Ionophore-based nanospheres enable selective and sensitive fluorescence detection of copper ions.

A novel ionophore-based fluorescent nanosensor has been successfully fabricated for the sensitive and selective detection of Cu2+ ions. The nanosensor was constructed through self-assembly of amphiphilic block copolymers, incorporating elesclomol as a Cu2+ ionophore and long-chain dialkylcarbocyanines (DiD) as a fluorescent dye. This design exhibits an "ON/OFF" fluorescence response, where Cu2⁺ ions are selectively sequestered within the nanosensors, resulting in fluorescence quenching of DiD. This strategy enables rapid and highly selective Cu2⁺ sensing with remarkable fluorescence quenching efficiency (up to 93.5 %) and an exceptionally low detection limit of 28.6 nM. The linear detection range extends over two orders of magnitude (0.05-10 µM). Furthermore, the feasibility of this nanosensor for practical applications was confirmed through successful determination of Cu2+ in real water and beer samples, with excellent recovery rates. This nanosensor offers advantages of simplicity, rapidity, and cost-effectiveness, holding significant potential for sensitive and selective Cu2+ detection in various biological and environmental samples.

Influence of endothelial nitric oxide synthase haplotypes on nitric oxide and peroxynitrite productions.

The impact of four clinically significant genetic variants of endothelial nitric oxide synthase (eNOS) polymorphisms on the concentrations of nitric oxide [NO] and peroxynitrite [ONOO-] has been given scant consideration. This study utilized a [NO]/[ONOO-] ratio to determine the extent of endothelial dysfunction caused by these variations in the eNOS gene. The single nucleotide polymorphisms (T-786C, C-665T, and Glu298Asp) and a variable number of tandem repeats (intron 4 a/b/c) were genotyped in human umbilical vein endothelial cells (HUVEC), using sanger sequencing and DNA electrophoresis, respectively. Nanosensors were used to determine the maximal [NO] and [ONOO-], while traditional and low-temperature SDS-PAGE were used to evaluate the expression of eNOS and the eNOS dimer-to-monomer ratio, respectively. The study results indicate that the eNOS haplotype H3 (G T/C C 4a/c allele) may have a protective effect against cardiovascular disease (CVD) with the [NO]/[ONOO-] ratio higher than 2. However, the eNOS haplotypes H2 (G T/C C 4a/b) and H5 (T T/C C 4b) increase the susceptibility to CVD with [NO]/[ONOO-] ratio lower than 1. The results suggest that certain eNOS genetic variants may influence susceptibility to cardiovascular disease (CVD) while other variants may have a protective effect.

WS2 Nanosheet-Based Ultrascaled Field-Effect Transistor for Hydrogen Gas Sensing: Addressing the Sensitivity-Downscaling Trade-Off.

In this paper, we propose an ultrascaled WS2 field-effect transistor equipped with a Pd/Pt sensitive gate for high-performance and low-power hydrogen gas sensing applications. The proposed nanosensor is simulated by self-consistently solving a quantum transport equation with electrostatics at the ballistic limit. The gas sensing principle is based on the gas-induced change in the metal gate work function. The hydrogen gas nanosensor leverages the high sensitivity of two-dimensional WS2 to its sur-rounding electrostatic environment. The computational investigation encompasses the nanosensor's behavior in terms of potential profile, charge density, current spectrum, local density of states (LDOS), transfer characteristics, and sensitivity. Additionally, the downscaling-sensitivity trade-off is analyzed by considering the impact of drain-to-source voltage and the electrostatics parameters on subthreshold performance. The simulation results indicate that the downscaling-sensitivity trade-off can be optimized through enhancements in electrostatics, such as utilizing high-k dielectrics and reducing oxide thickness, as well as applying a low drain-to-source voltage, which also contributes to improved energy efficiency. The proposed nanodevice meets the prerequisites for cutting-edge gas nanosensors, offering high sensing performance, improved scaling capability, low power consumption, and complementary metal-oxide-semiconductor compatibility, making it a compelling candidate for the next generation of ultrascaled FET-based gas nanosensors.

Quantum Dot-Based Nanosensors for In Vitro Detection of Mycobacterium tuberculosis.

Despite the existing effective treatment methods, tuberculosis (TB) is the second most deadly infectious disease, its carriers in the latent and active phases accounting for more than 20% of the world population. An effective method for controlling TB and reducing TB mortality is regular population screening aimed at diagnosing the latent form of TB and taking preventive and curative measures. Numerous methods allow diagnosing TB by directly detecting Mycobacterium tuberculosis (M.tb) biomarkers, including M.tb DNA, proteins, and specific metabolites or antibodies produced by the host immune system in response to M.tb. PCR, ELISA, immunofluorescence and immunochemical analyses, flow cytometry, and other methods allow the detection of M.tb biomarkers or the host immune response to M.tb by recording the optical signal from fluorescent or colorimetric dyes that are components of the diagnostic systems. Current research in biosensors is aimed at increasing the sensitivity of detection, a promising approach being the use of fluorescent quantum dots as brighter and more photostable optical tags. Here, we review current methods for the detection of M.tb biomarkers using quantum dot-based nanosensors and summarize data on the M.tb biomarkers whose detection can be made considerably more sensitive by using these sensors.

Profiling Breast Tumor Heterogeneity and Identifying Breast Cancer Subtypes Through Tumor-Associated Immune Cell Signatures and Immuno Nano Sensors.

Breast cancer is a complex and heterogeneous disease with varying cellular, genetic, epigenetic, and molecular expressions. The detection of intratumor heterogeneity in breast cancer poses significant challenges due to its complex multifaceted characteristics, yet its identification is crucial for guiding effective treatment decisions and understanding the disease progression. Currently, there exists no method capable of capturing the full extent of breast tumor heterogeneity. In this study, the aim is to identify and characterize metabolic heterogeneity in breast tumors using immune cells and an ultrafast laser-fabricated Immuno Nano Sensor. Combining spectral markers from both Natural Killer (NK) and T cells, a machine-learning approach is implemented to distinguish cancer from healthy samples, identify primary versus metastatic tumors, and determine estrogen receptor (ER)/progesterone receptor (PR) status at the single-cell level. The platform successfully distinguished heterogeneous breast cancer samples from healthy individuals, achieving 97.8% sensitivity and 92.2% specificity, and accurately identified primary tumors from metastatic tumors. Characteristic spectral signatures allow for discrimination between ER/PR-positive and negative tumors with 97.5% sensitivity. This study demonstrates the potential of immune cell-based metabolic profiling in providing a comprehensive assessment of breast tumor heterogeneity and paving the way for minimally invasive liquid biopsy approaches in breast cancer diagnosis and management.

Noninvasive Injectable Optical Nanosensor-Hydrogel Hybrids Detect Doxorubicin in Living Mice.

While the tissue-transparent fluorescence of single-walled carbon nanotubes (SWCNTs) imparts substantial potential for use in non-invasive biosensors, development of non-invasive systems is yet to be realized. Here, we investigated the functionality of a SWCNT-based nanosensor in several injectable SWCNT-hydrogel systems, ultimately finding SWCNT encapsulation in a sulfonated methylcellulose hydrogel optimal for detection of ions, small molecules, and proteins. We found that the hydrogel system and nanosensor signal were stable for several weeks in live mice. We then found that this system successfully detects local injections of the chemotherapeutic agent doxorubicin in mice. We anticipate future studies to adapt this device for detection of other analytes in animals and, ultimately, patients.

Tailoring molecularly imprinted polymer on titanium-multiwalled carbon nanotube functionalized gold electrode for enhanced chlorophyll determination in microalgae health assessment.

A unique method for determining chlorophyll content in microalgae is devised employing a gold interdigitated electrode (G-IDE) with a 10-µm gap, augmented by a nano-molecularly imprinted polymer (nano-MIP) and a titanium dioxide/multiwalled carbon nanotube (TiO2/MWCNT) nanocomposite. The nano-MIP, produced using chlorophyll template voids, successfully trapped chlorophyll, while the TiO2/MWCNT nanocomposite, synthesized by the sol-gel technique, exhibited a consistent distribution and anatase crystalline structure. The rebinding of procured chlorophyll powder, which was used as a template for nano-MIP synthesis, was identified with a high determination coefficient (R2 = 0.9857). By combining the TiO2/MWCNT nanocomposite with nano-MIP, the G-IDE sensing method achieved a slightly better R2 value of 0.9892 for detecting chlorophyll in microalgae. The presented G-IDE sensor showed a significant threefold enhancement in chlorophyll detection compared with commercially available chlorophyll powder. It had a detection limit of 0.917 mL (v/v) and a linear range that spanned from 10-6 to 1 mL. The effectiveness of the sensor in detecting chlorophyll in microalgae was confirmed through validation of its repeatability and reusability.

Modeling and Vibration Analysis of Carbon Nanotubes as Nanomechanical Resonators for Force Sensing.

Carbon nanotubes (CNTs) have attracted considerable attention as nanomechanical resonators because of their exceptional mechanical properties and nanoscale dimensions. In this study, a novel CNT-based probe is proposed as an efficient nanoforce sensing nanomaterial that detects external pressure. The CNT probe was designed to be fixed by clamping tunable outer CNTs. By using the mobile-supported outer CNT, the position of the partially clamped outer CNT can be controllably shifted, effectively tuning its resonant frequency. This study comprehensively investigates the modeling and vibration analysis of gigahertz frequencies with loaded CNTs used in sensing applications. The vibration frequency of a partially clamped CNT probe under axial loading was modeled using continuum mechanics, considering various parameters such as the clamping location, length, and boundary conditions. In addition, the interaction between external forces and CNT resonators was investigated to evaluate their sensitivity for force sensing. Our results provide valuable insights into the design and optimization of CNT-based nanomechanical resonators for high-performance force sensing applications.

An Internally Attached Aptameric Graphene Nanosensor for Sensitive Vasopressin Measurement in Critical Patient Monitoring.

This paper presents an aptameric graphene nanosensor for rapid and sensitive measurement of arginine vasopressin (AVP) toward continuous monitoring of critical care patients. The nanosensor is a field-effect transistor (FET) with monolayer graphene as the conducting channel and is functionalized with a new custom-designed aptamer for specific AVP recognition. Binding between the aptamer and AVP induces a change in the carrier density in the graphene and resulting in measurable changes in FET characteristics for determination of the AVP concentration. The aptamer, based on the natural enantiomer D-deoxyribose, possess optimized kinetic binding properties and is attached at an internal position to the graphene for enhanced sensitivity to low concentrations of AVP. Experimental results show that this aptameric graphene nanosensor is highly sensitive (with a limit of detection of 0.3 pM and a resolution of 0.1 pM) to AVP, and rapidly responsive (within 90 s) to both increasing and decreasing AVP concentration changes. The device is also reversable (within 4%), repeatable (within 4%) and reproducible (within 5%) in AVP measurements.

Spatial Measurement and Inhibition of Calpain Activity in Traumatic Brain Injury with an Activity-Based Nanotheranostic Platform.

Traumatic brain injury (TBI) is a major public health concern that can result in long-term neurological impairments. Calpain is a calcium-dependent cysteine protease that is activated within minutes after TBI, and sustained calpain activation is known to contribute to neurodegeneration and blood-brain barrier dysregulation. Based on its role in disease progression, calpain inhibition has been identified as a promising therapeutic target. Efforts to develop therapeutics for calpain inhibition would benefit from the ability to measure calpain activity with spatial precision within the injured tissue. In this work, we designed an activity-based nanotheranostic (ABNT) that can both sense and inhibit calpain activity in TBI. To sense calpain activity, we incorporated a peptide substrate of calpain flanked by a fluorophore/quencher pair. To inhibit calpain activity, we incorporated calpastatin peptide, an endogenous inhibitor of calpain. Both sensor and inhibitor peptides were scaffolded onto a polymeric nanoscaffold to create our ABNT. We show that in the presence of recombinant calpain, our ABNT construct is able to sense and inhibit calpain activity. In a mouse model of TBI, systemically administered ABNT can access perilesional brain tissue through passive accumulation and inhibit calpain activity in the cortex and hippocampus. In an analysis of cellular calpain activity, we observe the ABNT-mediated inhibition of calpain activity in neurons, endothelial cells, and microglia of the cortex. In a comparison of neuronal calpain activity by brain structure, we observe greater ABNT-mediated inhibition of calpain activity in cortical neurons compared to that in hippocampal neurons. Furthermore, we found that apoptosis was dependent on both calpain inhibition and brain structure. We present a theranostic platform that can be used to understand the regional and cell-specific therapeutic inhibition of calpain activity to help inform drug design for TBI.

Novel quantum dots-based assay for the determination of anti-hypertensive drugs minoxidil and timolol in different matrices.

The present work reports a sensitive, affordable, and ecologically friendly spectrofluorimetric method for the assessment of two antihypertensive medications, namely minoxidil and timolol. Blue-emitting sulfur and nitrogen co-doped carbon quantum dots (S,N-CQDs) were generated by exposing soluble starch and thiourea to a 15-minute microwave treatment. The so- prepared nanodots displayed fluorescence at 276/430 nm with a quantum yield of 22 %. Inspection of the so-prepared nano-sensor verified their doping with nitrogen and sulfur, and their size was in the range of 4.5-9.03 nm. The proposed method was found to be rectilinear in the range of 0.20-5.0 and 2.0-30.0 µg/mL, with LOQs of 0.16 and 0.82 µg/mL for minoxidil and timolol, respectively. The developed method was employed to assess the concentrations of minoxidil and timolol in their pharmaceutical formulations, with %recoveries varying between 99.00 % and 101.94 %, and low RSD values (less than 2 %). The high sensitivity of the developed method allowed its use for timolol measurement in artificial aqueous humor, with % recoveries between 97.60 %.and 101.57 %. The study further examined how each analyte interacted with the prepared dots, leading to a quenching of their fluorescence. Additionally, an interference study was utilized to evaluate the specificity of the proposed approach through determining analyte levels in the existence of common additives, co-formulated drugs, and co-administered drugs. The analytical eco-scale, GAPI and AGREE assessment techniques were utilized to confirm the suggested method greenness.

High Spatiotemporal Precision Mapping of Optical Nanosensor Array Using Machine Learning.

Optical nanosensors, including single-walled carbon nanotubes (SWCNTs), provide real-time spatiotemporal reporting at the single-molecule level within a nanometer-scale area. However, their superior sensitivity also makes them susceptible to slight environmental influences such as reference analytes in media, external fluid flow, and mechanical modulations. Consequently, they often fail to achieve the optimal limit of detection (LOD) and frequently convey misinformation spatiotemporally. To address this challenge, we developed a single-pixel mapping technique for optical nanosensor arrays that operates with high spatiotemporal precision using machine learning. We systematically measured the spatial sensing images of various analyte concentrations below the LOD by using a near-infrared (nIR) fluorescent SWCNT nanosensor array. For dopamine (DA) as an example analyte, we extracted single-pixel level sensing features such as entropy, the Laplacian operator, and neighboring values under noise levels. We then trained the artificial intelligence (AI) model to accurately identify specific reaction pixels of the nanosensor array, even below the LOD region. Additionally, our method can distinguish subtle noise caused by fluid in the media or mechanical modulation of the array substrate. As a result, our approach significantly improved the detection sensitivity of the nanosensor array, achieving a 13-fold increase over the original LOD and halving the detection time of the reporter pixels, with F1 scores exceeding 0.9. This method not only lowers the LOD of optical nanosensors but also isolates sensor responses specific to the analyte, providing accurate spatiotemporal information to the user, even in noisy conditions. It can be universally applied to various optical nanosensor materials and analytes, maximizing the sensitivity and accuracy of the nanosensors used in diagnostics and analysis.

Highly sensitive and selective detection of amoxicillin using molecularly imprinted ratiometric fluorescent nanosensor based on quantum dots.

A dual-emission ratiometric fluorescence sensor (CDs@CdTe@MIP) with a self-calibration function was successfully constructed for AMO detection. In the CDs@CdTe@MIP system, non-imprinted polymer-coated CDs and molecule-imprinted polymer-coated CdTe quantum dots were used as the reference signal and response elements, respectively. The added AMO quenched the fluorescence of the CdTe quantum dots, whereas the fluorescence intensity of the CDs remained almost unchanged. The AMO concentration was monitored using the fluorescence intensity ratio (log(I647/I465)0/(I647/I465)) to reduce interference from the testing environment. The sensor with a low detection limit of 0.15 µg/L enabled detection of the AMO concentration within 6 min. The ratiometric fluorescence sensor was used to detect AMO in spiked pork samples; it exhibited a high recovery efficiency and relative standard deviation (RSD) of 97.94-103.70% and 3.77-4.37%, respectively. The proposed highly sensitive and selective platform opens avenues for sensitive, reliable, and rapid determination of pharmaceuticals in the environment and food safety monitoring using ratiometric sensors.

Luminescent photon-upconversion nanoparticles with advanced functionalization for smart sensing and imaging.

Photon-upconversion nanoparticles (UCNP) have already been established as labels for affinity assays in analog and digital formats. Here, advanced, or smart, systems based on UCNPs coated with active shells, fluorescent dyes, and metal and semiconductor nanoparticles participating in energy transfer reactions are reviewed. In addition, switching elements can be embedded in such assemblies and provide temporal and spatial control of action, which is important for intracellular imaging and monitoring activities. Demonstration and critical comments on representative approaches demonstrating the progress in the use of such UCNPs in bioanalytical assays, imaging, and monitoring of target molecules in cells are reported, including particular examples in the field of cancer theranostics.

Ultrasensitive analyses of zearalenone in grain samples with a catalytic oxidation platform involving gold nanomaterials.

Zearalenone (ZEN) contamination in cereals poses a serious threat to human and animal health, yet existing rapid test methods still suffer from poor stability and low sensitivity. The studied sensor reduces inspection time while enabling applications for on-site grain inspection. Specifically, a ZEN detector that can sensitively detect ZEN content in grains was developed. Ion implantation is an effective method for modifying screen-printed electrodes (SPEs). Gold nanoparticles (AuNPs; 5-10 nm) were uniformly implanted using screen-printed electrodes as a catalytic oxidation medium to generate an electrochemical sensor. The surface structure of the modified electrode was characterized using scanning electron microscopy and X-ray photoelectron spectroscopy. The results showed that differential pulse voltammetry had good linear electrochemical response to ZEN at 10 ng/kg to 10 mg/kg, with a detection limit of 1.1 ng/kg. We used AuNP-SPE sensors to detect ZEN in grain samples such as maize and oats.

Selective and ultrasensitive detection of the herbicide glyphosate by means of plasmon catalysis on Ag nanoparticles.

This work aims at the detection of the important herbicide glyphosate based on the previous modification of glyphosate in two stages and final detection by surface-enhanced Raman spectroscopy (SERS). In a first step, the affinity of glyphosate for metal plasmonic surfaces was increased by inclusion of a sulphur containing group (dithiocarbamate). In a second step, the cyclization of the latter intermediate rendered a thiazole derivative of the herbicide. The latter compound exhibits higher Raman cross section which leads to stronger SERS enhancement factors. The second step was possible thanks to the plasmon catalysis driven by metal nanoparticles, specifically silver adatoms created at the surface, and irradiated at a proper wavelength. This methodology was optimized by selecting the most appropriate experimental conditions for the chemical reactions. Density Functional Theory treatment of all the involved molecules was done in order to obtain the theoretical spectra and to identify the structural marker bands. A key goal of this work was to develop an effective system of glyphosate detection based on portable PickMolTM technology developed and patented by the SAFTRA Photonics Ltd. company to ensure an easy, quick, low cost, in-situ, and univocal detection of glyphosate in the environment.

Highly Sensitive Plasmon Refractive Index Sensor Based on MIM Waveguide.

This paper introduces a novel plasmon refractive index nanosensor structure based on Fano resonance. The structure comprises a metal-insulator-metal (MIM) waveguide with an inverted rectangular cavity and a circle minus a small internal circle plus a rectangular cavity (CMSICPRC). This study employs the finite element method (FEM) to analyze the sensing characteristics of the structure. The results demonstrate that the geometrical parameters of specific structures exert a considerable influence on the sensing characteristics. Simulated experimental data show that the maximum sensitivity of this structure is 3240 nm/RIU, with a figure of merit (FOM) of 52.25. Additionally, the sensor can be used in biology, for example, to detect the concentration of hemoglobin in blood. The sensitivity of the sensor in this application, according to our calculations, can be 0.82 nm∙g/L.

Development of a Gold Nanoparticle-Based Sensor for Authentication of Organic Milk Based on Differential Levels of miRNA.

Dairy production systems significantly impact environmental sustainability, animal welfare, and human health. Intensive farming maximizes output through high-input practices, raising concerns about environmental degradation, animal welfare, and health risks from antibiotic residues. Conversely, organic farming emphasizes sustainable practices, animal welfare, and minimal synthetic inputs, potentially enhancing biodiversity, soil health, and milk quality. MicroRNAs (miRNAs), non-coding RNAs regulating gene expression, are promising biomarkers due to their response to various conditions. In this study, miRNAs bta-miR-103 and bta-miR-155, which are abundant in milk from pasture-fed cows, were selected. Additionally, bta-miR-215, which is abundant in milk fat from intensive systems, was also studied, in order to differentiate dairy production systems. A novel, cost-effective gold nanoparticle (AuNP)-based sensor was developed for miRNA detection, leveraging the unique plasmonic properties of AuNPs for visual detection. The method involves functionalizing AuNPs with complementary RNA probes and detecting miRNA-induced aggregation through colorimetric changes. This rapid, results in 30 min, and sensitive, visual limit of detection of 200 nM, assay requires minimal instrumentation and can be easily interpreted, offering significant advantages for field implementation in characterizing dairy production systems. This study demonstrates the successful application of this sensor in detecting miRNAs in 350 nM miRNA spiked raw milk, highlighting its potential for in situ dairy industry applications.

Aminophenylboronic acid-modified nitrogen-doped graphene quantum dots and their applications in lysine sensing based on interplaying fluorescent mechanisms.

Using nitrogen-doped graphene quantum dots (N-GQDs) and 3-aminophenylboronic acid (APBA), a novel fluorescence nanosensor was developed. This nanosensor exhibits high selectivity and sensitivity for lysine detection. Its sensing mechanism involves the suppression of electron transfer from APBA to the N-GQDs unit, thereby inhibiting photoinduced electron transfer and initiating internal charge transfer. At an optimal pH of 7, the protonated α-amine and ε-amine groups of lysine interact with the amide and boronic acid moieties, respectively. This interaction results in a redshift of fluorescence, substantially enhancing the response signal. A linear response was observed within a concentration range 0.40-3.01 µM, with the detection limit being 0.005 µM. A similar linear range was also achieved for the determination of lysine in human serum. Density functional theory calculations correlating molecular orbits and geometries support UV-vis and fluorescence findings. Additionally, the nanosensor was successfully applied to detect lysine in living cells and real samples, including milk and honey. For practical application, we construct a lysine-specific sensing platform using a commercial chip (TCS34725) that collects red, blue, and green signals, thereby facilitating the convenient use of the nanosensor. Overall, this study offers new perspectives on the development and application of fluorescent nanosensors for detecting individual amino acids.

3D Printed Nanosensors for Cancer Diagnosis: Advances and Future Perspective.

Cancer is the leading cause of mortality worldwide, requiring continuous advancements in diagnosis and treatment. Traditional methods often lack sensitivity and specificity, leading to the need for new methods. 3D printing has emerged as a transformative tool in cancer diagnosis, offering the potential for precise and customizable nanosensors. These advancements are critical in cancer research, aiming to improve early detection and monitoring of tumors. In current times, the usage of the 3D printing technique has been more prevalent as a flexible medium for the production of accurate and adaptable nanosensors characterized by exceptional sensitivity and specificity. The study aims to enhance early cancer diagnosis and prognosis by developing advanced 3D-printed nanosensors using 3D printing technology. The research explores various 3D printing techniques, design strategies, and functionalization strategies for cancer-specific biomarkers. The integration of these nanosensors with detection modalities like fluorescence, electrochemical, and surface-enhanced Raman spectroscopy is also evaluated. The study explores the use of inkjet printing, stereolithography, and fused deposition modeling to create nanostructures with enhanced performance. It also discusses the design and functionalization methods for targeting cancer indicators. The integration of 3D-printed nanosensors with multiple detection modalities, including fluorescence, electrochemical, and surface-enhanced Raman spectroscopy, enables rapid and reliable cancer diagnosis. The results show improved sensitivity and specificity for cancer biomarkers, enabling early detection of tumor indicators and circulating cells. The study highlights the potential of 3D-printed nanosensors to transform cancer diagnosis by enabling highly sensitive and specific detection of tumor biomarkers. It signifies a pivotal step forward in cancer diagnostics, showcasing the capacity of 3D printing technology to produce advanced nanosensors that can significantly improve early cancer detection and patient outcomes.