This paper builds on an earlier examination of the influence of sampling size and analyte surface density on the accuracy and precision of measurements using surface-enhanced Raman scattering (SERS) to read out heterogeneous immunoassays. Quantitation using SERS typically relies on interrogating a small area on the sample surface by using a micrometer-sized laser spot for signal generation. The information obtained using such a small portion of sample is then projected as being representative of the much larger sample, which can compromise the accuracy and precision of the measurement due to undersampling. For a heterogeneous immunoassay interrogated by SERS, quantitation is, therefore, sensitive to the size of the analyzed area and the surface density of the measured analyte. To identify conditions in which sampling error poses a threat to accuracy and precision, a simulation of a SERS immunoassay was developed and compared to experimental results. The simulation randomly distributes adsorbates across the capture surface and then measures the density of adsorbates inside areas of analysis of different sizes. This approach mimics the analysis of a heterogeneous immunoassay when using a Raman microscope with different laser spot sizes. The results of the simulations, which were confirmed experimentally by comparison to an immunoassay of human immunoglobulin G (IgG) show that the accuracy and precision of the measurement improved with larger analysis areas and higher analyte concentrations due to the increased apparent homogeneity of the analyte within the area of analysis. By imposing a threshold on precision (5%), we also begin to establish a framework for the parameters necessary to achieve reliable quantitative measurements (e.g., laser spot size, analyte concentration, and sample volume).
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December 2024
Department of Electronics and Communication Engineering, Dronacharya Group of Institutions, Greater Noida, UP, India.
Speaker verification in text-dependent scenarios is critical for high-security applications but faces challenges such as voice quality variations, linguistic diversity, and gender-related pitch differences, which affect authentication accuracy. This paper introduces a Gender-Aware Siamese-Triplet Network-Deep Neural Network (ST-DNN) architecture to address these challenges. The Gender-Aware Network utilizes Convolutional 2D layers with ReLU activation for initial feature extraction, followed by multi-fusion dense skip connections and batch normalization to integrate features across different depths, enhancing discrimination between male and female speakers.
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December 2024
School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, Life Sciences Building 85, University Road, Highfield, Southampton, SO17 1BJ, UK.
Osteoarthritis (OA) is a complex disease of cartilage characterised by joint pain, functional limitation, and reduced quality of life with affected joint movement leading to pain and limited mobility. Current methods to diagnose OA are predominantly limited to X-ray, MRI and invasive joint fluid analysis, all of which lack chemical or molecular specificity and are limited to detection of the disease at later stages. A rapid minimally invasive and non-destructive approach to disease diagnosis is a critical unmet need.
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December 2024
College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for efficiently addressing and enhancing control measures against mosquito-transmitted diseases.
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December 2024
School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China.
Microtextured microneedles are tiny needle-like structures with micron-scale microtextures, and the drugs stored in the microtextures can be released after entering the skin to achieve the effect of precise drug delivery. In this study, the skin substitution model of Ogden's hyperelastic model and the microneedle array and microtexture models with different geometrical parameters were selected to simulate and analyse the flow of the microtexture microneedle arrays penetrating the skin by the finite-element method, and the length of the microneedles was determined to be 200 μm, the width 160 μm, and the value of the gaps was determined to be 420 μm. A four-pronged cone was chosen as the shape of microneedles, and a rectangle was chosen as the shape of the drug-carrying microneedle.
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December 2024
Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST), Institute of Integrated Research (IIR), Institute of Science Tokyo, 4259 Nagatsuta-cho, Midori, Yokohama, 226-8503, Kanagawa, Japan.
The sense of smell is fundamental for various aspects of human existence including the flavor perception, environmental awareness, and emotional impact. However, unlike other senses, it has not been digitized. Its digitalization faces challenges such as the lack of reliable odor sensing technology or the precise scent delivery through olfactory displays.
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