Shahid Beheshti University of Medical Sciences and Health Services

About: Shahid Beheshti University of Medical Sciences and Health Services is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Cancer. The organization has 19456 authors who have published 33659 publications receiving 365676 citations.

Computational modelling of a non-viscous fluid flow in a multi-walled carbon nanotube modelled as a Timoshenko beam

Abstract: In the design of nanotube-based fluidic devices, a critical issue is the effect of the induced vibrations in the nanotube arising from the fluid flow, since these vibrations can promote structural instabilities, such as buckling transitions. It is known that the induced resonant frequencies depend on the fluid flow velocity in a significant manner. We have studied, for the first time, the flow of a non-viscous fluid in stubby multi-walled carbon nanotubes, using the Timoshenko classical beam theory to model the nanotubes as a continuum structure. We have obtained the variations of the resonant frequencies with the fluid flow velocity under several experimentally interesting boundary conditions and aspect ratios of the nanotube. The main finding from our work is that, compared to an Euler-Bernoulli classical beam model of a nanotube, the Timoshenko beam predicts the loss of stability at lower fluid flow velocities.

Effectiveness of Prenatal Vitamin D Deficiency Screening and Treatment Program: A Stratified Randomized Field Trial.

Abstract: Context: Despite evidence on the association between hypovitaminosis D and adverse pregnancy outcomes and the positive impact of vitamin D supplementation, no evidence exists supporting a universal screening program in pregnancy as part of routine prenatal care. Objective: We sought to determine the effectiveness of a prenatal screening program on optimizing 25-hydroxyvitamin D [25(OH)D] levels and preventing pregnancy complications. Also, to identify a safe regimen, we compared several regimens in a subgroup of vitamin D-deficient pregnant women. Design: Two cities of Masjed-Soleyman and Shushtar from Khuzestan province, Iran, were selected as the screening and nonscreening arms, respectively. Within the screening arm, a randomized controlled trial was conducted on 800 pregnant women. Setting: Health centers of Masjed-Soleyman and Shushtar cities. Patients or Participants: Pregnant women aged 18 to 40 years. Intervention: Women with moderate [25(OH)D, 10 to 20 ng/mL] and severe [25(OH)D, <10 ng/mL] deficiency were randomly divided into four subgroups and received vitamin D3 (D3) until delivery. Main Outcome Measure: Maternal concentration of 25(OH)D at delivery and rate of pregnancy complications. Results: After supplementation, only 2% of the women in the nonscreening site met the sufficiency level (>20 ng/mL) vs 53% of the women in the screening site. Adverse pregnancy outcomes, including preeclampsia, gestational diabetes mellitus, and preterm delivery, were decreased by 60%, 50%, and 40%, respectively, in the screening site. A D3 injection in addition to monthly 50,000 IU maintenance therapy contributed the most to achievement of sufficient levels at delivery. Conclusions: A prenatal vitamin D screening and treatment program is an effective approach in detecting deficient women, improving 25(OH)D levels, and decreasing pregnancy adverse outcomes.

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

Abstract: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate cancer (Pca) stages. Thirty-three Pca patients were included. All patients underwent pre- and post-IMRT T2-weighted (T2 W) and apparent diffusing coefficient (ADC) MRI. IMRT response was calculated in terms of changes in the ADC value, and patients were divided as responders and non-responders. A wide range of radiomic features from different feature sets were extracted from all T2 W and ADC images. Univariate radiomic analysis was performed to find highly correlated radiomic features with IMRT response, and a paired t test was used to find significant features between responders and non-responders. To find high predictive radiomic models, tenfold cross-validation as the criterion for feature selection and classification was applied on the pre-, post- and delta IMRT radiomic features, and area under the curve (AUC) of receiver operating characteristics was calculated as model performance value. Of 33 patients, 15 patients (45%) were found as responders. Univariate analysis showed 20 highly correlated radiomic features with IMRT response (20 ADC and 20 T2). Two and fifteen T2 and ADC radiomic features were found as significant (P-value ≤ 0.05) features between responders and non-responders, respectively. Several cross-combined predictive radiomic models were obtained, and post-T2 radiomic models were found as high predictive models (AUC 0.632) followed by pre-ADC (AUC 0.626) and pre-T2 (AUC 0.61). For GS prediction, T2 W radiomic models were found as more predictive (mean AUC 0.739) rather than ADC models (mean AUC 0.70), while for stage prediction, ADC models had higher prediction performance (mean AUC 0.675). Radiomic models developed by MR image features and machine learning approaches are noninvasive and easy methods for personalized prostate cancer diagnosis and therapy.

Corneal endothelial cell dysfunction: etiologies and management.

Abstract: A transparent cornea is essential for the formation of a clear image on the retina. The human cornea is arranged into well-organized layers, and each layer plays a significant role in maintaining the transparency and viability of the tissue. The endothelium has both barrier and pump functions, which are important for the maintenance of corneal clarity. Many etiologies, including Fuchs' endothelial corneal dystrophy, surgical trauma, and congenital hereditary endothelial dystrophy, lead to endothelial cell dysfunction. The main treatment for corneal decompensation is replacement of the abnormal corneal layers with normal donor tissue. Nowadays, the trend is to perform selective endothelial keratoplasty, including Descemet stripping automated endothelial keratoplasty and Descemet's membrane endothelial keratoplasty, to manage corneal endothelial dysfunction. This selective approach has several advantages over penetrating keratoplasty, including rapid recovery of visual acuity, less likelihood of graft rejection, and better patient satisfaction. However, the global limitation in the supply of donor corneas is becoming an increasing challenge, necessitating alternatives to reduce this demand. Consequently, in vitro expansion of human corneal endothelial cells is evolving as a sustainable choice. This method is intended to prepare corneal endothelial cells in vitro that can be transferred to the eye. Herein, we describe the etiologies and manifestations of human corneal endothelial cell dysfunction. We also summarize the available options for as well as recent developments in the management of corneal endothelial dysfunction.