This study examines the influence of divisor selection on the efficacy of advanced analytical spectrophotometric methods that integrate artificial intelligence (AI), green-chemistry principles, and white-analytical-chemistry (WAC) frameworks for pharmaceutical investigation. Advanced analytical chemistry, which combines environmental sustainability, analytical practice and computational cleverness, was employed to create innovative spectrophotometric techniques for the concurrent quantification of solifenacin succinate (SOF), and mirabegron (MIR), both utilized in the treatment of overactive bladder. Three divisor approaches were evaluated within complementary smart resolution strategies based on high impact amplitude manipulation method (HIAM) using normalized divisor of MIR, concentration-dependent divisor of MIR at 3.0, 8.0, and 14.0 µg/mL, as well as extracted zero order spectra of MIR obtained by absorbance resolution method (AR). Linearity for SOF was observed from 2.5 to 25.0 µg/mL using first derivative D1at 222 nm, while MIR exhibited linearity from 1.5 to 15.0 µg/mL at its maxima 249.0 nm. To assess the robustness and risk, cumulative validation score; CVS, was calculated, serving as instrumental sign for evaluating analytical reliability and method performance. We introduce Sustainable & Smart Analytical Chemistry (SSAC), conjoining Green Analytical Chemistry (GAC), WAC, and AI to develop analytical methods that are efficient, environmentally responsible, and consistent with the multiple Sustainable Development Goals; SDGs. The Sustainability of Analytical Methods Index (SAMI) was applied to evaluate the method's holistic alignment with the 17 SDGs. Using the Multi-Color Assessment Tool (MA), the method's greenness, realism, presentation, and novelty were evaluated, demonstrating its sustainability and global impact.
Sleep disorders include a range of common problems that affect the quality of sleep at night and, as a result, impact an individual's daily functioning. Treatment protocols vary from over-the-counter products to regulated pharmaceuticals. Melatonin and Tasimelteon are two compounds utilized for severe to moderate sleeping disorders. This study developed and validated a sensitive, simple bioanalytical LC-MS/MS method for the measurement of Melatonin and Tasimelteon in spiked rat brain tissue. Chromatographic analyses were conducted in isocratic mode, with Citalopram selected as an appropriate internal standard. The Supelco Ascentis® Express Phenyl-Hexyl column was used for the stationary phase, and the mobile phase comprised 0.2% formic acid in a mixture of acetonitrile and water (65:35, v/v). A response surface methodology is applied. The Box-Behnken design was used to optimize the influence of three independent factors (acetonitrile%, formic acid%, and flow rate (mL/min)) on the response. The study focused on finding the most significant factors influencing chromatographic separation, namely the resolution between Tasimelteon and Melatonin, as well as the tailing factors of both. Statistical analysis of variance provided the optimal conditions for separating the substances as well as the most influential factors. Validation of the analytical method was conducted in accordance with the International Council for Harmonization guideline M10 related to bioanalytical method validation. The method validated was precise and linear in 55.00-1650 (ng/mL) and 20-600 (ng/mL) for the Melatonin and Tasimelteon, respectively. The validated method's lower limit of quantification values was 55 and 20 ng/mL for Melatonin and Tasimelteon, respectively. For Melatonin, intraday accuracy (recovery, %) ranged from 96.53% to 102.68%, and precision (expressed as relative standard deviation) ranged from 0.26% to 0.96%. And inter-day accuracy ranged from 96.58% to 103.08%, and inter-day precision ranged from 0.33% to 3.55%. Intraday accuracy results for Tasimelteon 99.61%-103. 75% precision results were in the range 0.23%-0.93%; additionally, inter-day accuracy was 99.37-103.87%, and the precision range was 1.04-2.11%. The total run time was 3 min, with retention time for Melatonin and Tasimelteon at 1.9 and 2.5 min, respectively, achieving effective chromatographic separation under optimum conditions. The Red Green Blue 12 score for whiteness was determined to be 79.2%.
Background: Synovial pH, lactate, and glucose are established biomarkers for septic arthritis in native joints and have emerging utility in periprosthetic joint infection (PJI). In routine care, these biomarkers are commonly analyzed in central laboratories, which may delay clinical decision-making. Blood gas analyzers (BGAs), which can also measure these parameters, are widely available at the point of care, and their use could accelerate decision-making. However, BGAs are not validated for synovial fluid analysis. Materials and methods: This prospective analytical agreement study included 35 consecutive patients undergoing knee joint aspiration for suspected PJI or septic arthritis of the native joint. Each sample was measured in triplicate both in the central laboratory and using a BGA. The agreement between the two methods was assessed using Passing-Bablok and Bland-Altman analyses. The study was designed to assess analytical agreement between both methods rather than diagnostic accuracy. Results: BGA measurements for synovial pH, lactate, and glucose demonstrated good to excellent agreement with those obtained using central laboratory methods. Agreement was excellent for synovial glucose and overall good for lactate, with negligible mean bias. Linear regression showed very strong correlations for glucose ( r = 0.997) and lactate ( r = 0.989). Synovial pH showed greater variability, with a mean bias of - 0.10 pH units; however, repeatability analysis revealed lower within-sample variability for BGA-based pH measurements compared with laboratory pH measurements. Conclusion: BGAs enable rapid, reliable measurement of synovial pH, lactate, and glucose from small sample volumes and may support timely clinical decision-making in suspected septic arthritis and PJI. Further studies should assess inter-device generalizability and establish device-specific reference ranges.
Tobacco is a globally significant agricultural commodity, in which analytical chemistry plays a pivotal role for quality assessment. This study aimed to develop an integrated analytical strategy to decipher the quality traits of flue-cured tobacco cultivars. An integrated framework combining sensory evaluation, biochemical characterization, and volatile organic compound (VOC) profiling was applied to eleven flue-cured tobacco cultivars. Statistical analyses included hierarchical cluster analysis (HCA) and partial least squares-discriminant analysis (PLS-DA) based on VOC data, and Spearman correlation analysis (with Bonferroni correction) to explore relationships between sensory attributes, biochemical components, and VOCs. Sensory analysis categorized the cultivars into two groups: Group I (YN228, YN105, YN223, GY20, and YN87) scored higher in aftertaste, offensive taste, and moistness, while Group II (YN222, XY7, NC103, TZ113, GY2, and XZ01) excelled in aroma quality and cleanness. Biochemical profiling also revealed two distinct groups: Group I (YN228, TZ113, NC103, and YN87) had higher nitrogen and alkaloid contents, whereas Group II (YN222, XY7, GY20, XZ01, GY2, YN105, and YN223) exhibited elevated sugar and potassium levels. VOC-based HCA and PLS-DA identified three chemical clades and highlighted 75 VOCs (VIP > 1.0) as key differentiators. Significant correlations were established between biochemical components and sensory attributes; notably, total sugar content was positively correlated with irritancy, aroma quality, and smoke concentration. Specific VOCs, such as (furan-2-yl)methanol and 3-oxo-α-ionol, showed significant positive correlations with moistness and smoke concentration, respectively, while phenol was negatively correlated with aroma quality. This study establishes a reproducible sensory-omics framework that provides a robust analytical foundation for the quality assessment of agricultural products. The findings demonstrate the practical value of integrated analytical approaches in addressing complex quality assessment challenges, offering actionable insights for the evaluation and potential improvement of tobacco cultivars.
Precise control of liposome size is critical for drug delivery. We developed an in-line PAT-integrated machine learning model that predicts particle size with high accuracy (root mean square error 7.18 nm) using limited experimental data. By integrating physicochemical membrane characteristics, the model demonstrates generalization (root mean square error 7.53 nm) and interpretability, establishing a practical framework for advanced liposome particle size control.
Derrisisoflavone A is a prenylated isoflavonoid and a chemical marker in the stem of Derris scandens (Roxb.) Benth., it is a suitable chemical marker for this plant. Conventional analytical techniques, such as high-performance liquid chromatography, liquid chromatography-mass spectrometry, and immunoassays, offer high sensitivity but rely on complex analytical equipment and specialized expertise, thereby limiting their applicability for rapid on-site analysis. In this study, a lateral flow immunochromatographic assay (LFIA) employing gold nanoparticle (AuNP)-labeled monoclonal antibodies (mAbs) was developed for qualitative detection of derrisisoflavone A in D. scandens plant materials and herbal products. The LFIA was designed in a competitive format using AuNPs-mAbs conjugates as the detection probe, derrisisoflavone A-cationized ovalbumin conjugates applied on the test zone, and anti-mouse immunoglobulin G antibody on the control zone. Under optimized conditions, the assay was evaluated for sensitivity and specificity and validated by comparison with a well-established indirect competitive enzyme-linked immunosorbent assay (icELISA) using various D. scandens plant parts, commercial products, and representative Fabaceae species. The LFIA exhibited a visual limit of detection of 100 µg/mL, defined by complete inhibition of the test zone signal, and demonstrated high analytical specificity with undetectable cross-reactivity toward structurally related isoflavonoids or prenylated flavonoids. The analytical results showed good agreement with those obtained by icELISA. Although less sensitive than quantitative methods, the developed LFIA provides a rapid, simple, and reliable screening tool for on-site quality control and preliminary assessment of derrisisoflavone A in D. scandens and related products.
A novel, eco-friendly spectrofluorimetric method has been developed for the sensitive determination of capivasertib, based on resonance Rayleigh scattering enhancement. Unlike previously reported methods, this approach utilizes erythrosine B as a safer ion-pairing reagent in an acidic aqueous medium, eliminating the need for organic solvents or complex extraction steps. The interaction between capivasertib and erythrosine B leads to a stable ion-pair complex, producing a strong Rayleigh scattering signal measurable at λex530/λem550 nm. The method demonstrated excellent linearity over the range of 20-2000 ng mL⁻¹, with a detection limit of 5.61 ng mL⁻¹ and a quantification limit of 17 ng mL⁻¹. All analytical parameters were optimized and validated according to ICH guidelines. To holistically substantiate sustainability, the method's environmental and practical profiles were appraised using all contemporary greenness/whiteness/applicability metrics employed in this work: Analytical Eco-Scale (ESA), NEMI pictogram, GAPI, AGREE, and AGREE-prep for sample-preparation greenness; the White Analytical Chemistry RGB12 model (whiteness); and the Blue Applicability Grade Index (BAGI) (blueness/applicability). This work introduces a greener, simpler, and more accessible alternative for capivasertib analysis, with potential applications in pharmaceutical quality control and routine laboratory testing.
The residue of phthalates (PAEs) in edible products can cause endocrine disorders in the human body. In this study, a solid-phase microextraction (SPME) probe coated with fluoro-functionalized covalent organic frameworks (F-COFs) was developed for the extraction of PAEs. The synthesized F-COFs coating exhibited excellent hydrophobicity and high thermal stability, making it suitable for adsorbing PAEs. The established F-COF-SPME-GC method achieved a green analytical chemistry score of 0.63 in terms of environmental friendliness. It also exhibited satisfactory linear ranges of 0.02-100 μg L-1 for all PAEs (R²≥0.9901), and limits of detection (LODs) ranged from 0.010 to 0.019 μg L-1. The method was successfully applied to determine PAEs in six edible oils and six traditional medicinal crops, exhibiting relatively strong resistance to matrix interference. These results indicated that the F-COF-SPME probe provided significant promise for the efficient and robust adsorption and detection of PAEs in complex samples.
Carbon dot (CD)-based nanozymes have become promising substitutes to natural enzymes in high-performance analytical detection systems, due to their high-water solubility, tunable surface chemistry, and their ability to produce multiple signaling outputs. It has been shown that CDs have a variety of enzyme-mimetic activities, such as peroxidase (POD), oxidase (OXD), and superoxide dismutase (SOD)-like activities, and can be used in bioassays and environmental monitoring. Although such progress has been made, there is still no detailed theoretical framework that explains the origins of their catalytic activity and the mechanisms that underlie sensing selectivity, thus restricting the rational design and optimization of CD-based nanozymes. This is a systematic review of the impact of precursor selection, reaction conditions, and doping strategies on the surface functional groups, defect structures, and metal active centers of CDs. It also explains how these structural features work synergistically to regulate electron transfer processes and active site formation. Furthermore, the review suggests that interfacial noncovalent interactions are the main determinants of the sensing selectivity of CD nanozymes, which is accompanied by molecular recognition processes and energy-level complementation. Recent advances in multimodal signaling strategies to detect complex systems are also mentioned. Lastly, the present issues and future outlooks in the controlled construction and sensing uses of CDs are also pointed out, which can be useful in the rational design and practical use of these new nanozymes.
A sensitive analytical protocol was developed to quantify trace levels of three azole fungicides-ketoconazole (KZ), miconazole (MZ), and clotrimazole (CZ)-in cosmetic matrices. This method integrates fiber-in-tube solid-phase microextraction (FIT-SPME) with high-performance liquid chromatography and ultraviolet detection (HPLC-UV). The extraction medium utilized magnesium-aluminum layered double hydroxides (LDHs) intercalated with sodium dodecyl sulfate (SDS), prepared via urea hydrolysis. To fabricate the sorbent, this modified LDH was embedded within a polyvinyl alcohol (PVA) solution-chosen for its green chemistry attributes-and electrospun onto stainless steel substrates. To prevent dissolution in aqueous samples, the coating was thermally cross-linked using citric acid, ensuring robust mechanical stability. The device consisted of these coated fibers housed within a steel capillary, through which samples were circulated for equilibrium adsorption, followed by solvent desorption. A rigorous optimization process was conducted to determine ideal conditions for pH, ionic strength, flow rates, and timing variables. Performance metrics revealed low limits of detection (0.3-0.6 µg L-1) and high precision, with inter-day relative standard deviations (RSDs) not exceeding 6.2%. The technique displayed a broad linear dynamic range (up to 750.0 µg L-1) and satisfactory determination coefficients (R2 > 0.9913). Finally, the analysis of real samples, including shampoos, creams, and lotions, yielded relative recoveries ranging from 82% to 115%, confirming the method's reliability for complex formulations.
Comprehensive xenometabolome characterization is essential for understanding the effects of xenobiotics in biological systems. This study presents a multidimensional analytical workflow integrating orthogonal chromatographic separations, trapped ion mobility spectrometry (TIMS), high-resolution mass spectrometry and biotransformation-informed data processing to address xenometabolome assessment challenges. Zebrafish larvae exposed to 4-Methylbenzotriazole (4-MeBT) were used as a challenging case study. TIMS dimension provided orthogonal experimental evidence for isomer annotation, with inverse reduced mobility (1/K0) supporting conjugation site assignment for the dominant O-S-4MeBT and O-G-4MeBT isomers. The combination of TIMS with the Parallel Accumulation Serial Fragmentation (PASEF) acquisition further reduced spectral complexity, enhanced signal-to-noise ratio, and improved MS/MS coverage (70%), generating high-quality analytical evidence crucial for structural elucidation. To leverage these analytical dimensions, we developed a data processing strategy that leverages in-silico-based suspect screening and biotransformation-informed nontarget screening. In this regard, we introduce two novel frameworks; the "Building Blocks" (BB) concept which interprets unknown bio-TPs as modular assemblies of parent- and pathway-derived substructures, and the "Spectral Characteristics Knowledgebase" (SCKB), which use known biotransformation MS/MS motifs to provide structural insights and facilitate unknown identification. Our results demonstrated the identification of all previously known 4-MeBT bio-TPs with enhanced confidence (O-Sulfate- and O-Glucuronide-4MeBT) and the discovery of 29 new bio-TP features across 12 bio-TP classes, highlighting its efficacy in unraveling complex xenobiotic metabolism. Among these, a putative dimerization product (4-MeBT-263) was reported for the first time in zebrafish. Overall, this workflow has the potential to advance the understanding of bio-TP formation and detoxification processes in xenometabolome studies.
Persistent and mobile chemicals (PMs) threaten groundwater quality and drinking water safety, yet many remain undetected because analytical methods insufficiently address highly polar and ionic substances, while regulatory frameworks lack monitoring requirements for these compound classes. Here, we developed a supercritical fluid chromatography-high-resolution mass spectrometry-based smart-screen approach that integrates three key prioritisation strategies: (i) sampling site prioritisation, (ii) suspect-level prioritisation through tiered suspect lists, and (iii) candidate prioritisation using stepwise scoring. Additionally, the method achieved the sensitive identification and reliable quantification of PMs in groundwater, with a median limit of quantification of 6.8 ng/L, stable recoveries (75%), and low matrix effects (-12%) across diverse groundwater types. Prioritisation reduced 599 groundwater wells to 10 representative sites, yielding an 8.6-fold reduction in analytical workload while maintaining chemical diversity. The tiered suspect lists and stepwise scoring strategies improved confirmation efficiency and facilitated the detection of substances of high environmental relevance. Collectively, 34 PMs were detected across six substance groups including polar per- and polyfluoroalkyl substances, polyfluorinated inorganic species, transformation products, and amide or ether solvents at concentrations of 0.1-22,300 ng/L. Among these, 16 substances were newly detected in ambient groundwater and four were reported for the first time in any environmental compartment. Several substances (e.g. 2-phenylpropane-2-sulphonic acid) are not classified as persistent under EU regulation on registration, evaluation, authorisation and restriction of chemicals (REACH) yet occur ubiquitously in groundwater, suggesting an underestimation of PMs under aquifer conditions. These findings advance monitoring of PMs, supporting their regulation for groundwater and drinking water protection.
Lipids exhibit extensive molecular diversity and structural complexity, which poses major analytical challenges for comprehensive lipidomic profiling. Phospholipids, in particular, display extensive structural diversity and isomerism. Given the limited lipidomic data available for lymphoma cells, this work focuses on comprehensive phospholipid screening, which inherently requires the characterization of isomeric species, including plasmalogens that have been implicated in oxidative stress and ferroptosis-related cell death. Therefore, we present an efficient isomer-selective workflow based on reversed-phase liquid chromatography (RPLC) coupled to trapped ion mobility spectrometry (TIMS) and high-resolution tandem mass spectrometry (HR-MS/MS). High-confidence structural lipid annotation is achieved through the integrated evaluation of chromatographic retention time (tR), exact mass-to-charge ratio (m/z), collision cross section (CCS) and mobility-resolved MS/MS data. Applied to human lymphoma cell lipid extracts, the workflow enabled confident identification of 263 individual lipid species spanning 10 phospholipid and 2 sphingolipid subclasses, including the resolution of 63 isomeric species at the fatty-acyl compositional level. The multidimensional approach allowed partial discrimination of fatty-acyl compositional, sn- and double bond positional isomers. Notably, characteristic deviations in both retention time and ion mobility were observed for plasmalogens relative to alkyl-ether linked phospholipids, reflecting the unique physicochemical properties of the vinyl-ether linkage. These systematic offsets enabled confident plasmalogen assignment in representative cases, supported by authentic standards, co-chromatograms and mobility-resolved fragmentation data. Collectively, this streamlined analytical platform markedly expands phospholipidome coverage and provides enhanced structural resolution of complex lipid mixtures.
Accurate early screening for hepatocellular carcinoma (HCC) requires multi-target detection methods with high sensitivity and strong anti-interference capability. In this study, we developed an aptamer-mediated SERS sensing method based on bimetallic magnetic nanotubes for the simultaneous detection of HCC markers alpha-fetoprotein (AFP) and Golgi protein 73 (GP73). Tubular Fe3O4 nanostructures were innovatively synthesized as magnetic carriers, onto which a gold-layer, an internal standard molecule (4-mercaptophenylboronic acid), and a silver-layer were sequentially deposited to construct a capture substrate integrating signal calibration and electromagnetic enhancement functions. Raman tags with non-overlapping spectra in the Raman-silent region (1800-2500 cm-1) were screened to establish a sandwich detection system. Using a portable Raman spectrometer and intelligent software, this method achieved rapid quantification of AFP and GP73, with detection limits of 0.433 pg/mL and 0.370 pg/mL, respectively, and recovery rates in spiked serum samples ranging from 95.62% to 106.2%. By simply replacing the aptamers, this method can be readily extended to other targets, demonstrating excellent versatility. This work provides a reliable analytical tool for early HCC diagnosis and establishes a foundation for developing on-site multi-target detection systems for complex samples.
Dextran is a water-soluble α-glucan that can be produced from sucrose using dextransucrases from lactic acid bacteria. Numerous studies have investigated fermentatively and enzymatically produced dextrans and their structure. However, the fine structure of dextrans, particularly their side-chain architecture, was rarely characterized. In this study, a quantitative approach for fine structural characterization of dextrans was developed and applied to ten structurally diverse dextrans. The method was based on endo-dextranase hydrolysis and HPAEC-PAD quantification of the liberated mono-, di-, and oligosaccharides (branched at position O2, O3, and O4) by using their relative response factors (RRFs). The developed method yielded detailed information on the occurrence of different structural elements. To obtain more reliable and quantitative information on side-chain length, TEMPO oxidation was used to selectively oxidize the terminal glucose units in the dextrans. This pretreatment in combination with a subsequent analysis of the enzymatically liberated oligosaccharides allowed for the differentiation between mono-, di-, and trimeric side chains and elongated side chains (> 3 glucose units). The application of the method showed clear differences between the side chain architectures of different O3-branched as well as O4-branched dextrans. Overall, the developed analytical approach provides detailed, unprecedented insights into the fine structure of dextrans.
Crickets are widely consumed edible insects with high nutritional value, requiring reliable analytical methods for elemental characterization. Their complex matrix can cause matrix effects, making suitable reference materials essential for quality control. Because certified cricket reference materials are scarce, particularly in Brazil, this study aimed to prepare and characterize a national reference material candidate using black cricket (Gryllus assimilis). The production process was adapted to the matrix and included grinding, lyophilization, and packaging, yielding a batch of 25 bottles. The influence of particle size and between-bottle homogeneity was evaluated. Homogeneity was assessed by ANOVA, supported by Levene and Shapiro-Wilk tests, using five randomly selected bottles and three subsamples of 0.250 g per bottle. Elemental characterization was performed by energy-dispersive X-ray fluorescence. Expanded uncertainties were estimated with a coverage factor of k = 2 at approximately 95% confidence. Results showed satisfactory between-bottle homogeneity (p-value > 0.05) and indicated that particle sizes below 500 µm did not significantly affect concentrations. The candidate presented average mass fractions ± expanded uncertainty of Ca (1531.0 ± 176.5 mg kg⁻1), Cl (5559.4 ± 1381.2 mg kg⁻1), Cu (22.9 ± 1.7 mg kg⁻1), Mg (1083.1 ± 295.8 mg kg⁻1), P (10 397.0 ± 1084.6 mg kg⁻1), and S (7608.1 ± 398.0 mg kg⁻1). Coefficients of variation were below 11%, and expanded uncertainties remained under 30%. These results demonstrate adequate precision, reproducibility, and matrix suitability of the proposed material. The study supports continued evaluation of intra-bottle homogeneity, stability, and certification to enable its availability for laboratories performing elemental analysis of cricket-based foods, strengthening analytical reliability and food safety assessment in emerging insect protein chains worldwide. This contribution addresses national needs and supports sustainable nutrition research efforts.
Biosensors with good sensing performances with regards to high sensitivity, specificity, shorter response time, the ability to be multiplexed, excellent stability and reproducibility, are always in high demand. As modern biosensors are often fabricated using bioreceptors immobilized on nanoparticles to achieve efficient signal transduction or easier handling, the nanoparticle-bioreceptor (nano-bio) interface has a significant impact on the final sensing metrics. However, the role of nano-bio interfaces in sensing performance could be better understood, to facilitate the rational design of high performing nano-bio based devices. Herein, we aim to provide some basic rules and considerations to optimize nano-bio interfaces to achieve better detection performance when fabricating biosensors. The impact of the nano-bio interfaces on sensing characteristics is discussed from the perspective of bioreceptor-analyte interaction. Four interfacial parameters are included in this review: (1) the conformation of bioreceptors, (2) the coverage of the bioreceptors, (3) composition of mixed ligands, such as bioreceptors and other functional molecules and (4) spatial distribution of bioreceptors on nanoparticle surfaces. Methods to tailor these four interfacial factors are systematically investigated. In parallel, how these tailored nano-bio factors improve the sensing performances is emphasized with corresponding biosensor examples. The analytical methods for characterization of nano-bio interfaces are summarized, particularly at the single particle level. Additionally, the integration of artificial intelligence (AI) with nano-bio interfaces is discussed, highlighting how AI can improve nano-bio interfacial design. Finally, future perspectives on the role of nano-bio interfacial design in enhancing sensing capabilities are presented. This review aims to elucidate the relationship between nano-bio interfacial factors and sensing performances, as well as strategies for achieving precisely controlled nano-bio interfaces, which facilitates the rational design of high-performance biosensors.
This study aimed to measure the concentrations of essential and nonessential metals in raw and cooked rice samples from Ethiopia. Researchers collected rice samples, both local and imported, from the Jimma town market. The samples were stored in prerinsed plastic bags and rinsed with 2 mol/L HNO3 and deionized water to prevent contamination. Preparation involved wet digestion methods, and the samples were stored at 4°C until analysis. Flame atomic absorption spectrometry (FAAS) was used to analyze the samples in triplicate, and the results were validated for accuracy, precision, instrument detection limit (IDL), limit of detection (LOD), and limit of quantification (LOQ). The findings revealed significant differences (p < 0.05) in the mean concentrations of metals across all rice samples. The metals detected included both essential and nonessential types: chromium (Cr) ranged from nondetectable (ND) to 15.36 mg/kg; nickel (Ni) from ND to 17.76 mg/kg; cadmium (Cd) from 1.22 to 5.58 mg/kg; lead (Pb) from 0.17 to 0.98 mg/kg; iron (Fe) from 19.99 to 84.71 mg/kg; calcium (Ca) from 35.15 to 198.53 mg/kg; potassium (K) from 35.31 to 105.19 mg/kg; and magnesium (Mg) from 18.66 to 46.07 mg/kg. The percentage recoveries ranged from 80.5% to 120%, indicating good accuracy and repeatability of the analytical procedure. The study also found significant variations among the six metals, suggesting that geographic origin influences metal levels in rice. Notably, while there was no significant difference between cadmium and calcium concentrations, the levels of nonessential metals, cadmium, lead, and nickel, exceeded the recommended limits set by WHO/FAO. Based on these findings, the study recommends careful handling of rice during transportation, marketing, storage, and cultivation to minimize exposure to toxic metals.
Non-invasive, real-time monitoring of lactate in sweat is critical for personalized health tracking and sports performance optimization. However, conventional enzyme-based lactate sensors suffer from limited stability and high cost, while many reported nanozyme systems exhibit optimal activity only under alkaline conditions, limiting their applicability in physiological environments. In this report, we develop a wearable integrated nanozyme-based electrochemical sensor for sweat lactate monitoring. The sensor comprises cobalt oxide (Co3O4) and cobalt phosphate (Co3(PO4)2) nanoflakes on a screen-printed carbon electrode (SPCE), combined with a microfluidic unit for sweat collection and transport. Co3O4 nanoflakes were electrodeposited and electrochemically activated to form a Co3O4/Co3(PO4)2/SPCE platform for lactate detection. The structural morphologies, surface composition and chemical states, and crystalline information of the modified electrodes were analyzed using various analytical techniques, such as scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and transmission electron microscopy. The Co3O4/Co3(PO4)2/SPCE exhibited robust electrocatalytic activity for lactate detection at neutral pH, yielding a dynamic range of 1 - 80 mM with a sensitivity of 8.3 μA mM-1 cm-2 and a limit of detection of 0.3 mM. The developed sensor offers good selectivity against common electroactive sweat components (ascorbic acid, uric acid, and glucose). The microfluidic integrated sensor was tested dynamically with different concentrations of lactate, yielding a sensitivity of 5.2 μA mM-1 cm-2. The device was validated by on-body sweat lactate monitoring during cycling, showing excellent accuracy (>91%) versus a colorimetric reference test. The integrated sensor enables real-time sweat lactate analysis for sports monitoring and personalized health tracking.
Reliable identification of proteins and their post-translationally modified variants remains a formidable analytical challenge due to charge heterogeneity, sequence similarity, and comparable molecular weights. In this study, we demonstrate distinctive nanopore current fingerprints for clear identification of neurodegenerative disease-associated Tau protein and its phosphorylated variants using an asymmetric-electrolyte sensing system composed of different salts. The asymmetric configuration facilitates simultaneous detection of positively, neutrally, and negatively charged peptide fragments, resulting in 3.2-16-fold higher capture frequencies and 2.1-5.3-fold longer event durations, thereby yielding information-rich fingerprints that enhance protein recognition. Protein profiling was achieved within 1 min through integration with a droplet nanopore platform, which reduces sample consumption to the nanogram level while increasing throughput to >1800 events per minute. This work advances the nanopore fingerprinting approach for rapid, high-throughput, and low-sample protein biomarker detection, offering strong potential for clinical proteomics and early disease diagnosis.