A review on protein corona formation on nanoparticles and prediction of its composition using artificial intelligence tools.

Nanoparticles (NPs) represent critical roles both for drug delivery systems and diagnostics. Nevertheless, due to interaction in a biological medium and specific consequences-like formation of protein corona (PC), changes may happen that have influenced its behavior. Such a PC depicts the formation of biomolecule dynamic layers over the NPs, normally starting at exposure in any form to biofluid, because this altered cellular targeting, biodistribution, and toxic potential happen very well.

Exploring the experiences and perceptions of nursing students in utilizing artificial intelligence: a descriptive phenomenological study.

Background: Artificial intelligence is transforming healthcare by enhancing diagnostics, efficiency, and outcomes. Evaluating nursing students' knowledge helps identify educational gaps, as they directly engage in patient care and decision-making. This study explored their experiences with using artificial intelligence in clinical settings.

Extracellular vesicles as therapeutic agents in rheumatoid arthritis: a systematic review of current evidence.

Rheumatoid arthritis (RA) is defined as a chronic autoimmune disease that severely influences a patient's quality of life. Extracellular vesicles (EVs) have gained much attention in recent years as one of the most potent therapeutic agents for the treatment of RA. A systematic review was performed with the purpose of assessing the current evidence relating to the therapeutic applications of EVs in RA.

Defining the predictors for post renal transplant left ventricular dysfunction in end-stage renal disease patients.

Reduced left ventricular (LV) function predicts poor outcomes in end-stage renal disease (ESRD). This study aimed to identify the pre-renal transplantation echocardiographic parameters that can predict post-renal transplantation LV failure. This prospective longitudinal study was conducted on patients with ESRD who underwent renal transplantation during 1 year.

Synthesis, modification, characterization, and in vitro evaluation of chitosan-hyaluronic acid coated MIL-100 (Fe) nanoparticles for methotrexate delivery in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by inflammation of the joints, leading to pain, swelling, and potential joint destruction. Effective management of RA is crucial to improve patients' quality of life and prevent long-term disability. Methotrexate (MTX) is a widely used disease-modifying antirheumatic drug (DMARD) that has shown efficacy in treating RA.

Developing and validating of educational-therapeutic package based on psychological flexibility for nurses in the intensive care unit of COVID-19: Application of grounded theory.

Background: Caring for COVID-19 patients has caused high stress and burnses. Therefore, the current research aims to develop and validate an educational-therapeutic package based on psychological flexibility for COVID-19 nurses.

Materials And Methods: The approach of this research was Exploratory Sequential Mixed Method, which was carried out in 2019 to 2021.

Artificial intelligence in nanotechnology for treatment of diseases.

Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics, leading to diverse applications across different diseases. However, the complexity, cost and time-consuming nature of laboratory processes, the large volume of data, and the challenges in data analysis have prompted the integration of artificial intelligence (AI) tools.

Optimization of the Synthesis and Radiolabeling of ZIF-8 Nanoparticles.

Background: Lately, there has been increasing interest in the benefits of metal-organic frameworks, and among them, zeolitic imidazolate frameworks (ZIF - 8) stand out as one of the most commonly employed systems owing to their unique characteristics.

Objectives: Given that properties like particle size play a key role in biomedical applications of nanoparticles, optimizing the synthesis conditions becomes crucial. Additionally, it is essential to label these nanoparticles to track them effectively within the body.

Angiographic evaluation of coronary artery disease in diabetic patients with and without end-stage kidney disease.

The objective of the present investigation was to compare the coronary angiography results in diabetic patients with and without end-stage kidney disease (ESKD). We included prolonged diabetic patients with ESKD (93 patients) and without ESKD (control group, 126 patients). Angiography of the coronary arteries was performed on all patients.

Prediction of ovarian cancer using artificial intelligence tools.

Purpose: Ovarian cancer is a common type of cancer and a leading cause of death in women. Therefore, accurate and fast prediction of ovarian tumors is crucial. One of the appropriate and precise methods for predicting and diagnosing this cancer is to build a model based on artificial intelligence methods.

Predicting Pharmacokinetics of Drugs Using Artificial Intelligence Tools: A Systematic Review.

Background And Objective: Pharmacokinetic studies encompass the examination of the absorption, distribution, metabolism, and excretion of bioactive compounds. The pharmacokinetics of drugs exert a substantial influence on their efficacy and safety. Consequently, the investigation of pharmacokinetics holds great importance.

Natural agents as wound-healing promoters.

The management of acute and chronic wounds resulting from diverse injuries poses a significant challenge to clinical practices and healthcare providers. Wound healing is a complex biological process driven by a natural physiological response. This process involves four distinct phases, namely hemostasis, inflammation, proliferation, and remodeling.

Toxicity prediction of nanoparticles using machine learning approaches.

Nanoparticle toxicity analysis is critical for evaluating the safety of nanomaterials due to their potential harm to the biological system. However, traditional experimental methods for evaluating nanoparticle toxicity are expensive and time-consuming. As an alternative approach, machine learning offers a solution for predicting cellular responses to nanoparticles.

Organizational Climate of the COVID-19 Intensive Care Units: A Qualitative Content Analysis Study.

Introduction: To manage the psychological consequences of providing services in the COVID-19 intensive care units (ICUs), it is necessary to identify the experience of nurses from the organizational climate. The current study was conducted to explain the nurses' experience of the organizational climate of the COVID-19 ICUs.

Methods: This qualitative study was conducted in three teaching hospitals affiliated to Isfahan University of Medical Sciences.

Synthesis and Radiolabeling of Glu-Urea-Lys with Tc-Tricarbonyl-Imidazole-Bathophenanthroline Disulfonate Chelation System and Biological Evaluation as Prostate-Specific Membrane Antigen Inhibitor.

The Glu-Urea-Lys (EUK) pharmacophore as prostate-specific membrane antigen (PSMA)-targeted ligand was synthesized, radiolabeled with Tc-tricarbonyl-imidazole-BPS chelation system, and biological activities were evaluated. The strategy [2 + 1] ligand is applied for tricarbonyl labeling. (5-imidazole-1-yl)pentanoic acid as a monodentate ligand and bathophenanthroline disulfonate (BPS) as a bidentate ligand formed a chelate system with Tc-tricarbonyl.

The Safe Coping Strategy of Nurses Working in the Care Units of Patients with COVID-19: A Qualitative Study.

Background: Nurses are in direct contact with patients with COVID-19 and have faced much tension with the rapid spread of coronavirus. This study aimed to explore the safe coping strategies of nurses when facing the COVID-19 pandemic.

Materials And Methods: In this qualitative study, data were collected from September 20 to December 20, 2020, in Isfahan (Iran) through individual semi-structured interviews with 12 nurses working in the five referral centers for patients with COVID-19.

Nanoparticles labeled with gamma-emitting radioisotopes: an attractive approach for in vivo tracking using SPECT imaging.

Providing accurate molecular imaging of the body and biological process is critical for diagnosing disease and personalizing treatment with the minimum side effects. Recently, diagnostic radiopharmaceuticals have gained more attention in precise molecular imaging due to their high sensitivity and appropriate tissue penetration depth. The fate of these radiopharmaceuticals throughout the body can be traced using nuclear imaging systems, including single-photon emission computed tomography (SPECT) and positron emission tomography (PET) modalities.

Prognosis of COVID-19 patients using lab tests: A data mining approach.

Background: The rapid prevalence of coronavirus disease 2019 (COVID-19) has caused a pandemic worldwide and affected the lives of millions. The potential fatality of the disease has led to global public health concerns. Apart from clinical practice, artificial intelligence (AI) has provided a new model for the early diagnosis and prediction of disease based on machine learning (ML) algorithms.

Systematic review of content analysis algorithms based on deep neural networks.

Today according to social media, the internet, Etc. Data is rapidly produced and occupies a large space in systems that have resulted in enormous data warehouses; the progress in information technology has significantly increased the speed and ease of data flow.text mining is one of the most important methods for extracting a useful model through extracting and adapting knowledge from data sets.

Novel biodegradable molecularly imprinted polymer nanoparticles for drug delivery of methotrexate anti-cancer; synthesis, characterization and cellular studies.

Background: Recently biodegradable nanoparticles are the center of attention for the development of drug delivery systems. Molecularly imprinted polymer (MIP) is an interesting candidate for designing drug nano-carriers. MIP-based nanoparticles could be used for cancer treatment and exhibited the potential to fill gaps regarding to ligand-based nanomaterials.

Controllable Synthesis of Polymeric Micelles by Microfluidic Platforms for Biomedical Applications: A Systematic Review.

Polymeric micelles (PMs) are one of Nanoscale delivery systems with high stability, loading capacity, and biocompatibility. PMs are nano-sized and spherical particles with a hydrophilic shell and hydrophobic core or reverse depending on their applications. Polymeric micelles could be synthesized by different methods, such as direct dissolution, dialysis method, and lyophilization.

Correlation Between Fibroblast Growth Factor-23 and Pulmonary Arterial Hypertension in Hemodialysis Patients.

Introduction: Pulmonary artery hypertension (PAH) is common in end stage renal disease (ESRD) patients undergoing hemodialysis. Fibroblast growth factor-23 (FGF-23) increases in hemodialysis but its relationship with PAH is not completely understood. The aim of this study was to evaluate the relation between FGF-23 level and development of PAH in ESRD patients undergoing hemodialysis.

An investigation of affecting factors on MOF characteristics for biomedical applications: A systematic review.

Metal-organic frameworks (MOFs) are a fascinating class of crystalline porous materials composed of metal ions and organic ligands. Due to their attractive properties, MOFs can potentially offer biomedical field applications, such as drug delivery and imaging. This study aimed to systematically identify the affecting factors on the MOF characteristics and their effects on structural and biological characteristics.