Ferritin Protein Regulates the Degradation of Iron Oxide Nanoparticles

Proteins implicated in iron homeostasis are assumed to be also involved in the cellular processing of iron oxide nanoparticles. In this work, the role of an endogenous iron storage protein—namely the ferritin—is examined in the remediation and biodegradation of magnetic iron oxide nanoparticles. Previous in vivo studies suggest the intracellular transfer of the iron ions released during the degradation of nanoparticles to endogenous protein cages within lysosomal compartments. Here, the capacity of ferritin cages to accommodate and store the degradation products of nanoparticles is investigated in vitro in the physiological acidic environment of the lysosomes. Moreover, it is questioned whether ferritin proteins can play an active role in the degradation of the nanoparticles. The magnetic, colloidal, and structural follow‐up of iron oxide nanoparticles and proteins in lysosome‐like medium confirms the efficient remediation of potentially harmful iron ions generated by nanoparticles within ferritins. The presence of ferritins, however, delays the degradation of particles due to a complex colloidal behavior of the mixture in acidic medium. This study exemplifies the important implications of intracellular proteins in processes of degradation and metabolization of iron oxide nanoparticles.     

Analytical‐Based Methodologies for Examining the In Vitro Absorption,Distribution, Metabolism,and Elimination (ADME) of Silver Nanoparticles

The clinical applications of silver nanoparticles (AgNPs) remain limited due to the lack of well‐established methodologies for studying their nanokinetics. Hereby, the primary goal is to adapt a suite of analytical‐based methodologies for examining the in vitro absorption, distribution, metabolism, and elimination of AgNPs. Vero 76 and HEK 293 cells are exposed to ≈10‐nm spherical AgNPs⁺ and AgNPs^? at relevant concentrations (0–300 µg mL^?1) and times (4–48 h). Absorption: Inductively coupled plasma optical emission spectroscopy (ICP‐OES) demonstrates that the two AgNP formulations are not bioequivalent. For example, different bioavailabilities (C _maximum < 20.7 ± 4% and 6.82 ± 0.4%), absorption times (T _maximum > 48 and ≈24 h), and absorption rate laws (first‐ and zeroth‐order at 300 µg mL^?1) are determined in Vero 76 for AgNPs⁺ and AgNPs^?, respectively. Distribution: Raman and CytoViva hyperspectral imaging show different cellular localizations for AgNPs⁺ and AgNPs^?. Metabolism: Cloud point extraction (CPE)‐tangential flow filtration (TFF) reveal that ≤ 11% ± 4% of the administered, sublethal AgNPs release Ag⁺ and contribute to the observed cytotoxicity. Elimination: ICP‐OES‐CPE suggests that AgNPs are cleared via exocytosis.     

Spontaneously Embedded Scattering Structures in a Flexible Substrate for Light Extraction

A flexible hazy substrate (FHS) with embedded air bubbles to increase light extraction efficiency of organic light‐emitting diodes (OLEDs) is reported. In order to embed the air bubbles in the flexible substrate, micropatterned substrates are fabricated by plasma treatment, and then coated with a planarization layer. During the planarization layer coating, air bubbles are trapped between the substrate and the planarization layer. The haze of the FHS can be controlled from 1.7% to 68.4% by changing the size of micropatterns by adjusting the plasma treatment time. The FHS shows average haze of 68.4%, average total transmittance of 90.3%, and extremely flat surface with average roughness (R _a) of 1.2 nm. Rigorous coupled‐wave analysis and finite‐difference time‐domain simulations are conducted to demonstrate that the air bubbles in the substrate can effectively extract photons that are trapped in the substrate. The FHS increases the power efficiency of OLEDs by 22% and further increases by 91% combined with an external extraction layer. Moreover, the FHS has excellent mechanical flexibility. No defect has been observed after 10 000 bending cycles at bending radius of 4 mm.     

Recent advances in controlled modification of the size and morphology of metal-organic frameworks

Advances in metal-organic frameworks (MOFs) resulted in significant contributions to diverse applications such as carbon capture, gas storage, heat transformation and separation along with emerging applications toward catalysis, medical imaging, drug delivery, and sensing. The unique in situ and ex situ structural features of MOFs can be tailored by conceptual selection of the organic (e.g., ligand) and inorganic (e.g., metal) components. Here, we provide a comprehensive review on the synthesis and characterization of MOFs, particularly with respect to controlling their size and morphology. A better understanding of the specific size and morphological parameters of MOFs will help initiate a new era for their real-world applications. Most importantly, this assessment will help develop novel synthesis methods for MOFs and their hybrid/porous materials counterparts with considerably improved properties in targeted applications.

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The use of coevolution and the artificial immune system for ensemble learning

This paper presents two new approaches for constructing an ensemble of neural networks (NN) using coevolution and the artificial immune system (AIS). These approaches are extensions of the CLONal Selection Algorithm for building ENSembles (CLONENS) algorithm. An explicit diversity promotion technique was added to CLONENS and a novel coevolutionary approach to build neural ensembles is introduced, whereby two populations representing the gates and the individual NN are coevolved. The former population is responsible for defining the ensemble size and selecting the members of the ensemble. This population is evolved using the differential evolution algorithm. The latter population supplies the best individuals for building the ensemble, which is evolved by AIS. Results show that it is possible to automatically define the ensemble size being also possible to find smaller ensembles with good generalization performance on the tested benchmark regression problems. More interestingly, the use of the diversity measure during the evolutionary process did not necessarily improve generalization. In this case, diverse ensembles may be found using only implicit diversity promotion techniques.     

Simulation based alternatives for overall process improvement at the cardiac catheterization lab

Cardiac catheterization is one of the critical procedures in patient care. It is pertinent for all process related issues in this department to be handled with due priority. This research is a cross-functional effort with a leading hospital that was in its planning stage to implement an overall process improvement at its cardiac catheterization lab department. It has been determined that significant process delays exist in this department. One of the identified key factors to process improvement was to reduce patient turnaround time. Process mapping was used to study the system and identify potential sources of delays in the system. A set of qualitative recommendations were put forward. These recommendations, include the reduction of wait time of outpatients and inpatients and the reduction of non-value-added times such as transfer time of patients, were evaluated using a discrete event simulation approach. The simulation study shows that the daily operating hours at the catheterization lab could be reduced, aiding to reallocate staff for discharging other duties, as the hospital may require.