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Salemi Marianna de Melo,Gomes Vanessa Maria da Silva Alves,Bezerra Laylla Marjorye Rebouças,Melo Thania Maion de Souza,Alencar Geisa Guimarães de,Montenegro Iracema Hermes Pires de Mélo,Calado Alessan 사단법인약침학회 2021 Journal of Acupuncture & Meridian Studies Vol.14 No.6
Background: Cupping therapy is used to treat musculoskeletal conditions, including low back pain. Objectives: The study assessed the effects of dry cupping on pain and functional disability from persistent nonspecific low back pain. Methods: This was a randomized controlled trial, where participants were allocated to a cupping therapy (n = 19) or sham (n = 18) group, for five 10-minute sessions of cupping therapy, twice a week, to stimulate the acupoints related to low back pain (GV4, BL23, BL24, BL25, and BL30, BL40 and BL58) and emotional aspects (HT3 and ST36). All participants were assessed at baseline, post-treatment and follow up (a finalization period of four weeks) using a visual analogue scale (VAS) and the Oswestry Disability Index (ODI). Groups were compared using the analysis of covariance (ANCOVA) and the effect size was calculated using Cohen ̓s d. Results: The cupping therapy group presented a lower mean VAS when compared to the sham, at post-treatment (mean difference: –2.36; standard error [SE]: 0.58; p < 0.001; “large” effect size: –0.94) and follow up (mean difference: –1.71; SE: 0.81; p < 0.042; ‘large’ effect size: –0.83). The cupping therapy group presented a lower mean ODI when compared to the sham post-treatment (mean difference: –4.68; SE: 1.85; p: 0.017; ‘large’ effect size: –0.87), although in follow-up, there was no difference between the groups (mean difference: 4.16; SE: 2.97; p: 0.17; “medium” effect size: –0.70). Conclusion: Dry cupping was more effective in improving pain and functional disability in people with persistent nonspecific low back pain when compared to the sham.
Salemi, Zahra,Hosseinkhani, Saman,Ranjbar, Bijan,Nemat-Gorgani, Mohsen Korean Society for Biochemistry and Molecular Biol 2006 Journal of biochemistry and molecular biology Vol.39 No.5
Our previous studies indicated that native carbonic anhydrase does not interact with hydrophobic adsorbents and that it acquires this ability upon denaturation. In the present study, an apo form of the enzyme was prepared by removal of zinc and a comparative study was performed on some characteristic features of the apo and native forms by far- and near-UV circular dichroism (CD), intrinsic fluorescent spectroscopy, 1-anilino naphthalene-8-sulfonate (ANS) binding, fluorescence quenching by acrylamide, and Tm measurement. Results indicate that protein flexibility is enhanced and the hydrophobic sites become more exposed upon conversion to the apo form. Accordingly, the apo structure showed a greater affinity for interaction with hydrophobic adsorbents as compared with the native structure. As observed for the native enzyme, heat denaturation of the apo form promoted interaction with alkyl residues present on the adsorbents and, by cooling followed by addition of zinc, catalytically-active immobilized preparations were obtained.
Akbar Salemi,Reza Mikaeil,Sina Shaffiee Haghshenas 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.5
In this study, it is aimed to investigate the behavior of the concrete lining of circular shallow tunnels in sedimentary urban areasunder seismic loads using integration of numerical and metaheuristic techniques. The Tabriz Urban Railway (TUR) Tunnel is used asa case study in this investigation. The seismic and geotechnical characteristics of the area were studied, and seismic analysis wascarried out using a finite difference code (i.e., FLAC2D) and genetic algorithm. In the first step, final induced loads on lining due toDesign Base Level (DBL), Maximum Credible Level (MCL) and static loads were determined using FLAC2D software. Then, eightparts of lining were classified using genetic algorithm based on axial force, bending moment and shear force for two types ofearthquake loads. The results of classification were verified by the safety factors of the studied parts of the lining. By comparing theseresults, it can be concluded that the genetic algorithm can be reliably used to classify and evaluate the safety of lining based on staticand dynamic loads.
Dental age estimation using the pulp-to-tooth ratio in canines by neural networks
Farhadian, Maryam,Salemi, Fatemeh,Saati, Samira,Nafisi, Nika Korean Academy of Oral and Maxillofacial Radiology 2019 Imaging Science in Dentistry Vol.49 No.1
Purpose: It has been proposed that using new prediction methods, such as neural networks based on dental data, could improve age estimation. This study aimed to assess the possibility of exploiting neural networks for estimating age by means of the pulp-to-tooth ratio in canines as a non-destructive, non-expensive, and accurate method. In addition, the predictive performance of neural networks was compared with that of a linear regression model. Materials and Methods: Three hundred subjects whose age ranged from 14 to 60 years and were well distributed among various age groups were included in the study. Two statistical software programs, SPSS 21 (IBM Corp., Armonk, NY, USA) and R, were used for statistical analyses. Results: The results indicated that the neural network model generally performed better than the regression model for estimation of age with pulp-to-tooth ratio data. The prediction errors of the developed neural network model were acceptable, with a root mean square error (RMSE) of 4.40 years and a mean absolute error (MAE) of 4.12 years for the unseen dataset. The prediction errors of the regression model were higher than those of the neural network, with an RMSE of 10.26 years and a MAE of 8.17 years for the test dataset. Conclusion: The neural network method showed relatively acceptable performance, with an MAE of 4.12 years. The application of neural networks creates new opportunities to obtain more accurate estimations of age in forensic research.
Sobhani, Farshad,Salemi, Fatemeh,Miresmaeili, Amirfarhang,Farhadian, Maryam Korean Academy of Oral and Maxillofacial Radiology 2021 Imaging Science in Dentistry Vol.51 No.2
Purpose: Sex determination can be done by morphological analysis of different parts of the body. The mastoid region, with its anatomical location at the skull base, is ideal for sex identification. Statistical shape analysis provides a simultaneous comparison of geometric information on different shapes in terms of size and shape features. This study aimed to investigate the geometric morphometry of the inter-mastoid triangle as a tool for sex determination in the Iranian population. Materials and Methods: The coordinates of 5 landmarks on the mastoid process on the 80 cone-beam computed tomographic images(from individuals aged 17-70 years, 52.5% female) were registered and digitalized. The Cartesian x-y coordinates were acquired for all landmarks, and the shape information was extracted from the principal component scores of generalized Procrustes fit. The t-test was used to compare centroid size. Cross-validated discriminant analysis was used for sex determination. The significance level for all tests was set at 0.05. Results: There was a significant difference in the mastoid size and shape between males and females(P<0.05). The first 2 components of the Procrustes shape coordinates explained 91.3% of the shape variation between the sexes. The accuracy of the discriminant model for sex determination was 88.8%. Conclusion: The application of morphometric geometric techniques will significantly impact forensic studies by providing a comprehensive analysis of differences in biological forms. The results demonstrated that statistical shape analysis can be used as a powerful tool for sex determination based on a morphometric analysis of the inter-mastoid triangle.
Farhadian, Maryam,Salemi, Fatemeh,Shokri, Abbas,Safi, Yaser,Rahimpanah, Shahin Korean Academy of Oral and Maxillofacial Radiology 2020 Imaging Science in Dentistry Vol.50 No.4
Purpose: The mastoid region is ideal for studying sexual dimorphism due to its anatomical position at the base of the skull. This study aimed to determine sex in the Iranian population based on measurements of the mastoid process using different data mining algorithms. Materials and Methods: This retrospective study was conducted on 190 3-dimensional cone-beam computed tomographic (CBCT) images of 105 women and 85 men between the ages of 18 and 70 years. On each CBCT scan, the following 9 landmarks were measured: the distance between the porion and the mastoidale; the mastoid length, height, and width; the distance between the mastoidale and the mastoid incision; the intermastoid distance (IMD); the distance between the lowest point of the mastoid triangle and the most prominent convex surface of the mastoid (MF); the distance between the most prominent convex mastoid point (IMSLD); and the intersecting angle drawn from the most prominent right and left mastoid point (MMCA). Several predictive models were constructed and their accuracy was compared using cross-validation. Results: The results of the t-test revealed a statistically significant difference between the sexes in all variables except MF and MMCA. The random forest model, with an accuracy of 97.0%, had the best performance in predicting sex. The IMSLD and IMD made the largest contributions to predicting sex, while the MMCA variable had the least significant role. Conclusion: These results show the possibility of developing an accurate tool using data mining algorithms for sex determination in the forensic framework.
Dental age estimation using the pulp-to-tooth ratio in canines by neural networks
Maryam Farhadian,Fatemeh Salemi,Samira Saati,Nika Nafisi 대한영상치의학회 2019 Imaging Science in Dentistry Vol.49 No.1
Purpose: It has been proposed that using new prediction methods, such as neural networks based on dental data, could improve age estimation. This study aimed to assess the possibility of exploiting neural networks for estimating age by means of the pulp-to-tooth ratio in canines as a non-destructive, non-expensive, and accurate method. In addition, the predictive performance of neural networks was compared with that of a linear regression model. Materials and Methods: Three hundred subjects whose age ranged from 14 to 60 years and were well distributed among various age groups were included in the study. Two statistical software programs, SPSS 21 (IBM Corp., Armonk, NY, USA) and R, were used for statistical analyses. Results: The results indicated that the neural network model generally performed better than the regression model for estimation of age with pulp-to-tooth ratio data. The prediction errors of the developed neural network model were acceptable, with a root mean square error (RMSE) of 4.40 years and a mean absolute error (MAE) of 4.12 years for the unseen dataset. The prediction errors of the regression model were higher than those of the neural network, with an RMSE of 10.26 years and a MAE of 8.17 years for the test dataset. Conclusion: The neural network method showed relatively acceptable performance, with an MAE of 4.12 years. The application of neural networks creates new opportunities to obtain more accurate estimations of age in forensic research.