Drug delivery to central nervous system (CNS) diseases is very challenging since the presence of the innate blood-brain barrier (BBB) and the blood-cerebrospinal fluid barrier that impede drug delivery. Among new strategies to overcome these limitations and successfully deliver drugs to the CNS, nanotechnology-based drug delivery platform, offers potential therapeutic approach for the treatment of some common neurological disorders like Alzheimer's disease, frontotemporal dementia, amyotrophic lateral sclerosis, Parkinson's disease, Huntington's disease. This review aimed to highlight advances in research on the development of nano-based therapeutics for their implications in therapy of CNS disorders. The challenges during clinical translation of nanomedicine from bench to bed side is also discussed.

Silver nanoparticles have attracted great interests widely in medicine due to its great characteristics of antibacterial activity. In this research, the antibacterial activity and biocompatibility of a topical gel synthesized from polyvinyl alcohol, chitosan, and silver nanoparticles were studied. Hydrogels with different concentrations of silver nanoparticles (15 ppm, 30 ppm, and 60 ppm) were evaluated to compare their antibacterial activity, nanoparticles’ sizes, and in vivo behaviors. The resulted silver nanoparticles in the hydrogel were characterized by TEM showing the nanoparticles’ sizes less than 22 nm. The in vitro results prove that the antibacterial effects of all of the samples are satisfied. However, the in vivo results demonstrate the significant difference among different hydrogels in wound healing, where hydrogel with 30 ppm shows the best healing rate.

Green electrospinning has attracted great interest since non-toxic solvents were shown to be applicable in the fabrication of fibrous materials while ensuring health safety and environmental protection. Less harmful reagents such as acetone (AC) and acetic acid (AA) have been employed in this field in recent years. However, research in this area is still rare, yielding only preliminary results. In this study, two different types of solvents (pure AC and an AA/AC mixture) were used to fabricate electrospun polycaprolactone (PCL) membranes. Sample morphology, wettability, tensile strength, and chemical composition were compared between two types of membranes. Cell–scaffold interaction was also examined by cell adhesion and proliferation assays. The results demonstrate that the two types of solvents had significant effects on membrane morphology, physical strength, and cell adherence behaviors, which should be considered for different application purposes.

The rapid growth of point-of-care polysomnographic alternatives has necessitated standardized evaluation and validation frameworks. The current average across participant validation methods may overestimate the agreement between wearable sleep tracker devices and polysomnography (PSG) systems because of the high base rate of sleep during the night and the interindividual difference across the sampling population. This study proposes an evaluation framework to assess the aggregating differences of the sleep architecture features and the chronologically epoch-by-epoch mismatch of the wearable sleep tracker devices and the PSG ground truth. An AASM-based sleep stage categorizing method was proposed to standardize the sleep stages scored by different types of wearable trackers. Sleep features and sleep stage architecture were extracted from the PSG and the wearable device’s hypnograms. Therefrom, a localized quantifier index was developed to characterize the local mismatch of sleep scoring. We evaluated different commonly used wearable sleep tracking devices with the data collected from 22 different subjects over 30 nights of 8-h sleeping. The proposed localization quantifiers can characterize the chronologically localized mismatches over the sleeping time. The outperformance of the proposed method over existing evaluation methods was reported. The proposed evaluation method can be utilized for the improvement of the sensor design and scoring algorithm.

Tebuconazole is a triazole fungicide used in agriculture to treat pathogenic fungi. It is listed as a possible carcinogen and it shows a potential risk for the environment at very low concentration. Therefore, the detection and monitoring of tebuconazole in food and environment play an important role. The current methods for the analysis of tebuconazole employ gas-liquid chromatography (GLC) and high-performance liquid chromatography (HPLC) after sample extraction with organic solvents and column cleaning. Besides the advantages of these methods such as efficiency, repeatability, and accuracy, they are still time-consuming and costly. Herein, we report a simple, sensitive platform for the fast detection of pesticides with a low cost. The detection technique exploits a pesticide-specific DNA aptamer as the bioreceptor of an optical biosensor. Instead of trying to capture the pesticide on the sensor surface, our method allows the DNA aptamers, which are adsorbed on the nanoparticle’s surface, to detach from the nanoparticles when interacting with the pesticide. This leads to the pesticide-induced aggregation and the change of the absorption spectrum of metallic nanoparticles upon high-salt concentrations, which can be monitored with unaided eye or absorbance measurement. Using tebuconazole as a model analyte for detection of pesticide, the designed aptasensor showed a high sensitivity and selectivity with a detection limit of ~10 nM and reaction time within ~20 min. In the case of tebuconazole detection in spiked rice samples, the average recoveries were in the range of 89.90–110.86% with the relative standard deviations (RSD) of 3.11–4.32%. These results indicate that our sensing platform can be exploited for the rapid detection of pesticides in real samples.