Development of a Low-Molecular-Weight Aβ42 Detection System Using a Enzyme-Linked Peptide Assay

Strategies for measuring concentrations and forms of amyloid-β peptides

Alzheimer's disease (AD) is affecting more and more people worldwide without the effective treatment, while the existed pathological mechanism has been confirmed barely useful in the treatment. Amyloid-β peptide (Aβ), a main component of senile plaque, is regarded as the most promising target in AD treatment. Aβ clearance from AD brain seems to be a reliably therapeutic strategy, as the two exited drugs, GV-971 and aducanumab, are both developed based on it. However, doubt still exists. To exhaustive expound on the pathological mechanism of Aβ, rigorous analyses on the concentrations and aggregation forms are essential. Thus, it is attracting broad attention these years. However, most of the sensors have not been used in pathological studies, as the lack of the bridge between analytical chemist and pathologists. In this review, we made a brief introduce on Aβ-related pathological mechanism included in β-amyloid hypothesis to elucidate the detection conditions of sensor methods. Furthermore, a summary of the sensor methods was made, which were based on Aβ concentrations and form detections that have been developed in the past 10 years. As the greatest number of the sensors were built on fluorescent spectroscopy, electrochemistry, and Roman spectroscopy, detailed elucidation on them was made. Notably, the aggregation process is another important factor in revealing the progress of AD and developing the treatment methods, so the sensors on monitoring Aβ aggregation processes were also summarized.

Chiral nanomaterial-based approaches for diagnosis and treatment of protein-aggregated neurodiseases: current status and future opportunities

Protein misfolding and its aggregation, known as amyloid aggregates (Aβ), are some of the major causes of more than 20 diseases such as Parkinson's disease, Alzheimer's disease, and type 2 diabetes. The process of Aβ formation involves an energy-driven oligomerization of Aβ monomers, leading to polymerization and eventual aggregation into fibrils. Aβ fibrils exhibit multilevel chirality arising from its amino acid residues and the arrangement of folded polypeptide chains; thus, a chirality-driven approach can be utilized for the detection and inhibition of Aβ fibrils. In this regard, chiral nanomaterials have recently opened new possibilities for various biomedical applications owing to their stereoselective interaction with biological systems. Leveraging this chirality-driven approach with chiral nanomaterials against protein-aggregated diseases could yield promising results, particularly in the early detection of Aβ forms and the inhibition of Aβ aggregate formation via specific and strong "chiral-chiral interaction." Despite the advantages, the development of advanced theranostic systems using chiral nanomaterials against protein-aggregated diseases has received limited attention so far because of considerably limited formulations for chiral nanomaterials and lack of information of their chiroptical behavior. This review aims to present the current status of chiral nanomaterials explored for detecting and inhibiting Aβ forms. This review covers the origin of chirality in amyloid fibrils and nanomaterials and different chiral detection methods; furthermore, different chiral nanosystems such as chiral plasmonic nanomaterials, chiral carbon-based nanomaterials, and chiral nanosurfaces, which have been used so far for different therapeutic applications against protein-aggregated diseases, are discussed in detail. The findings from this review may pave the way for the development of novel approaches using chiral nanomaterials to combat diseases resulting from protein misfolding and can further be extended to other disease forms.

Aggregation-Induced Electrochemiluminescence Based on a Zinc-Based Metal-Organic Framework and a Double Quencher Au@UiO-66-NH2 for the Sensitive Detection of Amyloid β 42 via Resonance Energy Transfer

A novel sandwich electrochemiluminescence (ECL) biosensor based on aggregation-induced electrochemiluminescence resonance energy transfer (AIECL-RET) was designed for the sensitive detection of amyloid β42 (Aβ42). The synthesized silver nanoparticle-functionalized zinc metal-organic framework (Ag@ZnPTC) and gold nanoparticle-functionalized zirconium organic framework (Au@UiO-66-NH₂) were used as the ECL donor and acceptor, respectively. AgNPs were generated in situ on the surface of ZnPTC, which further improved the ECL intensity and the loading of antibody 1 (Ab1). Under the optimized experimental conditions, the linear detection range of Aβ42 concentration was 10 fg/mL to 100 ng/mL, and the detection limit was 2.4 fg/mL (S/N = 3). The recoveries of Aβ42 were 99.5-104%. The method has good stability, repeatability, and specificity. Ag@ZnPTC/Au@UiO-66-NH₂ provides an assay for the sensitive detection of disease biomarkers.

Computer-Assisted Design of Peptide-Based Radiotracers

In medical imaging, techniques such as magnetic resonance imaging, contrast-enhanced computerized tomography, positron emission tomography (PET), and single-photon emission computed tomography (SPECT) are extensively available and routinely used for disease diagnosis. PET probes with peptide-based targeting are typically composed of small peptides especially developed to have high affinity and specificity for a range of cellular and tissue targets. These probes’ key benefits include being less expensive than traditional antibody-based PET tracers and having an effective chemical modification process that allows them to be radiolabeled with almost any radionuclide, making them highly appealing for clinical usage. Currently, as with every pharmaceutical design, the use of in silico strategies is steadily growing in this field, even though it is not part of the standard toolkit used during radiopharmaceutical design. This review describes the recent applications of computational design approaches in the design of novel peptide-based radiopharmaceuticals.

Validating In Silico and In Vitro Patient-Specific Structural and Flow Models with Transcatheter Bicuspid Aortic Valve Replacement Procedure

INTRODUCTION

Bicuspid aortic valve (BAV) is the most common congenital cardiac malformation, which had been treated off-label by transcatheter aortic valve replacement (TAVR) procedure for several years, until its recent approval by the Food and Drug Administration (FDA) and Conformité Européenne (CE) to treat BAVs. Post-TAVR complications tend to get exacerbated in BAV patients due to their inherent aortic root pathologies. Globally, due to the paucity of randomized clinical trials, clinicians still favor surgical AVR as the primary treatment option for BAV patients. While this warrants longer term studies of TAVR outcomes in BAV patient cohorts, in vitro experiments and in silico computational modeling can be used to guide the surgical community in assessing the feasibility of TAVR in BAV patients. Our goal is to combine these techniques in order to create a modeling framework for optimizing pre-procedural planning and minimize post-procedural complications.

MATERIALS AND METHODS

Patient-specific in silico models and 3D printed replicas of 3 BAV patients with different degrees of post-TAVR paravalvular leakage (PVL) were created. Patient-specific TAVR device deployment was modeled in silico and in vitro-following the clinical procedures performed in these patients. Computational fluid dynamics simulations and in vitro flow studies were performed in order to obtain the degrees of PVL in these models.

RESULTS

PVL degree and locations were consistent with the clinical data. Cross-validation comparing the stent deformation and the flow parameters between the in silico and the in vitro models demonstrated good agreement.

CONCLUSION

The current framework illustrates the potential of using simulations and 3D printed models for pre-TAVR planning and assessing post-TAVR complications in BAV patients.