Background: Occupational exposure to crystalline silica is still an important health problem, especially in developing countries. Exposure to silica may be associated with the induction of toxic oxidative stress. Objectives: This study was conducted to assess oxidative stress biomarkers in workers exposed to respirable crystalline silica (RCS) in Hamadan city, the west of Iran. Methods: This descriptive-analytical study was conducted on two groups of exposed workers selected from four industries and unexposed office workers in 2017. The analysis of RCS in air samples was done by NIOSH method No. 7602. Malondialdehyde (MDA), total antioxidant capacity (TAC), and catalase (CAT) activity were measured in serum samples. Results: In this study, 48 healthy workers exposed to silica and 47 unexposed workers as controls were selected. The mean MDA levels (26.91 ± 14.26 nmol/mL) and CAT activity (10.83 ± 5.06 U/mL) were higher in the exposed group than in the unexposed group (P < 0.001). However, no statistically significant difference was observed in the TAC levels between the groups and no correlation was observed between exposure to RCS and oxidative stress biomarker levels in exposed subjects. Conclusions: Although there was a significant difference in the oxidative stress levels between the groups, according to other results of our study, it is not possible to claim that oxidative stress biomarkers are appropriate biological indices for silica exposure monitoring in occupational settings. Therefore, we still require a comprehensive study of other aspects of this research field.

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Background and Objectives:The main cause of incidents is human error. The occurrence of these errors in the use of medical equipment can result in harm to the patient, the destruction of equipment, the imposition of economic damages, and the deterioration of the credentials of the health sectors. Hence, the identification, evaluation and management of errors in the use of these equipment is very critical. The present study was conducted to reduce the risk of human errors in using a medical device in one of the hospitals in Iran. Methods:The study subject was a ventilator device, which was selected considering the high usage and the criticality of its use in hospitals. Identification and evaluation of human error were performed using the PUEA technique, as well as quantification of errors, and reduction of uncertainty in estimating the significance of detected human errors using fuzzy logic.Results: Based on the findings, 33 errors were detected in the use of the ventilator device. The most common types of errors were the type of error in operation. (72.72%). The most important causes of errors were slips and lapses (42.42%). The main primary consequences for the predicted errors were the device not being sterilized and the possibility of transmission of microbes to patients. In 42.42% of the cases, errors were not recoverable. The results of the PUEA technique and fuzzy logic showed that there is no relationship between the type of error, frequency of its occurrence, and the probability of error occurrence. Conclusion:In human error studies, the combined use of risk identification techniques and a quantitative approach that determines the probability of identified errors can reduce uncertainty in the final results.

Background: In recent years, the foundry industry has had a significant impact on Iran's economy. However, the health and safety conditions of this industry are in an unfavorable status, and these conditions have caused a lot of accidents. In this regards, one of the most important ways to prevent accidents in this industry can be identifying hazardous points and adopting appropriate control measures. The aim of the study was to identify hazardous points in foundry industry using a hybrid safety approach. Methods: This descriptive-analytic study was conducted in the foundry industry of Iran, in 2016. The study method consisted of two parts. First, the accidents of foundry were analyzed. Second, the Energy Trace and Barrier Analysis (ETBA) technique was used to identify hazards and assess the risks. The collected and obtained data of accidents and risk assessment were entered into the statistical SPSS software, version 22, and descriptive statistics (mean, percent) were used for analyzing. Also, Microsoft Excel was used to plot the graphs. Results: A total of 128 risks is identified, including 17 unacceptable risks, 93 undesirable risks, 13 acceptable risks with revision and five acceptable risks without revision. The mechanical and physical energies had the highest percentage of hazards. The results of accidents analysis showed that the cause of most accidents (40%) was mechanical, while 23% of them was the potential type. The study results indicated that accidents analysis along with risks identification can be useful in identifying all the dangerous locations (points). Conclusion: In addition to validating the results of risk assessment through the analysis of accidents, other causes affecting the occurrence of accidents can also be covered by accident analysis, including unsafe behaviors and organizational causes that are not seen in the risk assessment.

Peanut stem white rot caused by Sclerotium rolfsii Sacc. is a soil-borne disease that is widely prevailing across peanut farms, leading to serious economic losses. Screening for biocontrol agents against this pathogen is urgent. In this research, 166 fungal isolates including 136 isolates of S. rolfsii and 30 isolates of antagonistic endophytic fungi were obtained from a total of 220 samples collected from peanut farms in Guilan province, Iran. After morphological and molecular identification, six superior endophytic isolates were finally selected for the in vitro and greenhouse trials, including four isolates from Trichoderma viride, Trichoderma virens, Penicillium decaturense, and Aspergillus flavus and two isolates from Penicillium rubens. Four methods of biocontrol were used during the in vitro phase, i.e., dual culture, volatile metabolites assay, non-volatile metabolites assay (culture extract), and slide culture. It was found that T. virens had the highest capability of suppressing the mycelial growth of S. rolfsii in the dual culture method (90.98%). As for the volatile metabolites assay, the most effective isolates in inhibiting the pathogen’s mycelial growth were P. rubens (MN395854.1) and A. flavus (84.30% and 73.50% inhibition, respectively). In the non-volatile metabolites method, the isolates that performed the best in suppressing the mycelial growth of S. rolfsii were T. viride and P. rubens (MN395854.1) with 91.80% and 90.20% inhibitory effects, respectively. On the other hand, in the slide culture method, all isolates, except for T. virens and T. viride, successfully controlled the development of S. rolfsii hyphae. The greenhouse trials also supported the effectiveness of endophytic fungi in controlling the pathogen on the host plants. According to the results, T. viride, A. flavus, and P. rubens (MN395854.1) were 44%, 42%, and 38% effective in alleviating the disease incidence and severity. Moreover, the application of these antagonistic fungi in the greenhouse conditions increased the height, fresh weight, and dry weight of the Arachis hypogaea plants infected with the disease causal agent compared to the plants treated only with the pathogen. The results of the in vitro and greenhouse experiments revealed that the endophytic fungi occurring in the natural microbiota of peanut are capable of bio-controlling S. rolfsii, the causal agent of peanut stem white rot disease. These findings shed new insights into the possible resistance induction in A. hypogaea plants through biological protection.