Search

Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures., (© 2024. The Author(s).)

The achievement of a successful heating power response of Fe 3 O 4 nanoparticles for being applied in magnetic hyperthermia entails an exhaustive control of their magnetic characteristics and therefore, of the synthesis method employed. Despite the fact that one of the best wet-chemical methods to finely adjust Fe 3 O 4 nanoparticles (NPs) size over 15 ​nm is the thermal decomposition of iron(III) oleate, the studies about the specific influence of iron(III) oleate precursor on the IONPs are particularly scarce. So, in this work five iron(III) oleate precursors have been systematically prepared varying synthesis conditions and it has been analyzed how their characteristics affect the features of the ulterior magnetite NPs. The refined synthesis method has yield monophasic and monodisperse NPs of magnetite (Fe 3 O 4) with different sizes (in the 10–40 ​nm range) and morphologies (cuboctahedral, octahedral and spherical). A complete chemical, structural, morphological and magnetic characterization have been performed to correlate the properties of the iron(III) oleate with the features of the subsequent magnetite NPs. [Display omitted] • A proper control of the reaction conditions of Fe(oleate) 2 precursor can lead tailored magnetic nanoparticles. • Well-faceted nano-octahedra Fe 3 O 4 nanoparticles, with good shape/size homogeneity can been obtained from Fe:Oleate ratio ≤3. • High saturation magnetization (Ms) and a Verwey temperature (Tv) similar to bulk magnetite displayed by octahedral NPs. • Good monodispersity of octahedral nanosystems easily corroborated by EMR measurements. [ABSTRACT FROM AUTHOR]