Quantum dots in the biomedical world: A smart advanced nanocarrier for multiple venues application.

Quantum dots (QDs) are semiconducting nanoparticles having different optical and electrical properties when compared to larger particles. They exhibit photoluminescence when irradiated with ultraviolet light, which is due to the transition of an excited electron from the valence band to the conductance band followed by the return of the exciting electron back into the valence band. The size and material of QDs can affect their optical and other properties too. The QDs possess special attributes like high brightness, protection from photobleaching, photostability, color tunability, low toxicity, low production cost, a multiplexing limit, and a high surface-to-volume proportion, which make them a promising tool for biomedical applications. Here, in this study, we summarize the utilization of QDs in different applications including bioimaging, diagnostics, immunostaining, single-cell analysis, drug delivery, and protein detection. Moreover, we discuss the advantages and challenges of using QDs in biomedical applications when compared with other conventional tools.

Preclinical Models for Alzheimer's Disease: Past, Present, and Future Approaches.

A robust preclinical disease model is a primary requirement to understand the underlying mechanisms, signaling pathways, and drug screening for human diseases. Although various preclinical models are available for several diseases, clinical models for Alzheimer's disease (AD) remain underdeveloped and inaccurate. The pathophysiology of AD mainly includes the presence of amyloid plaques and neurofibrillary tangles (NFT). Furthermore, neuroinflammation and free radical generation also contribute to AD. Currently, there is a wide gap in scientific approaches to preventing AD progression. Most of the available drugs are limited to symptomatic relief and improve deteriorating cognitive functions. To mimic the pathogenesis of human AD, animal models like 3XTg-AD and 5XFAD are the primarily used mice models in AD therapeutics. Animal models for AD include intracerebroventricular-streptozotocin (ICV-STZ), amyloid beta-induced, colchicine-induced, etc., focusing on parameters such as cognitive decline and dementia. Unfortunately, the translational rate of the potential drug candidates in clinical trials is poor due to limitations in imitating human AD pathology in animal models. Therefore, the available preclinical models possess a gap in AD modeling. This paper presents an outline that critically assesses the applicability and limitations of the current approaches in disease modeling for AD. Also, we attempted to provide key suggestions for the best-fit model to evaluate potential therapies, which might improve therapy translation from preclinical studies to patients with AD.