Functionalized iron oxide nanoparticles (IONPs) are of great interest due to wide range applications, especially in nanomedicine. However, they face challenges preventing their further applications such as rapid agglomeration, oxidation, etc. Appropriate surface modification of IONPs can conquer these barriers with improved physicochemical properties. This review summarizes recent advances in the surface modification of IONPs with small organic molecules, polymers and inorganic materials. The preparation methods, mechanisms and applications of surface-modified IONPs with different materials are discussed. Finally, the technical barriers of IONPs and their limitations in practical applications are pointed out, and the development trends and prospects are discussed.

MgO is an attractive choice for carcinogenic cell destruction in photodynamic therapy, as confirmed by manifold analysis. The prime focus of the presented research is to investigate the toxicity caused by morphologically different MgO nanostructures obtained by annealing at various annealing temperatures. Smart (stimuli-responsive) MgO nanomaterials are a very promising class of nanomaterials, and their properties can be controlled by altering their size, morphology, or other relevant characteristics. The samples investigated here were grown by the co-precipitation technique. Toxicity-dependent parameters were assessed in a HeLa cell model after annealing the grown samples at 350 °C, 450 °C, and 550 °C. After the overall characterization, an analysis of toxicity caused by changes in the MgO nanostructure morphology was tested in a HeLa cell model using a neutral red assay and microscopy. The feasibility of using MgO for PDT was assessed. Empirical modelling was applied to corroborate the experimental results obtained from assessing cell viability losses and reactive oxygen species. The results indicate that MgO is an excellent candidate material for medical applications and could be utilized for its potential ability to upgrade conventionally used techniques.

Graphene-based materials have attracted considerable interest owing to their distinctive characteristics, such as their biocompatibility in terms of both their physical and intrinsic chemical properties. The use of nanomaterials with graphene as a biocompatible agent has increased due to an uptick in dedication from biomedical investigators. Here, GO-ZnO was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), ultraviolet-visible (UV-Vis) spectroscopy, energy dispersive X-ray analysis (EDAX), and Raman spectroscopy for structural, morphological, and elemental analysis. The toxic extent of GO-ZnO was noted by a methyl-thiazole-tetrazolium (MTT), while cellular morphology was observed towards the MCF-7 cells using an inverted microscope at magnification 40×. The cytotoxic effect of GO-ZnO investigated the cell viability reduction in a dose-dependent manner, as well as prompted the cell demise/destruction in an apoptotic way. Moreover, statistical analysis was performed on the experimental outcomes, with p-values < 0.05 kept as significant to elucidate the results. The generation of reactive oxygen species (ROS) demonstrated the potential applicability of graphene in tumor treatment. These key results attest to the efficacy of GO-ZnO nanocomposites as a substantial candidate for breast malignancy treatment.

Compressive sensing (CS) offers compression of data below the Nyquist rate, making it an attractive solution in the field of medical imaging, and has been extensively used for ultrasound (US) compression and sparse recovery. In practice, CS offers a reduction in data sensing, transmission, and storage. Compressive sensing relies on the sparsity of data; i.e., data should be sparse in original or in some transformed domain. A look at the literature reveals that rich variety of algorithms have been suggested to recover data using compressive sensing from far fewer samples accurately, but with tradeoffs for efficiency. This paper reviews a number of significant CS algorithms used to recover US images from the undersampled data along with the discussion of CS in 3D US images. In this paper, sparse recovery algorithms applied to US are classified in five groups. Algorithms in each group are discussed and summarized based on their unique technique, compression ratio, sparsifying transform, 3D ultrasound, and deep learning. Research gaps and future directions are also discussed in the conclusion of this paper. This study is aimed to be beneficial for young researchers intending to work in the area of CS and its applications, specifically to US.

Carcinogenesis is a complex molecular process starting with genetic and epigenetic alterations, mutation stimulation, and DNA modification, which leads to proteomic adaptation ending with an uncontrolled proliferation mechanism. The current research focused on the empirical modelling of the physiological response of human melanoma cells (FM55P) and human foreskin fibroblasts cells (AG01518) to the multilayer zinc oxide (ZnO) nanomaterials under UV-A exposure. To validate this experimental scheme, multilayer ZnO nanomaterials were grown on a femtotip silver capillary and conjugated with protoporphyrin IX (PpIX). Furthermore, PpIX-conjugated ZnO nanomaterials grown on the probe were inserted into human melanoma (FM55P) and foreskin fibroblasts cells (AG01518) under UV-A light exposure. Interestingly, significant cell necrosis was observed because of a loss in mitochondrial membrane potential just after insertion of the femtotip tool. Intense reactive oxygen species (ROS) fluorescence was observed after exposure to the ZnO NWs conjugated with PpIX femtotip model under UV exposure. Results were verified by applying several experimental techniques, e.g., ROS detection, MTT assay, and fluorescence spectroscopy. The present work reports experimental modelling of cell necrosis in normal human skin as well as a cancerous tissue. These obtained results pave the way for a more rational strategy for biomedical and clinical applications.

A urease trapped chitosan-Fe3O4 based nano-composite biosensor of controlled morphology is successfully fabricated by applying the aqueous chemical growth technique. Final product of nanodevice was characterized by applying various techniques. Log of the concentration of various solutions (1 to 80 mM) ranged between 0.0 to 2.5 mM for urea and glucose sample and an output signal of ~ 42 mV per decade was detected at room temperature. It disclosed the presence of chitosan composite with Fe3O4 results enhanced active surface area of sensing along with up to the mark precession, as compared to traditional biosensor for immobilization of enzymes. The current developed form of chitosan-Fe3O4 nano-composite biosensor illustrated a significant stable potentiometric response in the minimal time period. Besides, nafion/polypyrrole addition to the top surface of CH-Fe3O4 nanocomposite not only protected it from degradation but also upgraded the characteristic of sensor regarding rapid electron transfer enhancement and higher shelf life of this hybrid form of nanomaterial. The advanced form of this voltammetry implied that Ur-GLDH/CH-Fe3O4 bioelectrode is found to be very sensitive in the range of 4-120 mg/dl urea/glucose concentration and can detect as low amount as 0.4mg/dl.