CHINESE HERBAL MEDICINE AND PREDNISONE INCREASE PROPORTION OF SPLENIC CD4+CD25-FOXP3+ CELLS AND ALLEVIATE GLOMERULAR LESION IN MRL/LPR MICE

Objective: This study investigated the effects of Chinese herbal medicine and prednisone on CD4+FoxP3+ T cells (Tregs) and Th17 cells in the MRL/lpr mouse model of systemic lupus erythematosus. Methods: MRL/lpr mice were treated with herbal medicine (yin-nourishing and heat-clearing therapy), prednisone, and a combination of both for 7 weeks. The proportions of CD4+CD25+FoxP3+ cells, CD4+CD25-FoxP3+ cells, and CD4+IL-17+ cells in splenic mononuclear cell suspension were determined by flow cytometry. Histological slices of kidneys were stained by H&E, PAS, and Masson’s method. Activity indexes (AI) of glomerular lesions were scored. Results: The result showed that both herbal medicine and prednisone significantly increased the proportion of CD4+CD25-FoxP3+ cells (

A Rapid UPLC-MS Method for Quantification of Gomisin D in Rat Plasma and Its Application to a Pharmacokinetic and Bioavailability Study

Gomisin D, a lignan compound isolated from Fructus Schisandra, is a potential antidiabetic and anti-Alzheimer’s agent. Recently, gomisin D was used as a quality marker of some traditional Chinese medicine (TCM) formulas. In this study, a rapid ultra-performance liquid chromatography/tandem mass spectrometry method (UPLC-MS/MS) was developed and validated to quantify gomisin D in rat plasma for a pharmacokinetic and bioavailability study. Acetonitrile was used to precipitate plasma proteins. Separations were performed on a BEH C18 column with a gradient mobile phase comprising of acetonitrile and water (0.1% formic acid). An electrospray ionization source was applied and operated in the positive ion mode. The multiple reaction monitoring mode (MRM) was utilized to quantify gomisin D and nomilin (internal standard, IS) using the transitions of m/z 531.2 → 383.1 and m/z 515.3 → 161.0, respectively. The calibration curve was linear over the working range from 1 to 4000 ng/mL (R2 = 0.993). The intra- and interday precision ranged from 1.9% to 12.9%. The extraction recovery of gomisin D was in the range of 79.2–86.3%. The validated UPLC-MS/MS method was then used to obtain the pharmacokinetic characteristics of gomisin D after intravenous (5 mg/kg) and intragastric (50 mg/kg) administration to rats. The bioavailability of gomisin D was 107.6%, indicating that this compound may become a promising intragastrical medication. Our results provided useful information for further preclinical studies on gomisin D

CO2 Capture over Activated Carbon Derived from Pulverized Semi-Coke

Pulverized semi-coke was employed as raw material to prepare activated carbon via steam activation and evaluated as a CO2 adsorbent. The effects of the preparation parameters including demineralization, activation temperature, activation time and steam flow on the structure and performance of the synthesized activated carbon were investigated. It was found that the microporous structure of activated carbon was greatly influenced by demineralization order and activation conditions. Demineralization before activation significantly increased the microporous structure of the activated carbon, which was ascribed to the removal of the inorganic fraction. Compared to the commercial activated carbon, activated carbon obtained by employing 150 mL/min steam to treat the demineralized pulverized semi-coke at 700 °C for 70 min possessed a higher CO2/N2 selectivity of 34.4 and good cyclic performance, which was due to its narrow microporosity of 0.55 nm. Furthermore, it was proved that a pore size of smaller than 1 nm is favorable for CO2 sorption

A new denoising method for photon-counting LiDAR data with different surface types and observation conditions

Spaceborne photon-counting LiDAR is significantly affected by noise, and existing denoising algorithms cannot be universally adapted to different surface types and topographies under all observation conditions. Accordingly, a new denoising method is presented to extract signal photons adaptively. The method includes two steps. First, the local neighborhood radius is calculated according to photons' density, then the first-step denoising process is completed via photons’ curvature feature based on KNN search and covariance matrix. Second, the local photon filtering direction and threshold are obtained based on the first-step denoising results by RANSAC and elevation frequency histogram, and the local dense noise photons that the first-step cannot be identified are further eliminated. The following results are drawn: (1) experimental results on MATLAS with different topographies indicate that the average accuracy of second-step denoising exceeds 0.94, and the accuracy is effectively improves with the number of denoising times; (2) experiments on ICESat-2 under different observation conditions demonstrate that the algorithm can accurately identify signal photons in different surface types and topographies. Overall, the proposed algorithm has good adaptability and robustness for adaptive denoising of large-scale photons, and the denoising results can provide more reasonable and reliable data for sustainable urban development

Exploration of the minimal clinically important difference value of the 3‐min simulated pedal motion in patients with chronic obstructive pulmonary disease: A self‐controlled prospective clinical trial

Abstract Background To help elderly patients with severe or very severe chronic obstructive pulmonary disease (COPD) with pulmonary rehabilitation, we have developed Zheng's supine rehabilitation exercise (ZSRE). Currently, none of the terminal or critically ill patients with severe exercise limitation can complete the 6‐min walking distance (6MWD) and cardiopulmonary exercise testing (CPET). Methods In this study, we discuss the definition of the standardized 3‐min simulated pedal motion (3MSPM) test and its operational specifications. Also, we evaluate the minimal clinically important difference (MCID) value of the 3MSPM. Results The results showed that the mMRC score of COPD patients with acute exacerbation of dyspnea was progressively reduced from the second day of respiratory rehabilitation, and the difference between the first and seventh days was statistically significant (p < 0.000, χ2 = 176.664). 6MWD increased progressively, and the difference between 6MWD on day 1–7 was statistically significant (p = 0.024, F = 2.443). The difference between 3MSPM on day 1–7 was also statistically significant (p < 0.000, F = 4.481). Further analysis showed that 6MWD was negatively correlated with mMRC (p < 0.000, OR = −0.524). 3MSPM was positively correlated with 6MWD (p < 0.000, OR = 0.640) but negatively correlated with mMRC (p < 0.000, OR = −0.413). There is a linear regression relationship between 6MWD and 3MSPM, that is, 6MWD = 14.151 + 0.301 * 3MSPM, adjusted R2 = 0.401. Conclusion Based on the regression equation, 3MSPM can predict 6MWD, and it can be used as a simple exercise endurance method to evaluate patients with safety hazards in underground activities or who cannot complete the 6MWD test. The minimum clinically important difference value is increased by 23

Efficiency analysis of sorption-enhanced method in steam methane reforming process

The sorption-enhanced method can change the thermodynamic equilibrium by absorbing CO2. However, it also brings about the problems of high regeneration temperature of adsorbent and large regeneration energy consumption. In order to study the impact of enhanced adsorption methods on the overall energy cost of the system in the hydrogen production process, this paper analyzes and compares steam methane reforming and reactive adsorption-enhanced steam methane reforming with the energy consumption of hydrogen production products as the evaluation index. The results showed that the energy consumption per unit hydrogen production decreased from 276.21 MJ/kmol to 131.51 MJ/kmol, and the decomposition rate of H2O increased by more than 20% after the addition of adsorption enhancement method. It is proved that the advantage of sorption enhanced method on pre-separation of CO2 in the product makes up for the disadvantage of energy consumption of adsorbent regeneration. In addition, the ability of the process to obtain H element is improved by the high decomposition rate of H2O, which realizes a more rational distribution of the element

Comparative and Phylogenetic Analyses of Complete Chloroplast Genomes of <i>Scrophularia incisa</i> Complex (Scrophulariaceae)

The Scrophularia incisa complex is a group of closely related desert and steppe subshrubs that includes S. incisa, S. kiriloviana and S. dentata, which are the only S. sect. Caninae components found in Northwest China. Based on earlier molecular evidence, the species boundaries and phylogenetic relationships within this complex remain poorly resolved. Here, we characterized seven complete chloroplast genomes encompassing the representatives of the three taxa in the complex and one closely related species, S. integrifolia, as well as three other species of Scrophularia. Comparative genomic analyses indicated that the genomic structure, gene order and content were highly conserved among these eleven plastomes. Highly variable plastid regions and simple sequence repeats (SSRs) were identified. The robust and consistent phylogenetic relationships of the S. incisa complex were firstly constructed based on a total of 26 plastid genomes from Scrophulariaceae. Within the monophyletic complex, a S. kiriloviana individual from Pamirs Plateau was identified as the earliest diverging clade, followed by S. dentata from Tibet, while the remaining individuals of S. kiriloviana from the Tianshan Mountains and S. incisa from Qinghai–Gansu were clustered into sister clades. Our results evidently demonstrate the capability of plastid genomes to improve phylogenetic resolution and species delimitation, particularly among closely related species, and will promote the understanding of plastome evolution in Scrophularia

Urban building height extraction accommodating various terrain scenes using ICESat-2/ATLAS data

Although the photon point cloud data acquired from ICESat-2/ATLAS can be efficiently employed in urban building height extraction, its universal applicability in undulating terrain scenarios is constrained, and there are noticeable issues of false positives and false negatives. This research establishes a terrain-adaptive methodological framework based on ICESat-2/ATLAS photon point cloud to extract high-precision, high-density building height data across varied urban topographical conditions. First, a terrain-adaptive elevation buffer is utilized to coarse denoise the photon point cloud, involving the removal of the majority of noise photons in the scene, thereby enhancing the efficiency of subsequent algorithms. Second, urban signal photons are extracted from the remaining original photons using the Adaptive Method Based on Single-Photon Spatial Distribution (SPSD-AM). This approach demonstrates high universality across various urban scenes, while simultaneously ensuring a stable accuracy of urban signal photon extraction. Subsequently, ground photons are extracted from the urban signal photons and fit the ground curve based on the Adaptive Method Based on Spatial Differences of Urban Signal Photons (USPSD-AM), which addresses the challenge of the potential mixing of ground and building photons in complex terrain scenarios. A precise ground curve is then employed to extract building photons from urban signal photons. In order to mitigate issues such as false positives and negatives, post-processing steps, including completion and denoising of building photons, are implemented. Finally, the acquired building photons and ground curve are adopted to extract accurate building height parameters. The precision verification results show that the extracted building heights are considerably consistent with the reference building heights. The mean RMSE and MAE are 0.273 m and 0.202 m for flat terrains and 1.168 m and 0.759 m for undulating terrains, respectively. The proposed method demonstrates superior applicability across diverse urban scenarios, providing a robust theoretical foundation for large-scale urban building height retrieval efforts

Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity.

Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD), which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD