Trace ratio optimization with feature correlation mining for multiclass discriminant analysis

Copyright © 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Fisher's linear discriminant analysis is a widely accepted dimensionality reduction method, which aims to find a transformation matrix to convert feature space to a smaller space by maximising the between-class scatter matrix while minimising the within-class scatter matrix. Although the fast and easy process of finding the transformation matrix has made this method attractive, overemphasizing the large class distances makes the criterion of this method suboptimal. In this case, the close class pairs tend to overlap in the subspace. Despite different weighting methods having been developed to overcome this problem, there is still a room to improve this issue. In this work, we study a weighted trace ratio by maximising the harmonic mean of the multiple objective reciprocals. To further improve the performance, we enforce the 2,1-norm to the developed objective function. Additionally, we propose an iterative algorithm to optimise this objective function. The proposed method avoids the domination problem of the largest objective, and guarantees that no objectives will be too small. This method can be more beneficial if the number of classes is large. The extensive experiments on different datasets show the effectiveness of our proposed method when compared with four state-of-the-art methods

Seroepidemiological study of novel coronavirus disease (Covid-19) in Tehran, Iran

Backgrounds: A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread to all countries of the world, including Iran. Although anti-SARS-CoV-2 antibodies may be identified in patients using immunological methods with sufficient sensitivity and specificity, the conclusive diagnosis of the disease is made using the molecular RT-PCR method. A population-based seroepidemiological survey was conducted to quantify the proportion of the exposed population with SARS-CoV-2 antibodies and evaluate whether the antibodies are a marker of total or partial immunity compared to the population that remains susceptible to the virus. Material & Methods: This cross-sectional study was conducted to investigate the seroprevalence of COVID-19 in Valiasr, Sajad, and Ghaem hospitals in Tehran, the capital of Iran, from April to the end of October 2020. Clotted and heparinized blood specimens (2mL) were collected from the patients. The serum and plasma were separated and stored at −80 °C until use. Anti-SARS-CoV-2 IgG and IgM antibodies were examined in the serum samples of 1375 in-patients admitted to the hospitals using ELISA kits. The obtained data were analyzed using SPSS software Ver.22.0 by employing statistical tests such as Chi-square and Fisher’s exact tests. A p-value <.05 was considered as significant. Findings: In total, 1375 participants were enrolled in this study, and SARS‐CoV‐2 antibodies were detected in 291 patients using IgM‐IgG antibody assay. Among the seropositive patients studied, 187 were male (64.3), and 104 were female (35.7) (p<.05). The mean age of the patients was 49±8.4 years; the majority of whom (27) were in the age group of 31-40 years. Also, the lowest frequency of infected cases was related to the age group of 1-10 years (p <.05). The seroprevalence of SARS‐CoV‐2 IgM or IgG antibodies was determined to be 21.2. Diabetes mellitus was the most common underlying disease among SARS‐CoV‐2 patients p=.05; Odd Ratio=1.61(0.90-2.91). Conclusion: The use of conventional serological assays, such as the enzyme-linked immunoassay (ELISA), for detecting specific IgM and IgG antibodies in SARS‐CoV‐2 patients has a high-throughput advantage while minimizing false-negative results obtained using the RT-PCR method. In this study, the seroprevalence of SARS-CoV-2 antibodies was determined to be 21%. Control of diabetes, among other influential factors, plays an important role in the management and control of COVID-19. © 2021, TMU Press

Onychomycosis Caused by Rhodotorula mucilaginosa in a Young Immunocompetent Woman in Iran: A Case Report

Background and Aim: Rhodotorula mucilaginosa (R. mucilaginosa) has emerged as a potential pathogen in immunosuppressed hosts. This fungal agent rarely causes onychomycosis in immunocompetent hosts. In this study, onychomycosis caused by this strain on different fingernails and toenails in an Immunocompetent young adult is reported. Case Report: The patient was an 18-year-old woman with clinical symptoms of powdery, hyperkeratosis brief around erythema in the distal part of a toenail and deformity with a groove on surface of a fingernail who was referred to the Medical Mycology Laboratory of Hazrat Ghaem therapeutic center. After diagnostic procedures, he was treated with oral itraconazole 200 mg/day for 2 months along with topical clotrimazole and sulfacetamide ointment and was cured. The nails responded satisfactorily to the treatment. After two months of stopping the drug, the absence of fungus elements in the clinical samples was confirmed. Diagnosis and identification of the fungus was confirmed by morphological characteristics, culture, and DNA molecular method, and R. mucilaginosa was reported as the etiological agent of onychomycosis. Antifungal drug susceptibility was determined in laboratory using the disk diffusion method according to CLSI guidelines. Conclusion: The isolated species was reported as an unusual species of onychomycosis, which needs to be considered by mycology laboratory and clinical specialists for its sensitivity to ketoconazole, itraconazole, and econazole and its resistance to amphotericin B and nystatin. © 2023 Baqiyatallah University of Medical Sciences. All rights reserved