Label-free detection of β-amyloid peptides (Aβ40 and Aβ42): a colorimetric sensor array for plasma monitoring of Alzheimer's disease

Colorimetric sensing for translational applications: from colorants to mechanisms

Colorimetric sensing offers instant reporting via visible signals. Versus labor-intensive and instrument-dependent detection methods, colorimetric sensors present advantages including short acquisition time, high throughput screening, low cost, portability, and a user-friendly approach. These advantages have driven substantial growth in colorimetric sensors, particularly in point-of-care (POC) diagnostics. Rapid progress in nanotechnology, materials science, microfluidics technology, biomarker discovery, digital technology, and signal pattern analysis has led to a variety of colorimetric reagents and detection mechanisms, which are fundamental to advance colorimetric sensing applications. This review first summarizes the basic components (e.g., color reagents, recognition interactions, and sampling procedures) in the design of a colorimetric sensing system. It then presents the rationale design and typical examples of POC devices, e.g., lateral flow devices, microfluidic paper-based analytical devices, and wearable sensing devices. Two highlighted colorimetric formats are discussed: combinational and activatable systems based on the sensor-array and lock-and-key mechanisms, respectively. Case discussions in colorimetric assays are organized by the analyte identities. Finally, the review presents challenges and perspectives for the design and development of colorimetric detection schemes as well as applications. The goal of this review is to provide a foundational resource for developing colorimetric systems and underscoring the colorants and mechanisms that facilitate the continuing evolution of POC sensors.

A Coumarin-Based Array for the Discrimination of Amyloids

Self-assembly of misfolded proteins can lead to the formation of amyloids, which are implicated in the onset of many pathologies including Alzheimer's disease and Parkinson's disease. The facile detection and discrimination of different amyloids are crucial for early diagnosis of amyloid-related pathologies. Here, we report the development of a fluorescent coumarin-based two-sensor array that is able to correctly discriminate between four different amyloids implicated in amyloid-related pathologies with 100% classification. The array was also applied to mouse models of Alzheimer's disease and was able to discriminate between samples from mice corresponding to early (6 months) and advanced (12 months) stages of Alzheimer's disease. Finally, the flexibility of the array was assessed by expanding the analytes to include functional amyloids. The same two-sensor array was able to correctly discriminate between eight different disease-associated and functional amyloids with 100% classification.

Multiparametric modulation of magnetic transduction for biomolecular sensing in liquids

The recent COVID19 pandemic has remarkably boosted the research on in vitro diagnosis assays to detect biomarkers in biological fluids. Specificity and sensitivity are mandatory for diagnostic kits aiming to reach clinical stages. Whilst the modulation of sensitivity can significantly improve the detection of biomarkers in liquids, this has been scarcely explored. Here, we report on the proof of concept and parametrization of a novel biosensing methodology based on the changes of AC magnetic hysteresis areas observed for magnetic nanoparticles following biomolecular recognition in liquids. Several parameters are shown to significantly modulate the transducing capacity of magnetic nanoparticles to detect analytes dispersed in saline buffer at concentrations of clinical relevance. Magnetic nanoparticles were bio-conjugated with an engineered recognition peptide as a receptor. Analytes are engineered tetratricopeptide binding domains fused to the fluorescent protein whose dimerization state allows mono- or divalent variants. Our results unveil that the number of receptors per particle, analyte valency and concentration, nanoparticle composition and concentration, and field conditions play a key role in the formation of assemblies driven by biomolecular recognition. Consequently, all these parameters modulate the nanoparticle transduction capacity. Our study provides essential insights into the potential of AC magnetometry for customizing biomarker detection in liquids.

CRISPR-Powered Aptasensor for Diagnostics of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia, characterized by the accumulation of amyloid beta (Aβ) peptides in the brain. Here, we present a simple, rapid, and affordable CRISPR-powered aptasensor for the quantitative detection of Aβ40 and Aβ42 biomarkers in cerebrospinal fluid (CSF) samples, enabling early and accurate diagnostics of AD patients. The aptasensor couples the high specificity of aptamers for Aβ biomarkers with CRISPR-Cas12a-based fluorescence detection. The CRISPR-powered aptasensor enables us to detect Aβ40 and Aβ42 in CSF samples within 60 min, achieving a detection sensitivity of 1 pg/mL and 0.1 pg/mL, respectively. To validate its clinical utility, we quantitatively detected Aβ40 and Aβ42 biomarkers in clinical CSF samples. Furthermore, by combining CSF Aβ42 levels with the c(Aβ42)/c(Aβ40) ratio, we achieved an accurate diagnostic classification of AD patients and healthy individuals, showing superior performance over the conventional ELISA method. We believe that our innovative aptasensor approach holds promise for the early diagnostic classification of AD patients.

Detection of Femtomolar Amyloid-β Peptides for Early-Stage Identification of Alzheimer's Amyloid-β Aggregation with Functionalized Gold Nanoparticles

Progressive amyloid-β (Aβ) fibrillar aggregates have long been considered as the pathogenesis of Alzheimer's disease (AD). Biocompatible and stable cysteine-Aβ peptide-conjugated gold nanoparticles (Cys-Aβ@AuNP) are demonstrated as suitable materials for detecting subfemtomolar Aβ peptides in human plasma. Incubation with Aβ peptides causes the Cys-Aβ@AuNP to aggregate and changes its absorption spectra. The spectral change is especially apparent and noticeable when detecting subfemtomolar Aβ peptides, and the aggregates contain only two or three AuNPs. Cys-Aβ@AuNP can also be used to identify early-stage Aβ oligomerization, which is not possible using the conventional method, in which the fluorescence of thioflavin-T is measured. The ability to detect Aβ oligomerization can facilitate therapeutics for AD. In addition, the binding of Aβ peptides by Cys-Aβ@AuNP in combination with centrifugation redirects the conventional Aβ aggregation pathway and can effectively inhibit the formation of toxic Aβ oligomers or fibrils. Therefore, the proposed Cys-Aβ@AuNP can also be used to develop effective therapeutic agents to inhibit Aβ aggregation. The results obtained in this study are expected to open revolutionary ways to both detect and inhibit Aβ aggregation at an early stage.

Quantum dots-based "chemical tongue" for the discrimination of short-length Aβ peptides

A "chemical tongue" is proposed based on thiomalic acid-capped quantum dots (QDs) with signal enrichment provided by excitation-emission matrix (EEM) fluorescence spectroscopy for the determination of close structural analogs-short-length amyloid β (Aβ) peptides related to Alzheimer's disease. Excellent discrimination is obtained by principal component analysis (PCA) for seven derivatives: Aβ1-16, Aβ4-16, Aβ4-9, Aβ5-16, Aβ5-12, Aβ5-9, Aβ12-16. Detection of Aβ4-16, Aβ4-16, and Aβ5-9 in binary and ternary mixtures performed by QDs-based chemical tongue using partial least squares-discriminant analysis (PLS-DA) provided perfect 100% accuracy for the two studied peptides (Aβ4-16 and Aβ4-16), while for the third one (Aβ5-9) it was slightly lower (97.9%). Successful detection of Aβ4-16 at 1 pmol/mL (1.6 ng/mL) suggests that the detection limit of the proposed method for short-length Aβ peptides can span nanomolar concentrations. This result is highly promising for the development of simple and efficient methods for sequence recognition in short-length peptides and better understanding of mechanisms at the QD-analyte interface.

A chromogenic diarylethene-based probe for the detection of Cu2+ in aqueous medium in Drosophila for early diagnosis of Alzheimer

A diarylethene-based probe (Z)-N'-((2-amino-5-chlorophenyl)(phenyl)methylene)-2-hydroxy benzohydrazide (KBH) has been proficiently developed and its structure has been confirmed by single crystal X-ray diffraction technique. It displays a selective and sensitive colorimetric sensing of Cu2+ ions in aqueous medium with a naked eye colour change from colourless to yellow. It exhibits a significantly low limit of detection as 1.5 nM. A plausible binding mechanism has been proposed using Job's plot, FT-IR, 1H NMR titration, HRMS and DFT studies. The chemosensor is effectively reversible and reusable with EDTA. Test strip kit and real water sample analysis have been shown to establish its practical applicability. Further, the potential of KBH for the early diagnosis of Cu2+ ion-induced amyloid toxicity has been investigated in eye imaginal disc of Alzheimer's disease model of Drosophila 3rd instar larvae. The in-vivo interaction of KBH with Cu2+ in gut tissues of Drosophila larvae establishes its sensing capability in biological system. Interestingly, the in-vivo detection of Cu2+ has been done using bright field imaging which eliminates the necessity of a fluorescent label, hence making the method highly economical.

Combination of Ternary Electrochemiluminescence System of BNQDs/AgMOG-K2S2O8 and Electrochemiluminescence Resonance Energy Transfer Strategy for Ultrasensitive Immunoassay of Amyloid-β Protein

In this work, based on boron nitride quantum dots (BNQDs) as energy donors and MnO2@MWCNTs-COOH as energy receptors, we designed an efficient electrochemiluminescence resonance energy transfer (ECL-RET) immunosensor for the detection of amyloid-β (Aβ42) protein, a biomarker of Alzheimer's disease (AD). First, the signal amplification of a ternary ECL system composed of BNQDs (as the ECL emitter), K2S2O8 (as the coreactant), and silver metal-organic gels (AgMOG, as the coreaction accelerator) was realized, and PDDA as stabilizer was added, a strong and stable initial ECL signal was obtained. AgMOG could not only support a large amount of BNQDs and Aβ42 capture antibody (Ab1) through Ag-N bond but also exhibit excellent ECL catalytic performance and enhance the luminescent intensity of BNQDs@PDDA-K2S2O8 system. In addition, due to the broad absorption spectrum of MnO2@MWCNTs-COOH and the extensive overlap with the ECL emission spectrum of BNQDs, the quenching probe Ab2-MnO2@MWCNTs-COOH could be introduced into the ternary system through a sandwich immune response. On this basis, the signal on-off ECL immunosensor was constructed to achieve the ultrasensitive detection of Aβ42 through signal transformation. Under the optimal conditions, the prepared ECL biosensor manifested a wide linear range (10 fg/mL-100 ng/mL) with a detection limit of 2.89 fg/mL and showed excellent stability, selectivity, and repeatability, which provided an effective strategy for the ultrasensitive detection of biomarkers in clinical analysis.

Predicting the size and morphology of nanoparticle clusters driven by biomolecular recognition

Nanoparticle aggregation is a driving principle of innovative materials and biosensing methodologies, improving transduction capabilities displayed by optical, electrical or magnetic measurements. This aggregation can be driven by the biomolecular recognition between target biomolecules (analytes) and receptors bound onto nanoparticle surface. Despite theoretical advances on modelling the entropic interaction in similar systems, predictions of the fractal morphologies of the nanoclusters of bioconjugated nanoparticles are lacking. The morphology of resulting nanoclusters is sensitive to the location, size, flexibility, average number of receptors per particle f̄, and the analyte-particle concentration ratio. Here we considered bioconjugated iron oxide nanoparticles (IONPs) where bonds are mediated by a divalent protein that binds two receptors attached onto different IONPs. We developed a protocol combining analytical expressions for receptors and linker distributions, and Brownian dynamics simulations for bond formation, and validated it against experiments. As more bonds become available (e.g., by adding analytes), the aggregation deviates from the ideal Bethe's lattice scenario due to multivalence, loop formation, and steric hindrance. Generalizing Bethe's lattice theory with a (not-integer) effective functionality feff leads to analytical expressions for the cluster size distributions in excellent agreement with simulations. At high analyte concentration steric impediment imposes an accessible limit value facc to feff, which is bounded by facc < feff < f̄. A transition to gel phase, is correctly captured by the derived theory. Our findings offer new insights into quantifying analyte amounts by assessing nanocluster size, and predicting nanoassembly morphologies accurately is a first step towards understanding variations of physical properties in clusters formed after biomolecular recognition.

Multiplex Detection of Biogenic Amines for Meat Freshness Monitoring Using Nanoplasmonic Colorimetric Sensor Array

Biogenic amines (BAs) were presented as significant markers for the evaluation of the spoilage of meat and meat products. In this work, a colorimetric sensor array was developed for the discrimination and detection of spermine (SP), spermidine (SD), histamine (HS), and tryptamine (TP) as important BAs in food assessment. For this aim, two important spherical plasmonic nanoparticles, namely gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs), were utilized as the sensing elements of the probes. The cross-reactive interaction of the target biogenic amines and the plasmonic nanoparticles caused the aggregation-induced UV-Vis spectra changes, which were accompanied by visual color variation in the solution. The collected responses were analyzed by principal component analysis-linear discrimination analysis (PCA-LDA) to classify the four BAs. This colorimetric sensor array can also discriminate between the individual BAs and their mixture accurately. Partial least squares regression (PLS-R) was also utilized for quantitative analysis of the BAs. The wide linear concentration ranges of 0.1-10.0 µM for the four BAs and desirable figures of merits (FOMs) showed the potential of the developed sensor for quantitative detection of the BAs. Finally, the practical ability of the developed probe was studied by the determination of the BAs in the meat samples, which successfully proved the potential of the colorimetric sensor array in a food sample.

Ultrasensitive FET biosensor chip based on self-assembled organic nanoporous membrane for femtomolar detection of Amyloid-β

Early diagnosis of Alzheimer's disease (AD) is critical for preventing disease progression, however, the diagnosis of AD remains challenging for most patients due to limitations of current sensing technologies. A common pathological feature found in AD-affected brains is the accumulation of Amyloid-β (Aβ) polypeptides, which lead to neurofibrillary tangles and neuroinflammatory plaques. Here, we developed a portable ultrasensitive FET biosensor chip based on a self-assembled nanoporous membrane for ultrasensitive detection of Aβ protein in complex environments. The microscale semiconductor channel was covered with a self-assembled organic nanoporous membrane modified by antibody molecules to pick up and amplify the Aβ protein signal. The nanoporous structure helps protect the sensitive channel from non-target proteins and improves its stability since no chemical functionalization process involved, largely reduces background noise of the sensing platform. When a bio-gated target is captured, the doping state of the polymer bulk could be tuned and amplified the strength of the weak signal, achieving ultrasensitive detecting performance (enabling the device to detect target protein less than 1 fg/ml in 1 µl sample). Moreover, the device simplifies the circuit connection by integrating all the connections on a 2 cm × 2 cm chip, avoiding expensive and complex manufacturing processes, and makes it usable for portable prognosis. We believe that this ultrasensitive, portable, low-cost Aβ sensor chip shows the great potential in the early diagnosis of AD and large-scale population screening applications.

Chrono-colorimetric sensor array for detection and discrimination of halide ions using an all-in-one plasmonic sensor element

Most nanoparticle based colorimetric sensor array utilize several sensor elements and static response for discrimination of target analytes. This approach can be complicated and costly to synthesize or functionalize different nanoparticles for providing wide color variation. Herein, triangular silver nanoparticles (TSNPs) were used to develop a colorimetric sensor array by time-dimension responses. The principle of this sensor array is based on the diverse etching process of TSNPs in the presence of three halide ions, including bromide (Br^-), iodide (I^-) and chloride (Cl^-). Various etchings of TSNPs induced color changes at different reaction time intervals, which produced a colorimetric pattern for each ion. Therefore, using time dependent etching responses of TSNPs as a single sensing component can produce a wide color variation which can be distinguished by naked eyes. The colorimetric responses of TSNPs upon the addition of different concentrations of halide ions have been analyzed by PLS regression (PLS-R) and PLS discriminant analysis (PLS-DA). The analytical figures of merit confirmed that the developed chrono-colorimetric TSNPs -based sensor array is successful in both the discrimination and quantitative detection of halide ions. At the final step, the three halide ions were accurately determined in a real water sample, which verified the potential of the developed sensor in a real sample.

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Nanosensor-Driven Detection of Neuron-Derived Exosomal Aβ42 with Graphene Electrolyte-Gated Transistor for Alzheimer's Disease Diagnosis

Blood-based tests have sparked tremendous attention in non-invasive early diagnosis of Alzheimer's disease (AD), a most prevalent neurodegenerative malady worldwide. Despite significant progress in the methodologies for detecting AD core biomarkers such as Aβ₄₂ from serum/plasma, there remains cautious optimism going forward due to its controversial diagnostic value and disease relevance. Here, a graphene electrolyte-gated transistor biosensor is reported for the detection of serum neuron-derived exosomal Aβ₄₂ (NDE-Aβ₄₂), which is an emerging, compelling trove of blood biomarker for AD. Assisted by the antifouling strategy with the dual-blocking process, the noise against complex biological background was considerably reduced, forging an impressive sensitivity gain with a limit of detection of 447 ag/mL. An accurate detection of SH-SY5Y-derived exosomal Aβ₄₂ was also achieved with highly conformable enzyme-linked immunosorbent assay results. Importantly, the clinical analysis for 27 subjects revealed the immense diagnostic value of NDE-Aβ₄₂, which can outclass that of serum Aβ₄₂. The developed electronic assay demonstrates, for the first time, nanosensor-driven NDE-Aβ₄₂ detection, which enables a reliable discrimination of AD patients from non-AD individuals and even the differential diagnosis between AD and vascular dementia patients, with an accuracy of 100% and a Youden index of 1. This NDE-Aβ₄₂ biosensor defines a robust approach for blood-based confident AD ascertain.

Machine Learning-Assisted Nanoenzyme/Bioenzyme Dual-Coupled Array for Rapid Detection of Amyloids

Array-based sensing methods offer significant advantages in the simultaneous detection of multiple amyloid biomarkers and thus have great potential for diagnosing early-stage Alzheimer's disease. Yet, detecting low concentrations of amyloids remains exceptionally challenging. Here, we have developed a fluorescent sensor array based on the dual coupling of a nanoenzyme (AuNPs) and bioenzyme (horseradish peroxidase) to detect amyloids. Various ss-DNAs were bound to the nanoenzyme for regulating enzymatic activity and recognizing amyloids. A simplified sensor array was generated from a screening model via machine learning algorithms and achieved signal amplification through a two-step enzymatic reaction. As a result, our sensing system could discriminate the aggregation species and aggregation kinetics at 200 nM with 100% accuracy. Moreover, AD model mice and healthy mice were distinguished with 100% accuracy through the sensor array, providing a powerful sensing platform for diagnosing AD.

Machine-learning assisted multiplex detection of catecholamine neurotransmitters with a colorimetric sensor array

Catecholamine neurotransmitters (CNs), such as dopamine (DA), epinephrine (EP), norepinephrine (NEP), and levodopa (LD), are recognized as the primary biomarkers of a variety of neurological illnesses. Therefore, simultaneous monitoring of these biomarkers is highly recommended for clinical diagnosis and treatment. In this study, a high-performance colorimetric artificial tongue has been proposed for the multiplex detection of CNs. Different aggregation behaviors of gold nanoparticles in the presence of CNs under various buffering conditions generate unique fingerprint response patterns. Under various buffering conditions, the distinct acidity constants of CNs, and consequently their predominant species at a given pH, drive the aggregation of gold nanoparticles (AuNPs). The utilization of machine learning algorithms in this design enables classification and quantification of CNs in various samples. The response profile of the array was analyzed using the linear discriminant analysis algorithm for classification of CNs. This colorimetric sensor array is capable of accurately distinguishing between individual neurotransmitters and their combinations. Partial least squares regression was also applied for quantitation purposes. The obtained analytical figures of merit (FOMs) and linear ranges of 0.6-9 μM (R² = 0.99) for DA, 0.1-10 μM (R² = 0.99) for EP, 0.1-9 μM (R² = 0.99) for NEP and 1-70 μM (R² = 0.99) for LD demonstrated the potential applicability of the developed sensor array in precise and accurate determination of CNs. Finally, the feasibility of the array was validated in human urine samples as a complex biological fluid with LODs of 0.3, 0.5, 0.2, and 1.9 μM for DA, EP, NEP, and LD, respectively.

A Multichannel Fluorescent Tongue for Amyloid-β Aggregates Detection

Attention has been paid to the early diagnosis of Alzheimer's disease, due to the maximum benefit acquired from the early-stage intervention and treatment. However, the sensing techniques primarily depended upon for neuroimaging and immunological assays for the detection of AD biomarkers are expensive, time-consuming and instrument dependent. Here, we developed a multichannel fluorescent tongue consisting of four fluorescent dyes and GO through electrostatic and π-π interaction. The array distinguished multiple aggregation states of 1 µM Aβ40/Aβ42 with 100% prediction accuracy via 10-channel signal outputs, illustrating the rationality of the array design. Screening vital sensor elements for the simplified sensor array and the optimization of sensing system was achieved by machine learning algorithms. Moreover, our sensing tongue was able to detect the aggregation states of Aβ40/Aβ42 in serum, demonstrating the great potential of multichannel array in diagnosing the Alzheimer's diseases.

An efficient differential sensing strategy for phenolic pollutants based on the nanozyme with polyphenol oxidase activity

To realize the efficient differential sensing of phenolic pollutants in sewage, a novel sensing strategy was successfully developed based on one nanozyme (GMP-Cu) with polyphenol oxidase activity. Phenolic pollutants can be oxidized by GMP-Cu, and the oxidation products reacts subsequently with 4-aminoantipyrine to produce a quinone-imine compound. The absorption spectra of final quinone-imine products resulted from different phenolic pollutants showed obvious differences, which were due to the interaction difference between GMP-Cu and phenolic pollutants, as well as the different molecular structures of the quinone-imine products from different phenolic pollutants. Based on the difference of absorption spectra, a novel differential sensing strategy was developed. The genetic algorithm was used to select the characteristic wavelengths at different enzymatic reaction times, HCA and PLS-DA algorithms were utilized for the discriminant sensing of seven representative phenolic pollutants, including hydroquinone, resorcinol, catechol, resorcinol, phenol, p-chlorophenol, and 2,4-dichlorophenol. Scientific wavelength selection algorithm and recognition algorithm resulted in the successful identification of phenolic pollutants in sewage with a discriminant accuracy of 100%, and differentiation of the phenolic pollutants regardless of their concentration. These results indicate that sensing strategy can be used as an effective tool for the efficient identification and differentiation of phenolic pollutants in sewage.

Machine Learning-Assisted Sensor Array Based on Poly(amidoamine) (PAMAM) Dendrimers for Diagnosing Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, and the early diagnosis of AD remains challenging. Here we have developed a fluorescent sensor array composed of three modified polyamidoamine dendrimers. Proteins of various properties were differentiated via this array with 100% accuracy, proving the rationality of the array's design. The mechanism of the fluorescence response was discussed. Furthermore, the robust three-element array enables parallel detection of multiple Aβ40/Aβ42 aggregates (0.5 μM) in diverse interferents, serum media, and cerebrospinal fluid (CSF) with high accuracy, through machine learning algorithms, demonstrating the tremendous potential of the sensor array in Alzheimer's disease diagnosis.

Optical Sensor Array for the Early Diagnosis of Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common neurodegenerative disorder and has complicated pathobiology, leading to irreversible memory loss and severe cognitive dysfunction. For patients with AD, the advent of the disease usually occurs after years of pathological changes. The early diagnosis and monitoring of AD are of great significance as the early-stage intervention and treatment may be the most effective. Biomarkers, such as beta-amyloid and tau levels in cerebrospinal fluid (CSF) and brain, offer one of the most promising paths and are combined with neuroimaging and immunological detection for AD diagnosis. However, high expense and radiation of neuroimaging and low sensitivity of immunosorbent assay limited their applications. Meanwhile, the relevance of Aβ peptides and tau proteins to the development of AD remains highly debatable, meaning that detecting one specific biomarker holds limited prospects in achieving early and accurate detection of AD. Optical sensor arrays based on pattern recognition enable the discrimination of multiple analytes in complicated environments and are thus highly advantageous for the detection of AD with multi-biomarkers. In this review, we survey the recent advances of optical sensor arrays for the diagnosis of AD, as well as the remaining challenges.

Cross-Reactive Fluorescent Sensor Array for Discrimination of Amyloid Beta Aggregates

It has been hypothesized that misfolding and misassembly of proteins into various aggregation states contribute to several neurodegenerative diseases. For instance, amyloid beta (Aβ) aggregation is considered a major factor in Alzheimer's disease pathogenesis. Herein, a fluorescent sensor array for detecting Aβ aggregates was fabricated using two probe pairs of conjugated polyelectrolytes and organic dye molecules, PPE1-Thioflavin T (ThT) and PPESO3-Nile Red (NR). Pattern recognition was achieved by linear discriminant analysis and hierarchical clustering analysis algorithms. As a result of distinguishing among monomers and three pure aggregate species, namely oligomers, protofibrils, and fibrils, the cross-reactive sensor array was also able to monitor aggregation kinetics in various aggregate forms and distinguish between on- and off- aggregate pathways. Our study provides a convenient approach for simultaneous detection of Aβ aggregates in mixtures, which may also be applied to the analysis of other disease-related proteins that are prone to aggregates.

Distance-based β-amyloid protein detection on PADs for the scanning and subsequent follow-up of Alzheimer's disease in human urine samples

We report on the first development of a simple distance-based β-amyloid (Aβ) protein quantification using a paper-based device (dPAD) to screen for Alzheimer's disease (AD) and to subsequently follow up on its influence, i.e., clinical dementia. This sensor method is based on the transformation of a free acid form and its binding with a basic form of bromocresol purple (BCP) through its electrostatic interaction with an Aβ protein. This sensor can measure the length of color change from yellow to blue-green on a paper strip, with this change proportional to the amount of Aβ protein level. We found that the linearity for Aβ protein monitoring was in the range from 0.50 to 10.0 ng mL^-1, and the subsequent naked-eye detection limit for Aβ was 0.20 ng mL^-1. This system also provided high reproducibility and with no apparent interference effect for Aβ protein analysis in human urine samples. Furthermore, our developed dPAD constituted an accurate and effective device to precisely determine an Aβ protein concentration in real samples, with percentage recoveries in the range of 97-103%, and with the highest relative standard deviation of 5.41%. Subsequently, the validation of our assay was assessed by comparison with a commercial ELISA approach, with favorable results. Finally, the proposed dPAD was successfully applied to the determination of an Aβ protein in human urine samples and showed more benefits for the unskilled user, such as cost-efficiency, simplicity, low reagent usage, and low time consumption. It is also suitable for point-of-care monitoring.

Universal Nanoparticle Counting Platform for Tetraplexed Biomarkers by Integrating Immunorecognition and Nucleic Acid Hybridization in One Assay

The development of a simple and universal strategy for simultaneous quantification of proteins and nucleic acid biomarkers in one assay is valuable, particularly for disease diagnosis and pathogenesis studies. Herein, a universal and amplification-free quantum dot-doped nanoparticle counting platform was developed by integrating immunorecognition and nucleic acid hybridization in one assay. The assay can be performed at room temperature, which is friendly for routine analysis. Multiplexed biomarkers associated with Alzheimer's disease (AD) including proteins and nucleic acids were detected. For simultaneous detection of tetraplex biomarkers, the assay for amyloid β 1-42 (Aβ42), tau protein, miR-146a, and miR-138 presented limit of detection values of 250 pg/mL, 55.7 pg/mL, 52.5 pM, and 0.62 pM, respectively. By spiking all the above four biomarkers in one artificial cerebrospinal fluid sample, the recoveries were found to be 94.7-117.2%. Using tau protein as the model, four measurements in 88 days presented a coefficient of variance of 7.5%. The proposed platform for the multiplexed assay of proteins and nucleic acids presents the universality, reasonable sensitivity, and repeatability, which may open a new door for early diagnosis and pathogenesis research for AD and other diseases.

Nanozyme sensor array based on manganese dioxide for the distinction between multiple amyloid β peptides and their dynamic aggregation process

The determination of the amyloid β (Aβ) peptide and its aggregation intermediates helps to understand the pathological mechanism of Alzheimer's disease (AD) caused by toxic amyloid fragments. Because of the transient and heterogeneous properties of Aβ aggregates, it is very difficult to dynamically detect Aβ and its aggregation intermediates. Herein, we successfully constructed a two-dimensional manganese dioxide (MnO₂) nanozyme sensor array by modulating the peroxidase-mimicking activity using various Aβ species and accurately distinguished among six types of Aβ within 1 h through linear discriminant analysis (LDA), with a dynamic detection range of 0.01-500 nmol/L and a detection limit of 0.44 pmol/L. Subsequently, 30 unknown blind samples were used to verify the practicability of the sensor array, and all unknown samples were identified with 100% accuracy. It is worth noting that the sensor array successfully distinguished healthy individuals from AD patients using clinical blood samples. This study provides a convenient and reliable nanozyme biosensing system for detecting Aβ species and their related aggregation processes.

Lab-on-a-ZnO-Submicron-Particle Sensor Array for Monitoring AD upon Cd2+ Exposure with CSF Tau441% as an Effective Hallmark

In this study, based on the posttreatment strategy, blue-color-emissive ZnO submicron particles (B-ZnO SMPs) and red-color-emissive ZnO submicron particles (R-ZnO SMPs) were obtained from rationally designed Zn-infinite coordination polymer (ICP) precursors. After modification of thiol-containing aptamers, diverse spectral changes in the ultraviolet and visible regions of B- and R-ZnO SMPs toward different tau species were explored to construct a lab-on-a-ZnO-submicron-particle sensor array. Assisted by principal component analysis (PCA), the unique fingerprints of the sensor array enabled the simultaneous differentiation and quantitative detection of different tau species (tau381, tau410, and tau441) for the first time. Furthermore, the dynamic changes of tau441% (the ratio of the two most reported representative 4R isoform (full-length tau441) and 3R isoform (tau381)) in cerebrospinal fluid (CSF) during the Alzheimer's disease (AD) onset of Cd²⁺-exposed rats could also be monitored by the lab-on-a-ZnO-submicron-particle sensor array, which was supposed to be an effective hallmark and highly correlated with the formation of neurofibrillary tangles (NFTs). This study not only provides a further insight into the involvement of subchronic Cd²⁺ exposure in the tau etiology of AD but also offers more comprehensive and effective information about the asymptomatic stage of AD upon environmental risk, which has potential applications in the early diagnosis and therapy.

Nanoparticle-based colorimetric sensors to detect neurodegenerative disease biomarkers

Neurodegenerative disorders (NDDs) are progressive, incurable health conditions that primarily affect brain cells, and result in loss of brain mass and impaired function. Current sensing technologies for NDD detection are limited by high cost, long sample preparation, and/or require skilled personnel. To overcome these limitations, optical sensors, specifically colorimetric sensors, have garnered increasing attention towards the development of a cost-effective, simple, and rapid alternative approach. In this review, we evaluate colorimetric sensing strategies of NDD biomarkers (e.g. proteins, neurotransmitters, bio-thiols, and sulfide), address the limitations and challenges of optical sensor technologies, and provide our outlook on the future of this field.

Towards point-of-care diagnosis of Alzheimer's disease: Multi-analyte based portable chemiresistive platform for simultaneous detection of β-amyloid (1-40) and (1-42) in plasma

Label-free simultaneous detection of Alzheimer's disease (AD) specific biomarkers Aβ40 and Aβ42 peptides on a single platform using polypyrrole nanoparticle-based chemiresistive biosensors is reported here. The proposed interdigitated-microelectrode based inexpensive multisensor-platform can concurrently detect Aβ40 and Aβ42 in spiked-plasma in the range of 10-14 - 10-6 g/mL (with LoDs being 5.71 and 9.09 fg/mL, respectively), enabling the estimation of diagnostically significant Aβ42/Aβ40 ratio. A detailed study has been undertaken here to record the individual sensor responses against spiked-plasma samples with varying amounts and proportions of the two target peptides, towards enabling disease-progression monitoring using the Aβ-ratio. As compared to the existing cost-ineffective brain-imaging techniques such as PET and MRI, and the high-risk CSF based invasive AD biomarkers detecting procedures, the proposed approach offers a viable alternative for affordable point-of-care AD diagnostics, with possible usage in performance evaluation of therapeutic drugs. Towards point-of-care applications, the portable readout used in this work was conjugated with an android-based mobile app for data-acquisition and analysis.

Recent progress in plasmonic nanoparticle-based biomarker detection and cytometry for the study of central nervous system disorders

Neurological disorders affect hundreds of millions of people around the world, are often life-threatening, untreatable, and can result in debilitating symptoms. The high prevalence of these disorders, which feature biochemical or structural abnormalities in neuronal systems, has spurned innovations in both rapid and early detection to assist in the selection of appropriate treatment strategies to improve the patients' quality of life. Plasmonic nanoparticles (PNPs), a versatile and promising class of nanomaterials, are widely utilized in numerous imaging techniques, drug delivery systems, and biomarker detection methods. Recently, PNP-based nanoprobes have attracted considerable attention for the early diagnosis of neurological disorders. Gold nanoparticles (AuNPs), with high local surface plasmon resonance (LSPR) signals, have been particularly well exploited as probes for dynamic biomarker detection, with quantification sensitivity demonstrated down to the single-molecule level. In this review, we will discuss the possibilities of PNPs in the methodological development for rapid neurological disease identification. In addition, we will also describe a new digital cytometry method that combines dark-field imaging and machine learning for precise biomarker enumeration on single cells. The aim of this review is to attract researchers working on the future development of new plasmonic nanoprobe-based strategies for the diagnosis of neurological disorders.

Providing Multicolor Plasmonic Patterns with Au@Ag Core-Shell Nanostructures for Visual Discrimination of Biogenic Amines

Biogenic amines (BAs) are known as substantial indicators of the quality and safety of food. Developing rapid and visual detection methods capable of simultaneously monitoring BAs is highly desired due to their harmful effects on human health. In the present study, we have designed a multicolor sensor array consisting of two types of gold nanostructures (i.e., gold nanorods (AuNRs) and gold nanospheres (AuNSs)) for the discrimination and determination of critical BAs (i.e., spermine (SM), tryptamine (TT), ethylenediamine (EA), tyramine (TR), spermidine (SD), and histamine (HT)). The design principle of the probe was based on the metallization of silver ions on the surface of AuNRs and AuNSs in the presence of BAs, forming Au@Ag core-shell nanoparticles. Changes in the surface composition, size, and aspect ratio of AuNSs and AuNRs induced a blue shift in the plasmonic band, which was accompanied by sharp and rainbowlike color variations in the solution. The collected data were visually assessed and statistically analyzed by various data visualization and pattern recognition methods. Namely, linear discriminant analysis (LDA) and partial least squares (PLS) regression were employed for the qualitative and quantitative determination of BAs. The responses were linearly correlated to the concentrations of BAs in a wide range of 10-800, 20-800, 40-800, 40-800, 60-800, and 80-800 μmol L^-1 with the limit of detections of 2.46, 4.79, 8.58, 14.26, 10.03, and 27.29 μmol L^-1 for SD, SM, TT, HT, EA, and TR, respectively. Finally, the practical applicability of the sensor array was investigated by the determination of BAs in meat and fish samples by which the potential of the probe for on-site determination of food freshness/spoilage was successfully verified.

Development of a colorimetric sensor array based on monometallic and bimetallic nanoparticles for discrimination of triazole fungicides

Due to the widespread use of pesticides and their harmful effects on humans and wildlife, monitoring their residual amounts in crops is critically essential but still challenging regarding the development of high-throughput approaches. Herein, a colorimetric sensor array has been proposed for discrimination and identification of triazole fungicides using monometallic and bimetallic silver and gold nanoparticles. Aggregation-induced behavior of AgNPs, AuNPs, and Au-AgNPs in the presence of four triazole fungicides produced a fingerprint response pattern for each analyte. Innovative changes to the metal composition of nanoparticles leads to the production of entirely distinct response patterns that can be used for the detection and discrimination of triazoles. Pattern recognition methods, including linear discriminant analysis (LDA) and hierarchical cluster analysis, have been employed for the differentiation of triazoles in the concentration range of 0.1-0.55 μg mL^-1. Besides, the sensor array demonstrates promising practicability to satisfactorily distinguished triazole in mixtures and complex media of wheat flour and cucumber samples. The proposed colorimetric sensor array might pave the way towards a cost-effective and rapid, yet sensitive platform for high-throughput monitoring of residual amounts of pesticides for on-site applications.

Potential Role of Nanoparticles in Treating the Accumulation of Amyloid-Beta Peptide in Alzheimer's Patients

The disorder of Alzheimer's is marked by progressive pathophysiological neurodegeneration. The amino acid peptides in the amyloid plaques found in the brains of people with Alzheimer's disease (AD) are known as amyloid-beta (Aβ). Current treatments are not curative, and the effects associated with AD are reduced. Improving treatment results involved the targeting of drugs at optimum therapeutic concentration. Nanotechnology is seen as an unconventional, modern technology that plays a key role in the treatment of Alzheimer's disease. Using nanoparticles, molecular detection, effective drug targeting, and their combination offer high sensitivity. The aim of this review is to shed light on the function and successful role of nanoparticles to resolve Aβ aggregation and thus to help cure Alzheimer's disease. The analysis divides these nanoparticles into three categories: polymer, lipid, and gold nanoparticles. A thorough comparison was then made between the nanoparticles, which are used according to their role, properties, and size in the procedure. The nanoparticles can prevent the accumulation of Aβ during the efficient delivery of the drug to the cells to treat Alzheimer's disease. Furthermore, this comparison demonstrated the ability of these nanoparticles to deal efficiently with Alzheimer's disease. The role of these nanoparticles varied from delivering the drug to brain cells to dealing with the disease-causing peptide.

Plasmonic Nanoparticles as Optical Sensing Probes for the Detection of Alzheimer's Disease

Alzheimer's disease (AD), considered a common type of dementia, is mainly characterized by a progressive loss of memory and cognitive functions. Although its cause is multifactorial, it has been associated with the accumulation of toxic aggregates of the amyloid-β peptide (Aβ) and neurofibrillary tangles (NFTs) of tau protein. At present, the development of highly sensitive, high cost-effective, and non-invasive diagnostic tools for AD remains a challenge. In the last decades, nanomaterials have emerged as an interesting and useful tool in nanomedicine for diagnostics and therapy. In particular, plasmonic nanoparticles are well-known to display unique optical properties derived from their localized surface plasmon resonance (LSPR), allowing their use as transducers in various sensing configurations and enhancing detection sensitivity. Herein, this review focuses on current advances in in vitro sensing techniques such as Surface-enhanced Raman scattering (SERS), Surface-enhanced fluorescence (SEF), colorimetric, and LSPR using plasmonic nanoparticles for improving the sensitivity in the detection of main biomarkers related to AD in body fluids. Additionally, we refer to the use of plasmonic nanoparticles for in vivo imaging studies in AD.

Simultaneous detection and identification of thiometon, phosalone, and prothioconazole pesticides using a nanoplasmonic sensor array

In this work, a colorimetric sensor array has been designed for the identification and discrimination of thiometon (TM) and phosalone (PS) as organophosphate pesticides and prothioconazole (PC) as a triazole pesticide. For this purpose, two different plasmonic nanoparticles including unmodified gold nanoparticles (AuNPs) and unmodified silver nanoparticles (AgNPs) were used as sensing elements. The principle of the proposed strategy relied on the aggregation AuNPs and AgNPs through the cross-reactive interaction between the target pesticides and plasmonic nanoparticles. Therefore, these aggregation-induced UV-Vis spectra changes were utilized to discriminate the target pesticides with the help of linear discriminant analysis (LDA). Besides, we have employed the bar plots and the heat maps as visual non-statistical methods to differentiate the pesticides in a wide range of concentrations (i.e., 20-5000 ng mL^-1). Multivariate calibration plots from partial least squares (PLS)- regression indicated that the responses linearly depend on the pesticide concentrations in the range of 100-1000 ng mL^-1 with the limit of detections (LOD) of 66.8, 68.3, and 41.4 ng mL^-1, for TM, PS, and PC, respectively. Finally, the potential applicability of the proposed sensor array has been evaluated for the detection and identification of the pesticides in the mixtures, water samples, and cucumber fruit.

Nanomaterial-based Optical and Electrochemical Biosensors for Amyloid beta and Tau: Potential for early diagnosis of Alzheimer's Disease

INTRODUCTION

Alzheimer's disease (AD), a heterogeneous pathological process representing the most common causes of dementia worldwide, has required early and accurate diagnostic tools. Neuropathological hallmarks of AD involve the aberrant accumulation of Amyloid beta (Aβ) into Amyloid plaques and hyperphosphorylated Tau into neurofibrillary tangles, occurring long before the onset of brain dysfunction.Areas covered:Considering the significance of Aβ and Tau in AD pathogenesis, these proteins have been adopted as core biomarkers of AD, and their quantification has provided precise diagnostic information to develop next-generation AD therapeutic approaches. However, conventional diagnostic methods may not suffice to achieve clinical criteria that are acceptable for proper diagnosis and treatment. The advantages of nanomaterial-based biosensors including facile miniaturization, mass fabrication, ultra-sensitivity, make them useful to be promising tools to measure Aβ and Tau simultaneously for accurate validation of low-abundance yet potentially informative biomarkers of AD..

EXPERT OPINION

The study has identified the potential application of advanced biosensors as standardized clinical diagnostic tools for AD, evolving the way for new and efficient AD control with minimum economic and social burden. After clinical trial, nanobiosensors for measuring Aβ and Tau simultaneously possess innovative diagnosis of AD to provide significant contributions to primary Alzheimer's care intervention.

Plasmonic nanoparticles for colorimetric detection of nitrite and nitrate

Irregular and unknowingly use of chemical compounds is a serious threat to the environment, human health, and other living organisms attributable and intensified by the growing population and increasing demand for food. Nitrite and nitrate are among those compounds that are widely used in agricultural and industrial products. Therefore on-site, rapid, simple, and accurate monitoring of nitrite/nitrate is highly desirable. In this review, while emphasizing the importance of nitrite and nitrate in food chain safety and health of living organisms, their measurement methods, in particular, nanoplasmonic colorimetric sensors are comprehensively discussed based on the researches in this field. Nanoplasmonic-based sensors have proved to be successful in comparison with traditional methods due to their low cost, biocompatibility, high sensitivity and selectivity, and most importantly, the ability to visually detect and be used on-site to measure nitrite and nitrate. The design principle of nanoplasmonic sensors will be presented into two categories of aggregation- and etching-based detection followed by their applications in nitrite detection. The nitrate measurement will be discussed based on either direct detection of nitrate or indirect strategy in which nitrate is reduced to nitrite by enzymes or metals. Finally, the remaining challenges and prospects in this topic will be described and outlined.

Nanoplasmonic sensor array for the detection and discrimination of pesticide residues in citrus fruits

Great attention has been directed towards developing rapid and straightforward methods for the identification of various pesticides that are usually used simultaneously in citrus fruits. The extensive use of diverse classes of pesticides in citrus fruits and their high toxicity may cause serious diseases in the human body. In the current study, a non-enzymatic sensor array has been developed for the identification and discrimination of five different pesticides belonging to diverse classes, including organophosphate, carbamate, and bipyridylium. For this aim, two gold nanoparticles (AuNPs) with different capping agents, citrate and borohydride, were used as sensing elements. The aggregation-induced spectra alterations of AuNPs were utilized to identify the pesticides in a wide range of concentrations (20-5000 ng mL-1). We have employed data visualization methods (i.e., heat maps, bar plots, and color difference maps), a supervised pattern recognition method (i.e., linear discrimination analysis), and partial least squares regression to qualitatively and quantitatively determine the pesticides. Finally, the practical applicability of the developed sensor array was evaluated for the identification of target pesticides in lime peel. The outcomes revealed that the probe could accurately verify the absence or presence of the pesticides in lime fruit.

Protein discrimination based on DNA induced perylene probe self-assembly

The development of a simple and effective method for the highly sensitive and selective discrimination of proteins is a subject of enormous interest. Herein, we report the construction of a novel fluorescence detection method based on a perylene probe for the highly efficient discrimination of multiple proteins. Single-stranded DNA (ssDNA) could induce aggregation of the perylene probe which caused quenching of probe fluorescence. After the addition of a protein, the protein could interact with the ssDNA-probe assembly complex with "turn-on" or further "turn-off" fluorescence response. A sensor array was designed based on the above phenomena which could realize the successful discrimination of proteins with 100% accuracy of cross validation. Nine representative proteins were successfully recognized. Moreover, it was observed that a protein could induce characteristic effect on the DNA-probe assembly with varying pH of assay buffer. Thus, different proteins showed unique fluorescence response towards assay buffers having different pH values. The assay buffer pH was then utilized as a sensing channel. Based on Linear Discriminant Analysis (LDA) nine proteins were successfully discriminated at the nanomolar concentration with 100% accuracy of cross validation. Furthermore, the sensor array also demonstrated differentiation of the nine proteins regardless of their concentration. The developed sensor array could also detect the proteins with great precision in human urine sample at a quite low concentration, which suggests its practical applicability for analysis of biological fluids.

Advances in nanomedicines for diagnosis of central nervous system disorders

In spite of a great improvement in medical health services and an increase in lifespan, we have witnessed a skyrocket increase in the incidence of central nervous system (CNS) disorders including brain tumors, neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease), ischemic stroke, and epilepsy, which have seriously undermined the quality of life and substantially increased economic and societal burdens. Development of diagnostic methods for CNS disorders is still in the early stage, and the clinical outcomes suggest these methods are not ready for the challenges associated with diagnosis of CNS disorders, such as early detection, specific binding, sharp contrast, and continuous monitoring of therapeutic interventions. Another challenge is to overcome various barrier structures during delivery of diagnostic agents, especially the blood-brain barrier (BBB). Fortunately, utilization of nanomaterials has been pursued as a potential and promising strategy to address these challenges. This review will discuss anatomical and functional structures of BBB and transport mechanisms of nanomaterials across the BBB, and special emphases will be placed on the state-of-the-art advances in the development of nanomedicines from a variety of nanomaterials for diagnosis of CNS disorders. Meanwhile, current challenges and future perspectives in this field are also highlighted.

Bi-functional sterically hindered phenol lipid-based delivery systems as potential multi-target agents against Alzheimer's disease via an intranasal route

New lipid-based nanomaterials and multi-target directed ligands (MTDLs) based on sterically hindered phenol, containing a quaternary ammonium moiety (SHP-s-R, with s = 2,3) of varying hydrophobicity (R = CH2Ph and CnH2n+1, with n = 8, 10, 12, 16), have been prepared as potential drugs against Alzheimer's disease (AD). SHP-s-R are inhibitors of human cholinesterases with antioxidant properties. The inhibitory potency of SHP-s-R and selectivity ratio of cholinesterase inhibition were found to significantly depend on the length of the methylene spacer (s) and alkyl chain length. The compound SHP-2-16 showed the best IC50 for human AChE and the highest selectivity, being 30-fold more potent than for human BChE. Molecular modeling of SHP-2-16 binding to human AChE suggests that this compound is a dual binding site inhibitor that interacts with both the peripheral anionic site and catalytic active site. The relationship between self-assembly parameters (CMC, solubilization capacity, aggregation number), antioxidant activity and a toxicological parameter (hemolytic action on human red blood cells) was investigated. Two sterically hindered phenols (SHP-2-Bn and SHP-2-R) were loaded into L-α-phosphatidylcholine (PC) nanoparticles by varying the SHP alkyl chain length. For the brain AChE inhibition assay, PC/SHP-2-Bn/SHP-2-16 nanoparticles were administered to rats intranasally at a dose of 8 mg kg-1. The Morris water maze experiment showed that scopolamine-induced AD-like dementia in rats treated with PC/SHP-2-Bn/SHP-2-16 nanoparticles was significantly reduced. This is the first example of cationic SHP-phospholipid nanoparticles for inhibition of brain cholinesterases realized by the use of intranasal administration. This route has promising potential for the treatment of AD.

Paper-Based Platform with an In Situ Molecularly Imprinted Polymer for β-Amyloid

Alzheimer's disease (AD) is one of the most common forms of dementia affecting millions of people worldwide. Currently, an easy and effective form of diagnosis is missing, which significantly hinders a possible improvement of the patient's quality of life. In this context, biosensors emerge as a future solution, opening the doors for preventive medicine and allowing the premature diagnosis of numerous pathologies. This work presents a pioneering biosensor that combines a bottom-up design approach using paper as a platform for the electrochemical recognition of peptide amyloid β-42 (Aβ-42), a biomarker for AD present in blood, associated with visible differences in the brain tissue and responsible for the formation of senile plaques. The sensor layer relies on a molecularly imprinted polymer as a biorecognition element, created on the carbon ink electrode's surface by electropolymerizing a mixture of the target analyte (Aβ-42) and a monomer (O-phenylenediamine) at neutral pH 7.2. Next, the template molecule was removed from the polymeric network by enzymatic and acidic treatments. The vacant sites so obtained preserved the shape of the imprinted protein and were able to rebind the target analyte. Morphological and chemical analyses were performed in order to control the surface modification of the materials. The analytical performance of the biosensor was evaluated by an electroanalytical technique, namely, square wave voltammetry. For this purpose, the analytical response of the biosensor was tested with standard solutions ranging from 0.1 ng/mL to 1 μg/mL of Aβ-42. The linear response of the biosensor went down to 0.1 ng/mL. Overall, the developed biosensor offered numerous benefits, such as simplicity, low cost, reproducibility, fast response, and repeatability less than 10%. All together, these features may have a strong impact in the early detection of AD.

Label-Free SERS Strategy for In Situ Monitoring and Real-Time Imaging of Aβ Aggregation Process in Live Neurons and Brain Tissues

The aggregation of Aβ has been reported to closely correlate with Alzheimer's disease (AD). However, clear monitoring of the entire aggregation process of Aβ from monomer to fibril has been scarcely reported until now. Herein, we developed a label-free ratiometric surface enhanced Raman spectroscopic (SERS) platform for real-time monitoring of the entire process of Aβ aggregation in neurons and brain tissues. Different gold nanoparticles, generated in situ with Aβ monomer and fibril as templates separately, were served as effective SERS substrates to achieve a high sensitivity with a limit of detection (LOD) down to 70 ± 4 pM and 3.0 ± 0.5 pM for Aβ₄₀ monomer and fibrils, respectively. Besides, the introduction of ratiometric determination of Aβ monomer and fibril (I₁₂₄₄/I₁₂₆₈) realized real-time monitoring of the entire aggregation process of Aβ monomer with high accuracy and selectivity against other proteins and amino acids. The significant analytical performance of the developed platform, together with good biocompatibility, long-term stability, and remarkable spatial resolution, enabled the present SERS platform imaging and real-time monitoring and imaging of Aβ aggregation influenced by different metal ions (Cu²⁺, Zn²⁺, and Fe³⁺) in neurons and brain tissues at the single cell level. Our results suggested that Cu²⁺ and Zn²⁺ ion of low concentration (10 μM) promoted fibril formation, while Fe³⁺ and Zn²⁺ of high concentration (100 μM) showed inhibition of fibrosis.

Selective colorimetric detection of pentaerythritol tetranitrate (PETN) using arginine-mediated aggregation of gold nanoparticles

Detection of pentaerythritol tetranitrate (PETN) as an explosive has been of great interest because of public safety and military concerns. Here, we have presented a simple, selective and sensitive colorimetric method for direct detection of PETN. The gold nanoparticles (AuNPs) were first exposed to arginine which has primary amines in its structure. Electron deficient -NH₂ groups from arginine could strongly interact with -NO₂ groups of PETN as electron donors. Hydrogen bonding happens between the -NO₂ group of PETN and -NH₂ group of arginine molecules. Therefore, selective aggregation of AuNPs happened because of the donor-acceptor and hydrogen bonding interactions. Due to the aggregation, the color of reddish AuNPs turned to blue or purple depend on PETN concentration. A good linear relationship was achieved between the aggregation signal (absorbance ratio of A₆₅₀/A₅₂₀) of the probe and the concentration of PETN with a limit of detection of 0.169 μmol L^-1. Furthermore, we have found that the developed probe can detect PETN in complex matrices of groundwater and soil samples.

Gold Nanoparticles Crossing Blood-Brain Barrier Prevent HSV-1 Infection and Reduce Herpes Associated Amyloid-βsecretion

Infections caused by HSV-1 and their typical outbreaks invading the nervous system have been related to neurodegenerative diseases. HSV-1 infection may deregulate the balance between the amyloidogenic and non-amyloidogenic pathways, raising the accumulation of amyloid-β peptides, one of the hallmarks in the neurodegenerative diseases. An effective treatment against both, HSV-1 infections and neurodegeneration, is a major therapeutic target. Therefore, gold nanoparticles (NPAus) have been previously studied in immunotherapy, cancer and cellular disruptions with very promising results. Our study demonstrates that a new NPAus family inhibits the HSV-1 infection in a neural-derived SK-N-MC cell line model and that this new NPAus reduces the HSV-1-induced β-secretase activity, as well as amyloid-β accumulation in SK-APP-D1 modifies cell line. We demonstrated that NPAuG3-S8 crosses the blood-brain barrier (BBB) and does not generate cerebral damage to in vivo CD1 mice model. The NPAuG3-S8 could be a promising treatment against neuronal HSV-1 infections and neuronal disorders related to the Aβ peptides.

Bleomycin modulates amyloid aggregation in β-amyloid and hIAPP

Aberrant misfolding and amyloid aggregation, which result in amyloid fibrils, are frequent and critical pathological incidents in various neurodegenerative disorders. Multiple drugs or inhibitors have been investigated to avert amyloid aggregation in individual peptides, exhibiting sequence-dependent inhibition mechanisms. Establishing or inventing inhibitors capable of preventing amyloid aggregation in a wide variety of amyloid peptides is quite a daunting task. Bleomycin (BLM), a complex glycopeptide, has been widely used as an antibiotic and antitumor drug due to its ability to inhibit DNA metabolism, and as an antineoplastic, especially for solid tumors. In this study, we investigated the dual inhibitory effects of BLM on Aβ aggregation, associated with Alzheimer's disease and hIAPP, which is linked to type 2 diabetes, using both computational and experimental techniques. Combined results from drug repurposing and replica exchange molecular dynamics simulations demonstrate that BLM binds to the β-sheet region considered a hotspot for amyloid fibrils of Aβ and hIAPP. BLM was also found to be involved in β-sheet destabilization and, ultimately, in its reduction. Further, experimental validation through in vitro amyloid aggregation assays was obtained wherein the fibrillar load was decreased for the BLM-treated Aβ and hIAPP peptides in comparison to controls. For the first time, this study shows that BLM is a dual inhibitor of Aβ and hIAPP amyloid aggregation. In the future, the conformational optimization and processing of BLM may help develop various efficient sequence-dependent inhibitors against amyloid aggregation in various amyloid peptides.

Bleomycin acts as a dual inhibitor against both amyloid β and human islet amyloid polypeptide by binding to the β-sheet grooves considered as the amyloids hotspot.

ThThnated Development of a pH assisted AgNP-based colorimetric sensor Array for simultaneous identification of phosalone and azinphosmethyl pesticides

Development of simple and rapid methods for identification of pesticides, due to their broad usage and harmful effects on mammals, has been known as a critical demand. Herein, we have introduced a silver nanoparticle (AgNP) based colorimetric sensor array for simultaneous identification of Azinphosmethyl (AM) and Phosalone (PS) pesticides. In the presence of the target pesticides, unmodified AgNPs at various pHs (4.5, 5.5 and 9.5) showed different aggregation behaviors. As a result of aggregation, the color and UV-Vis spectra of AgNPs changed differentially, leading to distinct response patterns for AM and PS. The aggregation induced spectral changes of AgNPs, were used to identify AM and PS with the help of linear discriminant analysis (LDA). The applicability of the proposed sensor array was then evaluated by identifying the target pesticides in apple samples. Altogether, the developed AgNPs based colorimetric sensor array can be potentially exploited as an efficient discrimination tool in the near future for agrichemical applications.