Identification and Detection of Volatile Aldehydes as Lung Cancer Biomarkers by Vapor Generation Combined with Paper-Based Thin-Film Microextraction

Diagnosis and classification of kidney transplant rejection using machine learning-assisted surface-enhanced Raman spectroscopy using a single drop of serum

The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technologies. These technologies aim to detect antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR), which are asymptomatic and pose a risk of potential kidney damage. The protocols for managing rejection caused by ABMR and TCMR differ, and diagnosis has traditionally relied on invasive biopsy procedures. Therefore, a convergence system using a nano-sensing chip, Raman spectroscopy, and AI technology was introduced to facilitate diagnosis using serum samples obtained from patients with no major abnormality, ABMR, and TCMR after kidney transplantation. Tissue biopsy and Banff score analysis were performed across the groups for validation, and 5 μL of serum obtained at the same time was added onto the Au-ZnO nanorod-based Surface-Enhanced Raman Scattering sensing chip to obtain Raman spectroscopy signals. The accuracy of machine learning algorithms for principal component-linear discriminant analysis and principal component-partial least squares discriminant analysis was 93.53% and 98.82%, respectively. The collagen (an indicative of kidney injury), creatinine, and amino acid-derived signals (markers of kidney function) contributed to this accuracy; however, the high accuracy was primarily due to the ability of the system to analyze a broad spectrum of various biomarkers.

All-in-one spot test method for tetracycline using molecularly imprinted polymer-coated paper integrated into a portable 3D printed platform with smartphone-based fluorescent detection

A molecularly imprinted polymer (MIP) has been synthetized, characterized, impregnated on paper, and integrated into a 3D printed platform with smartphone-based fluorescent detection for the determination of tetracycline in water samples. The MIP synthesis was performed by precipitation polymerization, which was subsequently deposited onto a glass microfiber paper. The synthesized polymer and the MIP@paper have been characterized by FTIR spectroscopy, scanning electron microscopy, and EDS spectroscopy. Afterward, a 3D printed detection platform that houses monochromatic LED strips as radiation source and a smartphone as detector have been used for determination of tetracycline. Digital image processing was based on the RGB colour model using image J software and the red intensity channel was used as analytical signal due to its higher sensitivity. Several factors that affect the adsorption capacity and fluorescent detection have been optimized. Under optimum conditions, detection limit of 0.04 mg L-1 and good linearity up 5 mg L-1 (r = 0.998), were achieved. The intra- and inter-day precision of 4.9 and 7.2 %, respectively, expressed as relative standard deviation (%RSD) were obtained, showing the good precision of the proposed methodology. Satisfactory recoveries between 87 and 98 % were obtained spiking real water sample matrices at different concentrations (0.1-0.3 mg L-1). The portable 3D platform with smartphone-based fluorescent detection exploiting all-in-one spot test method for tetracycline using MIP@paper was evaluated with AGREE and GAPI metrics, evidencing its environmentally friendly approach. Furthermore, the BAGI tool demonstrated the practicality of the method, in terms of functionality and applicability compared to previous HPLC and spectrofluorometric methods.

Reaction-Modulated Surface-Enhanced Raman Scattering Strategy for Stereoselective Differentiation and Identification of Amino Acids

Surface-enhanced Raman scattering (SERS) sensing of racemates is a remarkably fascinating yet very sophisticated objective because of similar physicochemical features of enantiomers. Inspired by the enantiomeric selectivity of nucleophilic addition reaction (NAR) toward amino acids, we herein propose highly effective, robust SERS discrimination of d- and l-valine by synergizing asymmetric gold nanorods-embedded ZIF-8 nanoparticles (AGNZ) with NAR to engender stereoselective molecular fingerprint. Experimental and chemometric analyses disclose that enantioselectivity lies in dual aspects: (i) abundant interfacial cavities and 3D hot-spots in AGNZ offer necessary confined asymmetrical surroundings to trigger enantiospecific molecular adsorption and interaction affinity, and (ii) the specified NAR drags the racemates adjacent to the interfacial area of AGNZ for maximum analytes-substrate interaction. This strategy is universal and can be utilized for the recognition of different amino acid enantiomers. Importantly, multiple quantifications of the racemic ratio can be realized with superior prognostic performances. This synergizing strategy therefore provides a significant paradigm shift from traditional methods to realize highly effective SERS discrimination of racemates.

Effect of amino acids on the formation and distribution of volatile aldehydes in high oleic sunflower oil during frying

This research aims to assess the effect of amino acids as lipid antioxidants in reducing the formation of volatile aldehydes in frying oil. Methionine, histidine, and glycine at concentrations of 2.5, 5, and 10 mM were added to high oleic sunflower oil (HOSO) to investigate their effects on the distribution and formation of saturated, monounsaturated, and polyunsaturated volatile aldehydes. The results showed that the proportion of saturated volatile aldehydes was greater than that of unsaturated ones; Methionine exhibited the best inhibitory effect, after 12 h of frying, 10 mM methionine reduced the content of saturated volatile aldehydes by 24.21 %, monounsaturated by 52.4 %, and polyunsaturated by 54.73 % compared to the control. Methionine's sulfur-containing side chain was also proven to have strong antioxidant activity. Combined with the results of this study, this can also provide insights for using amino acids as lipid antioxidants.

Yolk-Shell Hierarchical Pore Au@MOF Nanostructures: Efficient Gas Capture and Enrichment for Advanced Breath Analysis

Surface-enhanced Raman scattering (SERS) offers a promising, cost-effective alternative for the rapid, sensitive, and quantitative analysis of potential biomarkers in exhaled gases, which is crucial for early disease diagnosis. However, a major challenge in SERS is the effective detection of gaseous analytes, primarily due to difficulties in enriching and capturing them within the substrate's "hotspot" regions. This study introduces an advanced gas sensor combining mesoporous gold (MesoAu) and metal-organic frameworks (MOFs), exhibiting high sensitivity and rapid detection capabilities. The MesoAu provides abundant active sites and interconnected mesopores, facilitating the diffusion of analytes for detection. A ZIF-8 shell enveloping MesoAu further enriches target molecules, significantly enhancing sensitivity. A proof-of-concept experiment demonstrated a detection limit of 0.32 ppb for gaseous benzaldehyde, indicating promising prospects for the rapid diagnosis of early stage lung cancer. This research also pioneers a novel approach for constructing hierarchical plasmonic nanostructures with immense potential in gas sensing.

Urchin-like covalent organic frameworks templated Au@Ag composites for SERS detection of emerging contaminants

Au@Ag core-shell composites were successfully fabricated on urchin-like covalent organic frameworks (COFs), providing a platform with numerous hot spots for the detection of two categories of emerging contaminants: sulfonamide antibiotics and nanoplastics, using surface-enhanced Raman spectroscopy (SERS). Au seeds (∼10 nm) were generated on the COFs, leveraging the reducing properties of the vinyl and imino groups within the framework. This ensured the growth of dense and uniformly distributed Ag nanoparticles. The COFs exceptionally large surface area (2324 m2 g-1) and high adsorption capacity, significantly contributed to the enrichment and detection of trace pollutants. As a result, using a portable Raman spectrometer, limits of detection of 0.008 μmol L-1 for sulfamethoxazole and 0.029 mg L-1 for polystyrene nanoplastics were achieved.

Recent Advances on the Metal-Organic Frameworks-Based Biosensing Methods for Cancer Biomarkers Detection

Sensitive and selective detection of cancer biomarkers is crucial for early diagnosis and treatment of cancer, one of the most dangerous diseases in the world. Metal-organic frameworks (MOFs), a class of hybrid porous materials fabricated through the assembly of metal ions/clusters and organic ligands, have attracted increasing attention in the sensing of cancer biomarkers, due to the advantages of adjustable size, high porosity, large surface area and ease of modification. MOFs have been utilized to not only fabricate active sensing interfaces but also arouse a variety of measurable signals. Several representative analytical technologies have been applied in MOF-based biosensing strategies to ensure high detection sensitivity toward cancer biomarkers, such as fluorescence, electrochemistry, electrochemiluminescence, photochemistry and colorimetric methods. In this review, we summarized recent advances on MOFs-based biosensing strategies for the detection of cancer biomarkers in recent three years based on the categories of metal nodes, and aimed to provide valuable references for the development of innovative biosensing platform for the purpose of clinical diagnosis.

Metal-Organic Frameworks in Surface Enhanced Raman Spectroscopy-Based Analysis of Volatile Organic Compounds

Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on-site detection without complex sample preparation. Surface-Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal-Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre-concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF-based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.

Plasmonic trimers designed as SERS-active chemical traps for subtyping of lung tumors

Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the 'hotspots', which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where 'hotspots' are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10-14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.

All-in-One Electrokinetic Strategy Coupled with a Miniaturized Chip for SERS Detection of Multipesticides

Complexed and tiresome pretreatment processes have significantly impeded in-field analysis of environmental specimens. Herein, an all-in-one sample separation and enrichment strategy based on a compact charge-selective capture/nanoconfined enrichment (CSC/NCE) device is exploited for marker-free surface-enhanced Raman spectroscopy (SERS) detection of charged pesticides in matrix specimens. This tactic incorporating in situ separations, seizing, and nanoconfined enhancement can greatly elevate the effectiveness of sample pretreatment. Importantly, CSC/NCE with excellent adsorption performances and excellent plasmonic features facilitates concentration and signal amplification of electrically charged pesticides. With the introduction of an electric field on this integrated CSC/NCE, the matrix effect in samples could be significantly eradicated, and a distinct SERS response is witnessed for targeted analytes. Accurate quantification of multipesticides is achieved by synergizing the CSC/NCE chip and chemometrics, and the contents found by the CSC/NCE-based sensing strategy agree with those obtained from chromatography assays with relative deviations lower than 10%. The facile and versatile all-in-one tactic infused in a compact chip exhibits enormous potential for field-test application in chemical measurement and food safety.

SERS-based AI diagnosis of lung and gastric cancer via exhaled breath

Distinct diagnosis between Lung cancer (LC) and gastric cancer (GC) according to the same biomarkers (e.g. aldehydes) in exhaled breath based on surface-enhanced Raman spectroscopy (SERS) remains a challenge in current studies. Here, an accurate diagnosis of LC and GC is demonstrated, using artificial intelligence technologies (AI) based on SERS spectrum of exhaled breath in plasmonic metal organic frameworks nanoparticle (PMN) film. In the PMN film with optimal structure parameters, 1780 SERS spectra are collected, in which 940 spectra come from healthy people (n = 49), another 440 come from LC patients (n = 22) and the rest 400 come from GC patients (n = 8). The SERS spectra are trained through artificial neural network (ANN) model with the deep learning (DL) algorithm, and the result exhibits a good identification accuracy of LC and GC with an accuracy over 89 %. Furthermore, combined with information of SERS peaks, the data mining in ANN model is successfully employed to explore the subtle compositional difference in exhaled breath from healthy people (H) and L/GC patients. This work achieves excellent noninvasive diagnosis of multiple cancer diseases in breath analysis and provides a new avenue to explore the feature of disease based on SERS spectrum.

Strategic Design of Non-d10 Luminescent Metal-Organic Frameworks as Dual-Mode Ultrafast and Selective Sensing Platforms for Aldehydes at the ppb Level

Utilizing a cautious design of luminescent MOFs of non-d10 divalent transition metals based on two factors (metal nodes in an octahedral geometry to minimize nonradiative energy dissipation and tailored organic chromophores), this work reports {[Ni2(oxdz)2(tpbn)]}n (1), {[Ni2(oxdz)2(tphn)]}n (2), and {[Ni2(oxdz)2(tpon)]}n (3), synthesized at room temperature, varying the spacer length of tpbn/tphn/tpon (four, six, and eight CH2 groups, respectively). This subtle change in 1-3 is correlated to their hydrophobicity and polarizing power via water vapor sorption and selective and sensitive detection of aldehydes at the ppb level, respectively. A decrease in water vapor uptake (14.8, 8.95, and 3.19 mmol g-1 for 1-3, respectively) is observed with an increase in their hydrophobicity. On the other hand, the solution phase detection limits of acetaldehyde and benzaldehyde (2.42 and 6.71 ppb for 1, 2.77 and 4.08 ppb for 2, and 10.35 and 10.4 ppb for 3, respectively) show a similar trend for their polarizing power. The best performance of 1 is expanded to the vapor-phase detection of acetaldehyde (297% luminescence enhancement) under different pH conditions. The second mode of detection of acetaldehyde via the metal-centered electrochemical behavior of 1 provides detection limits of 38.2 and 71.5 ppb at pH 7 and 13, respectively.

SERS-Based Hydrogen Bonding Induction Strategy for Gaseous Acetic Acid Capture and Detection

Surface-enhanced Raman scattering (SERS) can overcome the existing technological limitations, such as complex processes and harsh conditions in gaseous small-molecule detection, and advance the development of real-time gas sensing at room temperature. In this study, a SERS-based hydrogen bonding induction strategy for capturing and sensing gaseous acetic acid is proposed for the detection demands of gaseous acetic acid. This addresses the challenges of low adsorption of gaseous small molecules on SERS substrates and small Raman scattering cross sections and enables the first SERS-based detection of gaseous acetic acid by a portable Raman spectrometer. To provide abundant hydrogen bond donors and acceptors, 4-mercaptobenzoic acid (4-MBA) was used as a ligand molecule modified on the SERS substrate. Furthermore, a sensing chip with a low relative standard deviation (RSD) of 4.15% was constructed, ensuring highly sensitive and reliable detection. The hydrogen bond-induced acetic acid trapping was confirmed by experimental spectroscopy and density functional theory (DFT). In addition, to achieve superior accuracy compared to conventional methods, an innovative analytical method based on direct response hydrogen bond formation (IO-H/Iref) was proposed, enabling the detection of gaseous acetic acid at concentrations as low as 60 ppb. The strategy demonstrated a superior anti-interference capability in simulated breath and wine detection systems. Moreover, the high reusability of the chip highlights the significant potential for real-time sensing of gaseous acetic acid.

A fluorescence and SERS dual-mode sensing on tetracycline antibiotics based on Ag@NH2-MIL-101(Al) nanoprobe

Antibiotic residues are becoming more and more concern due to the increasingly serious resistance from bacteria to organism. On-site and accurate evaluation on antibiotics is necessary and urgent to effectively solve such public issue. To provide point-of-care-test (POCT) ideas for antibiotic accurate evaluation, a fluorescence (FL)-surface-enhanced Raman scattering (SERS) dual-mode detection of tetracycline antibiotic (TCs) was realized for the first time. Based on the inner filter effect in Ag@NH2-MIL-101(Al) nanoprobe, the fluorescence quenching was induced and the SERS signal was swiftly turn on through π-π interaction and hydrogen bonding in the presence of TCs. This FL-SERS dual mode sensor displayed excellent detection limits (FL in ∼10-3 ppm, SERS in ∼10-5 ppm), and achieved a reliable detection of TCs in honey with a recovery rate of 84.45%-112.08%. This method combines the advantages of FL and SERS detection, meanwhile, two techniques verified against each other to achieve highly sensitive and specific FL-SERS dual-mode sensor for TCs. We believe that such antibody-or aptamer-independent FL and SERS complementary nanoprobe can be applied to fast, direct and multiple sensing in environment and food hazards.

When it is too much: Identifying butamben excess on the surface of pharmaceutical preformulation samples by Raman mapping

Butamben is a topical local anesthetic which formulation in lipid-based drug delivery systems (DDS) is challenging due to its affinity for hydrophilic excipients. This means that a medium polarity excipient is preferred for the development of a stable nanostructured lipid carrier (NLC) formulation. In turn, in NLC, the type and number of excipients will determine the active pharmaceutical ingredient (API) solubility and the maximum drug upload. To solve this dilemma and get the best formulation, a throughout screening study to evaluate API solubilization in different excipients was carried out. Subsequently, excipients with different solubilization capacities were selected for microscopic evaluation by Raman mapping, and in turn analysis of the distributional homogeneity index (DHI) and standard deviation of the histograms allowed solving the posed question. Design of experiments (DoE) was employed to understand better the interactions between the excipients; linear and higher-order models were obtained with R2 above of 0.8824. Even though DHI is a good parameter to be used as response, an API concentration higher than 30% (w/w) provided a homogeneous surface in case of good miscibility and, in this case, this parameter needs to be employed with an inspection and/or evaluation of other parameters. A curve of concentration vs. mean scores of images proved to be an alternative to identify the saturation/limit of linear range.

Portable SERS sensing of volatile aldehydes in alcohols by aldol condensation reaction on liquid interfacial plasmonic arrays

An aldol condensation reaction on oil-in-water (O/W) liquid interfacial plasmonic arrays was developed for sensing volatile aldehydes in alcohols by using an aromatic aldehyde as the probe for portable SERS assays. The detection limit was 10-8 M. The substrate exhibited an RSD value of 6.9%, and the probe showed good selectivity to four common interferences.

Identification and Detection of Intracellular Reactive Sulfur Species Using a Reaction-Mediated Dual-Recognition Strategy

Reactive sulfur species (RSS) are emerging as a potential key gasotransmitter in diverse physiological processes linking two signaling molecules H2S and SO2. However, the exact roles of H2S and SO2 remain unclear. A major hurdle is the shortage of accurate and robust approaches for sensing of H2S and SO2 in biological systems. Herein, we report a reaction-mediated dual-recognition strategy-based nanosensor, silver nanoparticles (AgNPs)-loaded MIL-101 (Fe) (ALM) hybrids, for the simultaneous detection of H2S and SO2 in a living cell. Upon exposure to H2S, AgNPs can be oxidized to form Ag2S, causing a decrease of surface enhanced Raman spectroscopy (SERS) signals of p,p'-dimercaptoazobenzene. Moreover, SO2 reacts with the amino moiety of MIL-101 to form charge-transfer complexes, resulting in an increment of fluorescent (FL) intensity. The ALM with dual-modal signals can simultaneously analyze H2S and SO2 at a concentration as low as 2.8 × 10-6 and 0.003 μM, respectively. Most importantly, the ALM sensing platform enables targeting mitochondria and detection multiple RSS simultaneously in living cells under external stimulation, as well as displays indiscernible crosstalk between SERS and FL signals, which is very beneficial for the comprehension of physiological issues related with RSS.

Early-stage oral cancer diagnosis by artificial intelligence-based SERS using Ag NWs@ZIF core-shell nanochains

Surface-enhanced Raman spectroscopy (SERS) has great potential in the early diagnosis of diseases by detecting the changes of volatile biomarkers in exhaled breath, because of its high sensitivity, rich chemical molecular fingerprint information, and immunity to humidity. Here, an accurate diagnosis of oral cancer (OC) is demonstrated using artificial intelligence (AI)-based SERS of exhaled breath in plasmonic-metal organic framework (MOF) nanoparticles. These plasmonic-MOF nanoparticles were prepared using a zeolitic imidazolate framework coated on Ag nanowires (Ag NWs@ZIF), which offers Raman enhancement from the plasmonic nanowires and gas enrichment from the ZIF shells. Then, the core-shell nanochains of Ag NWs@ZIF prepared with 0.5 mL Ag NWs were selected to capture gaseous methanethiol, which is a tumor biomarker, from the exhalation of OC patients. The substrate was used to collect a total of 400 SERS spectra of exhaled breath of simulated healthy people and simulated OC patients. The artificial neural network (ANN) model in the AI algorithm was trained with these SERS spectra and could classify them with an accuracy of 99%. Notably, the model predicted OC with an area under the curve (AUC) of 0.996 for the simulated OC breath samples. This work suggests the great potential of the combination of breath analysis and AI as a method for the early-stage diagnosis of oral cancer.

Evaluation of Linkers' Influence on Peptide-Based Piezoelectric Biosensors' Sensitivity to Aldehydes in the Gas Phase

Recent findings qualified aldehydes as potential biomarkers for disease diagnosis. One of the possibilities is to use electrochemical biosensors in point-of-care (PoC), but these need further development to overcome some limitations. Currently, the primary goal is to enhance their metrological parameters in terms of sensitivity and selectivity. Previous findings indicate that peptide OBPP4 (KLLFDSLTDLKKKMSEC-NH₂) is a promising candidate for further development of aldehyde-sensitive biosensors. To increase the affinity of a receptor layer to long-chain aldehydes, a structure stabilization of the peptide active site via the incorporation of different linkers was studied. Indeed, the incorporation of linkers improved sensitivity to and binding of aldehydes in comparison to that of the original peptide-based biosensor. The tendency to adopt disordered structures was diminished owing to the implementation of suitable linkers. Therefore, to improve the metrological characteristics of peptide-based piezoelectric biosensors, linkers were added at the C-terminus of OBPP4 peptide (KLLFDSLTDLKKKMSE-linker-C-NH₂). Those linkers consist of proteinogenic amino acids from group one: glycine, L-proline, L-serine, and non proteinogenic amino acids from group two: β-alanine, 4-aminobutyric acid, and 6-aminohexanoic acid. Linkers were evaluated with in silico studies, followed by experimental verification. All studied linkers enhanced the detection of aldehydes in the gas phase. The highest difference in frequency (60 Hz, nonanal) was observed between original peptide-based biosensors and ones based on peptides modified with the GSGSGS linker. It allowed evaluation of the limit of detection for nonanal at the level of 2 ppm, which is nine times lower than that of the original peptide. The highest sensitivity values were also obtained for the GSGSGS linker: 0.3312, 0.4281, and 0.4676 Hz/ppm for pentanal, octanal, and nonanal, respectively. An order of magnitude increase in sensitivity was observed for the six linkers used. Generally, the linker's rigidity and the number of amino acid residues are much more essential for biosensors' metrological characteristics than the amino acid sequence itself. It was found that the longer the linkers, the better the effect on docking efficiency.

Detection of gases and organic vapors by cellulose-based sensors

The growing interest in the development of cost-effective, straightforward, and rapid analytical systems has found cellulose-based materials, including cellulose derivatives, cellulose-based gels, nanocellulosic materials, and the corresponding (nano)cellulose-based composites, to be valuable platforms for sensor development. The present work presents recent advances in the development of cellulose-based sensors for the determination of volatile analytes and derivatives of analytical relevance. In particular, strategies described in the literature for the fabrication and modification of cellulose-based substrates with responsive materials are summarized. In addition, selected contributions reported in the field of paper-based volatile sensors are discussed, with a particular emphasis on quick response (QR) code paper-based platforms, intelligent films for food freshness monitoring, and sensor arrays for volatile discrimination purposes. Furthermore, analytical strategies devised for the determination of ionic species by in situ generation of volatile derivatives in both paper-based analytical devices (PADs) and microfluidic PADs will also be described.

Combining microfluidic paper-based platform and metal-organic frameworks in a single device for phenolic content assessment in fruits

A microfluidic paper-based device (µPAD) has been combined with metal-organic frameworks (MOFs) for total phenolic compounds (TPC) quantification in fruit samples for the first time. The performance of the µPAD, based upon the vertical flow approach, was enhanced in order to determine the TPC content with high accuracy in fruit samples. The method was based on the traditional Folin-Ciocalteu Index using gallic acid or oenotannin as reference phenolic compounds. This novel design and construction of the device are in agreement with the principles of Green Chemistry avoiding wax technology (lower toxicity). The analytical parameters that affect the colorimetric method (using digital imaging of the colored zone) performance were optimized including design, sample volume, and MOF amount. Then, the analytical features of the developed method were investigated such as dynamic range (1.6-30 mg L^-1), limit of detection (0.5 mg L^-1), and precision (RSD < 9%). Besides, the in-field analysis is achievable with a color stability up to 6 h after the loading process of the sample and storage stability for at least 15 days without performance losses (under vacuum at - 20 °C). Furthermore, the MOF ZIF-8@paper was characterized to study its composition and the successful combination. The feasibility of the proposed method was demonstrated by determining the TPC in 5 fruit samples using oenotannin as reference solute. The accuracy was validated by comparison of the data with the results obtained with the recommended protocol proposed by the International Organisation of Vine and Wine (OIV).

Two Co-Based Metal-Organic Framework Isomers with Similar Metal-Carboxylate Sheets: Turn-On Ratiometric Luminescence Sensing Activities toward Biomarker N-Acetylneuraminic Acid and Discrimination of Ga3+ and In3

Two supramolecular Co-MOF isomers, namely, {[Co(L)_0.5(m-bimb)]·3H₂O}_n (LCU-115) and {[Co(L)_0.5(p-bimb)]·3H₂O}_n (LCU-116), were synthesized from an amide-containing carboxylic acid N,N″-(3,5-dicarboxylphenyl)benzene-1,4-dicarboxamide (H₄L) and two flexible positional isostructural N-containing ligands m-bimb and p-bimb (m-bimb = 1,3-bis((1H-imidazol-1-yl)methyl)benzene; p-bimb = 1,4-bis((1H-imidazol-1-yl)methyl)benzene). The carboxylate ligands connect Co(II) centers to form 2D metal-carboxylate sheets, which are extended further by m-bimb and p-bimb to form a 2D bilayer with parallel stacking (LCU-115) and a 3D framework (LCU-116), respectively. Luminescence measurements indicated that these two complexes exhibited interesting multiresponsive sensing activities toward pH, biomarker N-acetylneuraminic acid, and trivalent cations Ga³⁺/In³⁺. They show highly sensitive turn-on fluorescence responses in the acidic range and can also be regarded as on-off-on vapoluminescent sensors to typical acidic and basic gases HCl and Et₃N. It is worth noting that these complexes have excellent turn-on ratiometric fluorescence sensing ability for N-acetylneuraminic acid (NANA) with detection limits as low as 7.39 and 8.06 μM, respectively. Furthermore, they were successfully applied for the detection of NANA in simulated urine and serum samples with satisfactory results. For ion detection, LCU-116 could detect both Ga³⁺ and In³⁺, while LCU-115 could distinguish Ga³⁺ from In³⁺ with the latter showing luminescence quenching. The sensing mechanism was investigated in detail by XRD, UV-vis, EDS, XPS, SEM, and TEM. The results of interday and intraday precision studies gave low RSD values in the range of 1.19-3.53%, ascertaining the reproducibility of these sensors. The recoveries for the sensing analytes in simulated urine/serum or real water are satisfactory from 96.7 to 103.3% (toward NANA) and 96.6 to 115.0% (toward Ga³⁺ and In³⁺), indicating that these two complexes also possess acceptable reliability for monitoring in real samples. The results indicated that the supramolecular isomers LCU-115 and LCU-116 are promising material candidates for application in biological and environmental monitoring.

Preparation of SERS active filter paper for filtration and detection of pesticides residue from complex sample

The selectivity is needed mostly in SERS sensing because analytes of interest are commonly present in a complex mixture containing particles and impurities, which hinder the interactions between the laser and analyte being detected. In this manuscript, we describe our efforts developing a simple and instant. method to prepare a filter paper SERS sensor. Colloidal Ag nanoparticles were immobilized on one side of filter paper via an in-situ growth method. The fabrication process of the sensor could be finished in several minutes, and no special facility needed. The filter paper SERS sensor demonstrated a spectra uniformity with a 7.0 % point-by-point signal deviation. And the filter function of the sensor could effectively filter out interferences from samples in 1 min, that allowing the direct detection of thiram in ketchup by SERS with detection limit of 93 ppb. Furthermore, we used a Quick Easy Cheap Effective Rugged and Safe (QuEChERS) sample preparation method to detect malachite green (MG) in soil with a sensitivity as low as 0.01 ppm without any sample pre-treatment or purification. A SERS filter paper may open a new avenue for rapid testing of food quality during manufacturing as well as fast detection of potential contaminants in a myriad of substrates.

Recent advances in determination applications of emerging films based on nanomaterials

Sensitive and facile detection of analytes is crucial in various fields such as agriculture production, food safety, clinical diagnosis and therapy, and environmental monitoring. However, the synergy of complicated sample pretreatment and detection is an urgent challenge. By integrating the inherent porosity, processability and flexibility of films and the diversified merits of nanomaterials, nanomaterial-based films have evolved as preferred candidates to meet the above challenge. Recent years have witnessed the flourishment of films-based detection technologies due to their unique porous structures and integrated physical/chemical merits, which favors the separation/collection and detection of analytes in a rapid, efficient and facile way. In particular, films based on nanomaterials consisting of 0D metal-organic framework particles, 1D nanofibers and carbon nanotubes, and 2D graphene and analogs have drawn increasing attention due to incorporating new properties from nanomaterials. This paper summarizes the progress of the fabrication of emerging films based on nanomaterials and their detection applications in recent five years, focusing on typical electrochemical and optical methods. Some new interesting applications, such as point-of-care testing, wearable devices and detection chips, are proposed and emphasized. This review will provide insights into the integration and processability of films based on nanomaterials, thus stimulate further contributions towards films based on nanomaterials for high-performance analytical-chemistry-related applications.

An Overview of the Design of Metal-Organic Frameworks-Based Fluorescent Chemosensors and Biosensors

Taking advantage of high porosity, large surface area, tunable nanostructures and ease of functionalization, metal-organic frameworks (MOFs) have been popularly applied in different fields, including adsorption and separation, heterogeneous catalysis, drug delivery, light harvesting, and chemical/biological sensing. The abundant active sites for specific recognition and adjustable optical and electrical characteristics allow for the design of various sensing platforms with MOFs as promising candidates. In this review, we systematically introduce the recent advancements of MOFs-based fluorescent chemosensors and biosensors, mainly focusing on the sensing mechanisms and analytes, including inorganic ions, small organic molecules and biomarkers (e.g., small biomolecules, nucleic acids, proteins, enzymes, and tumor cells). This review may provide valuable references for the development of novel MOFs-based sensing platforms to meet the requirements of environment monitoring and clinical diagnosis.

Solid-phase microextraction: a fit-for-purpose technique in biomedical analysis

Solid-phase microextraction (SPME) possesses unique features that allow it to be used in analyses that would not be possible with traditional sample-preparation methods. The simplicity of SPME protocols and extraction devices makes it a uniform platform for analyzing biological samples, either via the headspace or in direct immersion mode. Furthermore, flexible probe design enables SPME to be applied to target objects of different sizes, offering analysis on a scale ranging "from single cell to living organs". SPME microfibers are minimally invasive, which enables them to be applied for the spatial and temporal monitoring of target analytes or to assess changes in the entire metabolome or lipidome. Furthermore, SPME permits the capture of the elusive portion of the metabolome, thus complementing exhaustive methods that are biased towards highly abundant and stable species. Significantly, SPME can be interfaced with analytical instrumentation to create a rapid diagnostic tool. However, despite these advantages, SPME has some limitations that must be well-understood and addressed. This paper presents examples of up-to-date applications of SPME, challenges related to particular studies, and future perspectives regarding the application of SPME in biomedical analysis.

Metal-organic frameworks based surface-enhanced Raman spectroscopy technique for ultra-sensitive biomedical trace detection

Metal-organic frameworks (MOFs) have attracted widespread interest due to their unique and unprecedented advantages in microstructures and properties. Besides, surface-enhanced Raman scattering (SERS) technology has also rapidly developed into a powerful fingerprint spectroscopic technique that can provide rapid, non-invasive, non-destructive, and ultra-sensitive detection, even down to single molecular level. Consequently, a considerable amount of researchers combined MOFs with the SERS technique to further improve the sensing performance and broaden the applications of SERS substrates. Herein, representative synthesis strategies of MOFs to fabricate SERS-active substrates are summarized and their applications in ultra-sensitive biomedical trace detection are also reviewed. Besides, relative barriers, advantages, disadvantages, future trends, and prospects are particularly discussed to give guidance to relevant researchers.

Inducing Ring Complexation for Efficient Capture and Detection of Small Gaseous Molecules Using SERS for Environmental Surveillance

Gas-phase surface-enhanced Raman scattering (SERS) remains challenging due to poor analyte affinity to SERS substrates. The reported use of capturing probes suffers from concurrent inconsistent signals and long response time due to the formation of multiple potential probe-analyte interaction orientations. Here, we demonstrate the use of multiple non-covalent interactions for ring complexation to boost the affinity of small gas molecules, SO₂ and NO₂ , to our SERS platform, achieving rapid capture and multiplex detection down to 100 ppm. Experimental and in-silico studies affirm stable ring complex formation, and kinetic investigations reveal a 4-fold faster response time compared to probes without stable ring complexation capability. By synergizing spectral concatenation and support vector machine regression, we achieve 91.7 % accuracy for multiplex quantification of SO₂ and NO₂ in excess CO₂ , mimicking real-life exhausts. Our platform shows immense potential for on-site exhaust and air quality surveillance.

Recent Advances in the Use of Surface-Enhanced Raman Scattering for Illicit Drug Detection

The rapid increase in illicit drug use and its adverse health effects and socio-economic consequences have reached alarming proportions in recent years. Surface-enhanced Raman scattering (SERS) has emerged as a highly sensitive analytical tool for the detection of low dosages of drugs in liquid and solid samples. In the present article, we review the state-of-the-art use of SERS for chemical analysis of illicit drugs in aqueous and complex biological samples, including saliva, urine, and blood. We also include a review of the types of SERS substrates used for this purpose, pointing out recent advancements in substrate fabrication towards quantitative and qualitative detection of illicit drugs. Finally, we conclude by providing our perspective on the field of SERS-based drug detection, including presently faced challenges. Overall, our review provides evidence of the strong potential of SERS to establish itself as both a laboratory and in situ analytical method for fast and sensitive drug detection and identification.

Machine learning for rapid quantification of trace analyte molecules using SERS and flexible plasmonic paper substrates

Given the intrinsic nature of low reproducibility and signal blinking in the surface enhanced Raman scattering (SERS) technique, especially while detecting trace/ultra-trace amounts, it remains a major challenge to quantify the analyte under study. Here we present a simple and economically viable, flexible hydrophobic plasmonic filter paper-based SERS substrate for the quantification of two trace analytes [crystal violet (CV) and picric acid (PA)] using machine learning techniques and SERS data. The wettability of the substrate was modified with an easy and low-cost technique of coating it with silicone oil. Gold nanoparticles were synthesized using a femtosecond laser ablation in water technique. The prepared nanoparticles were characterized using UV, TEM, and SEM techniques and subsequently loaded onto filter papers before using them for SERS studies. We have considered the SERS intensities of the analytes at different concentrations with over 900 spectra to train the model. Principal component analysis (PCA) was used to reduce the dimensionality and, hence, the complexity of the model. Furthermore, support vector regression was used to quantify the analyte molecules and we achieved an R² error of 0.9629 for CV and 0.9472 for PA. In conjunction with a portable Raman spectrometer and a computation time of less than <10 s, we believe that this is an affordable and rapid method for quantification of analytes using the SERS technique.

A dual-responsive nanozyme sensor with ultra-high sensitivity and ultra-low cross-interference towards metabolic biomarker monitoring

Accurate, sensitive and selective detection of metabolic biomarkers in biofluids are of vital significance for health self-monitoring and chronic disease prevention. Here, for the first time, a smart dual-responsive nanozyme sensor (DNS) was developed for simultaneous analysis of glucose and caffeine utilizing stimuli-responsive yolk-shell gold nanoparticles (GNPs)-embedded MIL-53 (Al) (GNPs@MIL-53) structures. After the introduction of glucose, GNPs@MIL-53 displays excellent glucose oxidase (GOx)-like activity to induce the conversion of glucose to gluconic acid and H₂O₂. H₂O₂ can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) with the generation a bright-blue color, enabling in-field visualization and surface enhanced Raman scattering (SERS) detection of glucose. Upon the addition of caffeine, 2-aminoterephthalic acid modified MIL-53 can react with the caffeine to form intermolecular hydrogen-bonded complexes, leading to strong cyan fluorescence and significant Raman enhancements. The DNS with multi-channel signal outputs can simultaneously determine glucose and caffeine at concentrations of as low as 3 × 10^-8 M and 1.2 × 10^-11 M, respectively. Importantly, the DNS-based analytical system not only enables visual discrimination and accurate assay of glucose and caffeine in biofluids, but also exhibits negligible cross-interference between glucose and caffeine determination. The combined characteristics of high selectivity, enhanced accuracy and superior quantitative performance make our platform suitable for the point-of-care monitoring of chronic-disease-related metabolic biomarkers.

A tri-modal paper device based on flower-like CuSe for the detection of an Alzheimer's disease-associated microRNA marker

A tri-modal paper device based on flower-like CuSe was developed for monitoring Alzheimer's disease (AD)-related miRNA by integrating colorimetric, photothermal and surface-enhanced Raman scattering approaches. Significantly, false-negative signals at the early stage of AD were completely eliminated by using our presented tri-modal strategy.

A wearable screen-printed SERS array sensor on fire-retardant fibre gloves for on-site environmental emergency monitoring

Glove-based wearable sensors can offer the potential ability to a fast and on-site environmental threat assessment, which is crucial for timely and informed incident management. In this study, an on-demand surface-enhanced Raman scattering (SERS) array sensor has been patterned on fire-retardant fibre gloves via the screen-printing technique in large batches. The screen-printed ink contains one-pot synthesized silver nanoparticle and molybdenum disulfide nanocomposite (Ag/MoS₂), and polyanionic cellulose (PAC) as a new adhesive agent. Rhodamine 6G (R6G) was employed as an initial probe molecule to systematically evaluate the performance of the resulting sensor. The results suggest that the fabricated fire-retardant screen-printed SERS array sensor displays high reproducibility and stability at 250 °C, with the lower detection limit of 10^-13 M for R6G. The spot-to-spot SERS signals show that the intensity variation was less than 10%. Besides, the SERS signals can be maintained over 7 weeks. Further investigation was then successfully carried out to detect polycyclic aromatic hydrocarbons (PAHs), which are commonly used as flammable chemicals. In our perception, this wearable fire-retardant screen-printed SERS array sensor would be an ideal candidate for practical on-site environmental emergency monitoring due to its fire-retardant capability and timely measurement on a portable carrier.

Enhancement of the Detection Performance of Paper-Based Analytical Devices by Nanomaterials

Paper-based analytical devices (PADs), including lateral flow assays (LFAs), dipstick assays and microfluidic PADs (μPADs), have a great impact on the healthcare realm and environmental monitoring. This is especially evident in developing countries because PADs-based point-of-care testing (POCT) enables to rapidly determine various (bio)chemical analytes in a miniaturized, cost-effective and user-friendly manner. Low sensitivity and poor specificity are the main bottlenecks associated with PADs, which limit the entry of PADs into the real-life applications. The application of nanomaterials in PADs is showing great improvement in their detection performance in terms of sensitivity, selectivity and accuracy since the nanomaterials have unique physicochemical properties. In this review, the research progress on the nanomaterial-based PADs is summarized by highlighting representative recent publications. We mainly focus on the detection principles, the sensing mechanisms of how they work and applications in disease diagnosis, environmental monitoring and food safety management. In addition, the limitations and challenges associated with the development of nanomaterial-based PADs are discussed, and further directions in this research field are proposed.

Recent Advances and Applications in Paper-Based Devices for Point-of-Care Testing

Point-of-care testing (POCT), as a portable and user-friendly technology, can obtain accurate test results immediately at the sampling point. Nowadays, microfluidic paper-based analysis devices (μPads) have attracted the eye of the public and accelerated the development of POCT. A variety of detection methods are combined with μPads to realize precise, rapid and sensitive POCT. This article mainly introduced the development of electrochemistry and optical detection methods on μPads for POCT and their applications on disease analysis, environmental monitoring and food control in the past 5 years. Finally, the challenges and future development prospects of μPads for POCT were discussed.

Paper-based plasmonic nanosensor monitors environmental lead pollution in real field

Development of a low-cost portable colorimetric nanosensor for real field pollution monitoring.

In situ detection of fluid media based on a three-dimensional dendritic silver surface-enhanced Raman scattering substrate

A simple substitution reaction was used to grow 3D dendritic silver structures in microfluidic channels, and a highly active SERS detection platform was formed. The system can realize in situ detection of 10−10 mol L−1 R6G solution.

Template-directed synthesis of zeolitic imidazolate framework-8 derived Zn-Al layered double oxides decorated on the electrochemically anodized nanoporous aluminum substrate for thin film microextraction of chlorophenols followed by determination with high-performance liquid chromatography

In this work, hierarchical ZIF-8 coated anodized aluminum foil was prepared through in situ template-directed method without addition of any zinc salt. The hierarchical sorbent was synthesized by the formation of the final HZIF-8 on the previously created layered double oxide (LDO) template. The LDO template was created by calcining the firstly in situ prepared desired layered double hydroxide (LDH) precursor coated on the electrochemically anodized porous Al foil in an air atmosphere. The microextraction ability of the extracting device was studied through direct immersion thin film microextraction (DI-TFME). The extracted analytes were quantified by high-performance liquid chromatography equipped by UV detector (HPLC-UV). The present strategy was used for the simultaneous extraction and quantification of four selected chlorophenols (CPs) (as model analyte). The variables of the TFME were optimized using response surface methodology (Plackett-Burman and Box-Behnken design). Under the obtained optimum condition, the prepared film presented acceptable extraction properties including low limits of detection (0.03-0.22 µgL^-1), good linear ranges (0.2-200 µgL^-1, r² > 0.9918) and satisfactory reproducibility (relative standard deviation, 3.6 < RSD < 5.8% for one film as inter- and intra-day RSD, 4.8 < RSD < 5.3% for film to film). Moreover, the obtained enrichment factors were in the range of 56-76. The kinetics and adsorption isotherm of the selected analytes adsorption to the prepared sorbent were also investigated. The maximum adsorption capacities of the selected analytes on the prepared sorbent were in the range of 26.4-80.1 mg g^-1. The adsorption isotherm obeyed the Langmuir and Freundlich models. Moreover, the adsorption of the selected chlorophenols on the prepared film followed the pseudo-second-order kinetic model. Finally, the HZIF-8 film was utilized for the quantification of selected CPs in different types of water and wastewater samples. The results showed satisfactory relative recoveries (93-102%) and acceptable precisions (3.6 < RSD < 9.2%).

Peak-fitting assisted SERS strategy for accurate discrimination of carboxylic acid enantiomers

A novel peak-fitting assisted SERS (PF-SERS) strategy was developed for the first time to discriminate carboxylic acid enantiomers. The PF-SERS method offered substantial improvement in accuracy, quantitative performance of enantioselective sensing and exceptionally strong enantiomeric recognition ability.

In Situ Monitoring of Hydrogen Peroxide Released from Living Cells Using a ZIF-8-Based Surface-Enhanced Raman Scattering Sensor

Hydrogen peroxide (H₂O₂) widely involves in intracellular and intercellular redox signaling pathways, playing a vital role in regulating various physiological events. Nevertheless, current analytical methods for the H₂O₂ assay are often hindered by relatively long response time, low sensitivity, or self-interference. Herein, a zeolitic imidazolate framework-8 (ZIF-8)-based surface-enhanced Raman scattering (SERS) sensor has been developed to detect H₂O₂ released from living cells by depositing ZIF-8 over SERS active gold nanoparticles (AuNPs) grafted with H₂O₂-responsive probe molecules, 2-mercaptohydroquinone. Combining the superior fingerprint identification of SERS and the highly efficient enrichment and selective response of H₂O₂ by ZIF, the ZIF-8-based SERS sensor exhibits a high anti-interference ability for H₂O₂ detection, with a limit of detection as low as 0.357 nM. Satisfyingly, owing to the enhanced catalytic activity derived from the successful integration of AuNPs and ZIF, the response time as short as 1 min can be obtained, demonstrating the effectiveness of the SERS sensor for rapid H₂O₂ detection. Furthermore, the developed SERS sensor enables real-time detection of H₂O₂ secreted from living cells under phorbol myristate acetate stimulation, as cells can be cultured on-chip. This study will pave the way toward the development of a metal-organic framework-based SERS platform for application in the fields of biosensing and early disease diagnosis associated with H₂O₂ secretion, thus exhibiting promising potential for future therapies.

Porous Inorganic Materials for Bioanalysis and Diagnostic Applications

Porous inorganic materials play an important role in adsorbing targeted analytes and supporting efficient reactions in analytical science. The detection performance relies on the structural properties of porous materials, considering the tunable pore size, shape, connectivity, etc. Herein, we first clarify the enhancement mechanisms of porous materials for bioanalysis, concerning the detection sensitivity and selectivity. The diagnostic applications of porous material-assisted platforms by coupling with various analytical techniques, including electrochemical sensing, optical spectrometry, and mass spectrometry, etc., are then reviewed. We foresee that advanced porous materials will bring far-reaching implications in bioanalysis toward real-case applications, especially as diagnostic assays in clinical settings.

A Review on the Role and Performance of Cellulose Nanomaterials in Sensors

Sensors and biosensors play a key role as an analytical tool for the rapid, reliable, and early diagnosis of human diseases. Such devices can also be employed for monitoring environmental pollutants in air and water in an expedited way. More recently, nanomaterials have been proposed as an alternative in sensor fabrication to achieve gains in performance in terms of sensitivity, selectivity, and portability. In this direction, the use of cellulose nanomaterials (CNM), such as cellulose nanofibrils (CNF), cellulose nanocrystals (CNC), and bacterial cellulose (BC), has experienced rapid growth in the fabrication of varied types of sensors. The advantageous properties are related to the supramolecular structures that form the distinct CNM, their biocompatibility, and highly reactive functional groups that enable surface functionalization. The CNM can be applied as hydrogels and xerogels, thin films, nanopapers and other structures interesting for sensor design. Besides, CNM can be combined with other materials (e.g., nanoparticles, enzymes, carbon nanomaterials, etc.) and varied substrates to advanced sensors and biosensors fabrication. This review explores recent advances on CNM and composites applied in the fabrication of optical, electrical, electrochemical, and piezoelectric sensors for detecting analytes ranging from environmental pollutants to human physiological parameters. Emphasis is given to how cellulose nanomaterials can contribute to enhance the performance of varied sensors as well as expand novel sensing applications, which could not be easily achieved using standard materials. Finally, challenges and future trends on the use of cellulose-based materials in sensors and biosensors are also discussed.