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Currently, there are saturated frequency bands that affect the quality of service for new users. Cognitive radio provides an alternative solution to this problem through dynamic spectrum access. However, the solutions proposed in the current literature are focused on a centralized network and do not allow demonstrating the behavior in a multi-user environment, much less the effect that cooperation between secondary users can have. This article establishes a decision-making model for the best spectral opportunity selection with a cooperative approach in decentralized cognitive radio networks and contrasts its results with three multi-criteria decision-making algorithms: SAW, TOPSIS, and VIKOR. So, this research suggests a cooperative decision-making model based on four main modules. (1) a collaborative module for the exchange of information between SU; (2) a module for PU characterization; (3) a module of the probability of SU arrival; and (4) the SO feedback selection module. The results are obtained through simulations fed with experimental spectral occupancy data captured in a measurement campaign. Handoff and throughput were used as evaluation metrics, along with five levels of collaboration: 10%, 20%, 50%, 80%, and 100%, and eight different scenarios based on the type of network: GSM and Wi-Fi, the application type: real-time and best-effort, and the level of traffic: high and low. The contribution of this study lies in the fact that no current work includes the following relevant aspects for an adequate validation and evaluation of this proposal: First, the consideration of a decentralized cognitive radio network; second, the decision-making with cooperative strategies; third, different techniques for SO selection; fourth, the validation and evaluation with experimental spectral occupancy data captured in measurement campaigns; finally, the performance analysis in diverse networks, traffic levels, and types of applications., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Cognitive radio networks promote better spectral efficiency of the electric radio spectrum. The vast majority of current spectral decision models for cognitive radio networks evaluate their performance based on a single secondary user. In reality, the network can experience multiple requests from spectral opportunities. Based on this, the intent of this article is to present and evaluate a spectral decision model for cognitive radio networks in a multi-user environment taking into account the effect of the decisions of the SU on the usefulness of the other SU. To achieve this, a spectral decision model was developed that allows secondary users to share relevant information before accessing the spectrum so that they can select the most appropriate spectral opportunities. The evaluation and validation of the model was performed using three multicriteria decision-making algorithms under the metric of the number of total handoffs in a conventional scenario and a real scenario, in the conventional scenario, only users that match the input of the multiuser module are included; in the real scenario, in addition to the conventional users, users that enter and leave at random times are included, a feature that alters the models for estimating the behavior of the radio environment. The results show better performance of the TOPSIS algorithm over VIKOR and SAW. The most important contribution of this work is the evaluation of the performance of the spectral decision algorithms implemented in a multi-user environment that allows multiple access and exchange of information between users, with experimental spectral occupation data., Competing Interests: The authors declare no conflict of interest., (© 2021 The Author(s).)

Purpose: To report the results of an association study between single-nucleotide polymorphisms of the p53 and LTA genes and the risk of proliferative vitreoretinopathy (PVR)/retinal detachment (RD) in a Mexican cohort., Methods: A total of 380 unrelated subjects were studied, including 98 patients with primary rhegmatogenous RD without PVR, 82 patients with PVR after RD surgery, and 200 healthy, ethnically matched subjects. Genotyping of single-nucleotide polymorphisms rs1042522 (p53 gene) and rs2229094 (LTA gene) was performed by direct nucleotide sequencing. Allele frequencies, genotype frequencies, and Hardy-Weinberg equilibrium were assessed with HaploView software., Results: No significant differences in the allelic distributions of the previously identified risk C allele for LTA rs2229094 were observed between RD subjects and controls (odds ratio [95% confidence interval] = 0.8 [0.5-1.2]; P = 0.3). Conversely, the C allele for rs1042522 in p53 was positively associated with an increased risk for RD (odds ratio [95% confidence interval] = 1.4 [1.01-1.9]; P = 0.04). No significant differences were observed when the subgroup of 82 RD + PVR subjects was compared with the subgroup of 98 patients with RD., Conclusion: The C allele for rs1042522 in p53 was genetically associated with a higher risk for RD but not for PVR in this cohort. This is the first association study attempting replication of PVR-associated risk alleles in a nonwhite population.

Primary angle closure glaucoma (PACG) is a major cause of blindness worldwide. We conducted a genome-wide association study (GWAS) followed by replication in a combined total of 10,503 PACG cases and 29,567 controls drawn from 24 countries across Asia, Australia, Europe, North America, and South America. We observed significant evidence of disease association at five new genetic loci upon meta-analysis of all patient collections. These loci are at EPDR1 rs3816415 (odds ratio (OR) = 1.24, P = 5.94 × 10(-15)), CHAT rs1258267 (OR = 1.22, P = 2.85 × 10(-16)), GLIS3 rs736893 (OR = 1.18, P = 1.43 × 10(-14)), FERMT2 rs7494379 (OR = 1.14, P = 3.43 × 10(-11)), and DPM2-FAM102A rs3739821 (OR = 1.15, P = 8.32 × 10(-12)). We also confirmed significant association at three previously described loci (P < 5 × 10(-8) for each sentinel SNP at PLEKHA7, COL11A1, and PCMTD1-ST18), providing new insights into the biology of PACG.