Essential Oils as Antimicrobials against : Experimental and Literature Data to Definite Predictive Quantitative Composition-Activity Relationship Models Using Machine Learning Algorithms.

Essential oils (EOs) exhibit a broad spectrum of biological activities; however, their clinical application is hindered by challenges, such as variability in chemical composition and chemical/physical instability. A critical limitation is the lack of chemical consistency across EO samples, which impedes standardization. Despite this, evidence suggests that EOs with differing chemical profiles often display similar (micro)biological activities, raising the possibility of standardizing EOs based on their biological effects rather than their chemical composition.

Chlorotoxin-functionalized mesoporous silica nanoparticles for pH-responsive paclitaxel delivery to Glioblastoma multiforme.

Glioblastoma multiforme (GBM) is a highly aggressive brain cancer associated with poor survival rates. We developed novel mesoporous silica nanoparticles (MSNs)-based nanocarriers for pH-responsive delivery of a therapeutic drug Paclitaxel (PTX) to GBM tumor cells. The pores of MSNs are loaded with PTX, which is retained by β-cyclodextrin (CD) moieties covalently linked to the pore entrances through a hydrazone linkage, which is cleavable in weakly acidic environment.

Single neuromorphic memristor closely emulates multiple synaptic mechanisms for energy efficient neural networks.

Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex functions such as short-term memory, short-term plasticity, and meta-plasticity - all collocated within each synapse. Here, we demonstrate memristive nano-devices based on SrTiO that inherently emulate all these synaptic functions. These memristors operate in a non-filamentary, low conductance regime, which enables stable and energy efficient operation.

Biosensors for Cancer Biomarkers Based on Mesoporous Silica Nanoparticles.

Mesoporous silica nanoparticles (MSNs) exhibit highly beneficial characteristics for devising efficient biosensors for different analytes. Their unique properties, such as capabilities for stable covalent binding to recognition groups (e.g.