Association between adult food insecurity and self-reported asthma in the United States: NHANES 2003-2018.

OBJECTIVE: Asthma is a chronic disease of the lungs. The development of asthma is related to various risk factors. Food insecurity is a critical social determinant of health, although there is little information on the association between adult food insecurity and asthma. The purpose of this study is to explore the potential correlation in US adults. METHODS: The study population data were extracted from NHANES 2003-2018. Food insecurity was measured using the USDA FSSM and categorized as full, marginal, low, or very low food security. The assessment of self-reported asthma was determined by self-report questionnaires. The self-reported positive outcomes were that participants had asthma and a history of asthma attacks and asthma-related ER visits in the past year. We developed two multivariate logistic regression models. Stratified analyses were performed by gender and age. RESULTS: A total of 38,077 participants were considered in our final analysis. Compared to participants with FFS, the ORs (95% CIs) for asthma were 1.16 (1.00-1.33), 1.42 (1.23-1.64), and 1.56 (1.34-1.80) for participants with MFS, LFS, and VLFS, respectively (Model II). Additionally, after full adjustment, individuals with VLFS had 49% greater risks of asthma attacks (OR = 1.49; 95% CI 1.13-1.97). The ORs (95% CIs) for asthma-related ER visits were 1.59 (1.14-2.23) and 1.98 (1.36-2.87) for participants with LFS and VLFS, respectively (Model II). The positive correlations remained robust when stratified by gender and age. CONCLUSION: Our research showed that food insecurity among US adults was associated with asthma, asthma attacks, and asthma-related ER visits.

Optimal Computational Power Allocation in Multi-Access Mobile Edge Computing for Blockchain.

Blockchain has emerged as a decentralized and trustable ledger for recording and storing digital transactions. The mining process of Blockchain, however, incurs a heavy computational workload for miners to solve the proof-of-work puzzle (i.e., a series of the hashing computation), which is prohibitive from the perspective of the mobile terminals (MTs). The advanced multi-access mobile edge computing (MEC), which enables the MTs to offload part of the computational workloads (for solving the proof-of-work) to the nearby edge-servers (ESs), provides a promising approach to address this issue. By offloading the computational workloads via multi-access MEC, the MTs can effectively increase their successful probabilities when participating in the mining game and gain the consequent reward (i.e., winning the bitcoin). However, as a compensation to the ESs which provide the computational resources to the MTs, the MTs need to pay the ESs for the corresponding resource-acquisition costs. Thus, to investigate the trade-off between obtaining the computational resources from the ESs (for solving the proof-of-work) and paying for the consequent cost, we formulate an optimization problem in which the MTs determine their acquired computational resources from different ESs, with the objective of maximizing the MTs' social net-reward in the mining process while keeping the fairness among the MTs. In spite of the non-convexity of the formulated problem, we exploit its layered structure and propose efficient distributed algorithms for the MTs to individually determine their optimal computational resources acquired from different ESs. Numerical results are provided to validate the effectiveness of our proposed algorithms and the performance of our proposed multi-access MEC for Blockchain.

Optimal Resource Allocation for Uplink Data Collection in Nonorthogonal Multiple Access Networks.

Accommodating massive connectivity for Internet of Things (IoT) applications is considered an important goal of future 5G cellular systems. Nonorthogonal multiple access (NOMA), which enables a group of mobile users to simultaneously share the same spectrum channel for transmission, provides an efficient approach to achieve the goals of spectrum-efficient data delivery. In this paper, we consider an uplink transmission in a sensor network in which a group of smart terminals (e.g., sensors) use NOMA to send their collected data to an access point. We aim to minimize the total radio resource consumption cost, including the cost for the channel usage and the cost for all senors' energy consumption to allow the sensors to complete their data delivery requirements. Specifically, we formulate a joint optimization of the decoding-order, transmit-power and time allocations to study this problem and propose an efficient algorithm to find the optimal solution. Numerical results are provided to validate our proposed algorithm and the performance advantage of our proposed joint optimization for the uplink data collection via NOMA transmission.

Inhibition of Kelch-like epichlorohydrin-related protein 1 promotes the progression and drug resistance of lung adenocarcinoma.

BACKGROUND: Lung cancer is a common malignant carcinoma of respiratory system with high morbidity and mortality. Kelch-like epichlorohydrin-related protein 1 (Keap1), a member of the BTB-Kelch protein family, has been reported as an important molecule in several cancers. However, its potential role in tumor is still controversial. Here we aim to clarify the effect of Keap1 on the biological characteristics and chemotherapy resistance in lung adenocarcinoma (LUAD). METHODS: Immunohistochemistry was conducted to compare Keap1 expression in lung adenocarcinoma tissues and matched non-cancerous tissues, and the correlation between Keap1 expression and clinicopathological features was analyzed. Subsequently, the stable A549 and H1299 cell lines with Keap1 knockdown or overexpression were constructed using lentivirus. The roles of Keap1 on the cell proliferation, migration, invasion and drug resistance were investigated by colony formation assay, cell proliferation assay, wound scratch test, transwell invasion assay and drug sensitivity assay, respectively. RESULTS: Keap1 was lowly expressed in tumor tissues compared to matched non-cancerous tissues, and its expression was correlated with TNM stage and lymph node metastasis. Early stage (I) tumors without lymph node metastasis had higher levels of Keap1 expression compared with late-stage tumors (II, III) with the presence of lymphatic metastasis. Colony formation assays showed that Keap1 knockdown promoted the proliferation of A549 and H1299 cells, and the cell growth curves further confirmed this feature. In contrast, wound scratch and transwell invasion experiments showed that Keap1 overexpression inhibited cell migration and invasive malignancy. The IC50 for cisplatin and paclitaxel were significantly increased by Keap1 knockdown in A549 and H1299 cell lines. CONCLUSION: Keap1 knockdown promotes tumor cell growth, proliferation, invasion, metastasis and chemotherapy resistance in LUAD. It may be a potential tumor marker to guide the staging and treatment of lung cancer.