Selectivity and Specificity: Pros and Cons in Sensing

Advancing Flexible Sensors through On-Demand Regulation of Supramolecular Nanostructures

The evolution of flexible sensors heavily relies on advances in soft-material design and sensing mechanisms. Supramolecular chemistry offers a powerful toolbox for manipulating nanoscale and molecular structures within soft materials, thus fostering recent advancements in flexible sensors and electronics. Supramolecular interactions have been utilized to nanoengineer functional sensing materials or construct chemical sensors with lower cost and broader targets. In this perspective, we will highlight the use of supramolecular interactions to regulate and optimize nanostructures within functional soft materials and illustrate their importance in expanding the nanocavities of bioreceptors for chemical sensing. Overall, a bridge between tissue-mimicking flexible sensors and cell-mimetic supramolecular chemistry has been built, which will further advance human healthcare innovation.

Fast and accurate identification of pathogenic bacteria using excitation-emission spectroscopy and machine learning

Fast and reliable identification of pathogenic bacteria is of upmost importance to human health and safety. Methods that are currently used in clinical practice are often time consuming, require expensive equipment, trained personnel, and therefore have limited applications in low resource environments. Molecular identification methods address some of these shortcomings. At the same time, they often use antibodies, their fragments, or other biomolecules as recognition units, which makes such tests specific to a particular target. In contrast, array-based methods use a combination of reporters that are not specific to a single pathogen. These methods provide a more data-rich and universal response that can be used for identification of a variety of bacteria of interest. In this report, we demonstrate the application of the excitation-emission spectroscopy of an environmentally sensitive fluorescent dye for identification of pathogenic bacterial species. 2-(4'-Dimethylamino)-3-hydroxyflavone (DMAF) interacts with the bacterial cell envelope resulting in a distinct spectral response that is unique to each bacterial species. The dynamics of dye-bacteria interaction were thoroughly investigated, and the limits of detection and identification were determined. Neural network classification algorithm was used for pattern recognition analysis and classification of spectral data. The sensor successfully discriminated between eight representative pathogenic bacteria, achieving a classification accuracy of 85.8% at the species level and 98.3% at the Gram status level. The proposed method based on excitation-emission spectroscopy of an environmentally sensitive fluorescent dye is a powerful and versatile diagnostic tool with high accuracy in identification of bacterial pathogens.

A novel immunoassay technique using principal component analysis for enhanced detection of emerging viral variants

Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown disease variants has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown variant that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.

Unpacking the packaged optical fiber bio-sensors: understanding the obstacle for biomedical application

A biosensor is a promising alternative tool for the detection of clinically relevant analytes. Optical fiber as a transducer element in biosensors offers low cost, biocompatibility, and lack of electromagnetic interference. Moreover, due to the miniature size of optical fibers, they have the potential to be used in microfluidic chips and in vivo applications. The number of optical fiber biosensors are extensively growing: they have been developed to detect different analytes ranging from small molecules to whole cells. Yet the widespread applications of optical fiber biosensor have been hindered; one of the reasons is the lack of suitable packaging for their real-life application. In order to translate optical fiber biosensors into clinical practice, a proper embedding of biosensors into medical devices or portable chips is often required. A proper packaging approach is frequently as challenging as the sensor architecture itself. Therefore, this review aims to give an unpack different aspects of the integration of optical fiber biosensors into packaging platforms to bring them closer to actual clinical use. Particularly, the paper discusses how optical fiber sensors are integrated into flow cells, organized into microfluidic chips, inserted into catheters, or otherwise encased in medical devices to meet requirements of the prospective applications.

Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses

To evaluate the suitability of an analytical instrument, essential figures of merit such as the limit of detection (LOD) and the limit of quantification (LOQ) can be employed. However, as the definitions k nown in the literature are mostly applicable to one signal per sample, estimating the LOD for substances with instruments yielding multidimensional results like electronic noses (eNoses) is still challenging. In this paper, we will compare and present different approaches to estimate the LOD for eNoses by employing commonly used multivariate data analysis and regression techniques, including principal component analysis (PCA), principal component regression (PCR), as well as partial least squares regression (PLSR). These methods could subsequently be used to assess the suitability of eNoses to help control and steer processes where volatiles are key process parameters. As a use case, we determined the LODs for key compounds involved in beer maturation, namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and 2-phenylethanol, and discussed the suitability of our eNose for that dertermination process. The results of the methods performed demonstrated differences of up to a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to suggest potential for monitoring via eNose.

Emerging trends in metal oxide-based electronic noses for healthcare applications: a review

An electronic nose (E-nose) is a technology fundamentally inspired by the human nose, designed to detect, recognize, and differentiate specific odors or volatile components in complex and chaotic environments. Comprising an array of sensors with meticulously designed nanostructured architectures, E-noses translate the chemical information captured by these sensors into useful metrics using complex pattern recognition algorithms. E-noses can significantly enhance the quality of life by offering preventive point-of-care devices for medical diagnostics through breath analysis, and by monitoring and tracking hazardous and toxic gases in the environment. They are increasingly being used in defense and surveillance, medical diagnostics, agriculture, environmental monitoring, and product validation and authentication. The major challenge in developing a reliable E-nose involves miniaturization and low power consumption. Various sensing materials are employed to address these issues. This review presents the key advancements over the last decade in E-nose technology, specifically focusing on chemiresistive metal oxide sensing materials. It discusses their sensing mechanisms, integration into portable E-noses, and various data analysis techniques. Additionally, we review the primary metal oxide-based E-noses for disease detection through breath analysis. Finally, we address the major challenges and issues in developing and implementing a portable metal oxide-based E-nose.

Surfactant-based supramolecular dye assembly: A highly selective and economically viable platform for quantification of heparin antidote

Herein, we have employed a supramolecular assembly of a cationic dye, LDS-698 and a common surfactant sodium dodecyl sulfate (SDS) as a turn-on fluorescent sensor for protamine (Pr) detection. Addition of cationic Pr to the solution of dye-surfactant complex brings negatively charged SDS molecules together through strong electrostatic interaction, assisting aggregation of SDS way before its critical micellar concentration (CMC). These aggregates encapsulate the dye molecules within their hydrophobic region, arresting non-radiative decay channels of the excited dye. Thus, the LDS-698•SDS assembly displays substantial enhancement in fluorescence intensity that follows a nice linear trend with Pr concentration, providing limit of detection (LOD) for Pr as low as 3.84(±0.11) nM in buffer, 124.4(±6.7) nM in 1% human serum and 28.3(±0.5) nM in 100% human urine. Furthermore, high selectivity, low background signal, large stokes shift, and emission in the biologically favorable deep-red region make the studied assembly a promising platform for Pr sensing. As of our knowledge it is the first ever Pr sensory platform, using a very common surfactant (SDS), which is economically affordable and very easily available in the market. This innovative approach can replace the expensive, exotic and specialized chemicals considered for the purpose and thus showcase its potential in practical applications.

Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry

Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons are frequently made to the mammalian nose or tongue and this perspective examines the role of sensing arrays in analyzing food and beverages for quality, veracity, and safety. I focus on optical sensor arrays as low-cost, easy-to-measure tools for use in the field, on the factory floor, or even by the consumer. Novel materials and approaches are highlighted and challenges in the research field are discussed, including sample processing/handling and access to significant sample sets to train and test arrays to tackle real issues in the industry. Finally, I examine whether the comparison of sensing arrays to noses and tongues is helpful in an industry defined by human taste.

Multiple-Emitting Luminescent Metal-Organic Framework as an Array-on-a-MOF for Rapid Screening and Discrimination of Nitroaromatics

Fluorescence array technologies have attracted great interest in the sensing field because of their high sensitivity, low cost, and capability of multitarget detection. However, traditional array sensing relies on multiple independent sensors and thus often requires time-consuming and laborious measurement processes. Herein, we introduce a novel fluorescence array strategy of the array-on-a-metal-organic framework (MOF), which integrates multiple array elements into a single MOF matrix to achieve facile sensing and discrimination of multiple target analytes. As a proof-of-concept system, we constructed a luminescent MOF containing three different emitting channels, including a lanthanide ion (europium/Eu3+, red emission), a fluorescent dye (7-hydroxycoumarin-4-acetic acid/HCAA, blue emission), and the MOF itself (UiO-66-type MOF, blue-violet emission). Five structurally similar nitroaromatic compounds (NACs) were chosen as the targets. All three channels of the array-on-a-MOF displayed rapid and stable fluorescence quenching responses to NACs (response equilibrium achieved within 30 s). Different responses were generated for each channel against each NAC due to the various quenching mechanisms, including photoinduced electron transfer, energy competition, and the inner filter effect. Using linear discriminant analysis, the array-on-a-MOF successfully distinguished the five NACs and their mixtures at varying concentrations and demonstrated good sensitivity to quantify individual NACs (detect limit below the advisory concentration in drinking water). Moreover, the array also showed feasibility in the sensing and discrimination of multiple NACs in real water samples. The proposed "array-on-a-MOF" strategy simplifies multitarget discrimination procedures and holds great promise for various sensing applications.

Wireless Detection of Trace Ammonia: A Chronic Kidney Disease Biomarker

Elevated levels of ammonia in breath can be linked to medical complications, such as chronic kidney disease (CKD), that disturb the urea balance in the body. However, early stage CKD is usually asymptomatic, and mass screening is hindered by high instrumentation and operation requirements and accessible and reliable detection methods for CKD biomarkers, such as trace ammonia in breath. Enabling methods would have significance in population screening for early stage CKD patients. We herein report a method to effectively immobilize transition metal selectors in close proximity to a single-walled carbon nanotube (SWCNT) surface using pentiptycene polymers containing metal-chelating backbone structures. The robust and modular nature of the pentiptycene metallopolymer/SWCNT complexes creates a platform that accelerates sensor discovery and optimization. Using these methods, we have identified sensitive, selective, and robust copper-based chemiresistive ammonia sensors that display low parts per billion detection limits. We have added these hybrid materials to the resonant radio frequency circuits of commercial near-field communication (NFC) tags to achieve robust wireless detection of ammonia at physiologically relevant levels. The integrated devices offer a noninvasive and cost-effective approach for early detection and monitoring of CKD.

Whole-cell bioreporter application for rapid evaluation of hazardous metal bioavailability and toxicity in bioprocess

Assessing heavy metal bioavailability and toxicity during bioprocess is critical for advancing green biotechnology. The capability of whole-cell bioreporters to measure heavy metal bioavailability has been increasingly recognized. The advantages of this technology being applied to bioprocess monitoring are less studied. Here we investigate the potential of a cadmium- and lead-sensitive bioreporter to be used for heavy metals as a class, which holds great interest for bioprocess applications. We evaluated the bioavailability of eight individual heavy metals with bioreporter zntA, as well as the bioavailability and toxicity of mixed metals. The bioavailability and toxicity of heavy metals in bioprocess samples were also evaluated. We have demonstrated for the first time that the zntA bioreporter can effectively detect the bioavailability of zinc, nickel, and cobalt with limit of detection lower than 0.01, 0.08 and 0.5 mg·L-1, respectively. The detection limits meet the requirements of the WHO, the U.S. Environmental Protection Agency, and the China drinking water quality standards, which makes this approach reasonable for monitoring heavy metal bioavailability in bioprocess. LIVE/DEAD toxicity experiments have been conducted for the detection of mixed metal solution toxicity to zntA bioreporter which shows an EC50 (as EC50, concentration for 50% of maximal effect) value of mixed metal solution is 3.84 mg·L-1. Samples from wastewater treatment plants, sludge treatment plants and kitchen waste fermentation processes were analyzed to extend upon the laboratory results. The results of this study confirm the potential for practical applications of bioreporter technology in bioprocess monitoring. In turn, development for such practical applications is key to achieve the necessary level of commercialization to further make the routine use of bioreporters in bioprocess monitoring feasible.

A biosensor encompassing fusarinine C-magnetic nanoparticles and aptamer-red/green carbon dots for dual-channel fluorescent and RGB discrimination of Campylobacter and Aliarcobacter

The diarrhea pathogens Campylobacter and Aliarcobacter are similar in morphology and their leading symptoms, making them difficult to be differentially diagnosed. Herein, we report a biosensor with two modules to differentiate the genera-representative species of C. jejuni and A. butzleri. Module 1 was fusarinine C-decorated magnetic nanoparticles; module 2 consisted of C. jejuni-specific aptamer modified with red-emitting carbon dots (CDs) and A. butzleri-specific aptamer-modified green-emitting CDs, consisting non-interfering dual-fluorescence detection channels. Module 1 was used to selectively capture C. jejuni and A. butzleri from an un-cultured sample, and the specific CDs in module 2 would then recognize and bind to their counterpart bacteria when subjected to the collected module 1-bacteria complex. By measuring the fluorescence intensities from the CDs-bound bacteria, the abundance of each bacterium could be differentially indicated. This biosensor exhibited a wide detection range of up to 1 × 107 CFU/mL and the lowest limit of detection (LOD) of 1 CFU/mL, for each bacterium. Thus, the biosensor with dual-fluorescent channels facilitated a culture-independent, ultrasensitive and discriminative detection of C. jejuni and A. butzleri. Remarkably, this fluorescent detection could be transformed into RGB color indication to render the visual discrimination. After the biosensor was coupled with microfluidics, a biosensing platform was developed, which could render fluorescent and RGB differentiation of the two bacteria in human stool or chicken broilers, achieving a LOD of 5 CFU/mL and turnaround time of 65 min. This work established the first biosensor-based methodology for the discriminative detection of Campylobacter and Aliarcobacter in real samples.

Selective bioelectronic sensing of pharmacologically relevant quinones using extracellular electron transfer in Lactiplantibacillus plantarum

Redox-active small molecules containing quinone functional groups play important roles as pharmaceuticals, but can be toxic if overdosed. Despite the need for a fast and quantitative method to detect quinone and its derivatives, current sensing strategies are often slow and struggle to differentiate between structural analogs. Leveraging the discovery that microorganisms use certain quinones to perform extracellular electron transfer (EET), we investigated the use of Lactiplantibacillus plantarum as a whole-cell bioelectronic sensor to selectively sense quinone analogs. By tailoring the native EET pathway in L. plantarum, we enabled quantitative quinone sensing of 1,4-dihydroxy-2-naphthoic acid (DHNA) - a gut bifidogenic growth stimulator. We found that L. plantarum could respond to environmental DHNA within seconds, producing concentration-dependent electrical signals. This sensing capacity was robust in different assay media and allowed for continuous monitoring of DHNA concentrations. In a simulated gut environment containing a mixed pool of quinone derivatives, this tailored EET pathway can selectively sense pharmacologically relevant quinone analogs, such as DHNA and menadione, amongst other structurally similar quinone derivatives. We also developed a multivariate model to describe the mechanism behind this selectivity and found a predictable correlation between quinone physiochemical properties and the corresponding electrical signals. Our work presents a new concept to selectively sense quinone using whole-cell bioelectronic sensors and opens the possibility of using probiotic L. plantarum for bioelectronic applications in human health.

Prediction of the Response of a Photoionization Detector to a Complex Gaseous Mixture of Volatile Organic Compounds Produced by α-Pinene Oxidation

Photoionization detectors (PIDs) are lightweight and respond in real time to the concentrations of volatile organic compounds (VOCs), making them suitable for environmental measurements on many platforms. However, the nonselective sensing mechanism of PIDs challenges data interpretation, particularly when exposed to the complex VOC mixtures prevalent in the Earth's atmosphere. Herein, two approaches to this challenge are investigated. In the first, quantum-chemistry calculations are used to estimate photoionization cross sections and ionization potentials of individual species. In the second, machine learning models are trained on these calculated values, as well as empirical PID response factors, and then used for prediction. For both approaches, the resulting information for individual species is used to model the overall PID response to a complex VOC mixture. In complement, laboratory experiments in the Harvard Environmental Chamber are carried out to measure the PID response to the complex molecular mixture produced by α-pinene oxidation under various conditions. The observations show that the measured PID response is 15% to 30% smaller than the PID response modeled by quantum-chemistry calculations of the photoionization cross section for the photo-oxidation experiments and 15% to 20% for the ozonolysis experiments. By comparison, the measured PID response is captured within a 95% confidence interval by the use of machine learning to model the PID response based on the empirical response factor in all experiments. Taken together, the results of this study demonstrate the application of machine learning to augment the performance of a nonselective chemical sensor. The approach can be generalized to other reactive species, oxidants, and reaction mechanisms, thus enhancing the utility and interpretability of PID measurements for studying atmospheric VOCs.

Precise isolation and structural origin of an ultra-specific nanobody against chemical compound

Highly specific antibodies are the key reagents for developing immunoassays with a low false positive rate for environmental monitoring. Here, we provide evidence that nanobodies have the potential to achieve higher specificity than conventional antibodies and explain why from their structural features. Using sulfadimethoxine (SDM) as a model analyte, we constructed an immune phage display library and precisely isolated an ultra-specific nanobody (H1-17) by a crucial homologous antigen counter selection strategy. H1-17 showed no observable cross-reactivity (CR) with other structural analogs of 41 SDM tested, which has never been achieved by conventional antibodies. The structurally original specificity of H1-17 was illuminated and compared with that of one conventional antibody by homology modeling and site-directed mutagenesis validation. It was found that the noncanonical disulfide bond (C50-C104) of H1-17 helped CDR3 form a tailor-made binding pocket and divide it into two parts to accommodate the common structure of sulfonamides and the characteristic methoxyl group of SDM, respectively. Besides, the mutual-checking hydrogen bonds also played important roles in the specific recognition. Lastly, immunoassays with zero false positive rate were developed to screen SDM in water and milk samples, indicating that nanobodies could be reliable reagents for the accurate detection of chemical compounds.

Label-Free Electrochemical Methods for Disease Detection

Label-free electrochemical biosensing leverages the advantages of label-free techniques, low cost, and fewer user steps, with the sensitivity and portability of electrochemical analysis. In this review, we identify four label-free electrochemical biosensing mechanisms: (a) blocking the electrode surface, (b) allowing greater access to the electrode surface, (c) changing the intercalation or electrostatic affinity of a redox probe to a biorecognition unit, and (d) modulating ion or electron transport properties due to conformational and surface charge changes. Each mechanism is described, recent advancements are summarized, and relative advantages and disadvantages of the techniques are discussed. Furthermore, two avenues for gaining further diagnostic information from label-free electrochemical biosensors, through multiplex analysis and incorporating machine learning, are examined.

Perylene diimide-based sensors for multiple analyte sensing (Fe2+/H2S/ dopamine and Hg2+/Fe2+): cell imaging and INH, XOR, and encoder logic

In this report, we present our results on the recognition of multiple analytes using trisubstituted PDI-based chemosensors DNP and DNB in 50% HEPES buffered-CH₃CN solution. Upon the addition of Hg²⁺, DNB showed a decrease and increase in absorbance intensity at 560 and 590 nm, respectively, with a detection limit of 7.17 μM and bleaching of the violet color (de-butynoxy). Similarly, the addition of Fe²⁺ or H₂S to the solution of DNP or DNB resulted in ratiometric changes (A_688nm/A_560nm) with respective detection limits of 185 nM and 27.6 nM for Fe²⁺, respectively, and a color change from violet to green. However, the addition of >37 μM H₂S caused a decrease in absorbance at 688 nm with a concomitant blue shift to 634 nm. Upon the addition of dopamine, the DNP + Fe²⁺ assay showed ratiometric (A_560nm/A_688nm) changes within 10 s along with a color change from green to violet. Moreover, DNP has been successfully used for the exogenous detection of Fe²⁺ in A549 cells. Further, the multiple outputs observed with DNP in the presence of H₂S have been used to construct NOR, XOR, INH and 4-to-2 encoder logic gates and circuits.

Identification of Proteins Using Supramolecular Gold Nanoparticle-Dye Sensor Arrays

The rapid detection of proteins is very important in the early diagnosis of diseases. Gold nanoparticles (AuNPs) can be engineered to bind biomolecules efficiently and differentially. Cross-reactive sensor arrays have high sensitivity for sensing proteins using differential interactions between sensor elements and bioanalytes. A new sensor array was fabricated using surface-charged AuNPs with dyes supramolecularly encapsulated into the AuNP monolayer. The fluorescence of dyes is partially quenched by the AuNPs and can be restored or further quenched due to the differential interactions between AuNPs with proteins. This sensing system enables the discrimination of proteins in both buffer and human serum, providing a potential tool for real-world disease diagnostics.

Mask device as a new wearable sampler for breath analysis: what can we expect in the future?

Human exhaled breath is becoming an attractive clinical source as it is foreseen to enable noninvasive diagnosis of many diseases. Because mask devices can be used for efficiently filtering exhaled substances, mask-wearing has been required in the past few years in daily life since the unprecedented COVID-19 pandemic. In recent years, there is a new development of mask devices as new wearable breath samplers for collecting exhaled substances for disease diagnosis and biomarker discovery. This paper attempts to identify new trends in mask samplers for breath analysis. The couplings of mask samplers with different (bio)analytical approaches, including mass spectrometry (MS), polymerase chain reaction (PCR), sensor, and others for breath analysis, are summarized. The developments and applications of mask samplers in disease diagnosis and human health are reviewed. The limitations and future trends of mask samplers are also discussed.

Technology Roadmap for Flexible Sensors

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity.

Single-Probe-Based Colorimetric and Photothermal Dual-Mode Identification of Multiple Bacteria

Effective identification of multiple pathogenic bacteria in unknown samples is important for disease prevention and control but remains a challenge yet. A single-mode array-based sensing approach is simple and sensitive, but it usually relies on the use of multiple cross-reactive receptors to construct sensor arrays, which is cumbersome and insufficiently accurate. Here, we developed a sensor array with colorimetric and photothermal dual mode of differentiating multiple pathogenic bacteria. The sensor array was based on boronic acid-functionalized Au-Fe₃O₄ nanoparticles (BA-GMNPs), which not only possess localized surface plasmon resonance properties, showing a burgundy color similar to that of AuNPs, but also exhibit mild superparamagnetism, allowing for the differentiation of bacteria before and after binding to the nanoparticles. Immobilization of BA-GMNPs on the bacterial cell surface by covalent bonding would diminish NaCl-induced assembly of BA-GMNPs. Different BA-GMNPs@bacterial complexes differed in their ability to resist assembly and produced different colorimetric and photothermal response signals. A unique molecular fingerprint of each bacterium was obtained by linear discriminant analysis of the response patterns, demonstrating an effective differentiation among the six species studied. Compared with single-mode sensing arrays based on multiple receptors, this method only requires the preparation of a single nanomaterial, which produces two signal outputs for the identification of multiple bacteria with better differentiation. It can distinguish not only multiple pathogenic bacteria but also Gram-negative and Gram-positive bacteria, and, more importantly, it can perform preliminary discrimination of unknown samples.

Peptomer substrates for quantitative pattern-recognition sensing of proteases

The utility of active proteases as biomarkers is often limited by overlapping substrate specificity. Here, this feature is leveraged to develop a quantitative pattern-recognition sensing system driven by the degradation patterns of peptide-peptoid hybrid substrates to classify proteases and estimate their concentration by multivariate data analysis.

Printed colorimetric chemosensor array on a 96-microwell paper substrate for metal ions in river water

Here, we propose a printed 96-well microtiter paper-based chemosensor array device (PCSAD) to simultaneously detect metal ions for river water assessment. Colorimetric chemosensors for metal ions have been designed based on molecular self-assembly using off-the-shelf catechol dyes and a phenylboronic acid (PBA) derivative. The colorimetric self-assembled chemosensors consisting of catechol dyes and a PBA derivative on a 96-well microtiter paper substrate demonstrated various color changes according to the disassembly of the ensembles by the addition of nine types of metal ions. An in-house-made algorithm was used to automate imaging analysis and extract color intensities at seven types of color channels from a captured digital image, allowing for rapid data processing. The obtained information-rich inset data showed fingerprint-like colorimetric responses and was applied to the qualitative and quantitative pattern recognition of metal ions using chemometric techniques. The feasibility of the 96-well microtiter PCSAD for environmental assessment has been revealed by the demonstration of a spike-and-recovery test against metal ions in a river water sample.

2D MXene-Based Biosensing: A Review

MXene emerged as decent 2D material and has been exploited for numerous applications in the last decade. The remunerations of the ideal metallic conductivity, optical absorbance, mechanical stability, higher heterogeneous electron transfer rate, and good redox capability have made MXene a potential candidate for biosensing applications. The hydrophilic nature, biocompatibility, antifouling, and anti-toxicity properties have opened avenues for MXene to perform in vitro and in vivo analysis. In this review, the concept, operating principle, detailed mechanism, and characteristic properties are comprehensively assessed and compiled along with breakthroughs in MXene fabrication and conjugation strategies for the development of unique electrochemical and optical biosensors. Further, the current challenges are summarized and suggested future aspects. This review article is believed to shed some light on the development of MXene for biosensing and will open new opportunities for the future advanced translational application of MXene bioassays.

A Surface Acoustic Wave (SAW)-Based Lab-on-Chip for the Detection of Active α-Glycosidase

Enzyme detection in liquid samples is a complex laboratory procedure, based on assays that are generally time- and cost-consuming, and require specialized personnel. Surface acoustic wave sensors can be used for this application, overcoming the cited limitations. To give our contribution, in this work we present the bottom-up development of a surface acoustic wave biosensor to detect active α-glycosidase in aqueous solutions. Our device, optimized to work at an ultra-high frequency (around 740 MHz), is functionalized with a newly synthesized probe 7-mercapto-1-eptyl-D-maltoside, bringing one maltoside terminal moiety. The probe is designed ad hoc for this application and tested in-cuvette to analyze the enzymatic conversion kinetics at different times, temperatures and enzyme concentrations. Preliminary data are used to optimize the detection protocol with the SAW device. In around 60 min, the SAW device is able to detect the enzymatic conversion of the maltoside unit into glucose in the presence of the active enzyme. We obtained successful α-glycosidase detection in the concentration range 0.15-150 U/mL, with an increasing signal in the range up to 15 U/mL. We also checked the sensor performance in the presence of an enzyme inhibitor as a control test, with a signal decrease of 80% in the presence of the inhibitor. The results demonstrate the synergic effect of our SAW Lab-on-a-Chip and probe design as a valid alternative to conventional laboratory tests.

Nanomaterial and interface advances in immunoassay biosensors

Biosensors have been used for a remarkable array of applications, including infectious diseases, environmental monitoring, cancer diagnosis, food safety, and numerous others. In particular, the global COVID-19 pandemic has exposed a need for rapid tests, so the type of biosensor that has gained considerable interest recently are immunoassays, which are used for rapid diagnostics. The performance of paper-based lateral flow and dipstick immunoassays is influenced by the physical properties of the nanoparticles (NPs), NP-antibody conjugates, and paper substrate. Many materials innovations have enhanced diagnostics by increasing sensitivity or enabling unique readouts. However, negative side effects can arise at the interface between the biological sample and biomolecules and the NP or paper substrate, such as non-specific adsorption and protein denaturation. In this Perspective, we discuss the immunoassay components and highlight chemistry and materials innovations that can improve sensitivity. We also explore the range of bio-interface issues that can present challenges for immunoassays.

Fluorescent Peptomer Substrates for Differential Degradation by Metalloproteases

Proteases, especially MMPs, are attractive biomarkers given their central role in both physiological and pathological processes. Distinguishing MMP activity with degradable substrates, however, is a difficult task due to overlapping substrate specificity profiles. Here, we developed a system of peptomers (peptide-peptoid hybrids) to probe the impact of non-natural residues on MMP specificity for an MMP peptide consensus sequence. Peptoids are non-natural, N-substituted glycines with a large side-chain diversity. Given the presence of a hallmark proline residue in the P3 position of MMP consensus sequences, we hypothesized that peptoids may offer N-substituted alternatives to generate differential interactions with MMPs. To investigate this hypothesis, peptomer substrates were exposed to five different MMPs, as well as bacterial collagenase, and monitored by fluorescence resonance energy transfer and liquid chromatography-mass spectrometry to determine the rate of cleavage and the composition of degraded fragments, respectively. We found that peptoid residues are well tolerated in the P3 and P3' substrate sites and that the identity of the peptoid in these sites displays a moderate influence on the rate of cleavage. However, peptoid residues were even better tolerated in the P1 substrate site where activity was more strongly correlated with side-chain identity than side-chain position. All MMPs explored demonstrated similar trends in specificity for the peptomers but exhibited different degrees of variability in proteolytic rate. These kinetic profiles served as "fingerprints" for the proteases and yielded separation by multivariate data analysis. To further demonstrate the practical application of this tunability in degradation kinetics, peptomer substrates were tethered into hydrogels and released over distinct timescales. Overall, this work represents a significant step toward the design of probes that maximize differential MMP behavior and presents design rules to tune degradation kinetics with peptoid substitutions, which has promising implications for diagnostic and prognostic applications using array-based sensors.

Sensors Based on the Carbon Nanotube Field-Effect Transistors for Chemical and Biological Analyses

Nano biochemical sensors play an important role in detecting the biomarkers related to human diseases, and carbon nanotubes (CNTs) have become an important factor in promoting the vigorous development of this field due to their special structure and excellent electronic properties. This paper focuses on applying carbon nanotube field-effect transistor (CNT-FET) biochemical sensors to detect biomarkers. Firstly, the preparation method, physical and electronic properties and functional modification of CNTs are introduced. Then, the configuration and sensing mechanism of CNT-FETs are introduced. Finally, the latest progress in detecting nucleic acids, proteins, cells, gases and ions based on CNT-FET sensors is summarized.

Rapid Fluorescence Sensor Guided Detection of Urinary Tract Bacterial Infections

Introduction

Urinary tract infections (UTI) are one of the most serious human bacterial infections affecting millions of people every year. Therefore, simple and reliable identification of the urinary tract pathogenic bacteria within a few minutes would be of great significance for diagnosis and treatment of clinical patients with UTIs. In this study, the fluorescence sensor was reported to guide the detection of urinary tract bacterial infections rapidly.

Methods

The Ami-AuNPs-DNAs sensor was fabricated by the amino-modified Au nanoparticles (Ami-AuNPs) and six DNAs signal molecules, which bound to the urinary tract pathogenic bacteria and generated corresponding response signals. Further, based on the collected response signals, identification was performed by principal component analysis (PCA) and linear discriminant analysis (LDA). The Ami-AuNPs and Ami-AuNPs-DNAs were characterized by transmission electron microscopy, UV−vis absorption spectrum, Fourier transform infrared spectrum, dynamic light scattering and zeta potentials. Thereafter, the Ami-AuNPs-DNAs sensor was used to discriminate and identify five kinds of urinary tract pathogenic bacteria. Moreover, the quantitative analysis performance towards individual bacteria at different concentrations were also evaluated.

Results

The Ami-AuNPs-DNAs sensor were synthesized successfully in terms of spherical, well-dispersed and uniform in size, which could well discriminate five main urinary tract pathogenic bacteria with unique fingerprint-like patterns and was sufficiently sensitive to determine individual bacteria with a detection limit to 1×10⁷ cfu/mL. Furthermore, the sensor had also been successfully applied to identify bacteria in urine samples collected from clinical UTIs.

Conclusion

The developed fluorescence sensor could be applied to rapid and accurate discrimination of urinary tract pathogenic bacteria and holds great promise for the diagnosis of the disease caused by bacterial infection.

A facile way to construct sensor array library via supramolecular chemistry for discriminating complex systems

Differential sensing, which discriminates analytes via pattern recognition by sensor arrays, plays an important role in our understanding of many chemical and biological systems. However, it remains challenging to develop new methods to build a sensor unit library without incurring a high workload of synthesis. Herein, we propose a supramolecular approach to construct a sensor unit library by taking full advantage of recognition and assembly. Ten sensor arrays are developed by replacing the building block combinations, adjusting the ratio between system components, and changing the environment. Using proteins as model analytes, we examine the discriminative abilities of these supramolecular sensor arrays. Then the practical applicability for discriminating complex analytes is further demonstrated using honey as an example. This sensor array construction strategy is simple, tunable, and capable of developing many sensor units with as few syntheses as possible.

Development of a rapid, high-sensitivity, low-cost fluorescence method for protein surface hydrophobicity determination using a Nanodrop fluorospectrometer

A microvolumetric method for surface hydrophobicity (H₀) determination of proteins using a Nanodrop fluorospectrometer was developed. This method reduces the protein and fluorophore quantities that are necessary for sample preparations and readings by two and three orders of magnitude, respectively, compared to conventional methods. In addition, readings can be obtained in just 2-6 s. Bovine serum albumin (BSA) and 1-anilino 8-naphthalene sulfonic acid (ANS) were used for the first optimization of appropriate fluorophore-protein conditions for H₀ determination (20 μM ANS, 0.5-4 μM BSA, pH 5). Based on validation guidelines, the novel method shows linear behavior, good intraday precision, accuracy, and sensitivity. This method was robust against several factors, as determined by a Youden-Steiner test. Additional surface hydrophobicity determinations using several proteins demonstrate suitable method applicability. The present microvolumetric method provides a reliable technique to determine the H₀ of proteins for pharmaceutical, biotechnological, and food applications.

Overcoming Major Barriers to Developing Successful Sensors for Practical Applications Using Functional Nucleic Acids

For many years, numerous efforts have been focused on the development of sensitive, selective, and practical sensors for environmental monitoring, food safety, and medical diagnostic applications. However, the transition from innovative research to commercial success is relatively sparse. In this review, we identify four scientific barriers and one technical barrier to developing successful sensors for practical applications, including the lack of general methods to (a) generate receptors for a wide range of targets, (b) improve sensor selectivity to overcome interferences, (c) transduce the selective binding to different optical, electrochemical, and other signals, and (d) tune dynamic range to match thresholds of detection required for different targets; and the costly development of a new device. We then summarize solutions to overcome these barriers using sensors based on functional nucleic acids that include DNAzymes, aptamers, and aptazymes and how these sensors are coupled to widely available measurement devices to expand their capabilities and lower the barrier for their practical applications in the field and point-of-care settings.

Water Quality Carbon Nanotube-Based Sensors Technological Barriers and Late Research Trends: A Bibliometric Analysis

Water is the key element that defines and individualizes our planet. Relative to body weight, water represents 70% or more for the majority of all species on Earth. Taking care of water as a whole is equivalent with taking care of the entire biodiversity or the whole of humanity itself. Water quality is becoming an increasingly important component of terrestrial life, hence intensive work is being conducted to develop sensors for detecting contaminants and assessing water quality and characteristics. Our bibliometric analysis is focused on water quality sensors based on carbon nanotubes and highlights the most important objectives and achievements of researchers in recent years. Due to important measurement characteristics such as sensitivity and selectivity, or low detection limit and linearity, up to the ability to measure water properties, including detection of heavy metal content or the presence of persistent organic compounds, carbon nanotube (CNT) sensors, taking advantage of available nanotechnologies, are becoming increasingly attractive. The conducted bibliometric analysis creates a visual, more efficient keystones mapping. CNT sensors can be integrated into an inexpensive real-time monitoring data acquisition system as an alternative for classical expensive and time-consuming offline water quality monitoring. The conducted bibliometric analysis reveals all connections and maps all the results in this water quality CNT sensors research field and gives a perspective on the approached methods on this specific type of sensor. Finally, challenges related to integration of other trends that have been used and proven to be valuable in the field of other sensor types and capable to contribute to the development (and outlook) for future new configurations that will undoubtedly emerge are presented.

Nano-enabled sensing of per-/poly-fluoroalkyl substances (PFAS) from aqueous systems - A review

Per-/poly-fluoroalkyl substances (PFAS) are an emerging class of environmental contaminants used as an additive across various commodity and fire-retardant products, for their unique thermo-chemical stability, and to alter their surface properties towards selective liquid repellence. These properties also make PFAS highly persistent and mobile across various environmental compartments, leading to bioaccumulation, and causing acute ecotoxicity at all trophic levels particularly to human populations, thus increasing the need for monitoring at their repositories or usage sites. In this review, current nano-enabled methods towards PFAS sensing and its monitoring in wastewater are critically discussed and benchmarked against conventional detection methods. The discussion correlates the materials' properties to the sensitivity, responsiveness, and reproducibility of the sensing performance for nano-enabled sensors in currently explored electrochemical, spectrophotometric, colorimetric, optical, fluorometric, and biochemical with limits of detection of 1.02 × 10^-6 μg/L, 2.8 μg/L, 1 μg/L, 0.13 μg/L, 6.0 × 10^-5 μg/L, and 4.141 × 10^-7 μg/L respectively. The cost-effectiveness of sensing platforms plays an important role in the on-site analysis success and upscalability of nano-enabled sensors. Environmental monitoring of PFAS is a step closer to PFAS remediation. Electrochemical and biosensing methods have proven to be the most reliable tools for future PFAS sensing endeavors with very promising detection limits in an aqueous matrix, short detection times, and ease of fabrication.

Cell-Based Chemical Safety Assessment and Therapeutic Discovery Using Array-Based Sensors

Synthetic chemicals are widely used in food, agriculture, and medicine, making chemical safety assessments necessary for environmental exposure. In addition, the rapid determination of chemical drug efficacy and safety is a key step in therapeutic discoveries. Cell-based screening methods are non-invasive as compared with animal studies. Cellular phenotypic changes can also provide more sensitive indicators of chemical effects than conventional cell viability. Array-based cell sensors can be engineered to maximize sensitivity to changes in cell phenotypes, lowering the threshold for detecting cellular responses under external stimuli. Overall, array-based sensing can provide a robust strategy for both cell-based chemical risk assessments and therapeutics discovery.

Engineering ligand-specific biosensors for aromatic amino acids and neurochemicals

Microbial biosensors have diverse applications in metabolic engineering and medicine. Specific and accurate quantification of chemical concentrations allows for adaptive regulation of enzymatic pathways and temporally precise expression of diagnostic reporters. Although biosensors should differentiate structurally similar ligands with distinct biological functions, such specific sensors are rarely found in nature and challenging to create. Using E. coli Nissle 1917, a generally regarded as safe microbe, we characterized two biosensor systems that promiscuously recognize aromatic amino acids or neurochemicals. To improve the sensors' selectivity and sensitivity, we applied rational protein engineering by identifying and mutagenizing amino acid residues and successfully demonstrated the ligand-specific biosensors for phenylalanine, tyrosine, phenylethylamine, and tyramine. Additionally, our approach revealed insights into the uncharacterized structure of the FeaR regulator, including critical residues in ligand binding. These results lay the groundwork for developing kinetically adaptive microbes for diverse applications. A record of this paper's transparent peer review process is included in the supplemental information.

Plastic Waste Precursor-Derived Fluorescent Carbon and Construction of Ternary FCs@CuO@TiO2 Hybrid Photocatalyst for Hydrogen Production and Sensing Application

A sustainable nexus between renewable energy production and plastic abatement is imperative for overall sustainable development. In this regard, this study aims to develop a cheaper and environmentally friendly nexus between plastic waste management, wastewater treatment, and renewable hydrogen production. Fluorescent carbon (FCs) were synthesized from commonly used LDPE (low-density polyethylene) by a facile hydrothermal approach. Optical absorption study revealed an absorption edge around 300 nm and two emission bands at 430 and 470 nm. The morphological analysis showed two different patterns of FCs, a thin sheet with 2D morphology and elongated particles. The sheet-shaped particles are 0.5 μm in size, while as for elongated structures, the size varies from 0.5 to 1 μm. The as-synthesized FCs were used for the detection of metal ions (reference as Cu2+ ions) in water. The fluorescence intensity of FCs versus Cu2+ ions depicts its upright analytical ability with a limit of detection (LOD) reaching 86.5 nM, which is considerably lesser than earlier reported fluorescence probes derived from waste. After the sensing of Cu2+, the as-obtained FCs@Cu2+ was mixed with TiO2 to form a ternary FCs@CuO@TiO2 composite. This ternary composite was utilized for photocatalytic hydrogen production from water under 1.5 AM solar light irradiation. The H2 evolution rate was found to be ~1800 μmolg−1, which is many folds compared to the bare FCs. Moreover, the optimized FCs@CuO@TiO2 ternary composite showed a photocurrent density of ~2.40 mA/cm2 at 1 V vs. Ag/AgCl, in 1 M Na2SO4 solution under the illumination of simulated solar light. The achieved photocurrent density corresponds to the solar-to-hydrogen (STH) efficiency of ~0.95%. The efficiency is due to the fluorescence nature of FCs and the synergistic effect of CuO embedded in TiO2, which enhances the optical absorption of the composite by reaching the bandgap of 2.44 eV, apparently reducing the recombination rate, which was confirmed by optoelectronic, structural, and spectroscopic characterizations.

EBC-SURE (exhaled breath condensate- scanning using rapid electro analytics): A non-faradaic and non-invasive electrochemical assay to screen for pro-inflammatory biomarkers in human breath condensate

The innovation of this work lies in the trace detection of inflammatory biomarkers (IL-6, hs-CRP) in human exhaled breath condensate on the developed EBC-SURE platform as a point-of-care aid for respiratory disorder diagnosis. The unique design of the EBC-SURE leverages non-faradaic electrochemical impedance spectroscopy to capture target-specific biomolecular interactions for highly sensitive biomarker detection. For sensor calibration, EBC-SURE's performance is assessed to measure the response of the sensor to a known concentration by spike and recovery analysis with a recovery error of <20% and an extended dynamic range over 3-log orders. The lowest detection limits for IL-6 and hs-CRP detection in EBC were found to be 3.2 pg/mL and 4 pg/mL respectively. The intra-assay and inter-assay efficacy of EBC-SURE for its usage as a diagnostic device was established through repeatability and reproducibility (over 48 h s) performance testing. The percentage variations (<20%) met the Clinical and Laboratory Standards Institute standards (CLSI) indicating a highly stable performance for robust biomarker detection. EBC-SURE generated highly selective IL-6 and hs-CRP responses in the presence of other non-specific cytokines. Statistical validation methods- Correlation and Bland Altman analysis established the one-to-one agreement between EBC-SURE and the reference method. Correlation analysis generated a Pearson's R value of 0.99 for IL-6 and hs-CRP. Bland-Altman analysis indicated a good agreement between both the methods with all data points confined within the ±2SD limits. We have demonstrated EBC-SURE's ability in detecting inflammatory biomarkers in human breath condensate towards developing a non-invasive technology that can quantify biomarker levels associated with healthy and acute inflammatory conditions.

Context-Aware Diagnostic Specificity (CADS)

Rapid detection of proteins is critical in a vast array of diagnostic or monitoring applications [...].

Nucleic acid-based electrochemical biosensors for rapid clinical diagnosis: Advances, challenges, and opportunities

Clinical diagnostic tests should be quick, reliable, simple to perform, and affordable for diagnosis and treatment of diseases. In this regard, owing to their novel properties, biosensors have attracted the attention of scientists as well as end-users. They are efficient, stable, and relatively cheap. Biosensors have broad applications in medical diagnosis, including point-of-care (POC) monitoring, forensics, and biomedical research. The electrochemical nucleic acid (NA) biosensor, the latest invention in this field, combines the sensitivity of electroanalytical methods with the inherent bioselectivity of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA). The NA biosensor exploits the affinity of single-stranded DNA/RNA for its complementary strand and is used to detect complementary sequences of NA based on hybridization. After the NA component in the sensor detects the analyte, a catalytic reaction or binding event that generates an electrical signal in the transducer ensues. Since 2000, much progress has been made in this field, but there are still numerous challenges. This critical review describes the advances, challenges, and prospects of NA-based electrochemical biosensors for clinical diagnosis. It includes the basic principles, classification, sensing enhancement strategies, and applications of biosensors as well as their advantages, limitations, and future prospects, and thus it should be useful to academics as well as industry in the improvement and application of EC NA biosensors.

Multichannel dual protein sensing using amphiphilic supramolecular assemblies

Protein sensing strategies have implications in detection of many human pathologies. Here, a supramolecular strategy for sensing two different proteins using a multichannel readout approach is outlined. Protein-ligand binding or enzymatic cleavage can both be programmed to induce supramolecular disassembly, which leads to fluorescence enhancement via aggregation-induced emission (AIE), protein-induced fluorescence enhancement (PIFE), or disassembly-induced fluorescence enhancement (DIFE). The accompanying signal change from two different fluorophores and their patterns are then used for specific protein sensing.

Portable Tools for COVID-19 Point-of-Care Detection: A Review

Recently, several methods for SARS-CoV-2 detection have been developed to obtain rapid, portable, cheap, and easy-to-use diagnostic tools. This review paper summarizes and discusses studies on the development of point-of-care devices for SARS-CoV-2 diagnosis with comparisons between them from several aspects. Various detection methods of the recently developed portable COVID-19 biosensor will be presented in this review. The discussion is divided into four major classifications based on the target biomarkers of SARS-CoV-2, such as antibodies, nucleic acids, antigens, and metabolic products. An overview of the potential development for future study is also provided. Moreover, basic knowledge of biosensors is also explained for tutoring the implementation of theory into the research of COVID-19 biosensors. This review paper is aimed to provide a tutorial by collecting the information on the development of a point-of-care device for SARS-CoV-2 detection to provide information for further research and propose the new COVID-19 portable diagnostic tool.

Harnessing selectivity in chemical sensing via supramolecular interactions: from functionalization of nanomaterials to device applications

Chemical sensing is a strategic field of science and technology ultimately aiming at improving the quality of our lives and the sustainability of our Planet. Sensors bear a direct societal impact on well-being, which includes the quality and composition of the air we breathe, the water we drink, and the food we eat. Pristine low-dimensional materials are widely exploited as highly sensitive elements in chemical sensors, although they suffer from lack of intrinsic selectivity towards specific analytes. Here, we showcase the most recent strategies on the use of (supra)molecular interactions to harness the selectivity of suitably functionalized 0D, 1D, and 2D low-dimensional materials for chemical sensing. We discuss how the design and selection of receptors via machine learning and artificial intelligence hold a disruptive potential in chemical sensing, where selectivity is achieved by the design and high-throughput screening of large libraries of molecules exhibiting a set of affinity parameters that dictates the analyte specificity. We also discuss the importance of achieving selectivity along with other relevant characteristics in chemical sensing, such as high sensitivity, response speed, and reversibility, as milestones for true practical applications. Finally, for each distinct class of low-dimensional material, we present the most suitable functionalization strategies for their incorporation into efficient transducers for chemical sensing.

Photoluminescent Nanoparticles for Chemical and Biological Analysis and Imaging

Research related to the development and application of luminescent nanoparticles (LNPs) for chemical and biological analysis and imaging is flourishing. Novel materials and new applications continue to be reported after two decades of research. This review provides a comprehensive and heuristic overview of this field. It is targeted to both newcomers and experts who are interested in a critical assessment of LNP materials, their properties, strengths and weaknesses, and prospective applications. Numerous LNP materials are cataloged by fundamental descriptions of their chemical identities and physical morphology, quantitative photoluminescence (PL) properties, PL mechanisms, and surface chemistry. These materials include various semiconductor quantum dots, carbon nanotubes, graphene derivatives, carbon dots, nanodiamonds, luminescent metal nanoclusters, lanthanide-doped upconversion nanoparticles and downshifting nanoparticles, triplet-triplet annihilation nanoparticles, persistent-luminescence nanoparticles, conjugated polymer nanoparticles and semiconducting polymer dots, multi-nanoparticle assemblies, and doped and labeled nanoparticles, including but not limited to those based on polymers and silica. As an exercise in the critical assessment of LNP properties, these materials are ranked by several application-related functional criteria. Additional sections highlight recent examples of advances in chemical and biological analysis, point-of-care diagnostics, and cellular, tissue, and in vivo imaging and theranostics. These examples are drawn from the recent literature and organized by both LNP material and the particular properties that are leveraged to an advantage. Finally, a perspective on what comes next for the field is offered.

Gold nanoparticles-mediated fluorescent chemical nose sensor for pathogenic diagnosis and phenotype

Pathogens are one of the important factors affecting national economic construction. An ideal detection system for pathogen control with excellent sensitivity, high specificity, and time-saving is needed. Here, we reported a method for bacterial detection using gold nanoparticles-mediated fluorescent "chemical nose" sensors (GFCEs). The technique consists of gold nanoparticles-coated magnetic particle using benzaldehyde, octyl aldehyde, and pyrimidine-4-formaldehyde modified, respectively. And these positively charged nanocompound interacting with three different fluorescent proteins (FPs) to form three kinds of GFCEs, respectively, named GFCE1, GFCE2, and GFCE3. Upon binding with pathogenic cells, functionalized gold nanoparticles could identify patches on hydrophobic/functional surfaces of microorganisms, and self-assemble with living bacteria by complementary electrostatic interactions. The binding ability between GFCEs and bacteria determines the change of fluorescence response of three FPs from GFCEs. These feature fluorescent level are pathogen-specific, highly repeatable, and can be analyzed by Linear Discriminant Analysis (LDA). The combination of GFCE1 and GFCE2 has the best performance when detecting pathogens with concentrations of 10⁶  cfu mL^-1 . The first discriminant within 15 minutes is 93.8%, which could be used for subsequent identification of unknown samples. The commonly applicable system provides a simple way for the rapid bacterial detection without preprocessing procedures.