Exploratory axis factoring for identifying the self-esteem latent factors and their correlation with the life quality of persons suffering from vitiligo

Objective

Our research aimed to measure the importance of self-esteem in assessing the disease burden in patients with vitiligo, which, according to our knowledge, had not been studied earlier. The purpose of this research study was to expand the state of knowledge regarding the influence of vitiligo on the quality of patients' life, with a particular focus on their self-esteem. We have formulated the following two hypotheses which include H1: two latent factors characterize the self-esteem of patients with vitiligo; H2: the self-esteem of the patients with Vitiligo is correlated with their life quality, by influencing it to a high degree.

Methods

We have used two validated questionnaires called Rosenberg (Q1), for the evaluation of self-esteem (for proving H1), and Dermatology Life Quality Index (DLQI) (Q2), to measure the health-related quality of life of patients (for proving H2). Both questionnaires with 10 questions were applied to the same set of 114 carefully selected patients with no missing values to questions. An in-depth statistical and reliability analysis was performed on the outcomes provided by Q1, applying a scale and subscale reliability analysis, using the Cronbach's alpha reliability indicator (Cα). An exploratory analysis called Principal Axis Factoring (PAF) with Oblimin with Kaiser Normalization rotation was applied to prove H1, verifying the assumptions regarding the average variance extracted (AVE) and convergent and discriminant validity (CDV). A scale reliability analysis of outcomes provided by Q2 was performed for proving H2, by calculating Cα. Additionally, a nonparametric correlation analysis was performed, by calculating the Spearman r correlation coefficient between the Rosenberg index and DLQI index, and the 95% confidence interval (CI).

Results

Based on the provided data, the value of Cα obtained in Q1 was 0.84. As a result of applying PAF on Q1, H1 has been proven and two latent factors of self-esteem have been extracted. These factors were named competence (eigenvalue = 4.126; 41.258% of total variance explained) and value (eigenvalue = 1.857; 18.57% of total variance explained). For the two subscales determined by the two factors, we have obtained the Cα values of 0.848 and 0.8, all indicating good reliability. For testing H2, on Q2 data we obtained Cα = 0.914. The Spearman correlation coefficient r = -0.734 (p < 0.0001), between the self-esteem questionnaire evaluation result and the life-quality index result indicated the existence of a strong negative correlation, which is significant according to 95% CI [-0.81, -0.63].

Discussion

The study focused on analyzing the self-esteem of patients with vitiligo. In addition, the psychometric properties of the Q1 questionnaire were analyzed and Q1 proved to have good internal consistency. PAF indicated a two-factorial structure, with factors called competence and value, proving H1, with a moderate correlation of 0.427 between the two latent constructs. The competence factor includes motivation, self-efficacy, initiative, and persistence in action. The value factor is much more complex, indicating a feeling, a personal evaluation, or a positive or negative attitude toward one's person, which better captures the entire phenomenology of self-esteem. The statistical analysis of the results provided by the self-esteem questionnaire included questions that proved to be internally consistent. The AVE and CDV assumptions were met. Q2 was proved to have excellent scale reliability. H2 proved a statistically significant strong negative correlation between the Rosenberg score and DLQI score.

Embolia cutis Medicamentosa (Nicolau syndrome): case series

Introduction

Embolia cutis medicamentosa or Nicolau syndrome is a rare drug reaction associated with the administration of various injectable medications. The pathogenesis of the disease is unknown, though intra and periarterial injection of the drug is a possible cause. The aim of this study was to describe and analyze the clinical characteristics of Nicolau syndrome in patients examined in daily dermatological practice.

Methods

We performed a retrospective chart review, between January 2011 and December 2020, in patients diagnosed with Nicolau syndrome, from the cases of a private dermatology medical office in Târgu Mureș, Romania.

Results

During the 10-year period, 7 patients were diagnosed with Nicolau syndrome. Of these, 4 (57%) patients were males and 3 (43%) were females, The male to female ratio was 1.33. The median age was 64 (interquartile range, IQR, 62-71), with the youngest patient being diagnosed at age 61 and the oldest at age 74. Regarding the drugs classes that caused Nicolau syndrome, these were intravenous antibiotics in 57%, and non-steroidal anti-inflammatory drugs in 43% of cases.

Conclusion

All patients healed in a period of 6 to 8 weeks. No complications occurred. In conclusion, Nicolau syndrome is a rare side effect of injectable drug administration.

Cancer and Chaos and the Complex Network Model of a Multicellular Organism

Simple Summary

Currently, knowledge on chaos has developed rapidly, and the link between cancer and “genomic chaos” seems obvious. Hopes for a deeper understanding of cancer, allowing cancer modeling, therefore relate to the meaning of the term “chaos”. It has many meanings, however. Chaos theory and medicine are conceptually quite distant, requiring the comparison and agreement of terms. This article was written by three authors whose fields cover both medical problems and complex dynamic networks suitable for modeling cancer, including chaotic phenomena. The article provides, first of all, a coherent, common interpretative basis linking chaos with modeling tools, which should significantly facilitate teams of specialists from various fields to undertake specific work on simulating cancer-related phenomena.

Abstract

In the search of theoretical models describing cancer, one of promising directions is chaos. It is connected to ideas of “genome chaos” and “life on the edge of chaos”, but they profoundly differ in the meaning of the term “chaos”. To build any coherent models, notions used by both ideas should be firstly brought closer. The hypothesis “life on the edge of chaos” using deterministic chaos has been radically deepened developed in recent years by the discovery of half-chaos. This new view requires a deeper interpretation within the range of the cell and the organism. It has impacts on understanding “chaos” in the term “genome chaos”. This study intends to present such an interpretation on the basis of which such searches will be easier and closer to intuition. We interpret genome chaos as deterministic chaos in a large module of half-chaotic network modeling the cell. We observed such chaotic modules in simulations of evolution controlled by weaker variant of natural selection. We also discuss differences between free and somatic cells in modeling their disturbance using half-chaotic networks.

Directed Evolution – A New Metaheuristc for Optimization

Recently, we have witnessed an infusion of calculating models based on models offered by nature, models with more or less fidelity to the original that have led to the development of various problem-solving computational procedures. Starting from the observation of natural processes at the macroscopic or microscopic level, various methods have been developed. Technological progress today allows the accelerated reproduction of natural phenomena in the laboratory, which is why a new niche has arisen in the landscape of nature-inspired methods. This niche is devoted to the emulation of artificial biological processes in computational problem-solving methods.

This paper proposes a novel approach, which is to develop novel computational methods in the field of Natural Computing based on the semi-natural process, namely Directed Evolution. In the first step we explain Directed Evolution, defined as the artificial reproduction of the process of evolution in the laboratory in order to obtain performing biological entities. For computer scientists, this provide a strong source of inspiration in the search for efficient methods of optimization. The computational model that proposed here largely overlaps with the Directed Evolution protocol, and the results obtained in the numerical experiments confirm the viability of such techniques inspired by processes which are more artificial than natural. The paper describes a novel general algorithm, inspired by Directed Evolution, which is able to solve different optimization problems, such as single optimization, multiobjective optimization and combinatorial optimization problems.