How does an innovative decision-making scheme affect the high-quality economic development driven by green finance and higher education?

This research examines the various elements that contribute to the achievement of high-quality economic development (HQED) in China. Specifically, it explores the influence of several major indices, such as the Green Finance Index, Energy Development Index, Higher Education, Technology Market Environment, and Human Capital. In this study, we utilize a Spatial Durbin Model to examine the interdependencies and spatial linkages between various variables, and their combined impact on China's efforts towards achieving HQED. The Green Finance Index serves as an indicator of a nation's dedication to the implementation of financially sustainable practices and investments that align with environmental objectives. The Energy Development Index assesses the extent to which the energy sector contributes to both economic growth and sustainability. The significance of education and skill development in promoting economic advancement is underscored by Higher Education and Human Capital measures. The Technology Market Environment Index examines the impact of the innovation ecosystem on fostering economic growth. The empirical analysis in our study utilizes extensive data sets collected from 30 provinces and regions throughout China. In this study, we analyze the spatial and temporal interactions of the indices, considering the potential spillover effects from adjacent locations. The findings offer significant contributions to understanding the intricate interconnections among green financing, energy development, education, technology, and human capital, and their combined influence on China's continuous endeavor towards achieving high-quality economic growth. Comprehending the intricate interconnections and spatial dynamics holds paramount importance for policymakers and stakeholders who aspire to foster sustainable, inclusive, and ecologically conscientious economic development in China. The results obtained from this study possess the potential to provide valuable insights for evidence-based policy decisions and strategies aimed at promoting the nation's pursuit of HQED objectives.

Mechanically Strong, Freeze-Resistant, and Ionically Conductive Organohydrogels for Flexible Strain Sensors and Batteries.

Conductive hydrogels as promising material candidates for soft electronics have been rapidly developed in recent years. However, the low ionic conductivity, limited mechanical properties, and insufficient freeze-resistance greatly limit their applications for flexible and wearable electronics. Herein, aramid nanofiber (ANF)-reinforced poly(vinyl alcohol) (PVA) organohydrogels containing dimethyl sulfoxide (DMSO)/H2 O mixed solvents with outstanding freeze-resistance are fabricated through solution casting and 3D printing methods. The organohydrogels show both high tensile strength and toughness due to the synergistic effect of ANFs and DMSO in the system, which promotes PVA crystallization and intermolecular hydrogen bonding interactions between PVA molecules as well as ANFs and PVA, confirmed by a suite of characterization and molecular dynamics simulations. The organohydrogels also exhibit ultrahigh ionic conductivity, ranging from 1.1 to 34.3 S m-1 at -50 to 60 °C. Building on these excellent material properties, the organohydrogel-based strain sensors and solid-state zinc-air batteries (ZABs) are fabricated, which have a broad working temperature range. Particularly, the ZABs not only exhibit high specific capacity (262 mAh g-1 ) with ultra-long cycling life (355 cycles, 118 h) even at -30 °C, but also can work properly under various deformation states, manifesting their great potential applications in soft robotics and wearable electronics.

Identification of Hypertension Subgroups through Topological Analysis of Symptom-Based Patient Similarity.

OBJECTIVE: To obtain the subtypes of the clinical hypertension population based on symptoms and to explore the relationship between hypertension and comorbidities. METHODS: The data set was collected from the Chinese medicine (CM) electronic medical records of 33,458 hypertension inpatients in the Affiliated Hospital of Shandong University of Traditional Chinese Medicine between July 2014 and May 2017. Then, a hypertension disease comorbidity network (HDCN) was built to investigate the complicated associations between hypertension and their comorbidities. Moreover, a hypertension patient similarity network (HPSN) was constructed with patients' shared symptoms, and 7 main hypertension patient subgroups were identified from HPSN with a community detection method to exhibit the characteristics of clinical phenotypes and molecular mechanisms. In addition, the significant symptoms, diseases, CM syndromes and pathways of each main patient subgroup were obtained by enrichment analysis. RESULTS: The significant symptoms and diseases of these patient subgroups were associated with different damaged target organs of hypertension. Additionally, the specific phenotypic features (symptoms, diseases, and CM syndromes) were consistent with specific molecular features (pathways) in the same patient subgroup. CONCLUSION: The utility and comprehensiveness of disease classification based on community detection of patient networks using shared CM symptom phenotypes showed the importance of hypertension patient subgroups.

MicroRNA-206 inhibits the proliferation, migration and invasion of colorectal cancer cells by regulating the c-Met/AKT/GSK-3ß pathway.

An imbalance in microRNA (miRNA/miR) expression is closely associated with tumorigenesis and progression. miR-206 is downregulated in different types of tumors, including colorectal cancer (CRC). However, the effects of miR-206 on the progression of CRC, and its underlying molecular mechanisms are yet to be elucidated. The present study aimed to investigate the effects of miR-206 on the proliferation, migration and invasion of colorectal cancer cells, and determine its potential molecular mechanism. The results of the present study demonstrated that the expression levels of miR-206 and c-Met were affected in HCT116 and SW480 cells by transfected with miR-206 mimic, inhibitor or small interfering RNA-c-Met. A Dual-luciferase reporter assay was performed to identify the miRNA targets. Cell proliferation, migration and invasion assays were also performed. The results demonstrated that overexpression of miR-206 significantly decreased the viability of HCT116 and SW480 cells. The results of the Transwell assay indicated that the cell migratory and invasive abilities were inhibited following transfection with miR-206 mimic. As a target of miR-206, knockdown of c-Met significantly suppressed cell viability, migration and invasion. In addition, c-Met knockdown or overexpression of miR-206 inhibited activation of the AKT/GSK-3ß pathway. Collectively, these results suggest that miR-206 suppresses the proliferation, migration and invasion of CRC cells by targeting the c-Met/AKT/GSK-3ß pathway.

Application of artificial neural networks in detection and diagnosis of gastrointestinal and liver tumors.

As a form of artificial intelligence, artificial neural networks (ANNs) have the advantages of adaptability, parallel processing capabilities, and non-linear processing. They have been widely used in the early detection and diagnosis of tumors. In this article, we introduce the development, working principle, and characteristics of ANNs and review the research progress on the application of ANNs in the detection and diagnosis of gastrointestinal and liver tumors.