MSCET : a multi-scenario offloading schedule for biomedical data processing and analysis in cloud-edge-terminal collaborative vehicular networks

With the rapid development of Artificial Intelligence (AI) and Internet of Things (IoTs), an increasing number of computation intensive or delay sensitive biomedical data processing and analysis tasks are produced in vehicles, bringing more and more challenges to the biometric monitoring of drivers. Edge computing is a new paradigm to solve these challenges by offloading tasks from the resource-limited vehicles to Edge Servers (ESs) in Road Side Units (RSUs). However, most of the traditional offloading schedules for vehicular networks concentrate on the edge, while some tasks may be too complex for ESs to process. To this end, we consider a collaborative vehicular network in which the cloud, edge and terminal can cooperate with each other to accomplish the tasks. The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge. We further construct the virtual resource pool which can integrate the resource of multiple ESs since some regions may be covered by multiple RSUs. In this paper, we propose a Multi-Scenario offloading schedule for biomedical data processing and analysis in Cloud-Edge-Terminal collaborative vehicular networks called MSCET. The parameters of the proposed MSCET are optimized to maximize the system utility. We also conduct extensive simulations to evaluate the proposed MSCET and the results illustrate that MSCET outperforms other existing schedules. © 2004-2012 IEEE

Effects of 5-aminolevulinic Acid on the Photosynthesis, Antioxidant System, and α-Bisabolol Content of Matricaria recutita

Matricaria recutita is a widely used medicinal plant with broad pharmacological effects, and α-bisabolol is the main active ingredient of this plant. To improve its α-bisabolol content, M. recutita was sprayed with different concentrations (1.0, 2.0,and 4.0 mmol.L−1) of 5-aminolevulinic acid (ALA) or with water as a control to study the effects of ALA treatment on the photosynthesis, antioxidant system, and α-bisabolol content of M. recutita. Results showed that the photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO2 concentration, soluble protein, total amino acids, soluble sugar, and α-bisabolol of M. recutita were significantly increased. Moreover, the activities of superoxide dismutase, peroxidase, and catalase of M. recutita were also enhanced by ALA treatment. Optimal results were obtained when the concentration of ALA was 2.0 mmol.L−1. Results showed that ALA treatment could improve the α-bisabolol content of M. recutita, and the underlying physiological mechanism was analyzed. ALA treatment was an effective measure for improving the medicinal value of M. recutita

Do Chinese Traditional and Modern Cultures Affect Young Adults’ Moral Priorities?

Dramatic cultural change has occurred in Mainland China over the past four decades, yet little is known about how this cultural shift impacts Chinese peoples’ moral values. The present research aims to fill this gap by examining whether Chinese traditional and modern cultures influence young adults’ moral judgments. Study 1 investigated the relation between psychological traditionality/modernity and moral concerns. Results indicated that participants who strongly endorsed Chinese traditional culture prioritize relationship concern rather than justice concern. Study 2 used the cultural priming method and tested the effects of traditional and modern icons on moral concerns. Results suggested that participants who were primed with traditional or modern or neutral icons did not give priority to relationship or justice concern. Together, our findings provide initial empirical evidence on whether Chinese traditional and modern cultures shift the moral mindsets of bicultural young Chinese among alternative (and even competing) moral codes

COVID-19 vaccination willingness among people living with HIV in Shijiazhuang, China: a cross-sectional survey

ObjectivesThe COVID-19 pandemic imposed an enormous disease and economic burden worldwide. SARS-CoV-2 vaccination is essential to containing the pandemic. People living with HIV (PLWH) may be more vulnerable to severe COVID-19 outcomes; thus, understanding their vaccination willingness and influencing factors is helpful in developing targeted vaccination strategies.MethodsA cross-sectional study was conducted between 15 June and 30 August 2022 in Shijiazhuang, China. Variables included socio-demographic characteristics, health status characteristics, HIV-related characteristics, knowledge, and attitudes toward COVID-19 vaccination and COVID-19 vaccination status. Multivariable logistic regression was used to confirm factors associated with COVID-19 vaccination willingness among PLWH.ResultsA total of 1,428 PLWH were included, with a 90.48% willingness to receive the COVID-19 vaccination. PLWH were more unwilling to receive COVID-19 vaccination for those who were female or had a fair/poor health status, had an allergic history and comorbidities, were unconvinced and unsure about the effectiveness of vaccines, were unconvinced and unsure about the safety of vaccines, were convinced and unsure about whether COVID-19 vaccination would affect ART efficacy, or did not know at least a type of domestic COVID-19 vaccine. Approximately 93.00% of PLWH have received at least one dose of the COVID-19 vaccine among PLWH, and 213 PLWH (14.92%) reported at least one adverse reaction within 7 days.ConclusionIn conclusion, our study reported a relatively high willingness to receive the COVID-19 vaccination among PLWH in Shijiazhuang. However, a small number of PLWH still held hesitancy; thus, more tailored policies or guidelines from the government should be performed to enhance the COVID-19 vaccination rate among PLWH

Should human papillomavirus vaccination target women over age 26, heterosexual men and men who have sex with men? A targeted literature review of cost-effectiveness.

BACKGROUND: Human papillomavirus (HPV) vaccination for young women up to age 26 is highly cost-effective and has been implemented in 65 countries globally. We investigate the cost-effectiveness for HPV vaccination program in older women (age > 26 years), heterosexual men and men who have sex with men (MSM). METHOD: A targeted literature review was conducted on PubMed for publications between January 2000 and January 2017 according to the PRISMA guidelines. We included English-language articles that reported the incremental cost-effectiveness ratio (ICER) of HPV vaccination programs for women over age 26, heterosexual men, and MSM and identified the underlying factors for its cost-effectiveness. RESULTS: We included 36 relevant articles (six, 26 and four in older women, heterosexual men and MSM, respectively) from 17 countries (12 high-income (HICs) and five low- and middle-income (LMICs) countries). Most (4/6) studies in women over age 26 did not show cost-effectiveness ($65,000-192,000/QALY gained). Two showed cost-effectiveness, but only when the vaccine cost was largely subsidised and protection to non-naïve women was also considered. Sixteen of 26 studies in heterosexual men were cost-effective (ICER =$19,600-52,800/QALY gained in HICs; $49-5,860/QALY gained in LMICs). Nonavalent vaccines, a low vaccine price, fewer required doses, and a long vaccine protection period were key drivers for cost-effectiveness. In contrast, all four studies on MSM consistently reported cost-effectiveness (ICER =$15,000-$43,000/QALY gained), particularly in MSM age < 40 years and those who were HIV-positive. Countries' vaccination coverage did not significantly correlate with its per-capita Gross National Income. CONCLUSION: Targeted HPV vaccination for MSM should be next priority in HPV prevention after having established a solid girls vaccination programme. Vaccination for heterosexual men should be considered when 2-dose 4vHPV/9vHPV vaccines become available with a reduced price, whereas targeted vaccination for women over age 26 is unlikely to be cost-effective

Disentangling land model uncertainty via Matrix-based Ensemble Model Inter-comparison Platform (MEMIP)

Background Large uncertainty in modeling land carbon (C) uptake heavily impedes the accurate prediction of the global C budget. Identifying the uncertainty sources among models is crucial for model improvement yet has been difficult due to multiple feedbacks within Earth System Models (ESMs). Here we present a Matrix-based Ensemble Model Inter-comparison Platform (MEMIP) under a unified model traceability framework to evaluate multiple soil organic carbon (SOC) models. Using the MEMIP, we analyzed how the vertically resolved soil biogeochemistry structure influences SOC prediction in two soil organic matter (SOM) models. By comparing the model outputs from the C-only and CN modes, the SOC differences contributed by individual processes and N feedback between vegetation and soil were explicitly disentangled. Results Results showed that the multi-layer models with a vertically resolved structure predicted significantly higher SOC than the single layer models over the historical simulation (1900–2000). The SOC difference between the multi-layer models was remarkably higher than between the single-layer models. Traceability analysis indicated that over 80% of the SOC increase in the multi-layer models was contributed by the incorporation of depth-related processes, while SOC differences were similarly contributed by the processes and N feedback between models with the same soil depth representation. Conclusions The output suggested that feedback is a non-negligible contributor to the inter-model difference of SOC prediction, especially between models with similar process representation. Further analysis with TRENDY v7 and more extensive MEMIP outputs illustrated the potential important role of multi-layer structure to enlarge the current ensemble spread and the necessity of more detail model decomposition to fully disentangle inter-model differences. We stressed the importance of analyzing ensemble outputs from the fundamental model structures, and holding a holistic view in understanding the ensemble uncertainty

COVID-19 vaccination status, side effects, and perceptions among breast cancer survivors: a cross-sectional study in China

IntroductionBreast cancer is the most prevalent malignancy in patients with coronavirus disease 2019 (COVID-19). However, vaccination data of this population are limited.MethodsA cross-sectional study of COVID-19 vaccination was conducted in China. Multivariate logistic regression models were used to assess factors associated with COVID-19 vaccination status.ResultsOf 2,904 participants, 50.2% were vaccinated with acceptable side effects. Most of the participants received inactivated virus vaccines. The most common reason for vaccination was “fear of infection” (56.2%) and “workplace/government requirement” (33.1%). While the most common reason for nonvaccination was “worry that vaccines cause breast cancer progression or interfere with treatment” (72.9%) and “have concerns about side effects or safety” (39.6%). Patients who were employed (odds ratio, OR = 1.783, p = 0.015), had stage I disease at diagnosis (OR = 2.008, p = 0.019), thought vaccines could provide protection (OR = 1.774, p = 0.007), thought COVID-19 vaccines were safe, very safe, not safe, and very unsafe (OR = 2.074, p &lt; 0.001; OR = 4.251, p &lt; 0.001; OR = 2.075, p = 0.011; OR = 5.609, p = 0.003, respectively) were more likely to receive vaccination. Patients who were 1–3 years, 3–5 years, and more than 5 years after surgery (OR = 0.277, p &lt; 0.001; OR = 0.277, p &lt; 0.001, OR = 0.282, p &lt; 0.001, respectively), had a history of food or drug allergies (OR = 0.579, p = 0.001), had recently undergone endocrine therapy (OR = 0.531, p &lt; 0.001) were less likely to receive vaccination.ConclusionCOVID-19 vaccination gap exists in breast cancer survivors, which could be filled by raising awareness and increasing confidence in vaccine safety during cancer treatment, particularly for the unemployed individuals

Identification of a six-gene signature to predict survival and immunotherapy effectiveness of gastric cancer

BackgroundGastric cancer (GC) ranks as the fifth most prevalent malignancy and the second leading cause of oncologic mortality globally. Despite staging guidelines and standard treatment protocols, significant heterogeneity exists in patient survival and response to therapy for GC. Thus, an increasing number of research have examined prognostic models recently for screening high-risk GC patients.MethodsWe studied DEGs between GC tissues and adjacent non-tumor tissues in GEO and TCGA datasets. Then the candidate DEGs were further screened in TCGA cohort through univariate Cox regression analyses. Following this, LASSO regression was utilized to generate prognostic model of DEGs. We used the ROC curve, Kaplan-Meier curve, and risk score plot to evaluate the signature’s performance and prognostic power. ESTIMATE, xCell, and TIDE algorithm were used to explore the relationship between the risk score and immune landscape relationship. As a final step, nomogram was developed in this study, utilizing both clinical characteristics and a prognostic model.ResultsThere were 3211 DEGs in TCGA, 2371 DEGs in GSE54129, 627 DEGs in GSE66229, and 329 DEGs in GSE64951 selected as candidate genes and intersected with to obtain DEGs. In total, the 208 DEGs were further screened in TCGA cohort through univariate Cox regression analyses. Following this, LASSO regression was utilized to generate prognostic model of 6 DEGs. External validation showed favorable predictive efficacy. We studied interaction between risk models, immunoscores, and immune cell infiltrate based on six-gene signature. The high-risk group exhibited significantly elevated ESTIMATE score, immunescore, and stromal score relative to low-risk group. The proportions of CD4+ memory T cells, CD8+ naive T cells, common lymphoid progenitor, plasmacytoid dentritic cell, gamma delta T cell, and B cell plasma were significantly enriched in low-risk group. According to TIDE, the TIDE scores, exclusion scores and dysfunction scores for low-risk group were lower than those for high-risk group. As a final step, nomogram was developed in this study, utilizing both clinical characteristics and a prognostic model.ConclusionIn conclusion, we discovered a 6 gene signature to forecast GC patients’ OS. This risk signature proves to be a valuable clinical predictive tool for guiding clinical practice