Quantitative analysis of the spatial diversity of Moraceae in China

Changes in distribution patterns of economically essential forest species under global change are urgently needed in the scientific forecast, and large-scale spatial modeling is a crucial tool. Using diversity pattern indicators and other data obtained through geographic information systems (GIS) and spatial data on Moraceae species obtained from published data, we quantitatively studied the spatial diversity patterns of genera in the Moraceae in China. The results revealed that the patch richness, diversity index, and total shape index of the genera with multiple species were significantly higher than those of the monotypic genera. Monotypic genera had no spatial diversity and no distribution in patterns of spatial diversity. Maclura had the most concentrated spatial distribution and the lowest distribution area among the Moraceae in China. The number of patches and the total area were the smallest, while the most significant patch index was the highest. Maclura had no spatial diversity. Streblus had the highest patch abundance compared to other genera with fewer species. Streblus had the smallest number of patches and total area of distribution, the lowest spatial distribution, and a small total shape index, indicating its concentrated distribution. The values of the Shannon’s Diversity Index (SHDI) and Simpson’s Diversity Index (SIDI) were the highest, and the spatial distribution was the most diverse among the genera with fewer species. The patch type of Streblus had a more considerable value than other genera, but the number of patches was small, and the total shape index was low. Streblus was primarily distributed in the south of Yunnan, western Guangxi, the west and central parts of Hainan, and southern Guangdong. Most of these areas were mountainous. The temperature decreased with elevation, providing diverse environmental conditions for the narrow-stem genus. Among the Moraceae in China, the spatial distribution of Ficus was the most diverse, with the highest number of patches, patch types, total shape index, SHDI, and SIDI values. The spatial diversity of Ficus could be used as a protected area for Moraceae in China

The red blood cell as a mediator of endothelial dysfunction in patients with familial hypercholesterolemia and dyslipidemia

Peer reviewe

Activation of adenosine A2A but not A2B receptors is involved in uridine adenosine tetraphosphate-induced porcine coronary smooth muscle relaxation

Activation of both adenosine A2A and A2B receptors (A2BR) contributes to coronary vasodilation. We previously demonstrated that uridine adenosine tetraphosphate (Up4A) is a novel vasodilator in the porcine coronary microcirculation, acting mainly on A2AR in smooth muscle cells (SMC). We further investigated whether activation of A2BR is involved in Up4A-mediated coronary SMC relaxation. Both A2AR and A2BR may stimulate H2O2 production leading to activation of KATP channels in SMCs, we also studied the involvement of H2O2 and KATP channels in Up4A-mediated effect. Coronary small arteries dissected from the apex of porcine hearts were mounted on wire myograph for Up4A concentration responses. Up4A-induced coronary SMC relaxation was attenuated by A2AR but not A2BR antagonism or non-selective P2R antagonism, despite greater endogenous A2BR expression vs. A2AR in both coronary small arteries and primary cultured coronary SMCs. Moreover, Up4A-induced coronary SMC relaxation was blunted by H2O2 catabolism. This effect was not altered by KATP channel blockade. Combination of H2O2 catabolism and A2AR antagonism attenuated Up4A-induced coronary SMC relaxation to the similar extent as A2AR antagonism alone. Collectively, Up4A-induced porcine coronary SMC relaxation is mediated by activation of A2AR-H2O2 pathway. This process does not involve A2BR, P2R or KATP channels

How are exclusively data journals indexed in major scholarly databases? An examination of four databases

Abstract The data paper is becoming a popular way for researchers to publish their research data. The growing numbers of data papers and journals hosting them have made them an important data source for understanding how research data is published and reused. One barrier to this research agenda is a lack of knowledge as to how data journals and their publications are indexed in the scholarly databases used for quantitative analysis. To address this gap, this study examines how a list of 18 exclusively data journals (i.e., journals that primarily accept data papers) are indexed in four popular scholarly databases: the Web of Science, Scopus, Dimensions, and OpenAlex. We investigate how comprehensively these databases cover the selected data journals and, in particular, how they present the document type information of data papers. We find that the coverage of data papers, as well as their document type information, is highly inconsistent across databases, which creates major challenges for future efforts to study them quantitatively, which should be addressed in the future

Fractal Analysis of Microscale and Nanoscale Pore Structures in Carbonates Using High-Pressure Mercury Intrusion

This paper investigated fractal characteristics of microscale and nanoscale pore structures in carbonates using High-Pressure Mercury Intrusion (HPMI). Firstly, four different fractal models, i.e., 2D capillary tube model, 3D capillary tube model, geometry model, and thermodynamic model, were used to calculate fractal dimensions of carbonate core samples from HPMI curves. Afterwards, the relationships between the calculated fractal dimensions and carbonate petrophysical properties were analysed. Finally, fractal permeability model was used to predict carbonate permeability and then compared with Winland permeability model. The research results demonstrate that the calculated fractal dimensions strongly depend on the fractal models used. Compared with the other three fractal models, 3D capillary tube model can effectively reflect the fractal characteristics of carbonate microscale and nanoscale pores. Fractal dimensions of microscale pores positively correlate with fractal dimensions of the entire carbonate pores, yet negatively correlate with fractal dimensions of nanoscale pores. Although nanoscale pores widely develop in carbonates, microscale pores have greater impact on the fractal characteristics of the entire pores. Fractal permeability model is applicable in predicting carbonate permeability, and compared with the Winland permeability model, its calculation errors are acceptable