Search

Background and aims: Respiratory allergens cause several problems for people with allergic rhinitis and are considered as a global challenge. This disease is an IgE-mediated nasal inflammatory disease that is triggered by the contact of the allergen. Therefore, this study was conducted to investigate respiratory allergens and associated factors in patients with allergic rhinitis who referred to a clinic in Shahrekord located in the southwest of Iran. Methods: In this cross-sectional study, 200 patients including 100 males and 100 females were enrolled using a convenience sampling technique. Diagnoses were made according to clinical symptoms and observation. In addition, the skin prick tests were used to detect the allergens. Finally, data were recorded and then analyzed by Stata. Results: Based on the results, 73.5%, 70.5%, 46%, and 43% of the patients were allergic to the following allergens including Dermatophagoid pteronyssinus, Dermatophagoides parinae, tree, and grass, respectively. Further, the mean height in the group with a positive and negative test for the inhaled allergens equaled 144.92±29.72 and 131.65±30.93, respectively, with a statistically significant difference (P0.05). Furthermore, the negative or positive reaction to the allergens failed to significantly differ with respect to gender, marital status, occupation, the county of residence, the area of residence, family size, and a family history of the disease (P>0.05). Conclusion: Allergic rhinitis is regarded as a common disorder among teenagers and young adults in this setting. Allergy to one or more respiratory allergens was found to be highly prevalent in patients with allergic rhinitis and the highest rate of allergy was observed to the mites, followed by tree and grass.

The number of inherited diseases and the spectrum of clinical manifestations of primary immunodeficiency disorders (PIDs) are ever-expanding. Molecular diagnosis using genomic approaches should be performed for all PID patients since it provides a resource to improve the management and to estimate the prognosis of patients with these rare immune disorders. The current update of Iranian PID registry (IPIDR) contains the clinical phenotype of newly registered patients during last 5 years (2013–2018) and the result of molecular diagnosis in patients enrolled for targeted and next-generation sequencing. Considering the newly diagnosed patients (n = 1395), the total number of registered PID patients reached 3056 (1852 male and 1204 female) from 31 medical centers. The predominantly antibody deficiency was the most common subcategory of PID (29.5%). The putative causative genetic defect was identified in 1014 patients (33.1%) and an autosomal recessive pattern was found in 79.3% of these patients. Among the genetically different categories of PID patients, the diagnostic rate was highest in defects in immune dysregulation and lowest in predominantly antibody deficiencies and mutations in the MEFV gene were the most frequent genetic disorder in our cohort. During a 20-year registration of Iranian PID patients, significant changes have been observed by increasing the awareness of the medical community, national PID network establishment, improving therapeutic facilities, and recently by inclusion of the molecular diagnosis. The current collective study of PID phenotypes and genotypes provides a major source for ethnic surveillance, newborn screening, and genetic consultation for prenatal and preimplantation genetic diagnosis.

BACKGROUND: Allergic rhinitis is one of the most common allergic diseases and characterised by sneezing, rhinorrhea, nasal congestion and nasopharyngeal itching. Subcutaneous immunotherapy (SCIT) for specific allergens is an effective treatment and induces the inhibitory effect of T regulatory lymphocytes and decreases clinical symptoms in allergic rhinitis.AIM: In this study effect of subcutaneous immunotherapy with specific allergens on clinical symptoms and T regulatory and T Helper cells cytokines, in patients with allergic rhinitis are evaluated.METHODS: In this study, 30 patients with moderate to severe allergic rhinitis according to clinical criteria and positive skin prick test for aeroallergens were selected and treated by SCIT. Clinical symptoms and T cells cytokines IL4, IL17, IFN gamma, TGF beta, GITR, FOXP3 and IL-10 (by RT-PCR) were evaluated before and one year after initiation of treatment.RESULTS: Thirty (30) patients with allergic rhinitis at age range 15-45 years old were treated by SCIT, and 23 (14 female, 9 male) patients continued the study, and 7 patients did not continue treatment. After immunotherapy, clinical symptoms decreased significantly. The specific cytokines TGF beta and IL10 levels increased and changes were statistically significant. (Respectively P = 0.013 and P = 0.05) The IL17 level was also increased, but not statistically significant. (P = 0.8) IFN gamma, IL4, GITR, FOXP3, all decreased, but the changes were not statistically significant (P > 0.05).CONCLUSION: Subcutaneous Immunotherapy for specific allergens decreases clinical symptoms in patients with allergic rhinitis and induces tolerance in T lymphocytes, especially by increasing T regulatory cells cytokines, TGF beta and IL10.

YKL-40 is an important protein that plays a critical role in chronic inflammation in hypersensitivity disease. In this study, the expression of YKL-40 was investigated among patients with moderate/severe persistent allergic rhinitis (M/S PAR), patients with mild (M) PAR and healthy individuals. Moreover, the association between YKL-40 and immunopathogenesis of M/S PAR was meticulously surveyed. For this purpose, surgical samples were tested by real-time polymerase chain reaction to evaluate YKL-40 mRNA expression. The presence and location of YKL-40 protein in the tissue samples were determined by immunohistochemistry. Additionally, we measured the number of eosinophils per field in the tissue samples, blood eosinophils, total serum IgE, specific serum IgE, total nasal syndrome score (TNSS) and YKL-40 serum levels. The data indicated that production of YKL-40 in patients with M/S PAR increased significantly when compared with the control group. Furthermore, local production of YKL-40 correlated with specific IgE, nasal eosinophil count and TNSS. The results of the present study indicate that YKL-40, for its correlation with allergic clinical manifestations and symptom severity in M/S PAR patients, should be considered as a trigger factor in AR.

Background: Hyper-immunoglobulin M (HIGM) syndrome is a rare heterogeneous group of primary immunodeficiency disorders characterized by low or absent serum levels of IgG and IgA along with normal or elevated serum levels of IgM. Methods: Clinical and immunological data were collected from the 75 patients’ medical records diagnosed in Children’s Medical Center affiliated to Tehran University Medical Sciences and other Universities of Medical Sciences in Iran. Among 75 selected patients, 48 patients (64%) were analyzed genetically using targeted and whole-exome sequencing. Results: The ratio of male to female was 2.9:1. The median age at the onset of the disease, time of diagnosis, and diagnostic delay were 10.5, 50, and 24 months, respectively. Pneumonia and lower respiratory tract infections (61.3%) were the most common complications. Responsible genes were identified in 35 patients (72.9%) out 48 genetically analyzed patients. Cluster of differentiation 40 ligand gene was the most mutated gene observed in 24 patients (68.5%) followed by activation-induced cytidine deaminase gene in 7 patients, lipopolysaccharide-responsive and beige-like anchor (1 patient), nuclear factor-kappa-B essential modulator (1 patient), phosphoinositide-3-kinase regulatory subunit 1 (1 patient), and nuclear factor kappa B subunit 1 (1 patient) genes. Nineteen (25.3%) patients died during the study period, and pneumonia was the major cause of death occurred in 6 (31.6%) patients. Conclusion: Physicians in our country should carefully pay attention to respiratory tract infections and pneumonia, particularly in patients with a positive family history. Further investigations are required for detection of new genes and pathways resulting in HIGM phenotype.

BACKGROUND: Predominantly antibody deficiencies (PADs) are the most common primary immunodeficiencies, characterized by hypogammaglobulinemia and inability to generate effective antibody responses. OBJECTIVE: We intended to report most common monogenic PADs and to investigate how patients with PAD who were primarily diagnosed as suffering from agammaglobulinemia, hyper-IgM (HIgM) syndrome, and common variable immunodeficiency (CVID) have different clinical and immunological findings. METHODS: Stepwise next-generation sequencing and Sanger sequencing were performed for confirmation of the mutations in the patients clinically diagnosed as suffering from agammaglobulinemia, HIgM syndrome, and CVID. RESULTS: Among 550 registered patients, the predominant genetic defects associated with agammaglobulinemia (48 Bruton's tyrosine kinase BTK and 6 mu heavy chain deficiencies), HIgM syndrome (21 CD40 ligand and 7 activation-induced cytidine deaminase deficiencies), and CVID (17 lipopolysaccharides-responsive beige-like anchor deficiency and 12 atypical Immunodeficiency, Centromeric instability, and Facial dysmorphism syndromes) were identified. Clinical disease severity was significantly higher in patients with mu heavy chain and CD40 ligand mutations compared with patients with BTK (P = .003) and activation-induced cytidine deaminase (P = .009) mutations. Paralysis following live polio vaccination was considerably higher in patients with mu heavy chain deficiency compared with BTK deficiency (P < .001). We found a genotype-phenotype correlation among patients with BTK mutations regarding clinical manifestation of meningitis and chronic diarrhea. Surprisingly, we noticed that first presentations in most patients with Immunodeficiency, Centromeric instability, and Facial dysmorphism were respiratory complications (P = .008), whereas first presentations in patients with lipopolysaccharides-responsive beige-like anchor deficiency were nonrespiratory complications (P = .008). CONCLUSIONS: This study highlights similarities and differences in the clinical and genetic spectrum of the most common PAD-associated gene defects. This comprehensive comparison will facilitate clinical decision making, and improve prognosis and targeted treatment.

Earlier we introduced a novel framework for implementation of Adaptive Autonomy (AA). This study presents an expert system realization of the AA framework, referred to as Adaptive Autonomy Expert System (AAES). The proposed AAES is based on the extracted rules from the Expert’s Judgment on proper Levels of Automation (LOA) for various environmental conditions, modeled as Performance Shaping Factors (PSFs). Decision fusion method is used as expert system inference engine, where eight decision fusion methods are developed as prospective ones. The AAES is realized in the practical case of electric power Utility Management Automation (UMA) for the Greater Tehran Electricity Distribution Company (GTEDC). The practical list of PSFs and the judgments of GTEDC’s experts are used as the expert system rule base in this research. The results of implementing the proposed AAES to GTEDC’s network are evaluated according to two criteria: average error and error margin. Five out of eight decision fusion methods are proven to be suitable inference engines, due to both criteria. Evaluation of the results shows that the proposed AAES can estimate proper LOAs for GTEDC’s UMA system, which change due to the changes in PSFs; thus providing a dynamic (adaptive) LOA scheme for UMA.

This chapter expresses three cognitive genres: descriptive genre, normative/prescriptive genre, and know-how genre. The descriptive genre introduces and discusses on the following disciplines: the core concepts of complexity, complex adaptive system (CAS) of systems (CASoS), the application domains of human-automation interaction (HAI) and adaptive autonomy (AA), especially in Smart Grid, and two implementation ideas of expert systems and Petri nets. The chapter describes the automation related notions, that is, automation and HAI, followed by the investigation of HAI models' evolution from the perspectives of dimensions and dynamism. The idea of AA is then introduced as a dynamic HAI scheme, followed by the classification of AA implementation methods. Petri nets are introduced as powerful tools for modeling complex systems (CxS). Finally, Petri net realization of the adaptive autonomy expert system (AAES) is presented, followed by a performance evaluation study. Özyeğin University

Background: Complications of Ventolin as the most common drug used for bronchiolitis are widely known. The present study was conducted to determine the efficacy of hypertonic saline 3%, compared with Ventolin, for treatment of acute bronchiolitis in children. Methods: This double-blinded clinical trial study was conducted in Hajar Hospital, Shahrekord, Iran, from 2011 to 2012. A total of 70 patients under the age of two years with bronchiolitis were divided into two groups of 35 each. Ventolin nebulizer and hypertonic saline 3% nebulizer three times per day were administered in the first (Ventolin) and second (Hypersaline) group, respectively. The length of recovery was compared between the two groups. The data were analyzed by SPSS software (version 22) using chi-square, t-test, paired t-test, and Mann-Whitney. Results: The mean±SD length of recovery was 4.14±0.9 and 3.06±0.6 in the Ventolin and hypersaline groups, respectively. The mean duration of recovery was significantly lower in the hypersaline group (p

We earlier introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI). This study presents an expert system for realization of AA, using Support Vector Machine (SVM), referred to as Adaptive Autonomy Support Vector Machine Expert System (AASVMES). The proposed system prescribes proper Levels of Automation (LOAs) for various environmental conditions, here modeled as Performance Shaping Factors (PSFs), based on the extracted rules from the experts' judgments. SVM is used as an expert system inference engine. The practical list of PSFs and the judgments of GTEDC's (the Greater Tehran Electric Distribution Company) experts are used as expert system database. The results of implemented AASVMES in response to GTEDC's network are evaluated against the GTEDC experts' judgment. Evaluations show that AASVMES has the ability to predict the proper LOA for GTEDC's Utility Management Automation (UMA) system, which changes in relevance to the changes in PSFs; thus providing an adaptive LOA scheme for UMA.

The complexity of humans and automation interaction in Smart Grid, as the future of power system, calls for embedding a level of intelligence in the system. Adaptive Autonomy (AA) theory is employed to manage high level complexity of the Human-Automation Interaction (HAI) system. The fuzzy expert system with Gradient Descent Algorithm (AAFGDES) is a data-driven approach applied to determine the Level of Automation (LOA). Six scenarios are developed to evaluate different learning strategies. The results will reveal the performance of the system. The research has been performed in collaboration with the Greater Tehran Electrical Distribution Company (GTEDC) - an enterprise that delivers electric energy to the end consumers.

Control of an unknown nonlinear time-varying plant has always been a great concern for control specialists, thus an appealing subject in this discipline. Many efforts have been dedicated to explore the various aspects of this problem. This research has led into introducing many new fields and methods. These methods can be categorized into two general classes as: data-driven and model-driven. Model driven methods in spite of having rigorous analytical basis are not employed as frequently as data-driven ones. On the other hand data-driven methods are suitable to be employed in nonlinear and dual controller design; however they are slightly unsuccessful in handling missing data, moreover these methods are in need of considerable amount of computation. This paper introduces a novel hybrid nonlinear controller which aggregates Gaussian Process Prior as a data-driven and a Fuzzy Controller as a model-driven method .This special structure brings model-driven and data-driven advantages altogether, thus naturally lead into a robust and adaptive controller. Since no prior knowledge of the plant is used to issue the control law, the proposed hybrid controller can also be regarded as a dual controller.

This paper presents an expert system for selecting a proper IT infrastructure for smart grid, based on a novel fuzzy approach to Tricotyledon Theory of System Design (Fuzzy-T3SD). The proposed Fuzzy-T3SD is a policy-driven decision making method that can change the result of the decision makings according to the utility's policy. The Fuzzy-T3SD is applied to the practical data of the Greater Tehran Electrical Distribution Company (GTEDC). Spread Spectrum (SS), Distribution Line Carrier (DLC) and Leased Line (LL) are regarded as alternatives for the IT infrastructure. The implemented results are examined by the developed policies scenarios.

We have introduced a novel framework for realization of Adaptive Autonomy (AA) in human-automation interaction (HAI) systems, as well as several expert system realizations of that. This study presents an expert system for realization of AA, using logistic regression (LR), referred to as Adaptive Autonomy Logistic Regression Expert System (AALRES). The proposed system prescribes proper Levels of Automation (LOAs) for various environmental conditions, here modeled as Performance Shaping Factors (PSFs), based on the extracted rules from the experts' judgments. LR is used as the expert system's inference engine. The practical list of PSFs and the judgments of GTEDC's (the Greater Tehran Electric Distribution Company) experts are used as expert system database. The results of implementing AALRES to GTEDC's network are evaluated against the exact predictions of the presented expert system. Evaluations show that AALRES can predict the proper LOA for GTEDC's Utility Management Automation (UMA) system, which change according to changes in PSFs; thus providing an adaptive LOA scheme for UMA.