Phase Engineering of Nanomaterials: Transition Metal Dichalcogenides.

Crystal phase, a critical structural characteristic beyond the morphology, size, dimension, facet, etc., determines the physicochemical properties of nanomaterials. As a group of layered nanomaterials with polymorphs, transition metal dichalcogenides (TMDs) have attracted intensive research attention due to their phase-dependent properties. Therefore, great efforts have been devoted to the phase engineering of TMDs to synthesize TMDs with controlled phases, especially unconventional/metastable phases, for various applications in electronics, optoelectronics, catalysis, biomedicine, energy storage and conversion, and ferroelectrics. Considering the significant progress in the synthesis and applications of TMDs, we believe that a comprehensive review on the phase engineering of TMDs is critical to promote their fundamental studies and practical applications. This Review aims to provide a comprehensive introduction and discussion on the crystal structures, synthetic strategies, and phase-dependent properties and applications of TMDs. Finally, our perspectives on the challenges and opportunities in phase engineering of TMDs will also be discussed.

YiQi GuBen capsule alleviates OVA-induced asthma through improving mitochondrial dysfunction.

Objective: This study aims to explore the effect of YiQi GuBen capsule on improving mitochondrial dysfunction in an animal model of asthma.Methods: The mice (n = 8) were divided into four groups including control (NC), ovalbumin (OVA), dexamethasone (OVA + DEX), and YiQi GuBen (OVA + YQGB) groups. Firstly, we established an OVA-induced mouse asthma model except for the NC group, which then were treated with dexamethasone and YiQi GuBen capsule. Subsequently, HE staining and Masson staining were used for pathological analysis of mice lung tissues. Next, we used transmission electron microscopy (TEM) to observe the effect of the Yiqi Guben capsule on the ultrastructure of mitochondria. Flow cytometry was used to analyze the ROS level, membrane potential, and the number of mitochondria in lung tissue. Moreover, we analyzed the copy number of mitochondrial DNA (mtDNA) and the expression levels of activator peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and mitochondrial transcription factor A (TFAM).Results: The results of the pathological analysis showed that after treatment with the YiQi GuBen capsule, the lung tissue damage was significantly reduced. In addition, we observed that the ultrastructural damage of mitochondria was improved. Flow cytometry proved that after treatment with the YiQi GuBen capsule, the level of ROS in the mitochondria was effectively reduced, while the mitochondrial membrane potential decreased and the number increased significantly. Moreover, we found that the copy number of mtDNA was significantly increased and the expression levels of PGC-1α and TFAM were significantly upgraded.Conclusion: This study suggests YiQi GuBen capsule can effectively improve mitochondrial dysfunction in the OVA-induced mouse model.

Thermal Decomposition Mechanism of P(DAC-AM) with Serial Cationicity and Intrinsic Viscosity.

The thermal decomposition of the thermodynamic, kinetic and mechanisms of copolymer P(DAC-AM) samples with serial cationicity and intrinsic viscosity ([η]), and the control samples of homopolymer PAM and PDAC, were studied and analyzed using TG, DSC, FTIR. The results of the thermal decomposition thermodynamics confirmed that the thermal decomposition processes of the serial P(DAC-AM) samples and the two control samples could be divided into two stages. It was found that the processes of the copolymer P(DAC-AM) samples were not a simple superposition of those of homopolymers, whose monomers had composed the unit structures of the copolymer, but there were interactions between the two suspension groups. The results of thermal decomposition kinetics showed that the apparent activation energy (E) of the thermal decomposition process of all polymer samples had different varying trends in the terms of weight-loss rate (α). The reaction order (n) of the thermal decomposition of P(DAC-AM) in Stage I and II was close to 1, but in the former and the latter it tended to be 2 and 0.5, respectively. Finally, the thermal decomposition mechanism of copolymer P(DAC-AM) samples was discussed. The above research could not only fill in the knowledge vacancy of the thermal decomposition of the thermodynamic, kinetic and mechanisms of P(DAC-AM), but could also lay a foundation for the study of thermal decomposition mechanisms of the other types of polymers, including cationic polymers.

Event-triggered finite-time formation tracking of multi-agent systems with mismatched disturbances under switching topologies.

The formation tracking of the leader-follower multi-agent systems (MASs) under switching topologies is investigated. The considered system is exposed to both the mismatched and matched disturbances in the dynamics of the leader and followers, which places higher requirements for the robustness of the control protocol. In the presence of disturbances and leader's unknown control input, an innovative distributed observer embedded with robust terms is designed firstly to estimate leader's states in finite time. Taking account of the switching topologies, a novel analysis scheme that divides the convergence process into two stages is proposed to establish the finite-time (FT) convergence of estimation errors. Then, by virtue of a constructed auxiliary variable, a FT controller with an event-triggered mechanism is put forward, in which multiple robust feedback terms are designed wisely to suppress the mismatched and matched disturbances effectively. As a result, the FT formation tracking can be achieved with saved resources, despite perturbed environments and switching topologies. Simulation examples are presented to confirm the effectiveness of the proposed algorithm.

Prediction of potential suitable habitats in the 21st century and GAP analysis of priority conservation areas of Chionanthus retusus based on the MaxEnt and Marxan models.

Chionanthus retusus (C. retusus) has a high economic and medicinal value, but in recent years it has been included in the list of China's major protected plants and China's Red List of Biodiversity due to the serious destruction of its wild germplasm resources. Based on 131 sample points of C. retusus, this study simulated potential habitats and spatial changes of C. retusus in the 21st century using the Maxent model combined with the geographic information system ArcGIS, predicted prioritized protected areas by the Marxan model, and assessed current conservation status through GAP analysis. The results showed that (1) when the regularization multiplier was 1.5 and the feature combinations were linear, quadratic, and fragmented, the area under the curve of the subjects in the training and test sets were both above 0.9, the true skill statistic value was 0.80, and the maximum Kappa value was 0.62, meaning that the model had high accuracy; (2) Temperature seasonality, annual precipitation, min temperature for coldest month, and precipitation of wettest month had relatively strong influences on species' ranges. (3) The moderately and optimally suitable habitats of C. retusus were primly located in the areas of southwestern Shanxi, central Hebei, western Henan, Shandong, Shaanxi, Anhui and Hubei; (4) Under different future climate scenarios, the area of each class of suitable habitat will increase for varied amounts compared to the current period, with a general trend of expansion to the south; (5) The C. retusus priority protected areas were mainly located in most of Shandong, southern Liaoning, southwestern Shanxi, western Henan, and central Hebei, and its conservation vacancy area was relatively large compared to its protected area. These results will provide scientific strategies for implementing long-term conservation of C. retusus in China and similar regions under warming conditions in the 21st century.

Potential habitat areas and priority protected areas of Tilia amurensis Rupr in China under the context of climate change.

Introduction: Tilia amurensis Rupr (T. amurensis) is one endangered and national class II key protected wild plant in China. It has ornamental, material, economic, edible and medicinal values. At present, the resources of T. amurensis are decreasing, and the prediction of the distribution of its potential habitat in China can provide a theoretical basis for the cultivation and rational management of this species. Methods: In this study, the R language was used to evaluate 358 distribution records and 38 environment variables. The MaxEnt model was used to predict the potential distribution areas of T. amurensis under the current and future climate scenarios. The dominant environmental factors affecting the distribution of T. amurensis were analyzed and the Marxan model was used to plan the priority protected areas of this species. Results: The results showed that Bio18, Slope, Elev, Bio1, Bio9 and Bio2 were the dominant environmental factors affecting the distribution of T. amurensis. Under the future climatic scenarios, the potential suitable areas for T. amurensis will mainly distribute in the Northeast China, the total suitable area will reduce compared with the current climate scenarios, and the general trend of the centroid of suitable habitat will be towards higher latitudes. The SPF value of the best plan obtained from the priority conservation area planning was 1.1, the BLM value was 127,616, and the priority conservation area was about 57.61×104 km2. The results suggested that climate, soil and topographic factors jointly affected the potential geographical distribution of T. amurensis, and climate and topographic factors had greater influence than soil factors. Discussion: The total suitable area of T. amurensis in China under different climate scenarios in the future will decrease, so more effective protection should be actively adopted.

The relationship between human blood metabolites and preeclampsia-eclampsia: A Mendelian randomization study.

Preeclampsia and eclampsia are serious complications of pregnancy, leading to high rates of maternal and neonatal mortality. During pregnancy, there are changes in relevant serum metabolites in women. However, it remains unclear if these serum metabolites contribute to the development of associated disorders during pregnancy. Therefore, we conducted a Mendelian randomization study to explore the causal relationship between serum metabolites and preeclampsia and eclampsia. We utilized the inverse variance weighted model as our primary analysis approach. We complemented this with sensitivity analyses, including the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis, to ensure the robustness of our findings. Furthermore, we conducted linkage disequilibrium score regression, multivariable Mendelian randomization, and metabolic pathway analysis to further explore the genetic data. The Mendelian randomization analysis has identified γ-glutamylglutamine, inosine, and isoleucine 10 metabolites that are significantly associated with preeclampsia, and γ-glutamylglutamine and phenylacetate 8 metabolites that may potentially contribute to the development of eclampsia. Notably, γ-glutamylglutamine has been found to have a causal relationship with both preeclampsia and eclampsia. In the multivariable Mendelian randomization analysis, our research findings suggest that both isoleucine and X-14304-leucylalanine directly impact preeclampsia within the context of amino acids and peptides. Moreover, our observations reveal that carbohydrates can also have a direct effect on preeclampsia. Importantly, it should be emphasized that only 3-lactate in amino acids has been shown to have a direct influence on eclampsia. This research has the potential to enhance our understanding of the biological variances related to disease status, providing a foundation for future investigations.

The potential habitat of Angelica dahurica in China under climate change scenario predicted by Maxent model.

Since the 20th century, global climate has been recognized as the most important environmental factor affecting the distribution of plants. Angelica dahurica (A. dahurica) has been in great demand as a medicinal herb and flavoring, but the lack of seed sources has hindered its development. In this study, we utilized the Maxent model combined with Geographic Information System (GIS) to predict the potential habitat of A. dahurica in China based on its geographical distribution and 22 environmental factors. This prediction will serve as a valuable reference for the utilization and conservation of A. dahurica resources.The results indicated that: (1) the Maxent model exhibited high accuracy in predicting the potential habitat area of A. dahurica, with a mean value of the area under the ROC curve (AUC) at 0.879 and a TSS value above 0.6; (2) The five environmental variables with significant effects were bio6 (Min temperature of the coldest month), bio12 (Annual Precipitation), bio17 (Precipitation of Driest Quarter), elevation, and slope, contributing to a cumulative total of 89.6%. Suitable habitats for A. dahurica were identified in provinces such as Yunnan, Guizhou, Guangxi, Sichuan, Hunan, and others. The total area of suitable habitat was projected to increase, with expansion primarily in middle and high latitudes, while areas of decrease were concentrated in lower latitudes. Under future climate change scenarios, the centers of mass of suitable areas for A. dahurica were predicted to shift towards higher latitudes in the 2050s and 2090s, particularly towards the North China Plain and Northeast Plain. Overall, it holds great significance to utilize the Maxent model to predict the development and utilization of A. dahurica germplasm resources in the context of climate change.

Prediction of potential invasion of two weeds of the genus Avena in Asia under climate change based on Maxent.

Avena sterilis L. (A. sterilis) and Avena ludoviciana Dur. (A. ludoviciana) are extremely invasive weeds with strong competitive ability and multiple transmission routes. Both species can invade a variety of dryland crops, including wheat, corn, and beans. Asia, as the world's major food-producing continent, will experience significant losses to agricultural production if it is invaded by these weeds on a large scale. This study used the MaxEnt model and ArcGIS to map the distribution of suitable habitats of the two species in Asia under climate change conditions. The constructed model comprised four levels, with a total of 25 index-level indicator factors used to evaluate the invasion risk of the two species. The results showed that the distribution of suitable habitats for both Avena species was highly dependent on precipitation and temperature. Under climate warming conditions, although overall the total suitable area is predicted to decrease compared to the current period, there are still moderately or highly suitable areas. Asian countries need to provide early warning for areas with significant increases in moderate and highly suitable zones for these two species of weeds under the background of climate change. If there is already an invaded area or if the suitability of the original area is increased, this should be closely monitored, and control measures should be taken to prevent further spread and deterioration.