Design of a novel multi-epitope vaccine candidate against Chlamydia trachomatis using structural and nonstructural proteins: an immunoinformatics study

Chlamydia trachomatis (C. trachomatis) is an obligate intracellular bacterium which causes eye and sexually transmitted infections. During pregnancy, the bacterium is associated with preterm complications, low weight of neonates, fetal demise and endometritis leading to infertility. The aim of our study was design of a multi-epitope vaccine (MEV) candidate against C. trachomatis. After protein sequence adoption from the NCBI, potential epitopes toxicity, antigenicity, allergenicity, MHC-I and MHC-II binding, cytotoxic T lymphocytes (CTLs), Helper T lymphocytes (HTLs) and interferon-γ (IFN-γ)- induction were predicted. The adopted epitopes were fused together using appropriate linkers. In the next step, the MEV structural mapping and characterization, three-dimensional (3D) structure homology modeling and refinement were also performed. The MEV candidate interaction with the toll-like receptor 4 (TLR4) was also docked. The immune responses simulation was assessed using the C-IMMSIM server. Molecular dynamic (MD) simulation verified the structural stability of the TLR4-MEV complex. The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach demonstrated the MEV high affinity of binding to the TLR4, MHC-I and MHC-II. The MEV construct was also stable and water soluble and had enough antigenicity and lacked allergenicity with stimulation of T cells and B cells and INF-γ release. The immune simulation confirmed acceptable responses of both the humoral and cellular arms. It is proposed that in vitro and in vivo studies are needed to evaluate the findings of this study.Communicated by Ramaswamy H. Sarma.

Novel islands of GGC and GCC repeats coincide with human evolution

BACKGROUND

Because of high mutation rate, overrepresentation in genic regions, and link with various neurological, neurodegenerative, and movement disorders, GGC and GCC short tandem repeats (STRs) are prone to natural selection. Among a number of lacking data, the 3-repeats of these STRs remain widely unexplored.

RESULTS

In a genome-wide search in human, here we mapped GGC and GCC STRs of ≥3-repeats, and found novel islands of up to 45 of those STRs, populating spans of 1 to 2 kb of genomic DNA. RGPD4 and NOC4L harbored the densest (GGC)3 (probability 3.09061E-71) and (GCC)3 (probability 1.72376E-61) islands, respectively, and were human-specific. We also found prime instances of directional incremented density of STRs at specific loci in human versus other species, including the FOXK2 and SKI GGC islands. The genes containing those islands significantly diverged in expression in human versus other species, and the proteins encoded by those genes interact closely in a physical interaction network, consequence of which may be human-specific characteristics such as higher order brain functions.

CONCLUSION

We report novel islands of GGC and GCC STRs of evolutionary relevance to human. The density, and in some instances, periodicity of these islands support them as a novel genomic entity, which need to be further explored in evolutionary, mechanistic, and functional platforms.

Development of Local Software for Automatic Measurement of Geometric Parameters in the Proximal Femur Using a Combination of a Deep Learning Approach and an Active Shape Model on X-ray Images

Proximal femur geometry is an important risk factor for diagnosing and predicting hip and femur injuries. Hence, the development of an automated approach for measuring these parameters could help physicians with the early identification of hip and femur ailments. This paper presents a technique that combines the active shape model (ASM) and deep learning methodologies. First, the femur boundary is extracted by a deep learning neural network. Then, the femur's anatomical landmarks are fitted to the extracted border using the ASM method. Finally, the geometric parameters of the proximal femur, including femur neck axis length (FNAL), femur head diameter (FHD), femur neck width (FNW), shaft width (SW), neck shaft angle (NSA), and alpha angle (AA), are calculated by measuring the distances and angles between the landmarks. The dataset of hip radiographic images consisted of 428 images, with 208 men and 220 women. These images were split into training and testing sets for analysis. The deep learning network and ASM were subsequently trained on the training dataset. In the testing dataset, the automatic measurement of FNAL, FHD, FNW, SW, NSA, and AA parameters resulted in mean errors of 1.19%, 1.46%, 2.28%, 2.43%, 1.95%, and 4.53%, respectively.

Dyads of GGC and GCC form hotspot colonies that coincide with the evolution of human and other great apes

BACKGROUND

GGC and GCC short tandem repeats (STRs) are of various evolutionary, biological, and pathological implications. However, the fundamental two-repeats (dyads) of these STRs are widely unexplored.

RESULTS

On a genome-wide scale, we mapped (GGC)2 and (GCC)2 dyads in human, and found monumental colonies (distance between each dyad < 500 bp) of extraordinary density, and in some instances periodicity. The largest (GCC)2 and (GGC)2 colonies were intergenic, homogeneous, and human-specific, consisting of 219 (GCC)2 on chromosome 2 (probability < 1.545E-219) and 70 (GGC)2 on chromosome 9 (probability = 1.809E-148). We also found that several colonies were shared in other great apes, and directionally increased in density and complexity in human, such as a colony of 99 (GCC)2 on chromosome 20, that specifically expanded in great apes, and reached maximum complexity in human (probability 1.545E-220). Numerous other colonies of evolutionary relevance in human were detected in other largely overlooked regions of the genome, such as chromosome Y and pseudogenes. Several of the genes containing or nearest to those colonies were divergently expressed in human.

CONCLUSION

In conclusion, (GCC)2 and (GGC)2 form unprecedented genomic colonies that coincide with the evolution of human and other great apes. The extent of the genomic rearrangements leading to those colonies support overlooked recombination hotspots, shared across great apes. The identified colonies deserve to be studied in mechanistic, evolutionary, and functional platforms.

Identification of Key Genes in Angiogenesis of Breast and Prostate Cancers in the Context of Different Cell Types

INTRODUCTION

Angiogenesis involves the development of new blood vessels. Biochemical signals start this process in the body, which is followed by migration, growth, and differentiation of endothelial cells that line the inside wall of blood vessels. This process is vital for the growth of cancer cells and tumors.

MATERIALS AND METHODS

We started our analysis by composing a list of genes that have a validated impact in humans with respect to angiogenesis-related phenotypes. Here, we have investigated the expression patterns of angiogenesis-related genes in the context of previously published single-cell RNA-Seq data from prostate and breast cancer samples.

RESULTS

Using a protein-protein interaction network, we showed how different modules of angiogenesis-related genes are overexpressed in different cell types. In our results, genes, such as ACKR1, AQP1, and EGR1, showed a strong cell type-dependent overexpression pattern in the two investigated cancer types, which can potentially be helpful in the diagnosis and follow-up of patients with prostate and breast cancer.

CONCLUSION

Our work demonstrates how different biological processes in distinct cell types contribute to the angiogenesis process, which can provide clues regarding the potential application of targeted inhibition of the angiogenesis process.

Evaluation of common protein biomarkers involved in the pathogenesis of respiratory diseases with proteomic methods: A systematic review

AIM

Respiratory disease (RD) is one of the most common diseases characterized by lung dysfunction. Many diagnostic mechanisms have been used to identify the pathogenic agents of responsible for RD. Among these, proteomics emerges as a valuable diagnostic method for pinpointing the specific proteins involved in RD pathogenesis. Therefore, in this study, for the first time, we examined the protein markers involved in the pathogenesis of chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), asthma, bronchiolitis obliterans (BO), and chemical warfare victims exposed to mustard gas, using the proteomics method as a systematic study.

MATERIALS AND METHODS

A systematic search was performed up to September 2023 on several databases, including PubMed, Scopus, ISI Web of Science, and Cochrane. In total, selected 4246 articles were for evaluation according to the criteria. Finally, 119 studies were selected for this systematic review.

RESULTS

A total of 13,806 proteins were identified, 6471 in COPD, 1603 in Asthma, 5638 in IPF, three in BO, and 91 in mustard gas exposed victims. Alterations in the expression of these proteins were observed in the respective diseases. After evaluation, the results showed that 31 proteins were found to be shared among all five diseases.

CONCLUSION

Although these 31 proteins regulate different factors and molecular pathways in all five diseases, they ultimately lead to the regulation of inflammatory pathways. In other words, the expression of some proteins in COPD and mustard-exposed patients increases inflammatory reactions, while in IPF, they cause lung fibrosis. Asthma, causes allergic reactions due to T-cell differentiation toward Th2.

Computer-assisted evaluation of small airway disease in CT scans of Iran-Iraq war victims of chemical warfare by a locally developed software: comparison between different quantitative methods

OBJECTIVE

Diagnosis of small airway disease on computed tomography (CT) scans is challenging in patients with a history of chemical warfare exposure. We developed a software package based on different methodologies to identify and quantify small airway disease in CT images. The primary aim was to identify the best automatic methodology for detecting small airway disease in CT scans of Iran-Iraq War victims of chemical warfare.

METHODS

This retrospective case-control study enrolled 46 patients with a history of chemical warfare exposure and 27 controls with inspiratory/expiratory (I/E) CT scans and spirometry tests. Image data were automatically segmented, and inspiratory images were registered into the expiratory images' frame using the locally developed software. Parametric response mapping (PRM) and air trapping index (ATI) mapping were performed on the CT images. Conventional QCT methods, including expiratory/inspiratory mean lung attenuation (E/I MLA) ratio, normal density E/I (ND E/I) MLA ratio, attenuation volume Index (AVI), %low attenuation areas (LAA) < -856 in exhale scans, and %LAA < -950 in inhale scans were also computed. QCT measurements were correlated with spirometry results and compared across the two study groups.

RESULTS

The correlation analysis showed a significant negative relationship between three air trapping (AT) measurements (PRM, ATI, and %LAAExp < -856) and spirometry parameters (Fev1, Fvc, Fev1/Fvc, and MMEF). Moreover, %LAAExp < -856 had the highest significant negative correlation with Fev1/Fvc (r = -0.643, P-value < 0.001). Three AT measurements demonstrated a significant difference between the study groups. The E/I ratio was also significantly different between the two groups (P-value < 0.001). Binary logistic regression models showed PRMFsad, %LAAExp < -856, and ATI as significant and strong predictors of the study outcome. Optimal cut-points for PRMFsad = 19%, %LAAExp < -856 = 23%, and ATI = 27% were identified to classify the participants into two groups with high accuracy.

CONCLUSION

QCT methods, including PRM, ATI, and %LAAExp < -856 can greatly advance the identification and quantification of SAD in chemical warfare victims. The results should be verified in well-designed prospective studies involving a large population.

A computational approach for the identification of key genes and biological pathways of chronic lung diseases: a systems biology approach

BACKGROUND

Chronic lung diseases are characterized by impaired lung function. Given that many diseases have shared clinical symptoms and pathogenesis, identifying shared pathogenesis can help the design of preventive and therapeutic strategies. This study aimed to evaluate the proteins and pathways of chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis (IPF), and mustard lung disease (MLD).

METHODS AND RESULTS

After collecting the data and determining the gene list of each disease, gene expression changes were examined in comparison to healthy individuals. Protein-protein interaction (PPI) and pathway enrichment analysis were used to evaluate genes and shared pathways of the four diseases. There were 22 shared genes, including ACTB, AHSG, ALB, APO, A1, APO C3, FTH1, GAPDH, GC, GSTP1, HP, HSPB1, IGKC, KRT10, KRT9, LCN1, PSMA2, RBP4, 100A8, S100A9, TF, and UBE2N. The major biological pathways in which these genes are involved are inflammatory pathways. Some of these genes activate different pathways in each disease, leading to the induction or inhibition of inflammation.

CONCLUSION

Identification of the genes and shared pathways of diseases can contribute to identifying pathogenesis pathways and designing preventive and therapeutic strategies.

Comparison of optimized machine learning approach to the understanding of medial tibial stress syndrome in male military personnel

PURPOSE

This study investigates the applicability of optimized machine learning (ML) approach for the prediction of Medial tibial stress syndrome (MTSS) using anatomic and anthropometric predictors.

METHOD

To this end, 180 recruits were enrolled in a cross-sectional study of 30 MTSS (30.36 ± 4.80 years) and 150 normal (29.70 ± 3.81 years). Twenty-five predictors/features, including demographic, anatomic, and anthropometric variables, were selected as risk factors. Bayesian optimization method was used to evaluate the most applicable machine learning algorithm with tuned hyperparameters on the training data. Three experiments were performed to handle the imbalances in the data set. The validation criteria were accuracy, sensitivity, and specificity.

RESULTS

The highest performance (even 100%) was observed for the Ensemble and SVM classification models while using at least 6 and 10 most important predictors in undersampling and oversampling experiments, respectively. In the no-resampling experiment, the best performance (accuracy = 88.89%, sensitivity = 66.67%, specificity = 95.24%, and AUC = 0.8571) was achieved for the Naive Bayes classifier with the 12 most important features.

CONCLUSION

The Naive Bayes, Ensemble, and SVM methods could be the primary choices to apply the machine learning approach in MTSS risk prediction. These predictive methods, alongside the eight common proposed predictors, might help to more accurately calculate the individual risk of developing MTSS at the point of care.

Safety and immunogenicity of a recombinant receptor-binding domain-based protein subunit vaccine (Noora vaccine™) against COVID-19 in adults: A randomized, double-blind, placebo-controlled, Phase 1 trial

The development of a safe and effective vaccine is essential to protect populations against coronavirus disease 2019 (COVID-19). There are several vaccine candidates under investigation with different mechanisms of action. In the present study, we have evaluated the safety and immunogenicity of a recombinant receptor-binding domain (RBD)-based protein subunit vaccine (Noora vaccine) against COVID-19 in adults. This Phase 1 trial is a randomized, double-blind, placebo-controlled study to evaluate the safety and immunogenicity of the recombinant RBD-based protein subunit vaccine (Noora vaccine) against COVID-19 in healthy adults volunteers. Eligible participants were included in this study after evaluating their health status and considering the exclusion criteria. They were then randomized into three groups and received three doses of vaccine (80 µg, 120 µg, and placebo) on Days 0, 21, and 35. Primary outcomes including solicited, unsolicited, and medically attended adverse events were recorded during this study. Secondary outcomes including the humoral and cellular immunity (including anti-RBD IgG antibody and neutralizing antibody) were measured on Days 0, 21, 28, 35, 42, and 49 by using the ELISA kit and the Virus Neutralization Test (VNT) was performed on day 49. Totally 70 cases were included in this Phase 1 trial and 60 of them completed the study. Safety assessments showed no severe adverse events. Local pain at the vaccine injection site occurred in 80% of the vaccinated volunteers. Induration and redness at the injection site were the other adverse reactions of this vaccine. There was no significant difference between the studied groups regarding adverse reactions. Anti-RBD IgG antibody and neutralizing antibody assessment showed significant seroconversion in comparison to the placebo group (80%, and 100% respectively, p < 0.001). The cellular immunity panel also showed mild to moderate induction of TH1 responses and the VNT showed 78% of seroprotection. The results of this Phase 1 trial showed acceptable safety without serious adverse events and significant seroconversions in the humoral and cellular immunity panel. The dose of 80 µg is an appropriate dose for injection in the next phases of the trial.

A complete, evidence-based review on novichok poisoning based on epidemiological aspects and clinical management

Background: The whole world has learned about the existence of a highly toxic neuro-paralytic substance called Novichok. A wide range of neuro-paralytic toxins were used during the wars of decades ago, which also had harmful and irreversible effects. Fortunately, the establishment of conventions prohibiting the use of these weapons prevented the adverse clinical consequences of these compounds. What we did in the present study was to evaluate the clinical features of Novichok, how to manage exposure to it, and to evaluate the prognostic aspects associated with this poisoning agent. Methods: The manuscript especial databases including Medline, Web of knowledge, Google scholar, and Scopus were deeply searched by the two blinded investigators for all eligible studies based on the considered keywords. Initially 98 articles were initially collected by database searching that considering eligibility criteria, 83 articles were finally eligible for the final assessment. There is a lack of clinical trials and case-cohort studies on general population about treatment and side effects when it comes to human nerve agents and most of the data in our search is based on animal studies. Results: In evaluating various clinical, auto physiological and prognostic aspects of exposure to these substances, special attention was necessary to the following points. First, Novichok agents are considered more potent than other toxic agents. Pathophysiologically, these agents irreversibly bind acetylcholinesterase and produce a rapid cholinergic toxidrome which is responsible for the clinical manifestations as well as the potential dangerous and life threatening side effects caused by these agents. Uniquely, these agents are thought to also target every neuron in the central and peripheral nervous system. As a managerial and therapeutic approach, early and timely treatment of its related complication along with prevents massive exposure and decontamination in addition to rapid resuscitation can prohibit debilitating neuropathy and death due to facing it. Conclusion: The present review highlights the importance of recognizing the potential acute toxic effects of Novichok agents, diagnostic and therapeutic approaches (life-saving antidotal therapy) to complications and ultimately the application of guidelines to improve the prognosis of exposure to these agents for both victims and medical community.

A Computer-based Analysis for Identification and Quantification of Small Airway Disease in Lung Computed Tomography Images: A Comprehensive Review for Radiologists

Computed tomography (CT) imaging is being increasingly used in clinical practice for detailed characterization of lung diseases. Respiratory diseases involve various components of the lung, including the small airways. Evaluation of small airway disease on CT images is challenging as the airways cannot be visualized directly by a CT scanner. Small airway disease can manifest as pulmonary air trapping (AT). Although AT may be sometimes seen as mosaic attenuation on expiratory CT images, it is difficult to identify diffuse AT visually. Computer technology advances over the past decades have provided methods for objective quantification of small airway disease on CT images. Quantitative CT (QCT) methods are being rapidly developed to quantify underlying lung diseases with greater precision than subjective visual assessment of CT images. A growing body of evidence suggests that QCT methods can be practical tools in the clinical setting to identify and quantify abnormal regions of the lung accurately and reproducibly. This review aimed to describe the available methods for the identification and quantification of small airway disease on CT images and to discuss the challenges of implementing QCT metrics in clinical care for patients with small airway disease.

Overview of herbal therapy of acute and chronic pulmonary disease: a conceptual map

Purpose

Acute and chronic obstructive pulmonary disease (COPD) is a common and progressive lung disease that makes breathing difficult over time and can even lead to death. Despite this, there is no definitive treatment for it yet. This study aims to evaluate the studies on single and combined herbal interventions affecting COPD.

Design/methodology/approach

In this study, all articles published in English up to 2020 were extracted from the Web of Science (WoS) database and collected using Boolean tools based on keywords, titles and abstracts. Finally, the data required for bibliographic analysis, such as the author(s), publication year, academic journal, institution, country of origin, institution, financial institution and keywords were extracted from the database.

Findings

A total of 573 articles were analyzed. The number of papers in the lung disease field showed an upward trend from 1984 to 2021, and there was a surge in paper publications in 2013. China, Korea and Brazil published the highest number of studies on COPD, and Chinese medical universities published the most papers. Three journals that received the highest scores in this study were the Journal of Ethnopharmacology, International Immunopharmacology and Plos One. In the cloud map, expression, activation and expression were the most frequently researched subjects. In the plus and author keywords, acute lung injury was the most commonly used word. Inflammation, expression of various genes, nitric oxide-dependent pathways, NFkappa B, TNFalpha and lipopolysaccharide-dependent pathways were the mechanisms underlying COPD. Scientometric analysis of COPD provides a vision for future research and policymaking.

Originality/value

This study aimed to evaluate the studies on single and combined herbal interventions affecting COPD.

Tandem repeats ubiquitously flank and contribute to translation initiation sites

Background

While the evolutionary divergence of cis-regulatory sequences impacts translation initiation sites (TISs), the implication of tandem repeats (TRs) in TIS selection remains largely elusive. Here, we employed the TIS homology concept to study a possible link between TRs of all core lengths and repeats with TISs.

Methods

Human, as reference sequence, and 83 other species were selected, and data was extracted on the entire protein-coding genes (n = 1,611,368) and transcripts (n = 2,730,515) annotated for those species from Ensembl 102. Following TIS identification, two different weighing vectors were employed to assign TIS homology, and the co-occurrence pattern of TISs with the upstream flanking TRs was studied in the selected species. The results were assessed in 10-fold cross-validation.

Results

On average, every TIS was flanked by 1.19 TRs of various categories within its 120 bp upstream sequence, per species. We detected statistically significant enrichment of non-homologous human TISs co-occurring with human-specific TRs. On the contrary, homologous human TISs co-occurred significantly with non-human-specific TRs. 2991 human genes had at least one transcript, TIS of which was flanked by a human-specific TR. Text mining of a number of the identified genes, such as CACNA1A, EIF5AL1, FOXK1, GABRB2, MYH2, SLC6A8, and TTN, yielded predominant expression and functions in the human brain and/or skeletal muscle.

Conclusion

We conclude that TRs ubiquitously flank and contribute to TIS selection at the trans-species level. Future functional analyses, such as a combination of genome editing strategies and in vitro protein synthesis may be employed to further investigate the impact of TRs on TIS selection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01075-5.

Comparative proteomic analysis of mustard lung as a complicated disease using systems biology approach

During Iraq-Iran conflict, chemical weapons, particularly SM gas, were used numerous times, whose aftereffects are still present. This study aimed to compare serum proteome in the chronic ML (n = 10) and HC (n = 10). TMT label-based quantitative proteomics was used to examine serums from two groups. Among total significant proteins, 14 proteins were upregulated (log₂ ≥ FC 0.5, p 0.05), and 6 proteins were downregulated (log₂ ≤ FC - 0.5, p 0.05). By helping PPI network, and EA, 11 main pathways connected to significantly different protein expression levels were discovered, including inflammatory and cell adhesion signaling pathways. It may be deduced that the wounded organs of exposed individuals experience poor repair cycles of cell degeneration and regeneration because certain repair signals were elevated while other structural and adhesion molecules were downregulated. The systems biology approach can help enhance our basic knowledge of biological processes, and contribute to a deeper understanding of pathophysiological mechanisms, as well as the identification of potential biomarkers of disease.

Tear proteomics analysis of patient suffered from delayed mustard gas keratopathy

Understanding the molecular and cellular mechanisms involved in the pathogenesis of ocular injured induced by mustard gas can help better identify complications and discover appropriate therapies. This study aimed to analyze the proteomics of tears of chemical warfare victims with mustard gas ocular injuries and compare it with healthy individuals. In this case-control research, 10 mustard gas victims with long-term ocular difficulties (Chronic) were included in the patient group, while 10 healthy persons who were age and sex matched to the patients were included in the control group. Schirmer strips were used to collect the tears of the participants. Proteomics experiments were performed using the high-efficiency TMT10X method to evaluate the tear protein profile, and statistical bioinformatics methods were used to identify the differently expressed proteins. 24 proteins had different expressions between the two groups. Among these 24 proteins, 8 proteins had increased expression in veterans' tears, while the remaining 16 proteins had decreased expression. Reactome pathways were used to look at proteins with various expressions, and 13 proteins were found to be engaged in the immune system, 9 of which were effective in the innate immune system, and 5 proteins were effective in the complement cascade. Ocular mustard gas exposure may cause a compromised immune system on the eye's surface, exposing the cornea to external and endogenous infections, and eventually causing corneal opacity and reduced vision.

Proteomics analysis of chronic skin injuries caused by mustard gas

Sulfur mustard (SM) is an alkylating and forming chemical that was widely used by Iraqi forces during the Iran–Iraq wars. One of the target organs of SM is the skin. Understanding the mechanisms involved in the pathogenesis of SM may help better identify complications and find appropriate treatments. The current study collected ten SM-exposed patients with long-term skin complications and ten healthy individuals. Proteomics experiments were performed using the high-efficiency TMT10X method to evaluate the skin protein profile, and statistical bioinformatics methods were used to identify the differentially expressed proteins. One hundred twenty-nine proteins had different expressions between the two groups. Of these 129 proteins, 94 proteins had increased expression in veterans' skins, while the remaining 35 had decreased expression. The hub genes included RPS15, ACTN1, FLNA, HP, SDHC, and RPL29, and three modules were extracted from the PPI network analysis. Skin SM exposure can lead to oxidative stress, inflammation, apoptosis, and cell proliferation.

Causal Path of COPD Progression-Associated Genes in Different Biological Samples

Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease with pulmonary and extra-pulmonary complications. Due to the disease's systemic nature, many investigations investigated the genetic alterations in various biological samples. We aimed to infer causal genes in COPD's pathogenesis in different biological samples using elastic-net logistic regression and the Structural Equation Model. Samples of small airway epithelial cells, bronchoalveolar lavage macrophages, lung tissue biopsy, sputum, and blood samples were selected (135, 70, 235, 143, and 226 samples, respectively). Elastic-net Logistic Regression analysis was implemented to identify the most important genes involved in COPD progression. Thirty-three candidate genes were identified as essential factors in the pathogenesis of COPD and regulation of lung function. Recognized candidate genes in small airway epithelial (SAE) cells have the highest area under the ROC curve (AUC = 97%, SD = 3.9%). Our analysis indicates that macrophages and epithelial cells are more influential in COPD progression at the transcriptome level.

Predominant monomorphism of the RIT2 and GPM6B exceptionally long GA blocks in human and enriched divergent alleles in the disease compartment

Across human protein-coding genes, the human neuron-specific genes, RIT2 and GPM6B, contain the two longest GA short tandem repeats (STRs) of 11 and 9-repeats, respectively, the length ranges of which are functional, and result in gene expression alteration. Here we sequenced the RIT2 and GPM6B STRs in 600 human subjects, consisting of late-onset neurocognitive disorder (n = 200), multiple sclerosis (n = 200), and controls (n = 200). Furthermore, we selected two large human databases, including the general-population-based gnomAD ( https://gnomad.broadinstitute.org ) and a mainly disease-phenotype-archiving database, TOPMed ( https://www.nhlbiwgs.org ), to compare allele frequencies in the general populations vs. the disease compartment. The RIT2 and GPM6B GA-repeats were monomorphic in the human subjects studied, at lengths of 11 and 9-repeats, respectively, and were predominantly human-specific in formula. Exception included a 9/11 genotype of the RIT2 GA-STR in an isolate case of female multiple sclerosis. Exceedingly rare alleles of the two GA repeats were significantly enriched in TOPMed vs. the gnomAD. We report prime instances of predominant monomorphism for specific lengths of STRs in human, and possible enrichment of rare divergent alleles in the disease phenotype compartment. While STRs are most attended because of their high polymorphic nature, STR monomorphism is an underappreciated feature, which may have a link with natural selection and disease.

Genome-wide prediction and prioritization of human aging genes by data fusion: a machine learning approach

Background

Machine learning can effectively nominate novel genes for various research purposes in the laboratory. On a genome-wide scale, we implemented multiple databases and algorithms to predict and prioritize the human aging genes (PPHAGE).

Results

We fused data from 11 databases, and used Naïve Bayes classifier and positive unlabeled learning (PUL) methods, NB, Spy, and Rocchio-SVM, to rank human genes in respect with their implication in aging. The PUL methods enabled us to identify a list of negative (non-aging) genes to use alongside the seed (known age-related) genes in the ranking process. Comparison of the PUL algorithms revealed that none of the methods for identifying a negative sample were advantageous over other methods, and their simultaneous use in a form of fusion was critical for obtaining optimal results (PPHAGE is publicly available at https://cbb.ut.ac.ir/pphage).

Conclusion

We predict and prioritize over 3,000 candidate age-related genes in human, based on significant ranking scores. The identified candidate genes are associated with pathways, ontologies, and diseases that are linked to aging, such as cancer and diabetes. Our data offer a platform for future experimental research on the genetic and biological aspects of aging. Additionally, we demonstrate that fusion of PUL methods and data sources can be successfully used for aging and disease candidate gene prioritization.

Link between short tandem repeats and translation initiation site selection

BACKGROUND

Despite their vast biological implication, the relevance of short tandem repeats (STRs)/microsatellites to the protein-coding gene translation initiation sites (TISs) remains largely unknown.

METHODS

We performed an Ensembl-based comparative genomics study of all annotated orthologous TIS-flanking sequences in human and 46 other species across vertebrates, on the genomic DNA and cDNA platforms (755,956 TISs), aimed at identifying human-specific STRs in this interval. The collected data were used to examine the hypothesis of a link between STRs and TISs. BLAST was used to compare the initial five amino acids (excluding the initial methionine), codons of which were flanked by STRs in human, with the initial five amino acids of all annotated proteins for the orthologous genes in other vertebrates (total of 5,314,979 pair-wise TIS comparisons on the genomic DNA and cDNA platforms) in order to compare the number of events in which human-specific and non-specific STRs occurred with homologous and non-homologous TISs (i.e., ≥ 50% and < 50% similarity of the five amino acids).

RESULTS

We detected differential distribution of the human-specific STRs in comparison to the overall distribution of STRs on the genomic DNA and cDNA platforms (Mann Whitney U test p = 1.4 × 10-11 and p < 7.9 × 10-11, respectively). We also found excess occurrence of non-homologous TISs with human-specific STRs and excess occurrence of homologous TISs with non-specific STRs on both platforms (p < 0.00001).

CONCLUSION

We propose a link between STRs and TIS selection, based on the differential co-occurrence rate of human-specific STRs with non-homologous TISs and non-specific STRs with homologous TISs.

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm

Introduction:

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5’s Algorithm.

Method:

An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5’s Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then.

Results:

The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase.

Conclusion:

Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Conceptual Model of Clinical Governance Information System for Statistical Indicators by Using UML in Two Sample Hospitals

Objective:

The purpose of this study was investigating situation and presenting a conceptual model for clinical governance information system by using UML in two sample hospitals.

Background:

However, use of information is one of the fundamental components of clinical governance; but unfortunately, it does not pay much attention to information management.

Material and Methods:

A cross sectional study was conducted in October 2012- May 2013. Data were gathered through questionnaires and interviews in two sample hospitals. Face and content validity of the questionnaire has been confirmed by experts. Data were collected from a pilot hospital and reforms were carried out and Final questionnaire was prepared. Data were analyzed by descriptive statistics and SPSS 16 software.

Results:

With the scenario derived from questionnaires, UML diagrams are presented by using Rational Rose 7 software. The results showed that 32.14 percent Indicators of the hospitals were calculated. Database was not designed and 100 percent of the hospital’s clinical governance was required to create a database.

Conclusion:

Clinical governance unit of hospitals to perform its mission, do not have access to all the needed indicators. Defining of Processes and drawing of models and creating of database are essential for designing of information systems.

The Diagnostic Value of Skin Disease Diagnosis Expert System

Background:

Evaluation is a necessary measure to ensure the effectiveness and efficiency of all systems, including expert systems. The aim of this study was to determine the diagnostic value of expert system for diagnosis of complex skin diseases.

Methods:

A case-control study was conducted in 2015 to determine the diagnostic value of an expert system. The study population included patients who were referred to Razi Specialized Hospital, affiliated to Tehran University of Medical Sciences. The control group was selected from patients without the selected skin diseases. Data collection tool was a checklist of clinical signs of diseases including pemphigus vulgaris, lichen planus, basal cell carcinoma, melanoma, and scabies. The sample size formula estimated 400 patients with skin diseases selected by experts and 200 patients without the selected skin diseases. Patient selection was undertaken with randomized stratified sampling and their sign and symptoms were logged into the system. Physician’s diagnosis was determined as the gold standard and was compared with the diagnosis of expert system by SPSS software version 16 and STATA. Kappa statistics, indicators of sensitivity, specificity, accuracy and confidence intervals were calculated for each disease. An accuracy of 90% was considered appropriate.

Results:

Comparing the results of expert system and physician’s diagnosis at the evaluation stage showed an accuracy of 97.1%, sensitivity of 97.5% and specificity of 96.5% The Kappa test indicated a high agreement of 93.6%.

Conclusion:

The expert system can diagnose complex skin diseases. Development of such systems is recommended to identify all skin diseases.

A comparative study of three speckle reducing methods for intima-media thickness ultrasound images

BACKGROUND

Ultrasonic evaluation of intima-media thickness (IMT) is an early marker of assessing the development of atherosclerosis and determining cardiovascular risk. To attain the best possible diagnosis, it is essential that medical images be clear, sharp and without noise and artifacts.

OBJECTIVES

Comparison of speckle reducing anisotropic diffusion (SRAD), discrete (DTD) and continuum topological derivative (CTD) on B-mode ultrasound images of common carotid and brachial arteries throughout the cardiac cycle.

PATIENTS AND METHODS

In a cross-sectional design, an examination was performed on forty-two human subjects with a mean age of 44 ± 6 years from April 2013 to June 2013. This study was approved by the ethics committees of Kashan University of Medical Sciences and Beheshti Hospital. An ultrasonic examination of common carotid and brachial arteries of forty-two human subjects was performed. The program was designed in MATLAB software to extract consecutive B-mode images and apply region of interest (ROI) on the IMT of the common carotid and brachial arteries. Then, three different noise reduction filters with the Canny edge detection were used in ROI separately. Finally, the program measured the image quality metrics.

RESULTS

According to values of eleven different image quality metrics (mentioned in the main text), there was a significant difference between CTD, DTD and SRAD filters with the Canny edge detection status in the common carotid and brachial arteries throughout the cardiac cycle (all P values < 0.001). For example, peak signal to noise ratios (PSNR) using CTD, DTD and SRAD filters were 95.43 ± 0.64, 88.86 ± 0.82 and 73.02 ± 0.20 in common carotid and 96.39 ± 1.25, 92.58 ± 0.11 and 88.27 ± 0.63 in brachial arteries, respectively (both P values < 0.001).

CONCLUSIONS

By measuring image quality metrics, this study showed that DTD and CTD filters with the Canny edge detection respectively, are better than SRAD filter with the Canny detection for speckle suppression and details preservation in both arteries in the ultrasound images.

Comparison of different edge detections and noise reduction on ultrasound images of carotid and brachial arteries using a speckle reducing anisotropic diffusion filter

BACKGROUND

Common carotid artery (CCA) ultrasound with measurement of intima-media thickness (IMT) is a safe and noninvasive technique for assessing subclinical atherosclerosis and determining cardiovascular risks. Moreover, the pattern of wall thickening in the brachial artery (BA) is rather diffuse compared to the carotid artery and may be a more sensitive indicator of long-term systemic exposure to risk factors. Therefore noninvasive evaluation of mechanical parameters changes of both arteries has gained the attention of researchers.

OBJECTIVES

The aim of this study was to compare different edge detection techniques with speckle reducing anisotropic diffusion (SRAD) de-noising filter in ultrasound images of both arteries.

PATIENTS AND METHODS

In a cross-sectional design, an examination was performed on ten men with mean age of 40 ± 5 years from September 2012 to March 2013 through random sampling. An ultrasonic examination of the left CCA and BA was performed. The program was designed in the MATLAB software to extract consecutive images in JPEG format from the AVI. Another program was designed in the MATLAB software to apply regions of interest (ROI) on the IMT of the posterior wall of common carotid and brachial arteries. Next, different edge detections and SRAD filter were applied to the ROI, separately. Finally, the program measured mean-squared error (MSE) and peak signal to noise ratio (PSNR).

RESULTS

The lowest values of MSE and highest values of PSNR were achieved by Canny edge detection with de-noising SRAD filter for IMT of left CCA and BA in 90 frames.

CONCLUSIONS

Based on the result, by measuring the MSE and PSNR, this study showed Canny edge detection with SRAD filter is better than other edge detections in terms of speckle suppression and details preservation in CCA and BA ultrasound images.

Conceptual Model of Clinical Governance Information System for Statistical Indicators by Using UML in Two Sample Hospitals

Objective:

The purpose of this study was investigating situation and presenting a conceptual model for clinical governance information system by using UML in two sample hospitals.

Background:

However, use of information is one of the fundamental components of clinical governance; but unfortunately, it does not pay much attention to information management.

Material and Methods:

A cross sectional study was conducted in October 2012- May 2013. Data were gathered through questionnaires and interviews in two sample hospitals. Face and content validity of the questionnaire has been confirmed by experts. Data were collected from a pilot hospital and reforms were carried out and Final questionnaire was prepared. Data were analyzed by descriptive statistics and SPSS 16 software.

Results:

With the scenario derived from questionnaires, UML diagrams are presented by using Rational Rose 7 software. The results showed that 32.14 percent Indicators of the hospitals were calculated. Database was not designed and 100 percent of the hospital’s clinical governance was required to create a database.

Conclusion:

Clinical governance unit of hospitals to perform its mission, do not have access to all the needed indicators. Defining of Processes and drawing of models and creating of database are essential for designing of information systems.

Improving service accessibility in service-oriented HIS

Nowadays, new trend in design and implementation of Hospital Information System (HIS) is towards using Web-based Service-Oriented Architecture (SOA). However, the standard SOA includes an insensitive service store through which the accessibility of some hospital services becomes difficult when their specification or network address are changed or missed. This paper discusses problems of insensitive service store and then presents a model where a sensitive service store is used to mitigate the problems. To show the efficiency of the proposed model, HIS of the Shahid Beheshti Hospital of Kashan including information systems of Admission, Outpatient, Ward, Pharmacy, Medical Document, Discharge and Insurance was designed and implemented with sensitive service store and its performance was considered.