Acute Effects of Air Pollution on Hospital Admissions for Asthma, COPD, and Bronchiectasis in Ahvaz, Iran.

Background and Aim: Although air pollution is a serious problem in Ahvaz, the association between air pollution and respiratory diseases has not been studied enough in this area. The aim of this study was to determine the relation between short-term exposure to air pollutants and the risk of hospital admissions due to asthma, COPD, and bronchiectasis in Ahvaz. Methods: Hospital admissions data and air pollutants including O3, NO, NO2, SO2, CO, PM10, and PM2.5 were obtained from 2008 to 2018. Adjusted Quasi-Poisson regression with a distributed lag model, controlled for trend, seasonality, weather, weekdays, and holidays was used for data analysis. Results: The results showed a significant increase in hospital admissions for asthma (RR=1.004, 95% CI: 1.002-1.007) and COPD (RR=1.003, 95% CI: 1.001-1.005) associated with PM2.5. PM10 was associated with increased hospital admissions due to bronchiectasis in both genders (Men: RR=1.003, 95% CI: 1.001-1.006) (Female: RR=1.003, 95% CI: 1.000-1.006). NO2 was also associated with an increased risk of hospital admissions for asthma (RR=1.040, 95% CI: 1.008-1.074) and COPD (RR=1.049, 95% CI: 1.010-1.090). SO2 was associated with the risk of hospital admissions of asthma (RR=1.069, 95% CI: 1.017-1.124) and bronchiectasis (RR=1.030, 95% CI: 1.005-1.056). Finally, CO was associated with COPD (RR=1.643, 95% CI: 1.233-2.191) and bronchiectasis (RR=1.542, 95% CI: 1.035-2.298) hospital admissions. Conclusion: Short-term exposure to air pollutants significantly increases the risk of hospital admissions for asthma, COPD, and bronchiectasis in the adult and elderly population.

The Effect of CoQ10 Supplementation on Quality of Life in Women with Breast Cancer Undergoing Tamoxifen Therapy: A Double-Blind, Placebo-Controlled, Randomized Clinical Trial.

BACKGROUND: Survival rates among breast cancer patients and the number of patients living with treatment side effects have improved, leading to increased focus on quality of life (QOL). The objective of this study was to determine the efficacy of CoQ10 on QOL scores among breast cancer patients in Iranian undergoing tamoxifen therapy. METHODS: Thirty breast cancer patients were randomized into two groups. The first group received 100 mg CoQ10, and the second group took fplacebo once a day for 8 weeks. QOL was evaluated by a standard QOL questionnaire and a specific questionnaire on QOL of breast cancer patients at baseline and the end of the study. Also, physical activity of patients was assessed with the IPAQ questionnaire and dietary intake determined by a 3-day dietary record. RESULTS: The data of 30 subjects were analyzed. According to QOL C30 data, CoQ10 led to a significant increase in physical functioning (P=0.029), emotional functioning (P=0.031), and cognitive functioning (P=0.023) compared to placebo. Symptom scales revealed a notable reduction in appetite loss in the first group (P=0.01). Global health status showed no significant changes in either study arm. On the QOL BR23, progress in functions and decline in symptoms were not statistically significant. Arm symptoms showed significant reduction (P=0.022) in patients that received placebo. CONCLUSION: This trial indicates that CoQ10 supplementation has effects in ameliorating some dimensions of QOL in breast cancer patients. To generalize the results, larger and longer intervention studies are needed. CLINICAL TRIAL REGISTRATION: IRCT2015042021874N1.

Prevalence of SARS-CoV-2 in Patients with Severe Pneumonia in Khuzestan Province, Iran.

The emergence of a highly pathogenic virus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) accounts for severe pneumonia throughout the world. More than 7 million world population have been infected with SARS-CoV-2, and the number of deaths is increasing every day. This study aimed to evaluate the frequency of SARS-CoV-2 in hospitalized patients with an acute respiratory infection (ARI). During an outbreak of the SARS-CoV-2, the nasopharyngeal and oropharyngeal swabs were collected from 909 hospitalized patients with severe pneumonia, including 517 (56.9%) males and 392 (43.1%) females. All the collected samples were from different cities of Khuzestan province from 19 February to- 27 March 2020. The RNA was extracted from samples and subjected to real-time polymerase chain reaction (PCR) tests for the detection of the SARS-CoV-2. Simultaneously, the computerized tomography (CT) scan was tested for the presence of ground-glass opacity in the lung among the patients. Of the total number of 909 specimens, 328 (36.08%) cases, including 185 (20.35%) females and 143 (15.73%) males, were positive for the SARS-CoV-2 while, 581 (63.9%) cases, including 374 (41.14%) males and 207 (22.77%) were negative for the SARS-CoV-2 by real-time PCR (p=0.001).Four hundred sixteen (45.76%) cases were positive for ground-glass opacity in the lung by CT scan, while 328/909 (36.08%) trials proved positive for SARS-CoV-2 by the real-time PCR (p=0.003).  In this study, 36.08% of patients were positive for SARS-CoV-2. Although the results of positive cases by CT scan showed higher than real-time PCR, screening the SARS-COV-2 with a real-time PCR method is the first line of choice.

Molecular Identification of Free-Living Amoebae (Naegleria spp., Acanthamoeba spp. and Vermamoeba spp.) Isolated from Un-improved Hot Springs, Guilan Province, Northern Iran.

BACKGROUND: This study was conducted to determine the presence and molecular identify of Acanthamoeba, Naegleria and Vermamoeba in unimproved hot springs. METHODS: From Jul to Aug 2017, 54 water samples were collected from hot springs in different parts of the Guilan Province, North Iran. For the isolation of Acanthamoeba, Naegleria and Vermamoeba approximately 500 ml of the water samples were filtered through a cellulose nitrate membrane with a pore size of 0.45 µm. The filter was transferred onto non-nutrient agar plates seeded with Gram-negative bacteria (Escherichia coli) as a food source. The morphological key of page was used to identify free-living amoebae (FLA) using an inverted microscope, PCR amplification targeting specific genes for each genus and sequencing determined frequent species and genotypes base on NCBI database. RESULTS: Fifteen of the 54 samples were positive by culture and/or PCR for Acanthamoeba and other FLA from unimproved hot springs. By sequencing the positive isolates, the strains were shown to belong to Acanthamoeba castellanii (12 case isolates belonged to T4 genotype), 4 cases of V. vermiformis, and 3 cases of N. australiensis, 2 cases of N. pagei and 1 cases of N. gruberi. CONCLUSION: Although FLA-mediated illnesses are not as high as in environmental distribution, but because of a poor prognosis, more investigations about FLA distribution in hot springs is critical. Hot spring may enhance exposure of the amoebae in individuals. Hence, more attention to unimproved hot springs is needed to prevent free-living amoebae mediated diseases.

Trihalomethanes formation in Iranian water supply systems: predicting and modeling.

Trihalomethanes (THMs) were the first disinfection by-products discovered in drinking water and are classified as probable carcinogens. This study measures and models THMs formation at two drinking water distribution systems (WDS1 and WDS2) in Ahvaz City, Iran. The investigation was based on field-scale investigations and an intensive 36-week sampling program, from January to September 2011. The results showed total THM concentrations in the range 17.4-174.8 µg/L and 18.9-99.5 µg/L in WDS1 and WDS2, respectively. Except in a few cases, the THM concentrations in WDS1 and WDS2 were lower than the maximum contaminant level values. Using two-tailed Pearson correlation test, the water temperature, dissolved organic carbon, UV254, bromide ion (Br-), free residual chlorine, and chlorine dose were identified as the significant parameters for THMs formation in WDS2. Water temperature was the only significant parameter for THMs formation in WDS1. Based on the correlation results, a predictive model for THMs formation was developed using a multiple regression approach. A multiple linear regression model showed the best fit according to the coefficients of determination (R2) obtained for WDS1 (R2=0.47) and WDS2 (R2=0.54). Further correlation studies and analysis focusing on THMs formation are necessary to assess THMs concentration using the predictive models.