Lectin-Functionalized Chitosan Nanoparticle-Based Biosensor for Point-of-Care Detection of Bacterial Infections

New bioelectrode based on graphene quantum dots-polypyrrole film and Concanavalin A for pathogenic microorganism detection

Infections caused by microorganisms are a public health problem worldwide. New biodetection systems are essential to diagnose with accuracy resulting in more effective treatment. In this work, we propose a ConA-conjugated graphene quantum dots and polypyrrole film-based biosensor for label-free detection of Candida albicans, Candida glabrata, Candida tropicalis, E. coli, B. subitilis, and S. aureus. We modified polypyrrole and graphene quantum dots (PPY-QDGs) with Concanavalin A (Con A) lectin. ConA is a glucose/mannose-specific lectin. The results showed that ConA lectin has the highest binding affinity for C. tropicalis and S. subtilis. PPY-GQDs-ConA binding profile revealed differential response for Candida spp (C. tropicalis > C. albicans > C. glabrata) and bacterial (B. subtilis > S. aureus > E. coli). The limits of detection (LOD) obtained were 1.42 CFU/mL for C. albicans, and 3.72 CFU/mL for C. glabrata. C. tropicalis yielded a LOD of 0.18 CFU/mL. The respective LODs for the evaluated bacteria were 0.39 CFU/mL for S. aureus, 0.72 CFU/mL for S. subtilis, and 2.63 CFU/mL for E. coli. The differential response obtained for the sensor can be attributed to the heterogeneous distribution of carbohydrates on the microorganism's surfaces. The proposed system based on a flexible substrate is effective for microbiological diagnosis.

Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications

BACKGROUND

The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification. In particular, Raman spectroscopy (RS) is becoming an attractive method for rapid and accurate detection of bacterial pathogens in recent years, among which the newly developed surface-enhanced Raman spectroscopy (SERS) shows the most promising potential.

AIM OF REVIEW

Recent advances in pathogen detection and diagnosis of bacterial infections were discussed with focuses on the development of the SERS approaches and its applications in complex clinical settings.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The current review describes bacterial classification using surface enhanced Raman spectroscopy (SERS) for developing a rapid and more accurate method for the identification of bacterial pathogens in clinical diagnosis. The initial part of this review gives a brief overview of the mechanism of SERS technology and development of the SERS approach to detect bacterial pathogens in complex samples. The development of the label-based and label-free SERS strategies and several novel SERS-compatible technologies in clinical applications, as well as the analytical procedures and examples of chemometric methods for SERS, are introduced. The computational challenges of pre-processing spectra and the highlights of the limitations and perspectives of the SERS technique are also discussed.Taken together, this systematic review provides an overall summary of the SERS technique and its application potential for direct bacterial diagnosis in clinical samples such as blood, urine and sputum, etc.

An overview of in vitro 3D models of the blood-brain barrier as a tool to predict the in vivo permeability of nanomedicines

The blood-brain barrier (BBB) prevents efficient drug delivery to the central nervous system. As a result, brain diseases remain one of the greatest unmet medical needs. Understanding the tridimensional structure of the BBB helps gain insight into the pathology of the BBB and contributes to the development of novel therapies for brain diseases. Therefore, 3D models with an ever-growing sophisticated complexity are being developed to closely mimic the human neurovascular unit. Among these 3D models, hydrogel-, spheroid- and organoid-based static BBB models have been developed, and so have microfluidic-based BBB-on-a-chip models. The different 3D preclinical models of the BBB, both in health and disease, are here reviewed, from their development to their application for permeability testing of nanomedicines across the BBB, discussing the advantages and disadvantages of each model. The validation with data from in vivo preclinical data is also discussed in those cases where provided.

Recent progressions in biomedical and pharmaceutical applications of chitosan nanoparticles: A comprehensive review

Nowadays, the most common approaches in the prognosis, diagnosis, and treatment of diseases are along with undeniable limitations. Thus, the ever-increasing need for using biocompatible natural materials and novel practical modalities is required. Applying biomaterials, such as chitosan nanoparticles (CS NPs: FDA-approved long-chain polymer of N-acetyl-glucosamine and D-glucosamine for some pharmaceutical applications), can serve as an appropriate alternative to overcome these limitations. Recently, the biomedical applications of CS NPs have extensively been investigated. These NPs and their derivatives can not only prepare through different physical and chemical approaches but also modify with various molecules and bioactive materials. The potential properties of CS NPs, such as biocompatibility, biodegradability, serum stability, solubility, non-immunogenicity, anti-inflammatory properties, appropriate pharmacokinetics and pharmacodynamics, and so forth, have made them excellent candidates for biomedical applications. Therefore, CS NPs have efficiently applied for various biomedical applications, like regenerative medicine and tissue engineering, biosensors for the detection of microorganisms, and drug delivery systems (DDS) for the suppression of diseases. These NPs possess a high level of biosafety. In summary, CS NPs have the potential ability for biomedical and clinical applications, and it would be remarkably beneficial to develop new generations of CS-based material for the future of medicine.