BACKGROUND: Benzene is a known occupational and environmental pollutant. Its urinary metabolite trans, trans-muconic acid (tt-MA) has been introduced by some environmental and occupational health regulatory associations as a biological index for the assessment of benzene exposure; however, recently, doubts have been raised about the specificity of tt-MA for low-level benzene exposures. In the present study, we investigated the association between urinary levels of tt-MA and inhalational exposure to benzene in different exposure groups. METHODS: Benzene exposure was assessed by personal air sampling. Collected benzene on charcoal tube was extracted by carbon disulfide and determined by a gas chromatograph (gas chromatography with a flame ionization detector). Urinary tt-MA was extracted by a strong anion-exchange column and determined with high-performance liquid chromatography–UV. RESULTS: Urinary levels of tt-MA in intensive benzene exposure groups (chemical workers and police officers) were significantly higher than other groups (urban and rural residents), but its levels in the last two groups with significant different exposure levels (mean = 0.081 ppm and 0.019 ppm, respectively) showed no significant difference (mean = 388 μg/g creatinine and 282 μg/g, respectively; p < 0.05). Before work shift, urine samples of workers and police officers showed a high amount of tt-MA and its levels in rural residents’ samples were not zero. CONCLUSION: Our results suggest that tt-MA may not be a reliable biomarker for monitoring low-level (below 0.5 ppm) benzene exposures.
Benzene* ; Carbon Disulfide ; Charcoal ; Chromatography ; Creatinine ; Environmental Monitoring ; Flame Ionization ; Humans ; Occupational Health ; Police ; Sensitivity and Specificity

PURPOSE: Epidemiologic evaluation and investigating the causes of visual impairment in any society is a matter of concern and has a direct effect on the country's health care planning. In this study we describe causes of low vision and blindness in Iranian patients referred to rehabilitation clinics for taking vision aids. METHODS: In this cross-sectional study, visual acuity was classified based on best-corrected visual acuity in the better eye according to the World Health Organization definition (blindness, visual acuity [VA] < 20 / 400; severe visual impairment, VA < 20 / 200-20 / 400; mild to moderate visual impairment, VA < 20 / 60-20 / 200). The causes of blindness and low vision were determined using the 10th version of International Classification of Diseases based on the main cause in both eyes. To describe data, we used mean +/- SD and frequency. RESULTS: The study included 432 patients, 65% male, with a mean age of 43.6 +/- 25.5 years (range, 3 to 92 years). Mild to moderate visual impairment, severe visual impairment and blindness were present in 122 (28.8%), 196 (46.4%) and 105 (24.8%) of the patients, respectively. The main causes of visual impairment were retinal and choroidal diseases (74.5%), optic nerve and optic tract diseases (9.8%), vitreous and globe disorders (5.3%), congenital cataract (3.1%), and glaucoma (2.6%). The distribution pattern of the causes was similar in all age subgroups. CONCLUSIONS: Diseases of the retina and choroid are the main cause of visual impairment among patients referred to an academic visual rehabilitation clinic in Iran.
Adolescent ; Adult ; Aged ; Aged, 80 and over ; Audiovisual Aids ; Blindness/*epidemiology/rehabilitation ; Child ; Child, Preschool ; Choroid Diseases/*epidemiology/rehabilitation ; Female ; Humans ; Iran/epidemiology ; Male ; Middle Aged ; Optic Nerve Diseases/epidemiology/rehabilitation ; Referral and Consultation/*statistics & numerical data ; Rehabilitation Centers/*statistics & numerical data ; Retinal Diseases/*epidemiology/rehabilitation ; Vision, Low/*epidemiology/rehabilitation ; Young Adult

Objective: To predict the daily incidence and fatality rates based on long short-term memory (LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran. Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other. Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females (49.7%), and 25 586 were males (50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively; for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.