PURPOSE: Field of view and voxel resolution of cone beam computed tomography (CBCT) might affect the diagnostic capability. This study was performed to compare between the standard and HiRes zoom modes in the diagnosis of external root resorption (ERR) using CBCT. MATERIALS AND METHODS: Sixty three small cavities (0.25 mm depth and 0.5 mm diameter) were simulated on the buccal, lingual, and proximal surfaces at three different levels of 16 roots of teeth. After covering the root with nail varnish, the roots were inserted in the sockets and the model was placed in a water-containing lacuna. CBCT scans were taken in both standard and HiRes zoom modes using NewTom VG (QR srl Company, Verona, Italy). Then, an observer assessed the images to determine the presence or absence of the cavities. This process was repeated by increasing the size and depth of cavities to 0.5 mm depth and 1 mm diameter. Data were analyzed by McNemar test. The sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratio in evaluation of the simulated cavities were calculated. RESULTS: There was a significant difference between the two imaging modes in diagnosing the shallow cavities (p=0.02).The sensitivity of the standard zoom in detecting the shallow cavities was lower than that of the HiRes zoom. The likelihood ratio of the HiRes zoom was higher in the diagnosis of both cavity types. CONCLUSION: This study suggested that a smaller voxel size in the HiRes zoom mode of CBCT is preferred for diagnosis of ERR.
Cone-Beam Computed Tomography ; Nails ; Paint ; Root Resorption ; Sensitivity and Specificity ; Tooth

Objective: To investigate the analgesic and anti-inflammatory property and possible involvement of opioid receptors of ethyl acetate extract from aerial parts of Daphne mucronata (D. mucronata) in mice by formalin test. Methods: Single doses of 2.5, 5.0 and 10.0 mg/kg of body weight of ethyl acetate extract of D. mucronata were intraperitoneally administered to the mice 30 min before analgesic test. The anti-nociceptive effect of preparations was evaluated based on the formalin in mice. Results: The results indicated that the extract (2.5, 5.0 and 10.0 mg/kg) increased the pain threshold of mice and induced analgesia in both phases of formalin test. Like morphine sulfate (5.0 mg/kg, i.p.), the extract also showed more effective analgesic effect on the late phase of formalin test. Pre-treatment of animals with naloxone (5.0 mg/kg i.p.) did not inhibit the effects of the extract. Conclusions: Our findings suggest that D. mucronata contains potential analgesic and anti-inflammatory compounds which support its traditional use. Moreover, it seems that the analgesic and anti-inflammatory effects of the extract is mediated by non-opioid mechanisms. Further pharmacological studies are required to determine whether the analgesic mechanisms are actually responsible for such properties.

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.