Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model.

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Identification of Risk Factors Associated with Tuberculosis in Southwest Iran: A Machine Learning Method.

Background: Tuberculosis is a principal public health issue. Reducing and controlling tuberculosis did not result in the expected success despite implementing effective preventive and therapeutic programs, one of the reasons for which is the delay in definitive diagnosis. Therefore, creating a diagnostic aid system for tuberculosis screening can help in the early diagnosis of this disease. This research aims to use machine learning techniques to identify economic, social, and environmental factors affecting tuberculosis. Methods: This case-control study included 80 individuals with TB and 172 participants as controls. During January-October 2021, information was collected from thirty-six health centers in Ahvaz, southwest Iran. Five different machine learning approaches were used to identify factors associated with TB, including BMI, sex, age , marital status, education, employment status, size of the family, monthly income, cigarette smoking, hookah smoking, history of chronic illness, history of imprisonment, history of hospital admission, first-class family, second-class family, third-class family, friend, co-worker, neighbor, market, store, hospital, health center, workplace, restaurant, park, mosque, Basij base, Hairdressers and school. The data was analyzed using the statistical programming R software version 4.1.1. Results: According to the calculated evaluation criteria, the accuracy level of 5 SVM, RF, LSSVM, KNN, and NB models is 0.99, 0.72, 0.97,0.99, and 0.95, respectively, and except for RF, the other models had the highest accuracy. Among the 39 investigated variables, 16 factors including First-class family (20.83%), friend (17.01%), health center (41.67%), hospital (24.74%), store (18.49%), market (14.32%), workplace (9.46%), history of hospital admission (51.82%), BMI (43.75%), sex (40.36%), age (22.83%), educational status (60.59%), employment status (43.58%), monthly income (63.80%), addiction (44.10%), history of imprisonment (38.19%) were of the highest importance on tuberculosis. Conclusion: The obtained results demonstrated that machine-learning techniques are effective in identifying economic, social, and environmental factors associated with tuberculosis. Identifying these different factors plays a significant role in preventing and performing appropriate and timely interventions to control this disease.

Social determinants of spatial inequalities in COVID-19 outcomes across England: A multiscale geographically weighted regression analysis.

A variety of factors are associated with greater COVID-19 morbidity or mortality, due to how these factors influence exposure to (in the case of morbidity) or severity of (in the case of mortality) COVID-19 infections. We use multiscale geographically weighted regression to study spatial variation in the factors associated with COVID-19 morbidity and mortality rates at the local authority level across England (UK). We investigate the period between March 2020 and March 2021, prior to the rollout of the COVID-19 vaccination program. We consider a variety of factors including demographic (e.g. age, gender, and ethnicity), health (e.g. rates of smoking, obesity, and diabetes), social (e.g. Index of Multiple Deprivation), and economic (e.g. the Gini coefficient and economic complexity index) factors that have previously been found to impact COVID-19 morbidity and mortality. The Index of Multiple Deprivation has a significant impact on COVID-19 cases and deaths in all local authorities, although the effect is the strongest in the south of England. Higher proportions of ethnic minorities are associated with higher levels of COVID-19 mortality, with the strongest effect being found in the west of England. There is again a similar pattern in terms of cases, but strongest in the north of the country. Other factors including age and gender are also found to have significant effects on COVID-19 morbidity and mortality, with differential spatial effects across the country. The results provide insights into how national and local policymakers can take account of localized factors to address spatial health inequalities and address future infectious disease pandemics.

Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens.

Radiotheranostics refers to the pairing of radioactive imaging biomarkers with radioactive therapeutic compounds that deliver ionizing radiation. Given the introduction of very promising radiopharmaceuticals, the radiotheranostics approach is creating a novel paradigm in personalized, targeted radionuclide therapies (TRTs), also known as radiopharmaceuticals (RPTs). Radiotherapeutic pairs targeting somatostatin receptors (SSTR) and prostate-specific membrane antigens (PSMA) are increasingly being used to diagnose and treat patients with metastatic neuroendocrine tumors (NETs) and prostate cancer. In parallel, radiomics and artificial intelligence (AI), as important areas in quantitative image analysis, are paving the way for significantly enhanced workflows in diagnostic and theranostic fields, from data and image processing to clinical decision support, improving patient selection, personalized treatment strategies, response prediction, and prognostication. Furthermore, AI has the potential for tremendous effectiveness in patient dosimetry which copes with complex and time-consuming tasks in the RPT workflow. The present work provides a comprehensive overview of radiomics and AI application in radiotheranostics, focusing on pairs of SSTR- or PSMA-targeting radioligands, describing the fundamental concepts and specific imaging/treatment features. Our review includes ligands radiolabeled by 68Ga, 18F, 177Lu, 64Cu, 90Y, and 225Ac. Specifically, contributions via radiomics and AI towards improved image acquisition, reconstruction, treatment response, segmentation, restaging, lesion classification, dose prediction, and estimation as well as ongoing developments and future directions are discussed.

Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis.

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module. Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes. In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.

Identification of Prognostic Biomarkers for Breast Cancer Metastasis Using Penalized Additive Hazards Regression Model.

Background: Breast cancer (BC) has been reported as one of the most common cancers diagnosed in females throughout the world. Survival rate of BC patients is affected by metastasis. So, exploring its underlying mechanisms and identifying related biomarkers to monitor BC relapse/recurrence using new statistical methods is essential. This study investigated the high-dimensional gene-expression profiles of BC patients using penalized additive hazards regression models. Methods: A publicly available dataset related to the time to metastasis in BC patients (GSE2034) was used. There was information of 22 283 genes expression profiles related to 286 BC patients. Penalized additive hazards regression models with different penalties, including LASSO, SCAD, SICA, MCP and Elastic net were used to identify metastasis related genes. Results: Five regression models with penalties were applied in the additive hazards model and jointly found 9 genes including SNU13, CLINT1, MAPK9, ABCC5, NKX3-1, NCOR2, COL2A1, and ZNF219. According the median of the prognostic index calculated using the regression coefficients of the penalized additive hazards model, the patients were labeled as high/low risk groups. A significant difference was detected in the survival curves of the identified groups. The selected genes were examined using validation data and were significantly associated with the hazard of metastasis. Conclusion: This study showed that MAPK9, NKX3-1, NCOR1, ABCC5, and CD44 are the potential recurrence and metastatic predictors in breast cancer and can be taken into account as candidates for further research in tumorigenesis, invasion, metastasis, and epithelial-mesenchymal transition of breast cancer.

Geographically weighted linear combination test for gene-set analysis of a continuous spatial phenotype as applied to intratumor heterogeneity.

Background: The impact of gene-sets on a spatial phenotype is not necessarily uniform across different locations of cancer tissue. This study introduces a computational platform, GWLCT, for combining gene set analysis with spatial data modeling to provide a new statistical test for location-specific association of phenotypes and molecular pathways in spatial single-cell RNA-seq data collected from an input tumor sample. Methods: The main advantage of GWLCT consists of an analysis beyond global significance, allowing the association between the gene-set and the phenotype to vary across the tumor space. At each location, the most significant linear combination is found using a geographically weighted shrunken covariance matrix and kernel function. Whether a fixed or adaptive bandwidth is determined based on a cross-validation cross procedure. Our proposed method is compared to the global version of linear combination test (LCT), bulk and random-forest based gene-set enrichment analyses using data created by the Visium Spatial Gene Expression technique on an invasive breast cancer tissue sample, as well as 144 different simulation scenarios. Results: In an illustrative example, the new geographically weighted linear combination test, GWLCT, identifies the cancer hallmark gene-sets that are significantly associated at each location with the five spatially continuous phenotypic contexts in the tumors defined by different well-known markers of cancer-associated fibroblasts. Scan statistics revealed clustering in the number of significant gene-sets. A spatial heatmap of combined significance over all selected gene-sets is also produced. Extensive simulation studies demonstrate that our proposed approach outperforms other methods in the considered scenarios, especially when the spatial association increases. Conclusion: Our proposed approach considers the spatial covariance of gene expression to detect the most significant gene-sets affecting a continuous phenotype. It reveals spatially detailed information in tissue space and can thus play a key role in understanding the contextual heterogeneity of cancer cells.

Geostatistical Modeling and Heterogeneity Analysis of Tumor Molecular Landscape.

Intratumor heterogeneity (ITH) is associated with therapeutic resistance and poor prognosis in cancer patients, and attributed to genetic, epigenetic, and microenvironmental factors. We developed a new computational platform, GATHER, for geostatistical modeling of single cell RNA-seq data to synthesize high-resolution and continuous gene expression landscapes of a given tumor sample. Such landscapes allow GATHER to map the enriched regions of pathways of interest in the tumor space and identify genes that have spatial differential expressions at locations representing specific phenotypic contexts using measures based on optimal transport. GATHER provides new applications of spatial entropy measures for quantification and objective characterization of ITH. It includes new tools for insightful visualization of spatial transcriptomic phenomena. We illustrate the capabilities of GATHER using real data from breast cancer tumor to study hallmarks of cancer in the phenotypic contexts defined by cancer associated fibroblasts.

Cardiovascular disease, mortality and exposure to particulate matter (PM): a systematic review and meta-analysis.

One of the main factors that causes health effects in humans such as hospital admissions for cardiovascular disease (HACVD), respiratory disease (RD), lung function, cardiovascular mortality (MCVD), lung cancer, and increased mortality is air pollution especially particulate matter (PM). This a systematic review and meta-analysis aims to investigate the effects of particulate matter on the occurrence of cardiovascular disease and mortality. A systematic review and meta-analysis of the literature was done from 2011 to 2021 based on various databases. Based on the result of this study, subgroup analysis based on temperature conditions showed a different estimation in cold cities (6.24, UR (4.36-8.12)), moderate cities (4.86, UR (3.57-6.15)) and warm cities (8.96, UR (7.06-10.86)). Test of group differences showed a significant difference (Q=12.22, p-value<0.001). There was publication bias among the studies (the Egger's test; (Z=14.18, p<0.001)). According result study pooled estimation of AP% for MCVD from the random-effect meta-analysis based on DerSimonian-Laird model, overall is 5.04, UR (3.65-6.43) (Figure 4). Subgroup analysis based on temperature conditions showed the estimation in cold cities (5.47, UR (3.97-6.97)) and moderate cities (4.65, UR (0.54-8.77)). Test of group differences showed a non-significant difference (Q=0.13, p-value=0.71). There was no publication bias among the studies (the Egger's test; (Z=0.82, p=0.376)). Exposed to air pollutants and particulate matter can be increase the risk of cardiovascular disease, respiratory disease, and cardiovascular mortality.

Anatomical characteristics of mandibular bone in skeletal class I, II and III patients by using cone beam computed tomography images in an iranian population / Características anatômicas do osso mandibular em pacientes Classe I, II e III esquelética usando imagens de Tomografia Computadorizada de Feixe Cônico: em uma População Iraniana

Objetive: This study aimed to compare the anatomical characteristics of the mandible in patients with skeletal class I, II and class III disorders using cone beam computed tomography (CBCT). Material and Methods: CBCT scans of patients between 17 to 40 years taken with NewTom 3G CBCT system with 12-inch field of view (FOV) were selected from the archive. Lateral cephalograms were obtained from CBCT scans of patients, and type of skeletal malocclusion was determined (Class I, II or III). All CBCT scans were evaluated in the sagittal, coronal and axial planes using the N.N.T viewer software. Results: The ramus height and distance from the mandibular foramen to the sigmoid notch in class II patients were significantly different from those in skeletal class I (P < 0.005). Distance from the mandibular canal to the anterior border of ramus in class III individuals was significantly different from that in skeletal class I individuals (P < .005). Conclusion: Length of the body of mandible in skeletal class I was significantly different from that in skeletal class II and III patients. Also, ramus height in skeletal class I was significantly different from that in skeletal class II patients. CBCT had high efficacy for accurate identification of anatomical landmarks. (AU)

Objetivo: Este estudo teve como objetivo comparar as características anatômicas da mandíbula em pacientes com desordem esquelética Classe I, II e III usando imagens de tomografia computadorizada de feixe cônico (TCFC). Material e Métodos: Foram selecionadas de arquivo, imagens de TCFC (Sistema NewTon 3G) com FOV (campo de visão) 12 polegadas e incluindo pacientes entre 17 a 40 anos. Cefalometrias laterais foram obtidas a partir das imagens de TCFC e o tipo de maloclusão esquelética foi determinada (Classe I, II ou III). Todas as imagens de TCFC foram avaliadas nos planos sagital, coronal e axial usando o software de visualização N.N.T. Resultados: A altura do ramo e distância do forame mandibular para a incisura da mandíbula em pacientes Classe II foi significativamente diferente daqueles Classe I esquelética (p< 0.005). A distância do canal mandibular até a borda anterior do ramo em indivíduos Classe III foi significativamente diferente daqueles indivíduos Classe I esquelética (p<0.005). Conclusão: O comprimento do corpo da mandíbula na Classe I esquelética foi diferente significativamente daqueles pacientes em Classe II e III esquelética. Além disso, a altura do ramo na Classe I esquelética foi significativamente diferente daqueles pacientes Classe II esquelética. A TCFC apresentou alta eficácia para a identificação precisa de marcos anatômicos. (AU)

Detecting Important Risk Factors of Survival Time of Lung Cancer Patients Using Censored Quintile Regression.

Objective: Lung cancer is the most frequently diagnosed cancer and the most leading cause of death due to cancer worldwide. This study aimed to use censored quintile regression model to estimate the effect of potential risk factors on survival of lung cancer patients. Methods: In this study we used a dataset of a retrospective cohort study conducted in West Azerbaijan (during 2007 and 2014). Demographic variables included age, and gender and biological variables included Eastern Cooperative Oncology Group, smoking, tumor type, stage, metastasis, and treatment were investigated as risk factors of survival of lung cancer patients by using censored quintile regression. Result: The mean (± standard deviation) age of the 347 lung cancer patients was 63.48 (± 13.55) years. The survival time ranges from 11 to 91. A total of 240 (67.6%) experienced death by the end of the study. The impact of Eastern Cooperative Oncology Group (IV), smoking and treatment were significant for most of quintiles (p<0.05). Stage of cancer and metastasis are the other affective risk factors on the survival of lung cancer patients(p<0.05). It was shown that Eastern Cooperative Oncology, smoking habit and treatment were significantly associated with a shorter time-to-death progression. Conclusion: As censored quintile regression could consider time-varying effects and the interpretation of its regression coefficients are easy it could be an adequate choice for analyzing survival data.

The reliability and validity of the Patient Health Questionnaire-9 (PHQ-9) and PHQ-2 in patients with infertility.

BACKGROUND: Depression in patients with infertility often goes undiagnosed and untreated. The Patient Health Questionnaire-9 (PHQ-9) and its ultra-brief version (i.e. PHQ-2) are widely used measures of depressive symptoms. These scales have not been validated in patients with infertility. The aim of the present study was to examine the reliability and validity of the PHQ-9 and PHQ-2 in patients with infertility. METHODS: In this cross-sectional study, a total of 539 patients with infertility from a referral infertility clinic in Tehran, Iran completed the PHQ-9, along with other relevant scales: the WHO-five Well-being Index (WHO-5), the Hospital Anxiety and Depression Scale (HADS), and the Generalized Anxiety Disorder-7 (GAD-7). Factor structure and internal consistency of PHQ-9 were examined via confirmatory factor analysis (CFA) and Cronbach's alpha, respectively. Convergent validity was evaluated by relationship with WHO-5, HADS and GAD-7. RESULTS: The mean total PHQ-9 and PHQ-2 scores were 8.47 ± 6.17 and 2.42 ± 1.86, respectively, and using a cut-off value of 10 (for PHQ-9) and 3 (for PHQ-2), the prevalence of depressive symptoms was 38.6 and 43.6%, respectively. The Cronbach's alphas for PHQ-9 and PHQ-2 were, respectively, 0.851 and 0.767, indicating good internal consistency. The CFA results confirmed the one-factor model of the PHQ-9 (χ2/df = 4.29; CFI = 0.98; RMSEA = 0.078 and SRMR = 0.044). Both PHQ-9 and PHQ-2 showed moderate to strong correlation with the measures of WHO-5, HADS-depression, HADS-anxiety, and the GAD-7, confirming convergent validity. In univariate analysis, female sex, long infertility duration, and unsuccessful treatment were significantly associated with depression symptoms. CONCLUSION: Both PHQ-9 and PHQ-2 are brief and easy to use measures of depressive symptoms with good psychometric properties that appear suitable for routine use in patients with infertility.

Relationship of gray values in cone beam computed tomography and bone mineral density obtained by dual energy X-ray absorptiometry.

OBJECTIVES: The aim of this study was to assess the correlation between bone mineral density (BMD) determined with cone beam computed tomography (CBCT) gray values and BMD determined by dual energy X-ray absorptiometry (DEXA). STUDY DESIGN: Women age greater than 50 years requiring CBCT for implant treatment were included in the study. BMD was determined by calculating the mean gray value of CBCT cross-sectional images of anterior, premolar, retromolar, and tuberosity areas of the mandible and maxilla. Patients were then subjected to DEXA of the femoral neck and lumbar spine. Independent t tests, analysis of variance (ANOVA), Pearson's correlation tests, and receiver operating characteristic (ROC) evaluation were used for data analysis. RESULTS: Of 61 asymptomatic patients (mean age 64 years), 47.5% and 55.7% had abnormal BMD, based on the T-scores of the femoral neck and lumbar spine, respectively. Significant correlations were noted between the T-scores of the femoral neck and lumbar spine and the gray values of the maxillary incisor and tuberosity areas. CONCLUSIONS: A strong correlation exists between the CBCT gray values at different sites in the maxilla and the results of DEXA. A gray value less than 298 at the maxillary tuberosity can help distinguish patients with osteoporosis from normal individuals, with 66% to 67% accuracy and suggests the need for DEXA analysis.

Evaluation of the effect of teriparatide therapy on mandibular fracture healing in rats with medication-related osteonecrosis of the jaw.

OBJECTIVE: The aim of this study was to evaluate the effect of teriparatide therapy on mandibular fracture healing in rats with medication-related osteonecrosis of the jaw (MRONJ). MATERIALS AND METHODS: To induce MRONJ, a total of 120 rats received intravenous zoledronate 0.06 mg/kg once a week for 6 weeks and their right mandibular first molar was extracted. Eighty of 94 rats with MRONJ were randomly selected and underwent unilateral mandibular osteotomy to replicate a fracture. After surgery, the rats were randomly assigned to T (teriparatide-treated) and C (control) groups. Group T (n = 40) received subcutaneous injection of 2 µg/kg/day teriparatide and group C (n = 40) received the same volume of normal saline until sacrifice. Four and 8 weeks after surgery, 20 rats in each group were sacrificed. Fracture healing was scored using a histological grading system (1 to 10). RESULTS: In group C, at 4 weeks and 8 weeks post-fracture, fibrous and cartilaginous tissues and scant bone formation at the fracture site and lacunae without osteocyte in adjacent mandibular bone were seen. In group T, substantial amounts of new trabecular bone rimmed by osteoblasts and some areas of remodeled mature bone were seen. After 8 weeks, extensive replacement of trabecular bone with mature bone occurred. Except between C4 and C8 groups, the healing score was significantly different between all subgroups. CONCLUSION: Teriparatide therapy successfully improved mandibular fracture healing in rats with MRONJ. However, this study was limited by the use of an animal model whose anatomy, physiology, and drug metabolism might be different from humans. CLINICAL RELEVANCE: The present study showed that teriparatide therapy may be used adjunctive to surgery in the treatment of mandibular fractures in MRONJ patients.

Determining Risk Factors for Gastric and Esophageal Cancers between 2009-2015 in East-Azarbayjan, Iran Using Parametric Survival Models

Background: Esophageal cancer (EC) and Gastric cancer (GC) have been identified as two of the most common cancers in the northeastern regions of Iran. The increasing rates of these types of cancers requires attention. This study aims to assess the potential risk factors for these two cancers and then determine shared risk factors between them in a population of Iranian patients using parametric survival models. Methods: This retrospective cohort study was conducted using 127 patients with EC and 184 patients with GC in East Azarbaijan, Iran who were diagnosed and registered during the years 2009-2010 in Iran's National Cancer Control Registration Program and were followed for five years. Parametric survival models were used to find the risk factors of the patients. Akaike Information Criteria was used to identify the best parametric model in this study. Interaction analysis was used to determine shared risk factors between EC and GC. Results: The mean (±standard deviation) age of diagnoses for EC and GC were 66.92(±11.95) and 66.5(±11.5) respectively. The survival time ranges of GC patients was (0.07-70.33) and the survival time ranges were from 0.10 to 69.03 months for EC patients. Multivariable Log- logistic model showed that being married (OR=2.25, 95% CI: 1.33 - 3.81) for EC patients and Esophagectomy surgery for EC (OR: 1.62, 95% CI: 1.04 ­ 2.55) and GC (OR: 1.60, 95% CI: 1.02 ­ 2.53) had significant effects on survival. Age at the time of diagnosis, job status, and Esophagectomy surgery were statistically comparable regarding their magnitude of effect on survival of two cancers (all Ps>0.05). Conclusion: Esophagectomy surgery and being married were important risk factors in EC and GC. The log-logistic model was the most appropriate statistical approach to identify significant risk factors on survival of both cancers.

Determining Overall Survival and Risk Factors in Esophageal Cancer Using Censored Quantile Regression

Background: Esophageal cancer is one of the leading causes of death worldwide. The global increasing rate of this type of cancer requires more attention. The purpose of this study was to determine the overall survival probability of esophageal cancer after diagnosis and to assess the potential risk factors in a population of Iranian patients. Materials and Methods: This retrospective cohort study was conducted on 127 cases with esophageal cancer in the Azarbaijan province, East of Iran. Participants in the study were diagnosed during 2009-2010 and were followed up for 5 years. The event was considered death due to esophageal cancer and those who survived until the end of the study were assumed as right censored. Censored quntile regression was fitted to find the overall survival of the patients using adjusted effects of variables and was compared with Cox regression model. Results: Patients' mean and median survival time were 16.99 and 10.06 months respectively and 89% off cases died by the end of the study. The 1, 3, 6, 12 and 36-month survival probabilities were 0.95, 0.76, 0.60, 0.43, and 0.18. The median survival time for females and males without surgery were 21.79 and 14.76 month respectively. The accuracy of predictions were 0.99 and 0.74 for the censored quantile regression and Cox, respectively. Conclusion: We concluded that being male, not having surgery, longer wait time between having symptoms and being diagnosed, low socioeconomic status and old age to be significant risk factors in reducing the probability of survival from esophageal cancer.

Factors Affecting Long-Survival of Patients with Esophageal Cancer Using Non-Mixture Cure Fraction Model

Objective: Esophageal cancer (EC) is one of the gastrointestinal malignancies with a very high morbidity and mortality rate due to poor prognosis. This study aims to assess the effects of risk factors on survival and cure fraction of patients with EC in a population of Iranian patients using a non-mixture cure fraction model. Methods: This retrospective cohort study was conducted on 127 patients with EC who were diagnosed during 2009-2010 and were followed up for 5 years in East-Azarbaijan, Iran. Stepwise selection and non-mixture cure fraction model were used to find the risk factors of EC survival patients. Results: The mean (±standard deviation) diagnosis age of the EC was 66.92(±11.95). One, three and five-year survival probabilities were 0.44 (95% confidence interval (CI): 0.36-0.54), 0.2 (95% CI: 0.14-0.28) and 0.13 (95% CI: 0.08-0.2) respectively. Female sex (Estimate=-0.99; 95% confidence interval (CI): -1.41,-0.58; p-value<0.001), low level socioeconomic status (Estimate=0.39; 95%CI: 0.12,0.66; p-value=0.043), the group who did not do esophagectomy surgery (Estimate=0.58; 95%CI: 0.17,0.99; p-value=0.005) and unmarried group (Estimate=0.58; 95%CI: 0.11-1.05; p-value=0.015) were found as the significant predictor of survival and cure fraction of the EC patients. Population cure rate was 0.11 (95%CI: 0.07-0.19) and Cure fraction was estimated 5.11 percent. Conclusion: This study found gender, socioeconomic status, Esophagectomy surgery and marital status as the potential risk factors for survival and cure fraction of Iranian EC patients. Moreover, non- mixture cure fraction provides more accurate and more reliable insight into long-term advantages of EC therapy compared to standard classic survival analysis alternatives.

Effect of different doses and durations of teriparatide therapy on resolution of medication-related osteonecrosis of the jaw: A randomized, controlled preclinical study in rats.

OBJECTIVE: To evaluate the effects of different doses and durations of teriparatide therapy on MRONJ resolution in rats. SUBJECTS AND METHODS: A total of 120 rats that had been affected with MRONJ (after six weekly zoledronate injections and tooth extraction) were randomly divided into eight subgroups: 2, 10, and 20 µg/kg/day teriparatide were administered to L4, M4, and H4 for 4 weeks, and to L8, M8, and H8 for 8 weeks, respectively. C4 and C8 received saline for 4 and 8 weeks, respectively. One week after the final injection, rats were sacrificed and assessed clinically (bone exposure/fistula) and histologically (number of osteocytes in extraction socket and empty lacunae in alveolar bone). RESULTS: MRONJ was clinically improved in 72.2%, 61.5%, and 40% of stage I, II, and III experimental rats, respectively. In the control rats, the results were 20.8% for stage I and no improvement for stages II and III. Aside from L4 and L8, the experimental subgroups had a significantly higher rate of clinical and histological improvement compared with their corresponding controls. There was a significantly higher number of osteocytes and lower number of empty lacunae in M4 and H4 compared with C4, in H4 compared with L4, in M8 and H8 compared with C8, and in H8 compared with L8. CONCLUSION: Teriparatide therapy improved clinical and histological features of MRONJ in a dose-dependent manner, but clinically relevant doses of teriparatide might not be sufficient for MRONJ resolution in rats. Extending the duration of teriparatide therapy from 4 to 8 weeks did not affect treatment outcomes.

Evaluation of mandibular fracture healing in rats under zoledronate therapy: A histologic study.

INTRODUCTION: To evaluate fracture healing in mandible of rats under zoledronate therapy. METHODS: A total of 135 Wistar rats were randomly allocated into 3 groups. Group L received two intravenous infusion of 0.06 mg/kg zoledronate 6 weeks apart. Group H received the same dose of zoledronate as group L once a week for 6 weeks and group C were treated with normal saline. Seven days after the last infusion, rats underwent unilateral mandibular osteotomy to replicate a fracture. Fifteen rats from each group were sacrificed 2, 4, and 6 weeks after surgery. Fracture calluses were examined and scored using a histological grading system (1 to 10). RESULTS: After 2 weeks, substantial woven bone and some lamellar bone were seen in control and L groups. In group H, healing was delayed and consisted of fibrous and cartilaginous tissue and some woven bone. After 4 weeks, most of woven bone in control group was replaced with lamellar bone but in group L, comparatively less bone remodeling occurred. In group H, healing process was nearly the same as that at 2 weeks. After 6 weeks, complete bone remodeling was seen in control group. In group L, bone remodeling was under way and in group H, histological findings were nearly the same as those at 2 and 4 weeks. Except for L and control groups at 2 weeks, healing score was significantly different between all corresponding groups. CONCLUSION: Zoledronate therapy delayed healing process of mandibular fracture in rats in a dose-dependent manner.

Effects of radiofrequency radiation in the presence of gold nanoparticles for the treatment of renal cell carcinoma.

Introduction: The most common type of kidney cancer is renal cell carcinoma (RCC), which accounts for more than 80% of all kidney cancers. Objectives: The aim of this study was to evaluate the effects of radiofrequency (RF) radiation in the presence of gold nanoparticles (GNPs) for the treatment of RCC. Materials and Methods: Human embryonic kidney (HEK) cancer cells were divided into 6 groups. Various tests were performed on HEK cells in the presence of RF and GNPs. In order to investigate the radiation effects on the cells' survival, MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-iphenyltetrazolium bromide] assay was performed at different days during and post-irradiation period. The repeated measure analysis of variance (ANOVA) method was used for statistical analysis of the cells' survival using SPSS version 16.0. A significant level of 0.05 was considered to the tests. Results: Using the ANOVA test, a significant decrease in cell's survival was seen in the RF exposed group 3 compared to the control group (P=0.035). While, differences were not significant between RF exposed group 2 and the control group (P>0.05). A significant decrease in cell's survival in the RF exposed groups 5 (P=0.025) and 6 (P=0.018) at the presence of GNP compared to the control group was seen. Conclusion: Results of this study showed that, this method can be efficiently used for RCC treatment as an alternative to nephrectomy. More follow up in vivo studies on mammalians are needed to investigate the potential of the presented method for clinical applications.