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Near-infrared PbS quantum dots functionalized with affibodies and ZnPP for targeted imaging and therapeutic applications
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Abstract<p>We report a new theranostic device based on lead sulfide quantum dots (PbS QDs) with optical emission in the near infrared wavelength range decorated with affibodies (small 6.5 kDa protein-based antibody replacements) specific to the cancer biomarker human epidermal growth factor receptor 2 (HER2), and zinc(II) protoporphyrin IX (ZnPP) to combine imaging, targeting and therapy within one nanostructure. Colloidal PbS QDs were synthesized in aqueous solution with a nanocrystal diameter of ∼5 nm and photoluminescence emission in the near infrared wavelength range. The Z<sub>HER2:432</sub> affibody, mutated through the introduction of two cysteine residues at the C-terminus (Afb2C), was used as capping ligand to form Afb2C-PbS QDs that have a high binding affinity for HER2, which is overexpressed in several types of cancer including breast cancer. Afb2C-PbS QDs were further modified by conjugation with ZnPP, which acts as an anticancer agent. The biological activity of these QDs was tested against SKBR3 (HER2-positive) and MDA-MB-231 (HER2-normal) breast cancer cells, with results showing that ZnPP-Afb2C-functionalized PbS QDs were successfully targeted to the HER2-overexpressing cancer cells and induced cell apoptosis thanks to the conjugation with ZnPP. These results expand the use of the QD nanoplatform with the formulation of novel nanomaterials for targeted delivery and combined imaging and therapy via direct surface-protein interaction.</p>
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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Classic Local Least Estimatop And Bayesian Methoid For Estimating Semiparametric Logistic Regression Model
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Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

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Publication Date
Tue Oct 11 2022
Journal Name
College Of Islamic Sciences
Directing Grammarians for Grammatical Dispute To Interpret and Explain the fourth part of the Holy Qur’an
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Abstract

 The miraculous of al-Quran has been surrounded by the attention of scholars, as it is the one that has astonished the rhetoricians with its eloquence. So , they paid attention to every part of it  and hugely they studied it with accuracy in respect to its Surah  ad Ayahs.   It is considered the most important source from which Arab scholars and early grammarians drew, given their unanimity that it is the highest degree of eloquence and the best record of the common literary language.

 

Among these sciences is the science of Grammar, and without Qur’an, this science would not have emerged, which later had control over every science of Arabic

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Publication Date
Sun Dec 10 2017
Journal Name
Al-academy
Representations and perceptions of anxiety about the future of artistic expression for students in middle school
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The tensions and crises and the psychological pressure as well as the rapid changes and great development which is taking place in the present time. And  witnessing community of wars and conflicts that give rise to future concern among members of the community in general and students in particular, as it included the current research a number of chapters, the First chapter contains the research problem, the important goal, then set researcher terminology that has defined and contained in the title of research in the form (concern the future, artistic expression, middle school). The Second chapter included three sections, the first included the nature of adolescence and traits, characteristics and pr

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Fri Jul 26 2013
Journal Name
Environmental Geochemistry And Health
Assessment of sulfurous springs in the west of Iraq for balneotherapy, drinking, irrigation and aquaculture purposes
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Publication Date
Sun Jan 01 2012
Journal Name
Aip Conference Proceedings
The electrical conductivity and thermoelectric power dependence on the thicknesses for thermally deposited thin CdS films
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Publication Date
Fri May 03 2024
Journal Name
Optical And Quantum Electronics
Design and analysis of a dual-core PCF biosensor based on SPR for cancerous cells detection
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Publication Date
Mon Oct 01 2018
Journal Name
Ieee Transactions On Network Science And Engineering
A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept
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Publication Date
Thu Jun 01 2023
Journal Name
Measurement: Sensors
Improved airborne computer system strategy for swarm drones flying based on skybrush suite and inspired technique
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Publication Date
Tue Mar 19 2019
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Material Removal Rate and Temperature in Magnetic Abrasive Finishing Process for Stainless Steel 304
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The effect of the magnetic abrasive finishing (MAF) method on the temperature rise (TR), and material removal rate (MRR) has been investigated in this paper. Sixteen runs were to determine the optimum temperature in the contact area (between the abrasive powder and surface of workpiece) and the MRR according to Taguchi orthogonal array (OA). Four variable technological parameters (cutting speed, finishing time, working gap, and the current in the inductor) with four levels for each parameter were used, the matrix is known as a L16 (44) OA. The signal to noise ratio (S/N) ratio and analysis of the variance (ANOVA) were utilized to analyze the results using (MINITAB17) to find the optimum condition and identify the significant p

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