Efficient Capture and T2 Magnetic Resonance Assay of Candida albicans with Inorganic Nanoparticles: Role of Nanoparticle Surface Charge and Fungal Cell Wall

Synergistic in vitro activity and mechanism of KBN lotion and miconazole nitrate against drug-resistant Candida albicans biofilms

Background

In the face of increasing antifungal resistance among Candida albicans biofilms, this study explores the efficacy of a combined treatment using Kangbainian lotion (KBN) and miconazole nitrate (MN) to address this challenge.

Methods

Using UPLC-Q-TOF/MS Analysis for Identification of Active Compounds in KBN Lotion; FICI for synergy evaluation, XTT and ROS assays for biofilm viability and oxidative stress, fluorescence and confocal laser scanning microscopy (CLSM) for structural and viability analysis, and real-time fluorescence for gene expression.

Conclusion

Our study indicates that the combined application of KBN and MN somewhat impacts the structural integrity of Candida albicans biofilms and affects the expression of several key genes involved in biofilm formation, including ALS1, ALS3, HWP1, HSP90, and CSH1. These preliminary findings suggest that there may be a synergistic effect between KBN and MN, potentially influencing not only the structural aspects of fungal biofilms but also involving the modulation of genetic pathways during their formation.

Surface-Charge Tuned Polymeric Nanoemulsions for Carvacrol Delivery in Interkingdom Biofilms

Biofilms, intricate microbial communities entrenched in extracellular polymeric substance (EPS) matrices, pose formidable challenges in infectious disease treatment, especially in the context of interkingdom biofilms prevalent in the oral environment. This study investigates the potential of carvacrol-loaded biodegradable nanoemulsions (NEs) with systematically varied surface charges─cationic guanidinium (GMT-NE) and anionic carboxylate (CMT-NE). Zeta potentials of +25 mV (GMT-NE) and -33 mV (CMT-NE) underscore successful nanoemulsion fabrication (∼250 nm). Fluorescent labeling and dynamic tracking across three dimensions expose GMT-NE's superior diffusion into oral biofilms, yielding a robust antimicrobial effect with 99.99% killing for both streptococcal and Candida species and marked reductions in bacterial cell viability compared to CMT-NE (∼4-log reduction). Oral mucosa tissue cultures affirm the biocompatibility of both NEs with no morphological or structural changes, showcasing their potential for combating intractable biofilm infections in oral environment. This study advances our understanding of NE surface charges and their interactions within interkingdom biofilms, providing insights crucial for addressing complex infections involving bacteria and fungi in the demanding oral context.

Label-free surface enhanced Raman scattering spectroscopy for discrimination and detection of dominant apple spoilage fungus

Fungal infection is one of the main causes of apple corruption. The main dominant spoilage fungi in causing apple spoilage are storage mainly include Penicillium Paecilomyces paecilomyces (P. paecilomyces), penicillium chrysanthemum (P. chrysogenum), expanded Penicillium expansum (P. expansum), Aspergillus niger (Asp. niger) and Alternaria. In this study, surface-enhanced Raman spectroscopy (SERS) based on gold nanorod (AuNRs) substrate method was developed to collect and examine the Raman fingerprints of dominant apple spoilage fungus spores. Standard normal variable (SNV) was used to pretreat the obtained spectra to improve signal-to-noise ratio. Principal component analysis (PCA) was applied to extract useful spectral information. Linear discriminant analysis (LDA) and non-linear pattern recognition methods including K nearest neighbor (KNN), Support vector machine (SVM) and back propagation artificial neural networks (BPANN) were used to identify fungal species. As the comparison of modeling results shown, the BPANN model established based on the characteristic spectra variables have achieved the satisfactory result with discrimination accuracy of 98.23%; while the PCA-LDA model built using principal component variables achieved the best distinguish result with discrimination accuracy of 98.31%. It was concluded that SERS has the potential to be an inexpensive, rapid and effective method to detect and identify fungal species.

Bioelectricity, Its Fundamentals, Characterization Methodology, and Applications in Nano-Bioprobing and Cancer Diagnosis

Bioelectricity is an essential characteristic of a biological system that has played an important role in medical diagnosis particularly in cancer liquid biopsy. However, its biophysical origin and measurements have presented great challenges in experimental methodologies. For instance, in dynamic cell processes, bioelectricity cannot be accurately determined as a static electrical potential via electrophoresis. Cancer cells fundamentally differ from normal cells by having a much higher rate of glycolysis resulting in net negative charges on cell surfaces. The most recent investigations on cancer cell surface charge that is the direct bio-electrical manifestation of the "Warburg Effect," which can be directly monitored by specially designed nanoprobes, has been provided. The most up-to-date research results from charge-mediated cell targeting are reviewed. Correlations between the cell surface charge and cancer cell metabolism are established based on cell/probe electrostatic interactions. Bioelectricity is utilized not only as an analyte for investigation of the metabolic state of the cancer cells, but also applied in electrostatically and magnetically capturing of the circulating tumor cells from whole blood. Also reviewed is on the isolation of Candida albicans via bioelectricity-driven nanoparticle binding on fungus with surface charges.