Search results for: Kianoush Mohammadnejad

Authors: Kianoush Mohammadnejad, Rahim Mohammadi, Ali Soleimanzadeh, Ali Shalizar Jalai, Farshid Sareafzadeh Rezaei

Abstract:

Testicular torsion and detorsion are significant clinical issues for infertile men. Torsion of the spermatic cord is an emergency condition resulting from the rotation of the testis and epididymis around the axis of the spermatic cord. A rat testis model was used to assess the effects of β-cryptoxanthin on ischemia-reperfusion injury. Twenty healthy male Wistar rats were included and randomized into four investigational groups (n = 5): Group SHAM: In this group, midline incision of the scrotum was performed, and the testicles were taken out for 2 hours with a 720-degree rotation. Group ISCHEMIA: In this group, a midline incision of the scrotum was performed, and the testicles were taken out and underwent ischemia for 2 hours with a 720-degree rotation. Group IS/REP/Oil: In this group, a midline scrotum cut was performed the testicles were taken out, and ischemia was created for 2 hours with a 720-degree rotation and at the end of ischemia 100 µL of corn oil (β-cryptoxanthin solvent) was injected intraperitoneally. Group IS/REP/CRPTXNTN 2.5: The same as group IS/REP/Oil as well as intraperitoneal administration of 100 µL of β-cryptoxanthin (2.5 µg/kg) at the end of ischemia. In all groups, the testes were returned back to the scrotum and, after 60 days, were dissected out and removed for histopathological analyses. β-cryptoxanthin at the dose of 2.5 µg/kg significantly improved histologic indices compared to other treatment groups (p<0.05). β-cryptoxanthin could be helpful in minimizing ischemia-reperfusion injury in testicular tissue exposed to ischemia.

Keywords: beta-cryptoxanthin, testis, Ischemia-reperfusion, Intraperitoneal

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Authors: M. Moharami Gargari, S. Javdani Zamani, A. Mohammadnejad, S. Abuali

Abstract:

As maritime container transport is developing fast, the need arises for efficient operations at container terminals. One of the most important determinants of container handling efficiency is the productivity of quay cranes and internal transportation vehicles, which are responsible transporting of containers for unloading and loading operations for container vessels. For this reason, this paper presents an integrated mathematical model formulation for discrete berths with quay cranes and internal transportations vehicles. The problems have received increasing attention in the literature and the present paper deals with the integration of these interrelated problems. A new mixed integer linear formulation is developed for the Berth Allocation Problem (BAP), Quay Crane Assignment and Scheduling Problem (QCASP) and Internal Transportation Scheduling (ITS), which accounts for cranes and trucks positioning conditions.

Keywords: discrete berths, container terminal, truck scheduling, dynamic vessel arrival

Procedia PDF Downloads 399

Authors: Emad Heydarnia, Aref Sepasi, Nika Asefi, Sara Khakshournia, Javad Mohammadnejad

Abstract:

Background: Despite breakthrough therapeutics in breast cancer, it is one of the main causes of mortality among women worldwide. Thus, drug therapies for treating breast cancer have recently been developed by scientists. Metformin and Sorafenib are well-known therapeutic in breast cancer. In the present study, we combined Sorafenib and PCL-sorafenib with metformin to improve drug absorption and promote therapeutic efficiency. Methods: The MCF-7 cells were treated with Metformin, Sorafenib, or PCL-sorafenib. The growth inhibitory effect of these drugs and cell viability were assessed using MTT and flow cytometry assays, respectively. The expression of targeted genes involved in cell proliferation, signaling, and the cell cycle was measured by Real-time PCR. Results: The results showed that MCF-7 cells treated with Metformin/Sorafenib and PCL-sorafenib/Metformin co-treatment contributed to 50% viability compared to untreated group. Moreover, PI and Annexin V staining tests showed that the cells viability for Metformin/Sorafenib and PCL-sorafenib/Metformin was 38% and 17%, respectively. Furthermore, Sorafenib/Metformin and PCL-sorafenib/Metformin leads to p53 gene expression increase by which they can increase ROS, thereby decreasing GPX4 gene expression. In addition, they affected the expression of BCL2, and BAX genes and altered the cell cycle. Conclusion: Together, the combination of PCL-sorafenib/Metformin and Sorafenib/Metformin increased Sorafenib absorption at lower doses and also leads to apoptosis and oxidative stress increases in MCF-7 cells.

Keywords: breast cancer, metformin, nanotechnology, sorafenib

Procedia PDF Downloads 70

Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

Abstract:

Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

Procedia PDF Downloads 123

Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

Abstract:

Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

Procedia PDF Downloads 210