDA) in liver tissues and reduced glutathione (GSH) as well as activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in liver tissue were assayed. Liver tissue damage was assessed histologically.Results: YLSL could significantly decrease the elevation of AST or ALT in liver injuries induced by CCl4 or D-GalN in mice, which showed a dose-effect relationship obviously. The high dose YLSL significantly decreased thymus weight relative to CCl4 and D-GalN (CCL4 CCL4+YLSL: 4.4213 ± 1.0544 vs 3.7120 ± 0.8534; D-GalN vs YLSL + D-GalN: 3.7272 ± 1.1655 vs 1.9548 ± 1.2996, p < 0.01). However, SOD activity was significantly increased (p < 0.01, p < 0.05). In treatment groups exposed to CCl4, GSH-Px activity was significantly increased (p < 0.01) and GSH levels decreased (middle dose group and positive control group). In treatment groups with D-GalN, GSH content was significantly increased (p < 0.01 or p < 0.05), while GSH-Px activity decreased (p <0.01).Conclusion: YLSL has protective effect against chemically-induced liver injury in mice. The mechanism may be related to attenuation of free radical-induced lipid peroxidation.Keywords: Millettia pulchra, Liver injury, Biochemical parameters, Thymus, Antioxidant, Dgalactosamine, Biphenyldicarboxylat

Thermodynamic Simulation of Carbonate Cements-Water-Carbon Dioxide Equilibrium in Sandstone for Prediction of Precipitation/Dissolution of Carbonate Cements

Carbonate cements, such as calcite, dolomite, ferrocalcite and ankerite, play important roles in the formation of pores in sandstones: precipitation of carbonate cements modifies pores and inhibits compaction, while dissolution creates secondary pores. This work proposed a precipitation-dissolution model for carbonate cements-CO2-H2O system by means of ion equilibrium concentration ([M2+], M = Ca, Mg, Fe or Mn) with different factors, such as temperature, depth, pH, [Formula: see text], variable rock composition and overpressure. Precipitation-dissolution reaction routes were also analyzed by minimization of the total Gibbs free energy (ΔG). Δ[M2+], the variation of [Ca2+], [Fe2+], [Mg2+] or [Mn2+] for every 100 m of burial depths, is used to predict precipitation or dissolution. The calculation results indicate that the increasing temperature results in decrease of equilibrium constant of reactions, while the increasing pressure results in a relatively smaller increase of equilibrium constant; As a result, with increasing burial depth, which brings about increase of both temperature and pressure, carbonate cements dissolve firstly and produces the maximal dissolved amounts, and then precipitation happens with further increasing depth; For example, calcite is dissolving from 0.0 km to 3.0 km with a maximal value of [Ca2+] at depth of 0.8 km, and then precipitates with depth deeper than 3.0 km. Meanwhile, with an increasing CO2 mole fraction in the gaseous phase from 0.1% to 10.0% in carbonate systems, the aqueous concentration of metal ions increases, e.g., dissolved amount of CaFe0.7Mg0.3(CO3)2 increases and reaches maximum of 1.78 mmol·L-1 and 8.26 mmol·L-1 at burial depth of 0.7 km with CO2 mole fraction of 0.1% and 10.0%, respectively. For the influence of overpressure in the calcite system, with overpressure ranging from 36 MPa to 83 MPa, pH reaches a minimum of 6.8 at overpressure of 51 MPa; meanwhile, Δ[Ca2+] increases slightly from -2.24 mmol·L-1 to -2.17 mmol·L-1 and remains negative, indicating it is also a precipitation process at burial depth of 3.9 km where overpressure generated. The method used in this study can be applied in assessing burial precipitation-dissolution processes and predicting possible pores in reservoirs with carbonate cement-water-carbon dioxide

The Effect of Conditioning on the Flotation of Pyrrhotite in the Presence of Chlorite

The influence of conditioning on the flotation of pyrrhotite in the presence of chlorite was investigated through flotation tests, sedimentation tests, and X-ray photoelectron spectroscopy (XPS) analysis. The flotation results show that chlorite slimes dramatically impair the flotation of pyrrhotite. Sedimentation and flotation tests reveal that conditioning can effectively remove chlorite slimes from pyrrhotite surfaces, resulting in an enhanced flotation recovery of pyrrhotite. When mixed minerals were conditioned under the natural atmosphere, a faster conditioning speed and longer conditioning time decreased the flotation recovery of pyrrhotite. However, when mixed minerals were conditioned under a nitrogen atmosphere, a more intensive conditioning process provided better flotation results. XPS analyses illustrate that a faster conditioning speed and longer conditioning time under the natural atmosphere accelerates the oxidation of pyrrhotite, leading to a decrease in the flotation recovery of pyrrhotite

SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation

Unsupervised semantic segmentation is a challenging task that segments images into semantic groups without manual annotation. Prior works have primarily focused on leveraging prior knowledge of semantic consistency or priori concepts from self-supervised learning methods, which often overlook the coherence property of image segments. In this paper, we demonstrate that the smoothness prior, asserting that close features in a metric space share the same semantics, can significantly simplify segmentation by casting unsupervised semantic segmentation as an energy minimization problem. Under this paradigm, we propose a novel approach called SmooSeg that harnesses self-supervised learning methods to model the closeness relationships among observations as smoothness signals. To effectively discover coherent semantic segments, we introduce a novel smoothness loss that promotes piecewise smoothness within segments while preserving discontinuities across different segments. Additionally, to further enhance segmentation quality, we design an asymmetric teacher-student style predictor that generates smoothly updated pseudo labels, facilitating an optimal fit between observations and labeling outputs. Thanks to the rich supervision cues of the smoothness prior, our SmooSeg significantly outperforms STEGO in terms of pixel accuracy on three datasets: COCOStuff (+14.9%), Cityscapes (+13.0%), and Potsdam-3 (+5.7%).Comment: Accepted by NeurIPS 2023. Code available: https://github.com/mc-lan/SmooSe

Intensity measurement bend sensors based on periodically tapered soft glass fibers

We demonstrate a novel technique for tapering periodically an all-solid soft glass fiber, consisting of two types of lead silicate glasses, by the use of a focused CO2 laser beam and investigate the bend sensing applications of the periodically-tapered soft glass fiber. Such a soft glass fiber with periodic microtapers could be used to develop promising bend sensors with a sensitivity of -27.75 µW/m-1 by means of measuring the bend-induced change of light intensity. The proposed bend sensor exhibits a very low measurement error of down to ±1%