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This study aims to evaluate the effect of social capital (SC), social support (SS), and social network formation (SNF) on the quality of life of American adults during COVID-19. Using a probability sample of American adults aged 49+, 2370 respondents were selected from the National Social Life Health and Aging Project (NSHAP) dataset for analysis using an integrated partial least squares based on structural equation modeling (PLS-SEM)-K-fold cross-validation approach. The analysis showed that social capital assessed using civic engagement, social cohesion, socioeconomic status (SES), social support, and social network formation were significantly and positively associated with American adults quality of life during the COVID-19 pandemic. Furthermore, the results showed that using the PLS-SEM and K-fold cross-validation approach produced a medium predictive power of the overall model, confirming the importance of SC, SS, and SNF in predicting quality of life-outcomes. These findings suggest that efforts to promote the well-being of American adults, especially older adults, during the pandemic should focus on strengthening social capital, social support and social network formation.

We have been presented the properties of asset return by simulation within the empirical data. However, is it possible to illustrate properties by statistical analysis? Most currently existing models fail to reproduce all these statistical features. In this paper, we will elaborate the properties by applying different statistical models: Geometric Brownian Motion and Ehrenfest URN. We will focus on the following properties: distributional properties, tail properties and extreme fluctuations, path-wise regularity, linear and nonlinear dependence of returns in time and across stocks. In this project, I will use S&P 500 index return as the data and apply it with the models to compare the results with empirical data.

Background Population aging is getting worse in our country. Family doctor contract service plays an important role in boosting the construction of hierarchical diagnosis and treatment system and establishing a reasonable and orderly medical order. Current research about family doctor contract service policy mainly focus on qualitative evaluation, and there are few researchers use tools to quantitatively evaluate each individual representative policy. Objective This study aims to quantitatively evaluate the pros and cons of six Chinese central government policies about family doctor contract service, thus, proposing strategies and measures to promote the high-quality development of our country's family doctor contract service, and helping the construction of healthy China. Methods We searched Peking University's PKULAW.com and websites of some relevant ministries of the State Council of China from January 1, 2015 to April 30, 2022. The key word was "family doctor". The software ROSTCM 6.0 was used for text mining. Based on the results, this study selected central government policies about family doctor contract services, then used the PMC index model to quantitatively evaluate these policies. Results This study included thirty-two policies based on inclusion and exclusion criteria. The top five high-frequency keywords in the field of family doctor services are "contract service" (n=274) , "health" (n=272) , "medical" (n=264) , "family doctor" (n=225) , and "contract" (n=180) . They were marked as P1-P6, respectively. In terms of methods and other aspects, the scores of each dimension are relatively high. The results of quantitative evaluation showed that the ranking of policies is P1>P3>P2>P6>P4>P5. Three policies were rated as excellent, the other three were rated as acceptable. The scores were relatively high in the policy content, policy nature, policy evaluation, policy field and policy role. Conclusion Our country's family doctor contract service policy had a relatively broad content and is relatively mature. It is suggested to pay attention to the combination of long-term, medium-term and short-term validity of the policies, improve incentive approaches from multiple perspectives, enhance the sense of professional honor of family doctors, and use a variety of policy tools and policy action.

Background: With the application of immune checkpoint inhibitors (ICIs) and the discovery of the synergistic effect of radiotherapy and immunotherapy, the intracranial benefit of thoracic radiotherapy (TRT) is receiving signiffcant clinical attention. The purpose of this study was to analyze the cranial benefits of ICIs and TRT in patients with extensive-stage small cell lung cancer (ES-SCLC) without baseline brain metastases (BMs). Materials and methods: From August 2019 to August 2022, data from patients diagnosed with ES-SCLC without baseline BMs were retroactively recorded. The Kaplan‒Meier method was used to calculate overall survival (OS), progression-free survival (PFS), and brain metastasis-free survival (BMFS), and the differences between the treatment groups were compared with the log-rank test. Risk factors associated with OS were analyzed via the Cox regression model. Results: A total of 216 patients were included, with a median follow-up of 24.73 months. Among these patients, 137 (63.4%) received first-line ICIs combined with chemotherapy (ChT), including 32 patients treated with anti-programmed death 1 antibody (αPD-1) and 105 patients treated with anti-programmed death-ligand 1 antibody (αPD-L1), and 79 patients (36.6%) received first-line ChT alone. Compared with the ChT-alone group, the ICI + ChT group demonstrated significantly improved PFS (8.07 vs. 6.87 months; p < 0.001) and OS (19.83 vs. 13.80 months; p = 0.001). The addition of ICIs to the ChT regimen did not significantly delay the onset of BMs compared to that with ChT alone (16.93 vs. 12.67 months; p = 0.379). Notably, the addition of TRT to the αPD-L1 + ChT regimen significantly prolonged BMFS compared to that without TRT (20.27 vs. 8.80 months; p = 0.045). Conclusion: In patients with ES-SCLC without baseline BMs, first-line chemoimmunotherapy significantly improves PFS and OS. However, it does not delay intracranial metastasis. The addition of TRT to αPD-L1 + ChT therapy significant delays the development of BMs. Clinical trial number: Not applicable. [ABSTRACT FROM AUTHOR]

Coarse-grained molecular dynamics simulations are employed to investigate the spatiotemporal evolution of vesicles (polymersomes) through the self-assembly of randomly distributed amphiphilic BAB triblock copolymers with hydrophilic A and hydrophobic B blocks in an aqueous solution. The vesiculation pathway consists of several intermediate structures, such as an interconnected network of copolymer aggregates, a cage of cylindrical micelles, and a lamellar cage. The cage-to-vesicle transition occurs at a constant aggregation number and practically eliminates the hydrophobic interfacial area between the B block and solvent. Molecular reorganization underlying the sequence of morphology transitions from a cage-like aggregate to a vesicle is nearly isentropic. The end-to-end distances of isolated copolymer chains in solution and those within a vesicular assembly follow lognormal probability distributions. This can be attributed to the preponderance of folded chain configurations in which the two hydrophobic end groups of a given chain stay close to each other. However, the probability distribution of end-to-end distances is broader for chains within the vesicle as compared with that of a single chain. This is due to the swelling of the folded configurations within the hydrophobic bilayer. Increasing the hydrophobicity of the B block reduces the vesiculation time without qualitatively altering the self-assembly pathway. [ABSTRACT FROM AUTHOR]