DGTTSSA: Data Gathering Technique Based on Trust and Sparrow Search Algorithm for WSNs.

Wireless Sensor Networks (WSNs) have been successfully utilized for developing various collaborative and intelligent applications that can provide comfortable and smart-economic life. This is because the majority of applications that employ WSNs for data sensing and monitoring purposes are in open practical environments, where security is often the first priority. In particular, the security and efficacy of WSNs are universal and inevitable issues. One of the most effective methods for increasing the lifetime of WSNs is clustering. In cluster-based WSNs, Cluster Heads (CHs) play a critical role; however, if the CHs are compromised, the gathered data loses its trustworthiness. Hence, trust-aware clustering techniques are crucial in a WSN to improve node-to-node communication as well as to enhance network security. In this work, a trust-enabled data-gathering technique based on the Sparrow Search Algorithm (SSA) for WSN-based applications, called DGTTSSA, is introduced. In DGTTSSA, the swarm-based SSA optimization algorithm is modified and adapted to develop a trust-aware CH selection method. A fitness function is created based on the nodes' remaining energy and trust values in order to choose more efficient and trustworthy CHs. Moreover, predefined energy and trust threshold values are taken into account and are dynamically adjusted to accommodate the changes in the network. The proposed DGTTSSA and the state-of-the-art algorithms are evaluated in terms of the Stability and Instability Period, Reliability, CHs Average Trust Value, Average Residual Energy, and Network Lifetime. The simulation results indicate that DGTTSSA selects the most trustworthy nodes as CHs and offers a significantly longer network lifetime than previous efforts in the literature. Moreover, DGTTSSA improves the instability period compared to LEACH-TM, ETCHS, eeTMFGA, and E-LEACH up to 90%, 80%, 79%, 92%, respectively, when BS is located at the center, up to 84%, 71%, 47%, 73%, respectively, when BS is located at the corner, and up to 81%, 58%, 39%, 25%, respectively, when BS is located outside the network.

Expression of Long Noncoding RNA, HOTAIR, and MicroRNA-205 and Their Relation to Transforming Growth Factor ß1 in Patients with Alopecia Areata.

Introduction: Alopecia areata (AA) is a common autoimmune condition that affects anagen hair follicles. The most commonly recognized theory is that it is a T-cell-mediated autoimmune disorder in a genetically susceptible individual. MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) were thought to play a function in the pathogenesis. The expression of lncRNA HOTAIR and miRNA-205 and their relation to transforming growth factor ß1 (TGF-ß1) in AA were not studied. Aim: The aim of the studywas to evaluate the role of miRNA-205, lncRNA, HOTAIR, and TGF-ß1 levels in AA pathogenesis, clinical course, and severity of AA. Methods: Two groups of subjects were included in this case-control study: 50 patients with AA and 50 healthy matched controls. miRNA-205 and lncRNA HOTAIR expression levels were assayed using quantitative RT-PCR, while serum levels of TGF-ß1 were assayed using ELISA techniques. Results: The serum expression of lncRNA HOTAIR was significantly downregulated in AA patients with a p value < 0.001, while the serum expression of both miRNA-205 and TGF-ß1 were significantly upregulated in patients. Discussion/Conclusion: This study highlights the potential role of high serum expression of miRNA-205 and TGF-ß1 and the low serum expression of lncRNA HOTAIR in AA pathogenesis. This could be used as a therapeutic target to treat AA.

Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector.

Artificial Intelligent (AI) applications in e-health have evolved considerably in the last 25 years. To track the current research progress in this field, there is a need to analyze the most recent trend of adopting AI applications in e-health. This bibliometric analysis study covers AI applications in e-health. It differs from the existing literature review as the journal articles are obtained from the Scopus database from its beginning to late 2021 (25 years), which depicts the most recent trend of AI in e-health. The bibliometric analysis is employed to find the statistical and quantitative analysis of available literature of a specific field of study for a particular period. An extensive global literature review is performed to identify the significant research area, authors, or their relationship through published articles. It also provides the researchers with an overview of the work evolution of specific research fields. The study's main contribution highlights the essential authors, journals, institutes, keywords, and states in developing the AI field in e-health.

MicroRNA-22 Level in Patients with Multiple Sclerosis and Its Relationship with Vitamin D and Vitamin D Receptor Levels.

INTRODUCTION: Multiple sclerosis (MS) is known to be a multifactorial disorder. Numerous observational studies have suggested the implication of multiple genetic and environmental factors in the pathogenesis of MS. The aim of this work was to evaluate expression of the microRNA-22 (miRNA-22) level, in relation to vitamin D (VD) and VD receptor (VDR) levels in patients with MS during remission state. METHODS: This case-control study was conducted in 50 patients with clinically definite MS and 50 age- and sex-matched healthy controls. miRNA-22 expression was assessed in both MS patients and controls using quantitative RT-PCR. The serum level of VD and VDR was assessed in both MS patients and controls using ELISA techniques. RESULTS: The miRNA-22 level was significantly downregulated in MS patients in comparison to controls (p value <0.001). MS patients had also significantly lower VD and VDR levels in comparison to controls (p value <0.001 and <0.001, respectively). Patients with secondary progressive MS (SPMS) have a significantly higher miRNA-22 level than patients with relapsing remitting MS (RRMS) (p value = 0.042). There was a statistically significant positive correlation between the miRNA-22 level and EDSS (p value = 0.033). There was also a statistically significant positive correlation between the miRNA-22 level and VDR level (p value = 0.002). CONCLUSION: The miRNA-22 level was significantly downregulated in MS patients, but it had a positive correlation with disability status. Patients with SPMS have a significantly higher miRNA-22 level than patients with RRMS. VD and VDR levels were significantly lower in MS patients than controls. The miRNA-22 level was positively correlated with the VDR level.

Omitting the Early Postoperative Follow-up in Uncomplicated Operative Supracondylar Humerus Fractures in Children Does Not Negatively Affect Outcomes.

BACKGROUND: Supracondylar humerus (SCH) fractures are the most common surgically treated elbow injuries in children. There have been debates regarding if an early postoperative follow-up before pin removal is necessary to decrease the complications related to surgical fixation. To date, studies examining this topic have included smaller sample sizes, limiting the generalizability of their findings. METHODS: A retrospective chart review of outcomes after operative management of Gartland type II and III SCH fractures at a single level 1 pediatric trauma center between 2005 and 2015 was performed. Patient demographics, fracture characteristics, pin number and configuration, timing of initial follow-up, change in treatment plan after initial follow-up, time to pin removal, initial and final fracture radiographic parameters, and complications were observed via chart review. RESULTS: A total of 1518 SCH fractures underwent operative fixation: 755 Gartland type II and 765 type III. Of the 1518 SCH fractures identified, 1370 met inclusion criteria and were included for analysis. Of these, 1196 patients returned for initial follow-up within 1 to 2 weeks of surgery, and 174 patients had their initial follow-up 3 to 4 weeks postoperatively. There were 8 incidences where initial early follow-up resulted in a change of management; however, change in management was limited to cast alteration in 7 of these cases. CONCLUSIONS: Closed reduction and percutaneous pin fixation of otherwise uncomplicated closed SCH fractures have good outcomes and a very low complication rate at a level 1 pediatric trauma center. Early postoperative follow-up before the pin removal visit provides minimal utility in decreasing complications and may be safely omitted as long as the initial fracture fixation is deemed to be stable. LEVEL OF EVIDENCE: Level III.

GWRA: grey wolf based reconstruction algorithm for compressive sensing signals.

The recent advances in compressive sensing (CS) based solutions make it a promising technique for signal acquisition, image processing and other types of data compression needs. In CS, the most challenging problem is to design an accurate and efficient algorithm for reconstructing the original data. Greedy-based reconstruction algorithms proved themselves as a good solution to this problem because of their fast implementation and low complex computations. In this paper, we propose a new optimization algorithm called grey wolf reconstruction algorithm (GWRA). GWRA is inspired from the benefits of integrating both the reversible greedy algorithm and the grey wolf optimizer algorithm. The effectiveness of GWRA technique is demonstrated and validated through rigorous simulations. The simulation results show that GWRA significantly exceeds the greedy-based reconstruction algorithms such as sum product, orthogonal matching pursuit, compressive sampling matching pursuit and filtered back projection and swarm based techniques such as BA and PSO in terms of reducing the reconstruction error, the mean absolute percentage error and the average normalized mean squared error.