Sample Preparation Research Articles

Operational feasibility and multi-centric evaluation of ‘TBDetect sputum microscopy kit’ for the direct detection of Mycobacterium tuberculosis in field settings

Background India relies primarily on direct smear microscopy for tuberculosis (TB) diagnosis. However, the low sensitivity of smear microscopy emphasizes the need to improve its performance. We recently described the development of ‘TBDetect’ kit which showed improved performance over direct smear microscopy at National Reference Laboratories (NRLs) in India. Methods The present study was aimed to assess the operational feasibility of ‘TBDetect’ microscopy in field settings. This was evaluated by (i) assessing the performance of ‘TBDetect’ microscopy vs. LED-fluorescence microscopy (LED-FM) on consecutive presumptive pulmonary TB patients (n = 5300) who attended Designated Microscopy Centres (DMCs, n = 13) under 4 NRLs at Bhubaneswar, Bhopal, Chennai, and New Delhi, and (ii) obtaining feedback from Scientists (n = 10) and laboratory technicians (n = 42) using semi-structured questionnaires under the following parameters: feasibility of initiation of ‘TBDetect’ microscopy in DMCs, sample preparation and testing, training, time-to-result, logistics, and troubleshooting. A scoring questionnaire was also used to assess ‘TBDetect’ microscopy vs. LED-FM and statistical significance of the scores was calculated using paired t-test. Results The overall positivity of ‘TBDetect’ microscopy was 10.32% (547/5300) vs. 8.96% (475/5300) of LED-FM at all sites and the increment in positivity was significant (p = 0.019). In addition, ‘TBDetect’ microscopy yielded an increment in smear grade status over LED-FM (p = 0.043). The feedback from the study-in-charge and kit users indicated that ‘TBDetect’ microscopy was easily adapted in point-of-care settings. An analysis of scoring feedback suggested that it was easy to perform and observe in comparison to LED-FM (p < 0.005). Conclusions This study established the feasibility of ‘TBDetect’ microscopy in field settings.

Rapid Determination of 12 Classes of Per- and Polyfluoroalkyl Substances in Water Samples from Environmental Forensic Cases.

The widespread use of per- and polyfluoroalkyl substances (PFASs) with different physico-chemical properties poses a great threat to the environment and human health. Simultaneous detection of different classes of PFASs is a difficult task, especially for rapid analysis of polluted water samples in environmental forensic cases. In this study, a simple sample preparation ultrahigh-performance liquid chromatography coupled with quadrupole Orbitrap high-resolution mass spectrometry was established for the detection of PFASs in a wide range of water matrices. By optimizing the conditions of pretreatment and the parameters of the instrument, the developed method provided good linearity of calibration standards (R2 > 0.99), and demonstrated excellent MLOQ (0.008-1.2 µg/L), with spiked recoveries ranging from 57.7% to 151% for 47 targets in surface water samples, and from 45.7 to 165% for 46 targets in ground and waste water samples, respectively. This method required an injection volume of 3 µL and an analysis time of only 18 min per sample. The validation method was successfully applied to the analysis of 20 environmental water samples, in which 15 target substances with different concentrations were detected, with total concentrations of 0.082 to 262.455 μg/L. The method is simple and exclusive, and can rapidly confirm the occurrence of PFASs in different water samples, providing a convenient and fast high-throughput analysis, which is especially suitable for the application in the environmental forensic investigation of PFASs pollution.

Solid Eutectic Systems and Natural Deep Eutectic Solvents in Matrix Solid-Phase Dispersion for the extraction of phenolic compounds from lettuce samples

A new and revolutionary material, called, Solid Eutectic Systems (SES) based on natural compounds are presented, prepared, and characterized for the first time. Matrix Solid-Phase Dispersion (MSPD) was used to extract and preconcentrate five important phenolic compounds from Lactuca sativa. SES based on thymol and citric acid (TC 1:1) and a Natural Deep Eutectic Solvent (NADES) based on lactic acid, glucose, and water (LGH 5:1:8) were selected as the most effective sorbent and eluent, respectively. The variables that influence the MSPD parameters were optimized: 100 mg of dried lettuce, 400 mg of TC 1:1 sorbent, 30 s of grinding time, and 1430 μL of LGH 5:1:8, obtaining AGREE and AGREEprep scores of 0.90 and 0.72. Recoveries (%) of the phenolic compounds were 70 to 115 %, with a relative standard deviations lower than 12 %. Finally, the limits of detection and quantification were 1.7–2.2 µg g−1 and 5.1–6.7 µg g−1, respectively. SES marks a transformative milestone, providing eco-friendly solutions with a streamlined preparation process. The versatile sample preparation ensures efficient cleanup across various matrices. Enhanced simplicity and adaptability can result from intelligent sorbent development for improved selectivity and sensitivity. In this study, SES was introduced as a novel green sorbent for MSPD, efficiently extracting phenolic compounds from lettuces.

Advanced Characterization and Sample Preparation Strategies for Nanoformulations

The escalating impact and remarkable progress of nanotechnology have shifted the paradigms of medicine and the healthcare system. Nanosystems have emerged, extensively holding the potential to advance disease diagnosis and treatment specificity. The extraordinary attributes imparted by nano-systems have helped in overcoming the limitations of conventional interventions to an extent and led to targeted therapy, to name one. The role of nanotechnology in diagnosis is another breakthrough in its appellation. This article aims to address the current characterization and sample preparation techniques for the analysis of nanosystems and provide insights into novel methodologies and in situ instrumentation that have eased sampling procedures.

Mapping the composite nature of clay matrix in mudstones: integrated micromechanics profiling by high-throughput nanoindentation and data analysis

AbstractMudstones and shales serve as natural barrier rocks in various geoenergy applications. Although many studies have investigated their mechanical properties, characterizing these parameters at the microscale remains challenging due to their fine-grained nature and susceptibility to microstructural damage introduced during sample preparation. This study aims to investigate the micromechanical properties of clay matrix composite in mudstones by combining high-speed nanoindentation mapping and machine learning data analysis. The nanoindentation approach effectively captured the heterogeneity in high-resolution mechanical property maps. Utilizing machine learning-based k-means clustering, the mechanical characteristics of matrix clay, brittle minerals, as well as measurements on grain boundaries and structural discontinuities (e.g., cracks) were successfully distinguished. The classification results were validated through correlation with broad ion beam-scanning electron microscopy images. The resulting average reduced elastic modulus (Er) and hardness (H) values for the clay matrix were determined to be 16.2 ± 6.2 and 0.5 ± 0.5 GPa, respectively, showing consistency across different test settings and indenter tips. Furthermore, the sensitivity of indentation measurements to various factors was investigated, revealing limited sensitivity to indentation depth and tip geometry (when comparing Cube corner and Berkovich tip in a small range of indentation depth variations), but decreased stability at lower loading rates. Box counting and bootstrapping methods were applied to assess the representativeness of parameters determined for the clay matrix. A relatively small dataset (indentation number = 60) is needed to achieve representativeness, while the main challenges is to cover a representative mapping area for clay matrix characterization. Overall, this study demonstrates the feasibility of high-speed nanoindentation mapping combined with data analysis for micromechanical characterization of the clay matrix in mudstones, paving the way for efficient analysis of similar fine-grained sedimentary rocks.

Separation of microplastics from deep-sea sediment using an affordable, simple to use, and easily accessible density separation device

Microplastics accumulate in the environment but methods to extract particles from sediment for quantification and identification often lack accuracy and reproducibility. Existing methods vary greatly and many do not achieve adequate microplastic separation. During method development for extraction procedures, spike-recovery experiments (positive controls) are essential to ensure accurate and reproducible results from each sample matrix. Furthermore, the large variability in grain size and organic matter can affect the extraction of microplastics from the matrix. Scientists have used density separation to separate microplastics from matrices for decades, but apparatuses are often made of plastic, need to be custom made, and require multiple sample transfers from one apparatus to another. This study presents an affordable, easily accessible, and simple to use Density Separation Device (DSD) to remove plastics from deep-sea sediments. Eight polymers were spiked into replicates of environmental sediment, including six fragments: high density polyethylene (HDPE), polypropylene (PP), polyvinyl chloride (PVC), polystyrene (PS), nylon (PA6), and crumb rubber (CR) and two fibers: cellulose acetate (CA) and polyester (PEST). Two size classes of polymers were used: 100 μm to 300 μm and > 300 μm. Using a sodium polytungstate solution at a density of 1.9 g/mL and reflectance FTIR microscopy for particle identification, mean recoveries of all fragments exceeded 78% (CR: 92.7% ± 30.8%, PP: 78.4% ± 34.0%, HDPE: 93.8% ± 13.5%, PS: 86.9% ± 25.7%, PA6: 98.4% ± 63.2%, PVC: 100.0% ± 12.4%). Fiber recovery was much lower (PEST: 28.1% ± 28.1% and CA: 25.9% ± 17.3%) because they aggregated, passed through sieves vertically, or were obscured under other particles. The fragment recovery success, accessibility (available online, all parts under $200) and ease of use of this DSD should facilitate widespread use, thus helping to standardize sample preparation methods for microplastic metrology.

Terahertz channel modeling based on surface sensing characteristics

The dielectric properties of environmental surfaces, including walls, floors and the ground, etc., play a crucial role in shaping the accuracy of terahertz (THz) channel modeling, thereby directly impacting the effectiveness of communication systems. Traditionally, acquiring these properties has relied on methods such as terahertz time-domain spectroscopy (THz-TDS) or vector network analyzers (VNA), demanding rigorous sample preparation and entailing a significant expenditure of time. However, such measurements are not always feasible, particularly in novel and uncharacterized scenarios. In this work, we propose a new approach for channel modeling that leverages the inherent sensing capabilities of THz channels, specifically by obtaining channel measurement data through the analysis of refractive indices. By comparing the results obtained through channel sensing with that derived from THz-TDS measurements, we demonstrate the its ability to yield dependable surface property information. Integrating it into a ray-tracing algorithm for channel modeling in both a miniaturized cityscape scenario and an indoor environment, the results show consistency with experimental measurements, thereby validating its effectiveness in real-world settings.

Colorimetric detection of Cr(VI) in water using tetramethyl benzidine (TMB) as an indicator

Hexavalent chromium (CrVI) poses a serious risk to both human and environment health. Hence, a simple, robust, and efficient analytical method must be developed to monitor the presence of Cr(VI) in the environment. The current investigation concentrated on the colorimetric detection of Cr(VI) using TMB as indicator in the presence of H2O2. The study found that Cr(VI) reacts with H2O2 to generate hydroxyl radicals which oxidize TMB in a concentration dependent manner. Under optimized conditions, the method obtained a good linearity range (0.025–0.5 mg/L, r2 = 0.9944) with LOD and LOQ of 0.009 mg/L and 0.029 mg/L, respectively. The technique was further improved by the addition of EDTA in the sample preparation protocol to reduce the false positive result by the presence of ions like Cu2+, Fe3+, etc. The study recorded improved Cr(VI) recoveries (81.73–111.40 %) at different fortification levels (0.1–0.5 mg/L). Under optimized conditions, the EDTA added method obtained a good linear response (r2 = 0.9952) with a detection limit of 0.023 mg/L which is less than the prescribed limits by WHO (0.05 mg/L) and US EPA (0.1 mg/L) for drinking water. The developed analytical method is very simple without use of any nanomaterial and the results with natural water samples show that it has the potential for real-time detection of Cr(VI) in the environment.

Correlating physico-chemical properties of analytes with Hansen solubility parameters of solvents using machine learning algorithm for predicting suitable extraction solvent

Artificial neural networks (ANNs) are biologically inspired algorithms designed to simulate the way in which the human brain processes information. In sample preparation for bioanalysis, liquid–liquid extraction (LLE) represents an important step with the extraction solvent selection is the key laborious step. In the current work, a robust and reliable ANNs model for LLE solvent prediction was generated which could predict the suitable solvent for analyte extraction. The developed ANNs model takes a set of chosen descriptors for the cited analyte as an input and predicts the corresponding Hansen solubility parameters of the suitable extraction solvent as a model output. Then, from the solvent combination’s appendix, the analyst can identify the proposed extraction solvents' combination for the cited analyte easily and efficiently. For the experimental validation of the model prediction capabilities, twenty structurally diverse drugs belonging to different pharmacological classes were extracted from human plasma. The extraction process was performed using the predicted extraction solvent combination for each drug and quantitively estimated by HPLC/UV methods to assess their extraction recovery. The developed LLE solvent prediction model is in- line with the global trend towards green chemistry since it limits the consumption of organic solvents.

A real-time on-site precision nutrient monitoring system for hydroponic cultivation utilizing LIBS

Indoor hydroponic farming is an advanced cultivation technique with diverse sustainability benefits, such as facilitating local produce, minimizing transportation costs and emissions, and enabling year-round crop cultivation. To optimize crop growth for enhanced yield, improved crop quality, and reduced environmental footprint, precise monitoring and replenishment of essential nutrients within hydroponic systems is crucial. Current methods employed in most commercial farms for online nutrient supply monitoring is limited to pH and conductivity measurements. These techniques can only offer an indication of the overall change in the complex nutrient mixture and lack the capability to precisely identify the specific nutrient or quantify the nutrient content. Most of the existing techniques for measuring individual nutrient levels are expensive and invasive, necessitating sample preparation, frequent recalibration, and skilled personnel for operation. In this context, we propose and demonstrate a real-time, on-site monitoring system for the precise analysis of hydroponic nutrient supply based on laser-induced breakdown spectroscopy (LIBS). We also discuss the system design considerations, parametric optimizations, limit of detection (LOD), and limit of quantitation (LOQ) of key nutrient components such as potassium (K), sodium (Na), calcium (Ca), and magnesium (Mg), using the proposed approach. The detection range of the developed LIBS-based monitoring system can encompass the typical concentration range observed in hydroponic nutrient solutions used at agricultural farms. This technique offers rapid online monitoring of individual nutrient components, providing precise, real-time analysis and the potential to enable comprehensive automation capabilities for current and future hydroponic farms.Graphical abstract

Comparison of SIMOA and VEUS technologies for serum neurofilament light chain measurement in multiple sclerosis

IntroductionThe gold standard for serum neurofilament light chain (sNfL) determination is the single molecule array (SIMOA), the use of which is limited by availability and cost. The VEUS method is a fully automated, user-friendly diagnostic system requiring no sample preparation, with high reported sensitivity, multiplexing capability, and rapid diagnostics. The aim of this study was to compare the SIMOA and VEUS methods for determining sNfL levels in patients with multiple sclerosis (MS). MethodologyA single-centre cross-sectional study was conducted at the MS Centre of University Hospital Ostrava. Patients were enrolled in the study from January 18 to January 31, 2024. Inclusion criteria were: 1) diagnosis of MS according to the revised 2017 McDonald criteria, 2) age ≥18 years, and 3) signed informed consent. The NF-light V2 diagnostic kit (SIMOA, Quanterix) and the Singleplex Neurology assay kit (VEUDx, EZDiatech) were used to determine sNfL concentrations. The two methods were compared by use of Spearman correlation, Passing–Bablok regression, and Bland–Altman analysis. ResultsA total of 49 patients were included in the study, of whom 39 (79.6 %) were female. The median sNfL concentration was 7.73 (IQR 5.80–9.93) ng/L determined by SIMOA and 1.31 (IQR 1.18–1.65) ng/L by VEUS. We did not find a correlation between SIMOA and VEUS (rs = 0.025, p = 0.866). Passing–Bablok regression demonstrated a systematic and proportional difference between the two methods. A significant disagreement between them was also confirmed by the Bland–Altman plots. On average, sNfL values measured by SIMOA were 3.56 ng/L (95 % CI 0.78 to 6.34) higher than those measured by VEUS. ConclusionOur investigation uncovered noteworthy disparities between the SIMOA and VEUS techniques in determining sNfL levels. Specifically, the VEUS technique systematically produces lower estimates of sNFL levels. This substantial variance emphasizes the importance of carefully evaluating assay methods when quantifying sNfL.

Artifact-free sample preparation of metal thin films using Xe plasma-focused ion beam milling for atomic resolution and in situ biasing analyses

The focused ion beam (FIB) technique using Ga ion beams is generally employed for transmission electron microscopy (TEM) sampling owing to its location-specific beam controllability on materials. However, Ga ion beam bombardment-induced damage hinders reliable structural analysis. Furthermore, Ga ions implanted in the damaged surface layer substantially lower the chemical stability of the samples, such as metal thin films. Here, aiming for atomic-level interface structural analysis, we propose a useful approach for the TEM sample preparation of heteroepitaxial Ag/Cu metal films without physical damage or chemical instabilities using the Xe plasma FIB (PFIB) system. Xe plasma-assisted sampling ensured that the interface structure of the Ag/Cu metal film remained intact; in contrast, the sample prepared using the focused Ga ion beam was damaged by elemental mixing. Furthermore, the sample prepared by Xe plasma milling exhibited robust structural stability over time after exposure to air in contrast to the sample prepared by Ga-ion milling, which induced structural decomposition owing to oxidation. In addition to the static structural analysis, the Cu thin film sample prepared by Xe PFIB exclusively exhibited pristine structural properties under in situ electrical biasing experiments, thus confirming the feasibility of conducting a fundamental study of Cu electromigration without artifacts.

Evaluation of an automatic sample preparer in the development and validation of an analytical method for vial wall sorptive extraction

Automation has transformed the field of analytical chemistry by enhancing efficiency and precision in laboratory processes. A crucial step in analytical workflows, sample preparation, has traditionally relied on manual techniques, leading to variability and inefficiency. Vial wall sorptive extraction (VWSE) is a promising alternative for automating and enhancing sample preparation in analytical processes. This study aims to evaluate the performance of automated VWSE in the analysis of alkanes (C10-C18) in aqueous phases and to explore its potential use in routine laboratory settings for analyzing contaminants in environmental analysis, quality control, and forensics. VWSE devices were developed and characterized, a chromatographic method was established, and the sample preparation process was automated using an automated liquid handling system. The devices manufactured exhibit the best overall response and low standard deviation. Statistical tests confirm the equivalence of the vials prepared. The developed method achieved good results in analytical validation, a wide linear range with a high coefficient of determination (R2 > 0.90), low limits of detection (0.01–1.02 ng mL−1), and low limits of quantification (0.05–1.05 ng mL−1) were achieved. The parameters repeatability (<26.91 %), recovery (91 to 116 %), and intermediate precision (<22.29 %) also achieved a good analytical performance. The developed automated VWSE method proves effective in quantifying alkanes and meets analytical method validation criteria. This research highlights the potential of automated VWSE for sample preparation in various analytical applications.

Elemental analysis of valuable byproducts by TXRF spectrometry: coal fly ash and activated carbon

In order to ensure that byproducts are environmentally friendly and fit for purpose, their chemical composition must be determined, with special attention to elements at trace level. The large variability in the type of matrices demands a versatile analytical technique, compatible with sample preparation methods allowing both fast composition screenings and accurate quantitative analysis.In this work, byproducts derived from carbon-rich matrices, including coal fly ash and activated carbon from coconut and almond shells, were investigated by means of total reflection x-ray spectrometry and different sample preparations. Suspension, acid digestion, solid-liquid extraction and ashing were performed and assessed as to their complexity and detection capabilities, ranging from 0.01 mg/kg to 16 mg/kg, depending on the element and sample preparation. The internal standard quantification with gallium, aided by a variation of the standard additions method to take into account its possible presence in the samples, allowed to determine elements of environmental and technological interest, including K, Ca, Ti, V, Mn, Cr, Ni, Cu, Zn, Ga, As, Sr, Pb. Assets, limits and possible developments are presented and discussed.

Biofluorescence imaging-guided spatial metabolic tracing: In vivo tracking of metabolic activity in circulating tumor cell-mediated multi-organ metastases

Circulating tumor cells (CTC) are considered metastatic precursors that are shed from the primary or metastatic deposits and navigate the bloodstream before undergoing extravasation to establish distant metastases. Metabolic reprogramming appears to be a hallmark of metastatic progression, yet current methods for evaluating metabolic heterogeneity within organ-specific metastases in vivo are limited. To overcome this challenge, we present Biofluorescence Imaging-Guided Spatial Metabolic Tracing (BIGSMT), a novel approach integrating in vivo biofluorescence imaging, stable isotope tracing, stain-free laser capture microdissection, and liquid chromatography-mass spectrometry. This innovative technology obviates the need for staining or intricate sample preparation, mitigating metabolite loss, and substantially enhances detection sensitivity and accuracy through chemical derivatization of polar metabolites in central carbon pathways. Application of BIGSMT to a preclinical CTC-mediated metastasis mouse model revealed significant heterogeneity in the in vivo carbon flux from glucose into glycolysis and the tricarboxylic acid (TCA) cycle across distinct metastatic sites. Our analysis indicates that carbon predominantly enters the TCA cycle through the enzymatic reaction catalyzed by pyruvate dehydrogenase. Thus, our spatially resolved BIGSMT technology provides fresh insights into the metabolic heterogeneity and evolution during melanoma CTC-mediated metastatic progression and points to novel therapeutic opportunities.

PrecivityAD2™ Blood Test: Analytical Validation of an LC-MS/MS Assay for Quantifying Plasma Phospho-tau217 and Non-Phospho-tau217 Peptide Concentrations That Are Used with Plasma Amyloid-β42/40 in a Multianalyte Assay with Algorithmic Analysis for Detecting Brain Amyloid Pathology.

Alzheimer's disease (AD) is a progressive irreversible neurodegenerative disorder that represents a major global public health concern. Traditionally, AD is diagnosed using cerebrospinal fluid biomarker analysis or brain imaging modalities. Recently, less burdensome, more widely available blood biomarker (BBM) assays for amyloid-beta (Aβ42/40) and phosphorylated-tau concentrations have been found to accurately identify the presence/absence of brain amyloid plaques and tau tangles and have helped to streamline AD diagnosis. However, few BBMs have been rigorously analytically validated. Herein, we report the analytical validation of a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) multiplex method for quantifying plasma phosphorylated-tau217 (p-tau217) and non-phosphorylated-tau217 (np-tau217) peptide concentrations. We combined the p-tau217/np-tau217 concentrations ratio (%p-tau217) and the previously validated LC-MS/MS multiplex assay for plasma Aβ42/40 into a new multianalyte assay with algorithmic analysis (MAAA; PrecivityAD2™ test) that identifies brain amyloid status based on brain amyloid positron emission tomography. We found (a) the %p-tau217 assay is precise, accurate, sensitive, and linear over a wide analytical measurement range, and free from carryover and interference; (b) the pre-analytical specimen collection, processing, storage, and shipping conditions that maintain plasma tau peptide stability; and (c) using the measured analytical imprecision for plasma Aβ42/40 and p-tau217/np-tau217 levels in a worst-case scenario model, the PrecivityAD2 test algorithm for amyloid pathology classification changed for only 3.5% of participants from brain amyloid positive to negative, or from negative to positive. The plasma sample preparation and LC-MS/MS methods underlying the PrecivityAD2 test are suitable for use in the clinical laboratory and valid for the test's intended purpose: to aid in the diagnostic evaluation of individuals aged 55 and older with signs or symptoms of mild cognitive impairment or dementia.

Efficient Taste Analysis via Single-Channel Hybrid Electronic Tongue

The prospective applications of electronic tongues (e-tongues) in the food, water, beverage, and pharmaceutical industries have long been hampered by the inconvenient nature of series measurements using expensive and specialised sensor arrays. A cost-efficeint and easier solution to this problem arises in the shape of a single-channel hybrid e-tongue, presenting a novel approach to overcoming restrictions. This progress uses data fusion from potentiometry and impedimetry to combine these measures into a single channel made up of unfunctionalized metal electrodes supported by a pH electrode.The hybrid e-tongue combines potentiometric response, which includes pH and open circuit potential, with impedimetric response, which takes into account comparable electric circuit parameters such as charge transfer resistance and double-layer capacitance. The taste discriminability of this low-cost single-channel hybrid e-tongue is validated using two metal electrodes, Pt and Ni, and two separate sample preparations of basic taste analytes, each at concentrations around the human tongue threshold.Principal component analysis (PCA) plots are used to test qualitative discrimination by reducing dimensionality and clustering analytes. Silhouette coefficients (SC) and hierarchical cluster analysis are used to assess clustering quality. Even without particular sample preparation, the Pt and Ni electrodes exhibit substantial clustering with SC values of 0.83 and 0.74, respectively. This significant outcome highlights the efficacy of the hybrid e-tongue in improving taste discriminability.Comparisons with potentiometric and impedimetric measurements performed independently show that the hybrid e-tongue, assisted by data fusion at a single channel, improves accuracy and clustering significantly. This finding not only speeds up the analysis process, but it also improves the overall effectiveness of taste discrimination.Correlations between taste analytes and physicochemical factors are formed using heatmap plots and PCA loading plots to provide a fuller knowledge of the hybrid e-tongue's mechanics. These visualisations provide vital insights into the complex interplay of several physicochemical processes, offering insight into the mechanism underlying the hybrid e-tongue's excellent performance.discrimination.Despite its remarkable capabilities, the study acknowledges that taste discriminability diminishes due to the buffer activity of the standard reference solution used for sample preparation. This recognition prompts further exploration and optimization of the solution to ensure the broad applicability of the hybrid e-tongue across various scenarios.In conclusion, the reported single-channel hybrid e-tongue represents a significant advancement in taste analysis technology. By addressing the challenges associated with series measurements on complex sensor arrays, this innovation opens new avenues for commercial e-tongues in diverse industries. The amalgamation of potentiometry and impedimetry in a single channel not only enhances accuracy and clustering but also provides valuable mechanistic insights. As the research community continues to refine and optimize this technology, the future holds great promise for the widespread adoption of single-channel hybrid e-tongues in analytical applications, advancing how we perceive and understand taste.

(Invited) MoS2 Photodetectors for Near-Infrared Biosensing Applications

Device researchers have been actively developing novel diagnostic biosensors using metallic nanoparticle-based plasmonic immunoassays.[1] In these biosensing devices, photodetectors with high photoresponsivity and low internal noise levels are integrated to detect the marginal optical signals change induced by biomarker binding events (i.e., Antigen-antibody binding). Recently, atomically thin layers of molybdenum disulfide (MoS2) have been integrated with plasmonic components to enable fast and sensitive colorimetric monitoring of disease-related biomarkers.[2] However, such biosensors are mostly operated in the ultraviolet/visible range, which needs a purification step to separate out a variety of unwanted biomaterials that absorb visible light and takes several hours of preparation steps. Thus, it would be amenable to develop biosensors for biomolecular detections or immunoassays in the whole blood (WB) analytes without any sample preparations.[3] To address the issues mentioned above, recent studies have demonstrated the engineered gold nanoparticles (AuNPs) that have localized surface plasmonic resonance (LSPR) shift around near-infrared (NIR) wavelength region. However, a high-sensitivity photodetector under NIR region is still required to detect marginal signal changes due to the target biomarker binding events. Meanwhile, the MoS2 material has been reported to exhibits superior photo-response characteristics.[4] MoS2 is a transition metal dichalcogenide material of which single- and multi-layer films exhibit an efficient electron-hole pair generation rate under photoexcitation and therefore high photo absorption as compared to silicon. Therefore, a systematical study on MoS2 photoconductors to optimize the optoelectronic properties under near-infrared (NIR) (λ = 650 nm) operation can enable zero-preparation WB immunoassays combined with specially engineered AuNPs.In this work, we study the photo-response properties (i.e., Photoresponsivity spectrum) of in-plane MoS2 photodetectors as the function of their geometric dimensions and fabrication conditions. Recent study shows that an annealing temperature after exfoliation can etch the upper layers of MoS2 flakes and clean stains on the device and therefore improve device performances (e.g., mobility). [5] This work enables the NIR operation capabilities of plasmonic colorimetric biosensing by introducing the optimized MoS2 photodetector fabrication practice. This approach reduces assay preparation times and mitigate background interference even with WB analytes and thereby enable the WB point-of-care immunoassays.

Additive Manufactured Multiplex Sensing Structures for Attomole-Sensitive Detection of Hypocalcemia

INTRODUCTION In the United States, 30-50% of dairy cows experience metabolic disorders due to nutritional deficiencies, leading to economic losses, especially from reduced milk yield due to hypocalcemia. Calcium is crucial for muscle and nerve function, skeletal strength, and immune function. Laboratory screening costs $60 per sample, and on-site testing costs around $1000. With approximately 33% subclinical and 5% clinical hypocalcemia prevalence in US dairy herds, there's a need for smart, cost-effective sensors. Early diagnosis is vital for disease prevention, relying on rapid, farm-side, accurate assessment of calcium (Ca2+) and phosphate (P) ion levels.Herein, an attomole-sensitive sensor was developed using 3D printed structures to detect ionized phosphate to calcium ratios in milk samples, diagnosing milk fever. Unique 3D printed sensor geometries with wrinkled surfaces provide an unprecedented limit-of-detection of 138 aM. Wrinkled surfaces of poly (3-octyl-thiophene) act as ion-to-electron transducers for Ca2+ and P detection. The P/Ca2+ ratio measurement with potentiometry technique not only indicates early disease but also enables on-site testing without any need for mediator or sample preparation. Our sensor validated using cow’s milk, whole milk, and fetal bovine serum, and results were compared with commercial meters. This low-cost, sensitive, and fast response (~10 s) sensor is a promising tool for in-farm diagnostic facilitating management of dairy cows. SENSOR FABRICATION The manufacturing process begins with 3D CAD design of the sensor base (Figure 3c). The sensor is produced using a high-resolution extrusion-based 3D printer, enables the manufacturing of microstructures. Prints undergo washing process, and resin is cured with UV light (405 nm). Figure 2b shows two distinct microstructure types on the sensor base, amplifying surface area. The lateral pattern enhances surface area, aiding 3D microelectrode formation for analyte diffusion. Besides, random wrinkles form unintentionally due to resin instability during UV exposure, serving as microelectrodes and increasing surface area, leading to enhanced sensitivity. Next, a Kapton shadow mask covers the sensor's surface, and an e-beam evaporator applies a gold thin layer to uncovered regions. Ca2+ and P ion sensing electrodes are modified with POT as the ion-to-electron layer, followed by drop-cast Ca2+ and P ion-selective membrane (ISM) on top of POT layer. The reference electrode is constructed by applying Ag/AgCl paste between two working electrodes, covered with a Nafion layer for stability and Cl¯ leaking prevention. To improve repeatability, each sensor section is treated with a high ion concentration solution of Ca2+ and P. RESULTS AND DISCUSSION Surface characterization of the electrode involved electrochemical and surface analyses. FE-SEM images in Figure 2b, d show the lateral pattern and micro-wrinkles of the sensor base. Cyclic voltammetry investigated electrochemical behavior, revealing distinct peaks during ferro/ferricyanide presence (Figure 2a). Gold catalyzed mediator redox reaction, with the POT layer decreasing peak currents due to increased surface resistance. The ISM, primarily PVC, elevated electrical resistance, and selectively allowing Ca2+ and P to pass through rather than mediators, reducing current. Electrochemical Impedance Spectroscopy confirmed findings, with Nyquist plots showing charge transfer resistance (Rct) in Figure 2c. Open circuit potentiometry (OCP) detected Ca2+ and P ions (Figure 1a, 1c). OCP response increasing with higher Ca2+ concentration and decreasing with elevated P ion concentration. Calibration graphs in Figure 1b, 1d demonstrated a linear relationship between ion concentrations and OCP. OCP measurements across various concentrations, sensor washing, and repeated measurements in Figure 1a, 1c indicated sensors repeatability. Finally, sensor tests with fresh milk samples from 15 lactating Holstein multiparous cows revealed notable variation in P levels compared to Ca2+ concentration. Examining the P/Ca2+ ion ratio in milk samples (Figure 6f) assessed milk fever in dairy cows, indicating health status in terms of hypocalcemia, and hypercalcemia. Note: The high quality images will be provided in the poster. Figure 1

Cryogenic Atom Probe Tomograph to Resolve Confined Electrochemical Interfaces

Atom Probe Tomography (APT) is an analysis technique capable of providing a 3-dimensional, element-sensitive map of needle-shaped samples (where the tip radius is about 50 nm) with sub-nanometre resolution [1]. APT analysis is carried out at temperatures in the range of 25-75 K to limit the thermal motion of surface atoms which improves the spatial and mass resolution. As a result, this enables the analysis of frozen liquids, and by extension solid-liquid interfaces, by so-called “cryo-APT”. While this was historically challenging, recent advancements in UHV-cryogenic transfer and sample preparation methods now make it possible for the atomic scale analysis of interfacial species in electrochemical systems [2-4].In this study, we will attempt to explore the effect of nanoscale geometrical confinement on the distribution of interfacial ions for the first time and to resolve the electric double layer, using cryo-APT. We will describe the workflow for cryo-APT sample preparation to study confined solid-liquid interfaces, using nanoporous gold as a template material with a frozen sodium iodide solution inside its pores. APT reconstructions will allow 3-dimensional mapping of aqueous interfacial species, helping to develop our understanding of the structure of the electric double layer under nanoscale geometrical confinement. The attached Figure shows an SEM image of the later stages of cryo-FIB milling of an APT tip of frozen deionised water and 50 mM sodium iodide and a segment of the related APT atom map reconstruction.