Kharazmi University

About: Kharazmi University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Membrane & Supply chain. The organization has 3395 authors who have published 5321 publications receiving 45645 citations. The organization is also known as: Tarbiat Moallem University of Tehran & Teacher Training University.

Feasibility and Therapeutic Potential of 177Lu-Fibroblast Activation Protein Inhibitor-46 for Patients With Relapsed or Refractory Cancers: A Preliminary Study.

Abstract: Introduction Fibroblast activation protein (FAP) is a member of the serine protease family and has a high expression in the stroma of approximately 90% of epithelial malignancies. The present investigation aimed to assess the feasibility, safety, and dosimetry data of 177Lu-FAPI-46 in diverse malignancies. Patients and methods Patients with advanced cancers with nonoperable tumors, or tumors refractory to conventional therapies, were enrolled. Treatment included escalating doses of 177Lu-FAPI-46 (1.85-4.44 GBq) per cycle using a combination of clinical and statistical expertise design, and intervals of 4 to 6 weeks were considered between the cycles. Biodistribution and dosimetry were examined by whole-body scans. We applied the National Cancer Institute Common Terminology Criteria for Adverse Events version 4.03 to measure peptide-targeted radionuclide therapy (PTRT)-associated toxicity. Results A total of 21 patients (11 females and 10 males) with a median age of 50 years (range, 6-79 years) were investigated. Of 21 participants, 18 cases were selected for PTRT. Overall, 36 PTRT cycles were performed. The median number of PTRT cycles and the median injected amount of activity in each cycle were 2 and 3.7 GBq, respectively. The dosimetric analysis revealed median absorbed doses of 0.026, 0.136, 0.886, and 0.02 with ranges of 0.023-0.034, 0.001-0.2, 0.076-1.39, and 0.002-0.2 mGy/MBq for the whole body, liver, kidneys, and spleen, respectively. The therapy was well tolerated in almost all patients. Conclusions The findings of this preliminary investigation might indicate the potential feasibility and safety of PTRT using 177Lu-FAPI-46 for different aggressive tumors. Moreover, the current study could be beneficial in determining the suitable amount of activity for a phase 2 study.

Evaluation of data-driven models (SVR and ANN) for groundwater-level prediction in confined and unconfined systems

Abstract: Modeling the behavior of groundwater levels is necessary to implement sustainable groundwater resource management. Groundwater is a non-linear and complex system, which can be modeled by data-driven models. This study evaluates the performances of data-driven models, support vector machine regression (SVR) and artificial neural network (ANN), for forecasting groundwater levels of confined and unconfined systems at 1-, 2-, and 3-month ahead. This is the first time that confined and unconfined aquifers have been compared using data-driven models. In addition, to identify the optimal input combination, a hybrid gamma test (GT) and genetic algorithm (GA) was used. The coefficient of correlation (R), Mean Absolute Error (MAE), root mean squared error (RMSE), Nash–Sutcliffe efficiency (NSE), and developed discrepancy ratio (DDR) were applied to evaluate the SVR and ANN models. Results showed that the SVR and ANN models were more accurate for the unconfined system than the confined system for forecasts up to 3-month ahead. In both hydrogeological systems for 1-month ahead, the models performed better than for 2- and 3-month ahead forecasts, and the accuracy of the models decreased as the months ahead increased. The SVR model performed better than the ANN model for 1-, 2-, and 3-month ahead groundwater-level forecasting. The SVR model could be successfully used in predicting monthly groundwater in confined and unconfined systems.

A comparative study on carbon, boron-nitride, boron-phosphide and silicon-carbide nanotubes based on surface electrostatic potentials and average local ionization energies

Abstract: A density functional theory study was carried out to predict the electrostatic potentials as well as average local ionization energies on both the outer and the inner surfaces of carbon, boron-nitride (BN), boron-phosphide (BP) and silicon-carbide (SiC) single-walled nanotubes. For each nanotube, the effect of tube radius on the surface potentials and calculated average local ionization energies was investigated. It is found that SiC and BN nanotubes have much stronger and more variable surface potentials than do carbon and BP nanotubes. For the SiC, BN and BP nanotubes, there are characteristic patterns of positive and negative sites on the outer lateral surfaces. On the other hand, a general feature of all of the systems studied is that stronger potentials are associated with regions of higher curvature. According to the evaluated surface electrostatic potentials, it is concluded that, for the narrowest tubes, the water solubility of BN tubes is slightly greater than that of SiC followed by carbon and BP nanotubes.