Nano/Micro Biosensors for Biomedical Applications.

Advances in nano/micro technologies in recent years have significantly improved biosensors in terms of their viability for biomedical purposes, from diagnostic to therapeutic applications, allowing for effective early detection and personalized treatment modalities [...].

Biomedical Applications of CNT-Based Fibers.

Carbon nanotubes (CNTs) have been regarded as emerging materials in various applications. However, the range of biomedical applications is limited due to the aggregation and potential toxicity of powder-type CNTs. To overcome these issues, techniques to assemble them into various macroscopic structures, such as one-dimensional fibers, two-dimensional films, and three-dimensional aerogels, have been developed. Among them, carbon nanotube fiber (CNTF) is a one-dimensional aggregate of CNTs, which can be used to solve the potential toxicity problem of individual CNTs. Furthermore, since it has unique properties due to the one-dimensional nature of CNTs, CNTF has beneficial potential for biomedical applications. This review summarizes the biomedical applications using CNTF, such as the detection of biomolecules or signals for biosensors, strain sensors for wearable healthcare devices, and tissue engineering for regenerating human tissues. In addition, by considering the challenges and perspectives of CNTF for biomedical applications, the feasibility of CNTF in biomedical applications is discussed.

Cold-Responsive Hyaluronated Upconversion Nanoplatform for Transdermal Cryo-Photodynamic Cancer Therapy.

Cryotherapy leverages controlled freezing temperature interventions to engender a cascade of tumor-suppressing effects. However, its bottleneck lies in the standalone ineffectiveness. A promising strategy is using nanoparticle therapeutics to augment the efficacy of cryotherapy. Here, a cold-responsive nanoplatform composed of upconversion nanoparticles coated with silica - chlorin e6 - hyaluronic acid (UCNPs@SiO2-Ce6-HA) is designed. This nanoplatform is employed to integrate cryotherapy with photodynamic therapy (PDT) in order to improve skin cancer treatment efficacy in a synergistic manner. The cryotherapy appeared to enhance the upconversion brightness by suppressing the thermal quenching. The low-temperature treatment afforded a 2.45-fold enhancement in the luminescence of UCNPs and a 3.15-fold increase in the photodynamic efficacy of UCNPs@SiO2-Ce6-HA nanoplatforms. Ex vivo tests with porcine skins and the subsequent validation in mouse tumor tissues revealed the effective HA-mediated transdermal delivery of designed nanoplatforms to deep tumor tissues. After transdermal delivery, in vivo photodynamic therapy using the UCNPs@SiO2-Ce6-HA nanoplatforms resulted in the optimized efficacy of 79% in combination with cryotherapy. These findings underscore the Cryo-PDT as a truly promising integrated treatment paradigm and warrant further exploring the synergistic interplay between cryotherapy and PDT with bright upconversion to unlock their full potential in cancer therapy.

Ionic Liquid-Based Extraction of Fulvic-like Substances from Wood Sawdust: Reproducing Unique Biological Activities of Fulvic Acids Using Renewable Natural Sources.

Fulvic acids (FAs) have been commercially used in cosmetics and agronomy due to their unique biological activities, such as plant stimulation and anti-inflammatory effects. However, the extraction sources of FAs, such as peat, are currently limited. Consequently, new extraction methods using renewable resources need to be developed, while reproducing the biological functions. Here, ionic liquids (ILs) effectively extracted fulvic-like substances (FLSs) from wood sawdust. The overall molecular weight distributions of FLSs were similar to those of commercial FAs, and key organic groups (e.g., aromatic, phenolic, and methoxy groups) were also found to be shared between commercial FAs and FLSs. Detailed compositional analysis revealed by high-resolution mass spectrometry showed that the extracts contain both lignin-like and lipid-like molecules, while commercial FAs are biased toward lignin-like and carbohydrate-like molecules. FLSs generally showed better and similar performance in radical scavenging activity against ABTS+· and H2O2. Fibroblast proliferation and lettuce growth enhancements were also observed with the extract containing 1-ethyl-3-methylimidazolium acetate and triethylammonium hydrogen sulfate, respectively, which performed better than commercial FAs. Immunofluorescence staining of in vitro human follicle dermal papilla cells supports that coexpression of hair growth-related proteins can be accelerated with FLSs, and this effect was further evidenced by in vivo mouse model experiments. Finally, the reusability of ILs in the extraction process was confirmed by analyzing the structural features of FLSs from each recycling. Our findings indicate that ILs are useful for obtaining biologically functional fulvic analogs from renewable plant sources.

Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system.

Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated needle-based surface-enhanced Raman scattering (SERS) sensor, integrated with endoscopy, for direct mucus sampling and label-free detection of CRC. The thin and flexible stainless-steel needle is coated with polymerized dopamine, which serves as an adhesive layer and simultaneously initiates the nucleation of gold nanoparticle (AuNP) seeds on the needle surface. The AuNP seeds are further grown through a surface-directed reduction using Au ions-hydroxylamine hydrochloride solution, resulting in the formation of dense AuNHs. The formation mechanism of AuNHs and the layered structure of the plasmonic needle-based SERS (PNS) sensor are thoroughly analyzed. Furthermore, a strong field enhancement of the PNS sensor is observed, amplified around the edges of the polyhedral shapes and at nanogap sites between AuNHs. The feasibility of the PNS sensor combined with endoscopy system is further investigated using mouse models for direct colonic mucus sampling and verifying noninvasive label-free classification of CRC from normal controls. A logistic regression-based machine learning method is employed and successfully differentiates CRC and normal mice, achieving 100% sensitivity, 93.33% specificity, and 96.67% accuracy. Moreover, Raman profiling of metabolites and their correlations with Raman signals of mucus samples are analyzed using the Pearson correlation coefficient, offering insights for identifying potential cancer biomarkers. The developed PNS-assisted endoscopy technology is expected to advance the early screening and diagnosis approach of CRC in the future.