The association of tobacco smoking and bone health in the elderly population of Iran: results from Bushehr elderly health (BEH) program

Smoking has been linked with osteoporosis, but further evidence is required, especially concerning the effects of different types of tobacco smoking. We sought to examine the association between smoking and bone health in a large cohort of elderly Iranians. Methods: The data from 2377 participants aged >60 years of Bushehr Elderly Health (BEH) program were used. Regardless of the type of smoking, participants were initially classified as non-smokers, ex-smokers and current smokers. Current smokers were also categorized based on the smoking type (pure cigarette, pure hookah and both). Dual-energy X-ray absorptiometry was used to evaluate bone density as well as Trabecular Bone Score (TBS). T-score ≤ −2.5 in either of the femoral neck, total hip or spinal sites was applied to determine the osteoporosis. The association of smoking and osteoporosis was assessed using multivariable modified Poisson regression model and reported as adjusted prevalence ratios (APR). The linear regression model was used to assess the association between smoking and TBS, adjusting for potential factors. Results: A total of 2377 (1225 women) were enrolled [mean age: 69.3 (±6.4) years], among which 1054 (44.3%) participants were nonsmokers. In all, 496 (20.9%) participants were current smokers. Multivariable regression analysis revealed no significant association between smoking (either current or past) and osteoporosis in women. In men, current smoking was negatively associated with osteoporosis (APR: 1.51, 95%CI: 1.16–1.96). Among current users, cigarette smoking was associated with osteoporosis (APR: 1.57, 95%CI: 1.20–2.03); however, we could not detect a significant association between current smoking of hookah and osteoporosis. In men, a significant association was also detected between current cigarette smoking and TBS (coefficient: -0.03, 95%CI: −0.01, −0.04). Conclusion: Current cigarette smoking is associated with both the quantity and quality of bone mass in elderly men. Although we could not detect a significant association between hookah and osteoporosis in men, considering the prevalence of hookah smoking in the middle eastern countries, further studies are needed to determine the effect of hookah smoking on bone health

The association of heart rate recovery immediately after exercise with coronary artery calcium: the coronary artery risk development in young adults study

We tested whether slower heart rate recovery (HRR) following graded exercise treadmill testing (GXT) was associated with the presence of coronary artery calcium (CAC). Participants (n = 2,648) ages 18–30 years at baseline examination underwent GXT, followed by CAC screening 15 years later. Slow HRR was not associated with higher odds of testing positive (yes/no) for CAC at year 15 (OR = 0.99, p = 0.91 per standard deviation change in HRR). Slow HRR in young adulthood is not associated with the presence of CAC at middle age

Review of thermo-physical properties, wetting and heat transfer characteristics of nanofluids and their applicability in industrial quench heat treatment

The success of quenching process during industrial heat treatment mainly depends on the heat transfer characteristics of the quenching medium. In the case of quenching, the scope for redesigning the system or operational parameters for enhancing the heat transfer is very much limited and the emphasis should be on designing quench media with enhanced heat transfer characteristics. Recent studies on nanofluids have shown that these fluids offer improved wetting and heat transfer characteristics. Further water-based nanofluids are environment friendly as compared to mineral oil quench media. These potential advantages have led to the development of nanofluid-based quench media for heat treatment practices. In this article, thermo-physical properties, wetting and boiling heat transfer characteristics of nanofluids are reviewed and discussed. The unique thermal and heat transfer characteristics of nanofluids would be extremely useful for exploiting them as quench media for industrial heat treatment

The Role and Status of Interdisciplinary Studies in the Development of the Humanities in Iran

Interdisciplinary studies can play a pivotal role in the growth and development of sciences, especially the humanities. In the present article, through semi-structured interviews with some experts and thinkers in Iran and the content analysis of their ideas, attempt is made to answer these questions: in the view of experts, what are the main obstacles to the development of humanities in Iran? And what role can interdisciplinary studies play in the development of humanities? The results of the study show that according to experts, “interdisciplinary development”, having the twelfth place among the sixteen important factors in the development of humanities, does not have a considerable effect on the development of humanities in Iran per se, and its efficacy depends on the existence of more important conditions, such as the provision of an open intellectual climate at universities and the independence of scientific community. The development of interdisciplinary studies can play a part in the development of humanities in Iran, only if it results in scientific synergy among experts in different disciplines of humanities, improves the scientific ability of professors, students and researchers, and makes humanities more applicable in society

Fluvoxamine treatment response prediction in obsessive-compulsive disorder: association rule mining approach

Hesam Hasanpour,1 Ramak Ghavamizadeh Meibodi,1 Keivan Navi,1 Jamal Shams,2 Sareh Asadi,3 Abolhassan Ahmadiani4 1Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran; 2Behavioral Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; 3Neurobiology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; 4Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Background: Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder characterized by intrusive thoughts or repetitive behaviors. Clinicians use serotonin reuptake inhibitors (SRIs) for OCD treatment, but 40%–60% of the patients do not respond to them adequately. Here, we described an association rule mining approach for treatment response prediction using an Iranian OCD data set.Patients and methods: Three hundred and thirty OCD patients fulfilling DSM-5 criteria were initially included, but 151 subjects completed their pharmacotherapy which was defined as 12-week treatment with fluvoxamine (150–300 mg). Treatment response was considered as >35% reduction in the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score. Apriori algorithm was applied to the OCD data set for extraction of the association rules predicting response to fluvoxamine pharmacotherapy in OCD patients. We considered the association of each attribute with treatment response using interestingness measures and found important attributes that associated with treatment response.Results: Results showed that low obsession and compulsion severities, family history of mental illness, illness duration less than 5 years, being married, and female were the most associated variables with responsiveness to fluvoxamine pharmacotherapy. Meanwhile, if an OCD patient reported a family history of mental illness and his/her illness duration was less than 5 years, he/she responded to 12-week fluvoxamine pharmacotherapy with the probability of 91%. We also found useful and applicable rules for resistant and refractory patients.Conclusion: This is the first study where association rule mining approach was used to extract predicting rules for treatment response in OCD. Application of this method in personalized medicine may help clinicians in taking the right therapeutic decision. Keywords: data mining, apriori algorithm, family history, refractory patient

Analysis of non-dimensional numbers of fluid flowing inside tubes of flat plate solar collector

The aim of this paper is to discuss the non-dimensional numbers of fluid flowing through inside the tubes of flat plate solar collectors. Empirically, to abate the cost and energy consumption or to boost up the performance and efficiency of solar collectors; computational simulation plays a vital role. In this study, CFD numerical simulation of aqueous ethylene glycol (60% water + 40%) ethylene glycol fluid flow has been done with ANSYS 15.0. Non-dimensional numbers such as surface Nusselt number, Skin friction coefficient and Prandtl number of fluids have been observed based on empirical and experimental properties. The geometry of design has been prepared using Solidworks software in accordance with the actual experimental model. The analysis revealed that the Nusselt number showed effective convection behavior, the skin friction coefficient was positive while the Prandtl number was large for both properties of aqueous ethylene glycol

Man against Machine: Diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

Background: Deep learning convolutional neural networks (CNN) May facilitate melanoma detection, but data comparing a CNN\u2019s diagnostic performance to larger groups of dermatologists are lacking. Methods: Google\u2019s Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists\u2019 diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN\u2019s performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge. Results: In level-I dermatologists achieved a mean (6standard deviation) sensitivity and specificity for lesion classification of 86.6% (69.3%) and 71.3% (611.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (69.6%, P \ubc 0.19) and specificity to 75.7% (611.7%, P < 0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P < 0.01) and level-II (75.7%, P < 0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P < 0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge. Conclusions: For the first time we compared a CNN\u2019s diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians\u2019 experience, they May benefit from assistance by a CNN\u2019s image classification