Characteristics of Familial Lung Cancer in Yunnan-Guizhou Plateau of China

Background: Lung cancer has inherited susceptibility and show familial aggregation, the characteristics of familial lung cancer exhibit population heterogeneity. Despite previous studies, familial lung cancer in China's Yunnan-Guizhou plateau remains understudied.Methods: Between 2015 and 2017, 1,023 lung cancer patients (residents of Yunnan-Guizhou plateau) were enrolled with no limitation on other parameters, 152 subjects had familial lung cancer. Clinicopathologic parameters were analyzed and compared, 4,754 lung cancer patients from NCI-GDC were used to represent a general population.Results: Familial lung cancer (FLC) subjects showed unique characters: early-onset; increased rate of female, adenocarcinoma, stage IV and other cancer history; unbalance in anatomic sites; all ruling out significant difference in smoking status. Unbalanced distribution of co-existing diseases or symptoms was also discovered. FLC patients were more likely to develop benign lesions (polyps, nodules, cysts) early in life, especially early-growth of multiple pulmonary nodules at higher frequency. Typical diseases with family history like diabetes and hypertension were also increased in FLC population. Compared to GDC data, our subject population was younger: the age peak of our FLC group was in 50–59; our sporadic group had an age peak around 60; while GDC patients' age peak was in 60–69. Importantly, the biggest difference happened in age 40–49: our FLC group and sporadic group had 3 times and 2 times higher ratio than GDC population, respectively. Moreover, the age peaks of our FLC males and FLC females were both in 50–59; while our sporadic females had the age peak in 50–59, much earlier than sporadic males (around 60–69); reflecting gender-specific or age-specific characters in our subject population.Conclusions: Familial lung cancer in China's Yunnan-Guizhou plateau showed unique clinicopathologic characters, differences were found in gender, age, histologic type, TNM stage and co-existing diseases or symptoms. Identification of hereditary factors which lead to increased lung cancer risk will be a challenge of both scientific and clinical significance

A general lithography-free method of microscale/nanoscale fabrication and patterning on Si and Ge surfaces

Here, we introduce and give an overview of a general lithography-free method to fabricate silicide and germanide micro-/nanostructures on Si and Ge surfaces through metal-vapor-initiated endoepitaxial growth. Excellent controls on shape and orientation are achieved by adjusting the substrate orientation and growth parameters. Furthermore, micro-/nanoscale pits with controlled morphologies can also be successfully fabricated on Si and Ge surfaces by taking advantage of the sublimation of silicides/germanides. The aim of this brief report is to illustrate the concept of lithography-free synthesis and patterning on surfaces of elemental semiconductors, and the differences and the challenges associated with the Si and the Ge surfaces will be discussed. Our results suggest that this low-cost bottom-up approach is promising for applications in functional nanodevices

How Risk Prevention Mechanisms Regulate Serial Entrepreneurs to Achieve Sustainable Entrepreneurship—A Policy Text Analysis

With the advent of the “Industry 4.0” era, the outbreak of the new epidemic, and the frequent occurrence of economic crises, sustainable entrepreneurship has led to the entrepreneurial ambition of serial entrepreneurs. Although a large number of supportive policies have been recently enacted by administrations at all levels to promote sustainable entrepreneurship among serial entrepreneurs, there is a lack of policy evaluation. In addition, although academics recognize the importance of policy regulation in leading sustainable entrepreneurship, in-depth research on the entrepreneurship policy system is still lacking. Based on this, this paper applied the “policy instrument–policy target” analysis framework and selected Chinese policy texts that support the sustainable entrepreneurship of serial entrepreneurs for textual content analysis. The results of this paper suggest that the synergy of various policy instruments and the appropriateness of the policy instrument–target fit need to be improved. The findings of this paper can provide a theoretical basis and practical implications for governmental entities to guide serial entrepreneurs to prevent social, economic, and environmental risks and achieve sustainable entrepreneurship goals

How Risk Prevention Mechanisms Regulate Serial Entrepreneurs to Achieve Sustainable Entrepreneurship—A Policy Text Analysis

With the advent of the “Industry 4.0” era, the outbreak of the new epidemic, and the frequent occurrence of economic crises, sustainable entrepreneurship has led to the entrepreneurial ambition of serial entrepreneurs. Although a large number of supportive policies have been recently enacted by administrations at all levels to promote sustainable entrepreneurship among serial entrepreneurs, there is a lack of policy evaluation. In addition, although academics recognize the importance of policy regulation in leading sustainable entrepreneurship, in-depth research on the entrepreneurship policy system is still lacking. Based on this, this paper applied the “policy instrument–policy target” analysis framework and selected Chinese policy texts that support the sustainable entrepreneurship of serial entrepreneurs for textual content analysis. The results of this paper suggest that the synergy of various policy instruments and the appropriateness of the policy instrument–target fit need to be improved. The findings of this paper can provide a theoretical basis and practical implications for governmental entities to guide serial entrepreneurs to prevent social, economic, and environmental risks and achieve sustainable entrepreneurship goals

How Social Network Influences the Growth of Entrepreneurial Enterprises : Perspective on Organizational and Personal Network

Network size, network density, and tie strength together determine the function of social network and affect the growth of entrepreneurial enterprises. However, how the role of network size, network density, and tie strength on the growth of entrepreneurial enterprises remains inconsistent, as well as the effect of organizational and personal network remains unclear. To solve these relationships, we employ meta-analysis to reach study goals by researching 31 independent samples from 28 references with 5,259 observations. Results have shown two main findings: (1) Both network size and tie strength have a positive and significant impact on the growth of entrepreneurial enterprises, while network density does not correlate with the growth. (2) Organizational network mainly plays a positive effect between network size and growth, while personal network plays a more significant role in the relationship of tie strength and growth than organizational network. These results promote managers to take productive strategies for entrepreneurial enterprises growth. Our study provides a meta-analysis to merge different sounds about the relationship of network properties to the growth of entrepreneurial enterprises, emphasizing moderators of organizational and personal networks among these above relationships. Thus, these findings make significant contributions to the field of entrepreneurship.Funding Agencies|National Social Science Project Foundation [20FGLB007]</p

Diversity Distribution, Driving Factors and Assembly Mechanisms of Free-Living and Particle-Associated Bacterial Communities at a Subtropical Marginal Sea

Free-living (FL) and particle-associated (PA) bacterioplankton communities play critical roles in biogeochemical cycles in the ocean. However, their community composition, assembly process and functions in the continental shelf and slope regions are poorly understood. Based on 16S rRNA gene amplicon sequencing, we investigated bacterial communities’ driving factors, assembly processes and functional potentials at a subtropical marginal sea. The bacterioplankton community showed specific distribution patterns with respect to lifestyle (free living vs. particle associated), habitat (slope vs. shelf) and depth (surface vs. DCM and Bottom). Salinity and water temperature were the key factors modulating turnover in the FL community, whereas nitrite, silicate and phosphate were the key factors for the PA community. Model analyses revealed that stochastic processes outweighed deterministic processes and had stronger influences on PA than FL. Homogeneous selection (Hos) was more responsible for the assembly and turnover of FL, while drift and dispersal limitation contributed more to the assembly of PA. Importantly, the primary contributor to Hos in PA was Gammaproteobacteria:Others, whereas that in FL was Cyanobacteria:Bin6. Finally, the PICRUSt2 analysis indicated that the potential metabolisms of carbohydrates, cofactors, amino acids, terpenoids, polyketides, lipids and antibiotic resistance were markedly enriched in PA than FL

Predicting the individual effects of team competition on college students’ academic performance in mobile edge computing

Abstract Mobile edge computing (MEC) has revolutionized the way of teaching in universities. It enables more interactive and immersive experiences in the classroom, enhancing student engagement and learning outcomes. As an incentive mechanism based on social identity and contest theories, team competition has been adopted and shown its effectiveness in improving students’ participation and motivation in college classrooms. However, despite its potential benefit, there are still many unresolved issues: What type of students and teams benefit more from team competition? In what teaching context is team competition more effective? Which competition design methods better increase student academic performance? Mobile edge computing provides the ability to obtain the data of the teaching process and analyze the causal effect between team competition and students’ academic performance. In this paper, the authors first design a randomized field experiment among freshmen enrolled in college English courses. Then, the authors analyze the observation data collected from the online teaching platform, and predict individual treatment effects of academic performance in college English through linear and nonlinear machine learning models. Finally, by carefully investigating features of teams and individual students, the prediction error is reduced by up to 30%. In addition, through interpreting the predictive models, some valuable insights regarding the practice of team competition in college classrooms are discovered