CCSynergy: an integrative deep-learning framework enabling context-aware prediction of anti-cancer drug synergy.

Combination therapy is a promising strategy for confronting the complexity of cancer. However, experimental exploration of the vast space of potential drug combinations is costly and unfeasible. Therefore, computational methods for predicting drug synergy are much needed for narrowing down this space, especially when examining new cellular contexts. Here, we thus introduce CCSynergy, a flexible, context aware and integrative deep-learning framework that we have established to unleash the potential of the Chemical Checker extended drug bioactivity profiles for the purpose of drug synergy prediction. We have shown that CCSynergy enables predictions of superior accuracy, remarkable robustness and improved context generalizability as compared to the state-of-the-art methods in the field. Having established the potential of CCSynergy for generating experimentally validated predictions, we next exhaustively explored the untested drug combination space. This resulted in a compendium of potentially synergistic drug combinations on hundreds of cancer cell lines, which can guide future experimental screens.

Using the Bayesian variational spike and slab model in a genome-wide association study for finding associated loci with bipolar disorder.

OBJECTIVE: The genome-wide association studies (GWAS) analysis, the most successful technique for discovering disease-related genetic variation, has some statistical concerns, including multiple testing, the correlation among variants (single-nucleotide polymorphisms) based on linkage disequilibrium and omitting the important variants when fitting the model with just one variant. To eliminate these problems in a small sample-size study, we used a sparse Bayesian learning model for finding bipolar disorder (BD) genetic variants. METHODS: This study used the Wellcome Trust Case Control Consortium data set, including 1998 BD cases and 1500 control samples, and after quality control, 380,628 variants were analysed. In this GWAS, a Bayesian logistic model with hierarchical shrinkage spike and slab priors was used, with all variants considered simultaneously in one model. In order to decrease the computational burden, an alternative inferential method, Bayesian variational inference, has been used. RESULTS: Thirteen variants were selected as associated with BD. The three of them (rs7572953, rs1378850 and rs4148944) were reported in previous GWAS. Eight of which were related to hemogram parameters, such as lymphocyte percentage, plateletcrit and haemoglobin concentration. Among selected related genes, GABPA, ELF3 and JAM2 were enriched in the platelet-derived growth factor pathway. These three genes, along with APP, ARL8A, CDH23 and GPR37L1, could be differential diagnostic variants for BD. CONCLUSIONS: By reducing the statistical restrictions of GWAS analysis, the application of the Bayesian variational spike and slab models can offer insight into the genetic link with BD even with a small sample size. To uncover related variations with other traits, this model needs to be further examined.

Novel anthropometric indices for predicting type 2 diabetes mellitus.

BACKGROUND: This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community. METHODS: In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC). RESULTS: The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes. CONCLUSION: The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.

Interleukin-24-mediated antitumor effects against human glioblastoma via upregulation of P38 MAPK and endogenous TRAIL-induced apoptosis and LC3-II activation-dependent autophagy.

BACKGROUND: Melanoma differentiation-associated gene 7 (Mda-7) encodes IL-24, which can induce apoptosis in cancer cells. A novel gene therapy approach to treat deadly brain tumors, recombinant mda-7 adenovirus (Ad/mda-7) efficiently kills glioma cells. In this study, we investigated the factors affecting cell survival and apoptosis and autophagy mechanisms that destroy glioma cells by Ad/IL-24. METHODS: Human glioblastoma U87 cell line was exposed to a multiplicity of infections of Ad/IL-24. Antitumor activities of Ad/IL-24 were assessed by cell proliferation (MTT) and lactate dehydrogenase (LDH) release analysis. Using flow cytometry, cell cycle arrest and apoptosis were investigated. Using the ELISA method, the tumor necrosis factor (TNF-α) level was determined as an apoptosis-promoting factor and Survivin level as an anti-apoptotic factor. The expression levels of TNF-related apoptosis inducing ligand(TRAIL) and P38 MAPK genes were assessed by the Reverse transcription-quantitative polymerase chain reaction(RT­qPCR) method. The expression levels of caspase-3 and protein light chain 3-II (LC3-II) proteins were analyzed by flow cytometry as intervening factors in the processes of apoptosis and autophagy in the cell death signaling pathway, respectively. RESULTS: The present findings demonstrated that transduction of IL-24 inhibited cell proliferation and induced cell cycle arrest and cell apoptosis in glioblastoma. Compared with cells of the control groups, Ad/IL24-infected U87 cells exhibited significantly increased elevated caspase-3, and TNF-α levels, while the survivin expression was decreased. TRAIL was shown to be upregulated in tumor cells after Ad/IL-24 infection and studies of the apoptotic cascade regulators indicate that Ad/IL-24 could further enhance the activation of apoptosis through the TNF family of death receptors. In the current study, we demonstrate that P38 MAPK is significantly activated by IL-24 expression. In addition, the overexpression of mda-7/IL-24 in GBM cells induced autophagy, which was triggered by the upregulation of LC3-II. CONCLUSIONS: Our study demonstrates the antitumor effect of IL-24 on glioblastoma and may be a promising therapeutic approach for GBM cancer gene therapy.

Health-related quality of life in persons with haemophilia in Afghanistan.

INTRODUCTION: Haemophilia is the most common severe congenital bleeding disorder and can significantly influence patients' quality of life. The health-related quality of life (HRQoL) is a multi-dimensional concept that assess effect of different aspects of health status, including physical, mental, and social domains. Identification of the factors affecting the HRQoL of Persons with Haemophilia (PWH) can guide health care system to better management of patients. AIM: The aim of the present study is to evaluate HRQoL in PWH in Afghanistan. METHODS: This cross-sectional study was conducted on 100 PWH in Kabul City, Afghanistan. Data were collected using 36-Item-Short-Form Health Survey (SF-36) questionnaire and analysed using correlation coefficients and regression analysis. RESULTS: The mean scores for the SF-36 questionnaire 8 domains range from 33 ± 38.3 to 58.15 ± 20.5. The highest mean value belongs to physical function (PF) (58.15), whereas the lowest is related to restriction of activities due to emotional problems (RE) (33.00). A significant association (p < .005) was observed between all domains of SF-36 and patients' age except for PF (p = .055) and general health (GH) (p = .75). A significant association was also observed between all HRQoL domains and the severity of haemophilia (p < .001). The severity of haemophilia was the significant predictor for Physical Component Summary (PCS) and Mental Component Summary (MCS) (p < .001). CONCLUSION: Due to the reduced HRQoL in Afghan PWH, special attention by health care system should be paid to improve patients' quality of life.

Towards Feasible Solutions for Load Monitoring in Quebec Residences.

For many years, energy monitoring at the most disaggregate level has been mainly sought through the idea of Non-Intrusive Load Monitoring (NILM). Developing a practical application of this concept in the residential sector can be impeded by the technical characteristics of case studies. Accordingly, several databases, mainly from Europe and the US, have been publicly released to enable basic research to address NILM issues raised by their challenging features. Nevertheless, the resultant enhancements are limited to the properties of these datasets. Such a restriction has caused NILM studies to overlook residential scenarios related to geographically-specific regions and existent practices to face unexplored situations. This paper presents applied research on NILM in Quebec residences to reveal its barriers to feasible implementations. It commences with a concise discussion about a successful NILM idea to highlight its essential requirements. Afterward, it provides a comparative statistical analysis to represent the specificity of the case study by exploiting real data. Subsequently, this study proposes a combinatory approach to load identification that utilizes the promise of sub-meter smart technologies and integrates the intrusive aspect of load monitoring with the non-intrusive one to alleviate NILM difficulties in Quebec residences. A load disaggregation technique is suggested to manifest these complications based on supervised and unsupervised machine learning designs. The former is aimed at extracting overall heating demand from the aggregate one while the latter is designed for disaggregating the residual load. The results demonstrate that geographically-dependent cases create electricity consumption scenarios that can deteriorate the performance of existing NILM methods. From a realistic standpoint, this research elaborates on critical remarks to realize viable NILM systems, particularly in Quebec houses.

Role of genetic variants and host polymorphisms on COVID-19: From viral entrance mechanisms to immunological reactions.

Coronavirus disease 2019 (COVID-19), caused by a highly pathogenic emerging virus, is called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Knowledge regarding the pathogenesis of this virus is in infancy; however, investigation on the pathogenic mechanisms of the SARS-CoV-2 is underway. In COVID-19, one of the most remarkable characteristics is the wide range of disease manifestation and severity seen across individuals of different ethnic backgrounds and geographical locations. To effectively manage COVID-19 in the populations, beyond SARS-CoV-2 detection, serological response assessment, and analytic techniques, it is critical to obtain knowledge about at-risk individuals and comprehend the identified variations in the disease's severity in general and also in the populations' levels. Several factors can contribute to variation in disease presentation, including population density, gender and age differences, and comorbid circumstances including diabetes mellitus, hypertension, and obesity. Genetic factors presumably influence SARS-CoV-2 infection susceptibility. Besides this, COVID-19 has also been linked with a higher risk of mortality in men and certain ethnic groups, revealing that host genetic characteristics may affect the individual risk of death. Also, genetic variants involved in pathologic processes, including virus entrance into cells, antiviral immunity, and inflammatory response, are not entirely understood. Regarding SARS-CoV-2 infection characteristics, the present review suggests that various genetic polymorphisms influence virus pathogenicity and host immunity, which might have significant implications for understanding and interpreting the matter of genetics in SARS-CoV-2 pathogenicity and customized integrative medical care based on population investigation.

Cytotoxicity of metformin against HT29 colon cancer cells contributes to mitochondrial Sirt3 upregulation.

Cancer and diabetes, the two mitochondria-related diseases, have recently been linked to silent mating-type information regulation 2 homolog 3 (SIRT3) activity irregularities. In this study, the effect of metformin, an antidiabetic with anticancer properties, has been evaluated on mitochondrial functionality markers, cell death pathways, and SIRT3 enzyme activity in the colon cancer cell line, HT-29, and human embryonic kidney cells (HEK 293). HT-29 cells were treated with metformin (5, 10, 20, 40, and 80 µM) for 24, 48, and 72 h for measuring the IC50 concentration. Reactive oxygen species (ROS) production, apoptosis, mitochondrial membrane potential, SIRT3 activity, and expression were evaluated against the colon cancer cell line, HT-29. Results indicated a higher ROS production at 6 than 12 h with metformin treatment. Metformin modified the mitochondrial membrane potential, resulting in cell death induction. Results from SIRT3 activity and expression showed that metformin increased its activity and expression in cancer cells. In conclusion, metformin in HT-29 cells disturbed the mitochondrial activity via increased ROS levels and SIRT3 activity, and these rapid modifications may play a key role in its cytotoxic property.

Genomic organization underlying deletional robustness in bacterial metabolic systems.

Large-scale DNA deletions and gene loss are pervasive in bacterial genomes. This observation raises the possibility that evolutionary adaptation has altered bacterial genome organization to increase its robustness to large-scale tandem gene deletions. To find out, we systematically analyzed 55 bacterial genome-scale metabolisms and showed that metabolic gene ordering renders an organism's viability in multiple nutrient environments significantly more robust against tandem multigene deletions than expected by chance. This excess robustness is caused by multiple factors, which include the clustering of essential metabolic genes, a greater-than-expected distance of synthetically lethal metabolic gene pairs, and the clustering of nonessential metabolic genes. By computationally creating minimal genomes, we show that a nonadaptive origin of such clustering could in principle arise as a passive byproduct of bacterial genome growth. However, because genome randomization forces such as translocation and inversion would eventually erode such clustering, adaptive processes are necessary to sustain it. We provide evidence suggesting that this organization might result from adaptation to ongoing gene deletions, and from selective advantages associated with coregulating functionally related genes. Horizontal gene transfer in the presence of gene deletions contributes to sustaining the clustering of essential genes. In sum, our observations suggest that the genome organization of bacteria is driven by adaptive processes that provide phenotypic robustness in response to large-scale gene deletions. This robustness may be especially important for bacterial populations that take advantage of gene loss to adapt to new environments.

LncRNA HSPC324 plays role in lung development and tumorigenesis.

Lung cancer is a leading cause of cancer-related death in the world. Therefore, identifying the genes and molecular pathways involved in lung development and tumorigenesis can help us improve the therapeutic strategies of lung cancer. Accumulating evidence confirms that long noncoding RNAs, as a novel layer of regulatory RNA molecules, play an important role in various aspects of the cells. Here, using available high throughput gene expression data, we identified an lncRNA (HSPC324) with high expression level in lung tissue that is distinctly expressed in lung tumor tissues relative to normal. Using GO enrichment and KEGG pathway analyses, we further analyzed the functions and pathways involving the HSPC324-correlated genes. Ectopic expression of lncRNA HSPC324 significantly inhibited proliferation, cell cycle and migration; on the other hand, increased apoptosis and ROS production in lung adenocarcinoma cells. Overall, this study introduces HSPC324 as a new player in the development of lung cancer.

Trends of human brucellosis in Central Iran (2010-2018).

BACKGROUND: Brucellosis is one of the most common infectious diseases worldwide which is caused by direct contact with affected animals or their products. It puts a huge impact on the economy, society, and the environment. Iran is the fourth endemic country for brucellosis in the world. It has been described a new epidemiological feature of the disease and its trends in Isfahan province, as one of the endemic areas of brucellosis in Central Iran. MATERIALS AND METHODS: This is a cross-sectional, population-based study. Data collection was performed using epidemiological questionnaires through Epi-2006 software from the private and public sectors in 22 districts of Isfahan province over 9 years (2010-2018). The results were obtained by the description statistics using the SPSS Statistics software version 20 (SPSS Inc., Chicago, IL, USA). RESULTS: Altogether, 5751 new brucellosis patients were recorded over 9 years. About 70% of these cases were male. The majority of cases had occurred in the age group of 21-30 years. The average incidence of brucellosis over the 9 years was 14.1 cases/100,000 population including 8.8 in the urban versus 45.2 cases in the rural areas. During the 9-year study period, the incidence of brucellosis was increased between 2010 and 2014. From 2014 to 2017, the trend has been decreasing, but in the last year of the study, the trend has been increasing again. Seasonally, the incidence rate was variable between the lowest from October to January and the highest from June to July. CONCLUSION: According to the fluctuation of incidence trend of brucellosis during the 9-year study period in Central Iran, it seems some policy changes regarding to the control and prevention of brucellosis have a role, changes that should be fixed and corrected.

Factors Affecting the Implementation of Early Rehabilitation Care in Patients with Traumatic Brain Injury: A Multidisciplinary Perspective.

Background: Traumatic brain injury is now regarded as the silent epidemic. This disease can cause some physical, cognitive, and psychological impairments that require proper and early rehabilitation interventions. Therefore, the aim of this study was to explore the factors affecting early rehabilitation care in patients with traumatic brain injury based on the experiences of the rehabilitation team. Methods: This qualitative study was conducted as a conventional content analysis from September 2019 to August 2020. For this purpose and given the maximum diversity, 22 members of the rehabilitation team, patients, and their caregivers in trauma level 1 hospitals affiliated with Tehran University of Medical Sciences were selected based on a purposeful sampling method. The data were also collected using semi-structured interviews until data saturation is obtained. Graneheim and Lundman's content analysis method was performed to analyze the data. Results: The data analysis results eventually led to the introduction of three main themes and eight categories. The main themes were associated with early rehabilitation barriers, which included cultural factors and rehabilitation infrastructures. Rehabilitation management was regarded as the main theme regarding the early rehabilitation facilitator. Conclusion: Early rehabilitation is considered a vital rehabilitation stage for patients with traumatic brain injury. Hence, accurate identification of the influential factors on early rehabilitation can help the rehabilitation team promote early rehabilitation care among these patients; it can lead to the revival of the patients' abilities and the improvement of their quality of life.

Tropisetron attenuates tumor growth and progression in an experimental model of mouse lung cancer.

The antineoplastic effects of 5-hydroxytryptamine (5-HT) receptor antagonists have been shown in previous studies. However, the exact underlying mechanisms mediating these antineoplastic effects are unclear. In the present study, we assessed the antineoplastic effects of tropisetron, a 5-HT receptor antagonist, in an experimental model of lung cancer in BALB/c mouse. Lewis lung carcinoma cell line was used to induce lung cancer. Mice were divided into four groups (n = 6) as follows: tumor-bearing mice + tropisetron (5 mg/kg intraperitoneally [IP]), tumor-bearing mice + tropisetron (10 mg/kg IP), tumor-bearing mice + saline, healthy mice + tropisetron (10 mg/kg). Tumor burden, interferon-γ (IFN-γ), interleukin (IL)-4, pathological response, Ki-67, and E-cadherin were assessed using enzyme-linked immunosorbent assay, and real-time polymerase chain reaction. Comet assay was used to assess DNA toxicity. Tropisetrone-treated animals (either 5 or 10 mg/kg) showed significantly lower tumor sizes at the day 24th after tumor induction. Tropisetron received animals also showed significantly higher levels of IFN-γ, E-cadherin, pathologic response, and necrotic cells compared to the saline-treated counterparts. In addition, the levels of IL-4, and Ki-67 were significantly lower in tropisetrone treated mice in comparison with control. Furthermore, tropisteron coadministration signifcantly reduced H2 O2 -induced DNA toxicity while treatment with tropisteron alone showed no adverse effect on DNA. Tropisetrone can be used as a potential antineoplastic drug in lung cancer. This agent can promote its antineoplastic effects in part through modulating inflammatory and proliferating markers.

Estimating the predictability of cancer evolution.

MOTIVATION: How predictable is the evolution of cancer? This fundamental question is of immense relevance for the diagnosis, prognosis and treatment of cancer. Evolutionary biologists have approached the question of predictability based on the underlying fitness landscape. However, empirical fitness landscapes of tumor cells are impossible to determine in vivo. Thus, in order to quantify the predictability of cancer evolution, alternative approaches are required that circumvent the need for fitness landscapes. RESULTS: We developed a computational method based on conjunctive Bayesian networks (CBNs) to quantify the predictability of cancer evolution directly from mutational data, without the need for measuring or estimating fitness. Using simulated data derived from >200 different fitness landscapes, we show that our CBN-based notion of evolutionary predictability strongly correlates with the classical notion of predictability based on fitness landscapes under the strong selection weak mutation assumption. The statistical framework enables robust and scalable quantification of evolutionary predictability. We applied our approach to driver mutation data from the TCGA and the MSK-IMPACT clinical cohorts to systematically compare the predictability of 15 different cancer types. We found that cancer evolution is remarkably predictable as only a small fraction of evolutionary trajectories are feasible during cancer progression. AVAILABILITY AND IMPLEMENTATION: https://github.com/cbg-ethz/predictability\_of\_cancer\_evolution. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Discovering the signature of a lupus-related microRNA profile in the Gene Expression Omnibus repository.

Lupus is one of the most prevalent systemic autoimmune diseases. It is a multifactorial disease in which genetic, epigenetic and environmental factors play significant roles. The pathogenesis of lupus is not yet well understood. However, deregulation of microRNAs (miRNAs) - one of the post-transcriptional regulators of genes - can contribute to the development of autoimmune diseases. Over the last two decades, advances in the profiling of miRNA using microarray have received much attention, and it has been demonstrated that miRNAs play a regulatory role in the pathogenesis of lupus. Therefore, dysregulated miRNAs can be considered as promising diagnostic biomarkers for lupus. This article is an overview of lupus-related miRNA profiling studies and arrays in the Gene Expression Omnibus (GEO) database. The aims of our study were to widen current knowledge of known dysregulated miRNAs as potential biomarkers of SLE and to introduce a bioinformatics approach to using microarray data and finding novel miRNA and gene candidates for further study. We identified hsa-miR-4709-5p, hsa-miR-140, hsa-miR-145, hsa-miR-659, hsa-miR-134, hsa-miR-150, hsa-miR-584, hsa-miR-409 and hsa-miR-152 as potential biomarkers by integrated bioinformatics analysis.

Syntrophy emerges spontaneously in complex metabolic systems.

Syntrophy allows a microbial community as a whole to survive in an environment, even though individual microbes cannot. The metabolic interdependence typical of syntrophy is thought to arise from the accumulation of degenerative mutations during the sustained co-evolution of initially self-sufficient organisms. An alternative and underexplored possibility is that syntrophy can emerge spontaneously in communities of organisms that did not co-evolve. Here, we study this de novo origin of syntrophy using experimentally validated computational techniques to predict an organism's viability from its metabolic reactions. We show that pairs of metabolisms that are randomly sampled from a large space of possible metabolism and viable on specific primary carbon sources often become viable on new carbon sources by exchanging metabolites. The same biochemical reactions that are required for viability on primary carbon sources also confer viability on novel carbon sources. Our observations highlight a new and important avenue for the emergence of metabolic adaptations and novel ecological interactions.

Evaluation of transgenic Leishmania infantum expressing mLLO-BAX-SMAC in the apoptosis of the infected macrophages in vitro and in vivo.

BACKGROUND: Leishmaniasis is an important infectious disease that develops because of escaping parasite from the host immune system or preventing host macrophages apoptosis. Recently, the development of transgenic methods and the manipulation of the parasite genome has provided many advantages. So, in this study, the effect of the transgenic Leishmania infantum expressing mLLO-BAX-SMAC proteins was examined in accelerating host cell apoptosis. METHOD: The entire coding sequence of designed codon-optimized mLLO-Bax-Smac was cloned in the pLexyNeo2 vector and integrated downstream of the 18srRNA locus of L infantum genome by homologous recombination. Next, the expression of mLLO-BAX-SMAC fusion protein was evaluated by the Western blotting technique and the pathogenesis of transgenic parasite was surveyed in vitro and in vivo. RESULTS: The results of PCR and Western blot confirmed proper integration and expression of mLLO-Bax-Smac sequence into the 18srRNA locus of L infantum. Flow cytometry showed accelerating apoptosis of transgenic Leishmania-infected macrophages compared to wild-type parasite. Also, transgenic parasites were less virulent as a fewer parasitic burden was found in the spleen and liver of transgenic-infected mice compared to the control. CONCLUSION: The data suggested that the transgenic L infantum expressing BAX-SMAC can be used as an experimental model for developing vaccination against leishmaniasis.

Socioeconomic - related inequalities in overweight and obesity: findings from the PERSIAN cohort study.

BACKGROUND: Overweight and obesity are major health concerns worldwide, with adverse health consequences during the life span. This study measured socioeconomic inequality in overweight and obesity among Iranian adults. METHODS: Data were extracted from 129,257 Iranian adults (aged 35 years and older) participated in the Prospective Epidemiologic Research Studies in IrAN (PERSIAN) in 14 provinces of Iran in 2014. Socioeconomic-related inequality in overweight and obesity was estimated using the Concentration Index (Cn). The Cn further decomposed to find factors explaining the variability within the Socioeconomic related inequality in overweight and obesity. RESULTS: Of the total number of participants, 1.98, 26.82, 40.76 and 30.43% had underweight, normal weight, overweight and obesity respectively. The age-and sex standardized prevalence of obesity was higher in females than males (39.85% vs 18.79%). People with high socioeconomic status (SES) had a 39 and 15% higher chance of being overweight and obese than low SES people, respectively. The positive value of Cn suggested a higher concentration of overweight (0.081, 95% confidence interval [CI]; 0.074-0.087) and obesity (0.027, 95% CI; 0.021-0.034) among groups with high SES. There was a wide variation in socioeconomic-related inequality in overweight and obesity rate across 14 provinces. The decomposition results suggested that SES factor itself explained 66.77 and 89.07% of the observed socioeconomic inequalities in overweight and obesity among Iranian adults respectively. Following SES, province of residence, physical activity, using hookah and smoking were the major contributors to the concentration of overweight and obesity among the rich. CONCLUSIONS: Overall, we found that overweight and obesity is concentrated among high SES people in the study population. . Accordingly, it seems that intersectional actions should be taken to control and prevent overweight and obesity among higher socioeconomic groups.

Considering smoking status, coexpression network analysis of non-small cell lung cancer at different cancer stages, exhibits important genes and pathways.

Non-small cell lung cancer (NSCLC) is the most common subtype of lung cancer among smokers, nonsmokers, women, and young individuals. Tobacco smoking and different stages of the NSCLC have important roles in cancer evolution and require different treatments. Existence of poorly effective therapeutic options for the NSCLC brings special attention to targeted therapies by considering genetic alterations. In this study, we used RNA-Seq data to compare expression levels of RefSeq genes and to find some genes with similar expression levels. We utilized the "Weighted Gene Co-expression Network Analysis" method for three different datasets to create coexpressed genetic modules having relations with the smoking status and different stages of the NSCLC. Our results indicate seven important genetic modules having important associations with the smoking status and cancer stages. Based on investigated genetic modules and their biological explanation, we then identified 13 newly candidate genes and 7 novel transcription factors in association with the NSCLC, the smoking status, and cancer stages. We then examined those results using other datasets and explained our results biologically to illustrate some important genes in relation with the smoking status and metastatic stage of the NSCLC that can bring some crucial information about cancer evolution. Our genetic findings also can be used as some therapeutic targets for different clinical conditions of the NSCLC.

A panel of noncoding RNAs in non-small-cell lung cancer.

Non-small-lung cancer (NSCLC) is the leading cause of cancer death. Early detection of NSCLC could pave the way for effective therapies. Analysis of molecular genetic biomarkers in biological fluids has been proposed as a useful tool for cancer diagnosis. Here, we aimed to develop a panel of noncoding RNAs (ncRNAs) in sputum for NSCLC early detection. Expression of 11 ncRNAs were analyzed by real-time polymerase chain reaction in sputum samples of 30 NSCLC patients and 30 sex- and age-matched cancer-free controls. Stability of endogenous microRNAs (miRNAs) in sputum was evaluated after 3 and 6 days at 4°C, 6 months, and 1 year at -80°C. Nine ncRNAs showed significant differences of their expression in sputum between NSCLC patients and controls. A logistic regression model with the best prediction was built based on miR-145, miR-126, and miR-7. The composite of the three miRNAs produced 90% sensitivity and specificity in distinguishing NSCLC patients from the controls. Results indicate that miRNAs could be useful biomarkers based on their stability under various storage conditions and maintain differential changes between cancer and control groups. Moreover, measurement of miRNAs in sputum could be a noninvasive approach for detection of lung cancer.