Hand-held Instrument Research Articles

Data-Driven and Machine-Learning-Based Real-Time Viscosity Measurement Using a Compliant Mechanism

In this work, a novel method of viscosity measurement is proposed using a device comprising a compliant mechanism, a vibration source, and a piezoelectric sensor. The vibration source creates linear harmonic vibrations in the compliant mechanism suspended in the liquid, and the acceleration response of the mechanism is measured using the piezoelectric sensor. The vibration source is located in the central mass of the compliant mechanism, which is designed to have the necessary directional stiffness. As the mechanism vibrates, the links in the mechanism undergo damping due to the shearing action of the fluid because of its viscosity. A series of viscosity measurements are carried out with the use of water–glycerol solutions such that the acceleration of the mass is influenced by the fluid’s viscosity. During the working of the device, the mechanism is immersed in the liquid whose viscosity is to be measured. The acceleration response of the mass is recorded as time domain data using NI Lab View hardware and software, which are used to train a machine learning model. Later, a regression-based machine learning model is used for the estimation of dynamic viscosity for the given acceleration input. Experiments are performed with the prototype device using the water–glycerol solution within a viscosity ranging from 10 cP to 60 cP. The proposed sensor can be used for in-line measurements or used as a handheld instrument for quick measurements. The machine learning model achieved a high level of accuracy, evidenced by an R-squared value of 0.99, indicating that it explains 99% of the variance in the data.

Smartphone-Based Leaf Colorimetric Analysis of Grapevine (Vitis vinifera L.) Genotypes

Leaf chlorophyll content is a key indicator of plant physiological status in viticulture; therefore, regular evaluation to obtain data for nutrient supply and canopy management is of vital importance. The measurement of pigmentation is most frequently carried out with hand-held instruments, destructive off-site spectrophotometry, or remote sensing. Moreover, smartphone-based applications also ensure a promising way to collect colorimetric information that could correlate with pigmentation. In this study, four grapevine genotypes were investigated using smartphone-based RGB (Red, Green, Blue) and CIE-L*a*b* colorimetry and a portable chlorophyll meter. The objective of this study was to evaluate the correlation between leaf chlorophyll concentration and RGB- or CIE-L*a*b*-based color indices. A further aim was to find an appropriate model for discriminating between the genotypes by leaf coloration. For these purposes, fully developed leaves of ‘Chardonnay’, ‘Sauvignon blanc’, and ‘Pinot noir’ clones 666 and 777 were investigated with the Color Grab smartphone application to obtain RGB and CIE-L*a*b* values. Using these color values, chroma, hue, and a further 31 color indices were calculated. Chlorophyll concentrations were determined using an Apogee MC100 device, and the values were correlated with color values and color indices. The results showed that the chlorophyll concentration and color indices significantly differed between the genotypes. According to the results, certain color indices show a different direction in their relationship with leaf pigmentation for different grapevine genotypes. The same index showed a positive correlation for the leaf chlorophyll concentration for one variety and a negative correlation for another, which raises the possibility that the relationship is genotype-specific and not uniform within species. In light of this result, further study of the species specificity of the commonly used vegetation indices is warranted. Support Vector Machine (SVM) analysis of the samples based on color properties showed a 71.63% classification accuracy, proving that coloration is an important ampelographic feature for the identification and assessment of true-to-typeness.

Emission Factors for Biochar Production from Various Biomass Types in Flame Curtain Kilns

Simple and low-cost flame curtain (“Kon-Tiki”) kilns are currently the preferred biochar technology for smallholder farmers in the tropics. While gas and aerosol emissions have been documented for woody feedstocks (twigs and leaves) with varying moisture contents, there is a lack of data on emissions from other types of feedstocks. This study aims to document the gas and aerosol emissions for common non-woody feedstocks and to compare emissions from finely grained, high-lignin feedstock (coffee husk) with those from coarser, low-lignin feedstocks (maize cobs, grass, sesame stems). Throughout each pyrolysis cycle, all carbon-containing gases and NOx were monitored using hand-held sensitive instruments equipped with internal pumps. Carbon balances were used to establish emission factors in grams per kilogram of biochar. The resulting methane emissions were nearly zero (<5.5 g/kg biochar) for the pyrolysis of three dry (~10% moisture) maize cobs, grass, and a 1:1 mixture of grass and woody twigs. For sesame stems, methane was detected in only two distinct spikes during the pyrolysis cycle. Carbon monoxide (CO) and aerosol (Total Suspended Particles, TSP) emissions were recorded at levels similar to earlier data for dry twigs, while nitrogen oxide (NOx) emissions were negligible. In contrast, the pyrolysis of finely grained coffee husks generated significant methane and aerosol emissions, indicating that technologies other than flame curtain kilns are more suitable for finely grained feedstocks. The emission results from this study suggest that certification of biochar made from dry maize, sesame, and grass biomass using low-tech pyrolysis should be encouraged. Meanwhile, more advanced systems with syngas combustion are needed to sufficiently reduce CO, CH4, and aerosol emissions for the pyrolysis of finely grained biomasses such as rice, coffee, and nut husks. The reported data should aid overarching life-cycle analyses of the integration of biochar practice in climate-smart agriculture and facilitate carbon credit certification for tropical smallholders.

Eco-sustainable and flexible SERS platform based on waste cellulose decorated by Ag nanoparticles

This paper presents an innovative and environmentally friendly technology for the fabrication of low-cost SERS (Surface-Enhanced Raman Spectroscopy) sensors based on flexible substrates made of cellulose fibers reclaimed from waste. The substrates are decorated with nanostructured silver (Ag) thin films produced by pulsed laser deposition (PLD). In this process, the deposition conditions (laser fluence, gas pressure, target-substrate distance, deposition time, etc.) were optimized to enhance the SERS response. Different types of paper with different textures were tested, as it was also observed that the paper roughness significantly influences SERS efficiency. The samples were characterized using UV–Vis absorption spectroscopy, SEM microscopy, and surface profilometry to evaluate both the paper and the deposited films' morphologies. The SERS activity was assessed by detecting Rhodamine 6G in aqueous solutions drop-casted on the sensors, with concentrations ranging from 10−2 M to 10−10 M. Measurements were carried out using a handheld instrument equipped with dual excitation laser lines centered at 785 nm and 833 nm. The observed lower detection limit of 10−10 M was achieved across all paper types tested. These results demonstrate the potential of integrating smart, eco-friendly materials in the fabrication of chemical sensors for sustainable advancement in environmental monitoring and safety. The materials not only exhibit excellent sensing capabilities but also minimize ecological footprints through renewable sourcing and eco-friendly production processes. While the deposition protocol is well-established for other substrates, this study marks the first exploration of its use on biomass-derived substrates.

Baseline survey of environmental parameters, radiation, and drip water hydrochemistry in Niah Caves (Sarawak, Malaysia)

Relict caves in fenglin karst may typically have numerous entrances and openings. Hence, they host a variety of environments in which parameters such as light, airflow, humidity, and temperature may vary significantly over short distances. Similarly, drip water hydrochemistry, including isotopic values, may vary due to different contributions of various sources and residence time in the karst. This study investigated environmental parameters, including radiation, using hand-held instruments, along a transect within several major caves in the Niah karst of Sarawak (Malaysia). This has led to a baseline data set which showed an inverse relationship between humidity and temperature, gamma radiation levels that are about 25% of that in surrounding non-karst region, and high percentages of twilight zones in the studied caves. Airflow was found to be variable, with high values of 530 m3/s in Painted Cave and 122 m2/s in parts of Gan Kira passage, with flow towards the southeast at the time of the study. The hydrochemistry of the drip water and surface water was also analyzed and found to be dominantly Ca–Mg–Cl water type which indicates dissolution of minerals through water–rock interaction. In addition, the cave environment, particularly air temperature, humidity, and ventilation, also influences the drip water composition and isotopic values. Three different origins (precipitation, evaporation, and paleo-recharge) of drip water have been identified through the δ18O-δ2H diagram. Enriched isotopic values were observed in the cave entrance due to increased evaporation caused by lower humidity and higher air temperature. Factor analysis identifies the key geochemical processes responsible for the drip water chemistry. The outcome of this study provides the first baseline environmental data for the Niah caves, which could support future initiatives for sustainable management of this famous archeological site in southeast Asia.

Analytical HPLC Method for Determination of Miconazole Nitrate and Eugenol in Formulated Emulgel

A diabetic foot ulcer (DFU) is the prime cause of poor quality of life among diabetic patients. DFU leads to physical disability and an enormous economic burden on diabetic patients. The development and prognosis of DFU are preventable in most patients by modifying the risk factors for DFU. Programs intervened by clinical pharmacists can enhance rational drugs use and improve the early identification and prevention of DFU. This study intended to prove the beneficial outcome in identifying the risk factors and the provision of patient-tailored referral advice regarding DFU among diabetic patients. This cross-sectional study assessed the neuropathy through Michigan Neuropathy Screening Instrument (MNSI), Monofilament and Vibration test using Tuning Fork and Handheld Doppler for assessing the lower limb vascular disease as per NICE guideline among 137 diabetic patients. 64% of patients were found to have symptoms of neuropathy through the neuropathy assessment test whereas 36% did not have the symptoms. Foot sensory using monofilament test was found to be normal in 49.64% of DFU patients, reduced in 43.80%, and absent in 6.57% of DFU patients. The Ankle Brachial Index (ABI) was found to be normal in 48% of patients, mild in 34% of patients, moderate in 12% of patients, and incompressible in 6% of patients. Clinical Pharmacist intervened risk assessment through Hand-held Doppler, MNSI instrument, and Vibration test helped in screening the DFU patients for Neuropathy, and implementation of effective per patient-tailored education was found to be beneficial in the early identification of DFU and referral to specialty hospitals

Saliva-STAT: Sample-to-answer saliva test for COVID-19

Highly accessible and highly accurate diagnostics are necessary to combat rapidly-spreading infectious diseases, such as the recent COVID-19 pandemic. While lateral flow antigen tests have become pervasive, they are insufficiently sensitive to detect early or asymptomatic disease. Nucleic acid amplification tests provide the needed sensitivity, but accessibility of these tests continues to be a challenge due to the need for precise sample processing steps. Here we report a sample-to-answer test for saliva samples (saliva-STAT) that utilizes a battery-powered handheld instrument and a low-cost easily-manufacturable sample cassette to perform a nucleic acid amplification test for viral pathogens. To enable a completely automated assay, we leverage thermally responsive alkane partitions (TRAPs) and paramagnetic beads for virus purification and concentration, as well as reagent addition and mixing. Notably, the saliva STAT easily accommodates directly-dispensed saliva samples (in contrast to microfluidic devices), which is necessary for self-testing. Using the saliva-STAT platform, we demonstrate detection of down to 0.2 copies/μL of SARS-CoV-2 virus in saliva samples. We envision that the saliva-STAT could be used in walk-in clinics, mobile clinics, public testing locations, and in the home. With minor adjustments to the assay, the saliva-STAT platform can easily be adapted for other respiratory viruses, such as Influenza.

Wide-range and high-accuracy wireless sensor with self-humidity compensation for real-time ammonia monitoring

Real-time and accurate biomarker detection is highly desired in point-of-care diagnosis, food freshness monitoring, and hazardous leakage warning. However, achieving such an objective with existing technologies is still challenging. Herein, we demonstrate a wireless inductor-capacitor (LC) chemical sensor based on platinum-doped partially deprotonated-polypyrrole (Pt-PPy+ and PPy0) for real-time and accurate ammonia (NH3) detection. With the chemically wide-range tunability of PPy in conductivity to modulate the impedance, the LC sensor exhibits an up-to-180% improvement in return loss (S11). The Pt-PPy+ and PPy0 shows the p-type semiconductor nature with greatly-manifested adsorption-charge transfer dynamics toward NH3, leading to an unprecedented NH3 sensing range. The S11 and frequency of the Pt-PPy+ and PPy0-based sensor exhibit discriminative response behaviors to humidity and NH3, enabling the without-external-calibration compensation and accurate NH3 detection. A portable system combining the proposed wireless chemical sensor and a handheld instrument is validated, which aids in rationalizing strategies for individuals toward various scenarios.

Design and optimization of handheld alloy analysis instrument based on microjoule high pulse repetition frequency LIBS.

We briefly describe the design of a handheld metal detection instrument based on microjoule high repetition frequency laser-induced breakdown spectroscopy. The instrument uses a Raspberry Pi as the control core and a laser with a frequency of 10kHz and a single pulse energy of 100 µJ as the excitation source. In addition, a mini-putter is built into the instrument to move the laser, allowing the ablation of the sample surface line area without external auxiliary equipment. The excitation-generated plasma radiation is collected by a simple optical path and transmitted directly to the spectrometer. We also constructed and trained a Backpropagation Artificial Neural Network (BP-ANN) model based on 12 different grades of alloys and transplanted the feedback process of the BP-ANN to the Raspberry Pi, which realized the rapid classification of the 12 alloys with >95% classification accuracy on the handheld instrument.

Rapid prediction of the chemical composition of pet food using a benchtop and handheld near-infrared spectrometer

Quality of pet foods can be affected by many factors such as raw materials, formulations, and processing techniques. The pet food manufacturers require fast analyses to control the nutritional quality of their products. Herein, near-infrared spectroscopy (NIR) was evaluated to quantify the chemical composition of pet food, and the performances of two NIR spectrometers were investigated and compared: a benchtop instrument (1000–2500 nm) and a low-cost handheld instrument (900–1700 nm). Seventy cat food and thirty-six dog samples were characterized using reference methods for crude protein, crude fat, crude fibre, crude ash, moisture, calcium (Ca), and phosphorus (P). Principal component regression (PCR) and partial least squares regression (PLSR) were used to establish the models that involved the cat food and mixed model. The characteristic wavelengths were selected using a competitive adaptive reweighted-sampling (CARS) algorithm. The Optimal models obtained from the benchtop instrument for crude protein, crude fat, and moisture were classified as “Good” or “Very good” (Residual prediction variation (RPD) > 3), for crude fibre were classified as “Poor” (RPD>2), and for crude ash, Ca and P (RPD<2) were classified as “Very poor”. The Optimal calibrations obtained from the handheld instrument for crude protein, crude fat, and moisture were classified as “Good” or “Very good” (RPD>3), for crude fibre, crude ash, Ca, and P were classified as “Very poor” (RPD<2). Generally, the the performance of benchtop and handheld instrument was close, and the cat food model outperformed the mixed model. Results from the current study revealed the potential to monitor the chemical compositions in pet food on a large scale.

A handheld polarimetric imaging device and calibration technique for accurate mapping of terahertz Stokes vectors

In recent years, handheld and portable terahertz instruments have been in rapid development for various applications ranging from non-destructive testing to biomedical imaging and sensing. For instance, we have deployed our Portable Handheld Spectral Reflection (PHASR) Scanners for in vivo full-spectroscopic imaging of skin burns in large animal models in operating room settings. In this paper, we debut the polarimetric version of the PHASR Scanner, and describe a generalized calibration technique to map the spatial and spectral dependence of the Jones matrix of an imaging scanner across its field of view. Our design is based on placement of two orthogonal photoconductive antenna (PCA) detectors separated by a polarizing beam splitter in the PHASR Scanner housing. We show that as few as three independent measurements of a well-characterized polarimetric calibration target are sufficient to determine the polarization state of the incident beam at the sample location, as well as to extract the Jones propagation matrix from the sample location to the detectors. We have tested the accuracy of our scanner by validating polarimetric measurements obtained from a birefringent crystal rotated to various angles, as compared to the theoretically predicted response of the sample. This new version of our PHASR scanner can be used for high-speed imaging and investigation of heterogeneity of polarization-sensitive samples in the field.

Heterogeneous Integration of Acoustic Microextraction with an Optoelectronic Sensor on Glass for Nucleic Acid Testing.

Lab-on-a-chip systems (LOCs), characterized by their high sensitivity, low sample consumption, and portability, have significantly advanced the field of on-site testing. Despite the evolution of integrated LOCs from qualitative to quantitative analyses, on-chip full integration of sample preparation, purification, and multiplexed detection remains a challenge. Here, we propose a strategy for the heterogeneous integration of a set of complementary metal oxide semiconductor-compatible devices including acoustic resonator, thin-film resistors, and temperature/photosensors as a new type of LOC for nucleic acid testing (NAT). Programmed acoustic streaming-based particles and fluid manipulations largely simplify the nucleic acid extraction process including cell lysis, nucleic acid capture, and elution. The design of the acoustic microextraction module and extraction process was thoroughly studied. Benefitted by the microelectromechanical system approach, the conventional mechanical actions and complex flow control are avoided, which enables a compact hand-held NAT instrument without complicated peripherals. Validation experiments conducted on plasma-harboring mutations in the epidermal growth factor receptor (EGFR) gene confirmed the robustness of the system, achieving an impressive nucleic acid (NA) extraction efficiency of approximately 90% within 5 min and a limit of detection of the target NA in the plasma of 1 copy/μL.

Comparison of Thermal and Mechanical Pain Testing Modalities in Sprague Dawley and Fischer 344 Rats (Rattus norvegicus).

While rodents are used extensively for studying pain, there is a lack of reported direct comparisons of thermal and mechanical pain testing methods in rats of different genetic backgrounds. Understanding the range of interindividual variability of withdrawal thresholds and thermal latencies based on these testing methods and/or genetic background is important for appropriate experimental design. Testing was performed in two common rat genetic backgrounds: outbred Sprague-Dawley (SD) and inbred Fischer 344 (F344). Male and female, 10- to 14-wk-old F344 and SD rats were used to assess withdrawal thresholds in 3 different modalities: the Randall-Selitto test (RST), Hargreaves test (HT), and tail flick test (TFT). The RST was performed by using an operator-controlled handheld instrument to generate a noxious pressure stimulus to the left hind paw. The HT and the TFT used an electronically controlled light source to deliver a noxious thermal stimulus to the left hind paw or tail tip, respectively. Rats of each sex and genetic background underwent one type of test on day 0 and day 7. Withdrawal thresholds and thermal latencies were compared among tests. No significant differences were observed. Our findings can serve as a guide for researchers considering these nociceptive tests for their experiments.

Mineral and particle-size chemometric classification using handheld near-infrared instruments for soil in Northeast Brazil

The characterization of soil variations crucial for agriculture is challenging due to soil having different mineral composition and particle-size distribution. Traditional methods are costly and time-consuming for large-sized areas. Spectroscopic techniques coupled with chemometrics are alternative ways to overcome these drawbacks. Miniaturized near-infrared (NIR) spectrophotometers provide fast, cost-effective spectra acquisition for assessing soil chemistry and distribution despite challenges like overlapped bands and reduced spectral range. This study presents a pattern recognition strategy to address these limitations, enhancing the use of handheld NIR instruments for soil analysis. The study analyzed 176 soil samples from 15 soil groups in the Northeast region of Brazil. First, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) and energy-dispersive X-ray fluorescence spectrometry (EDXRF) were employed to characterize the samples, providing complementary vibrational and elemental information, respectively. Common Dimension Analysis (ComDim) identified links between ATR-FTIR and EDXRF data, aiding soil characterization. The Common Components (CCs) from ComDim were used in Partitioning Around Medoids (PAM) clustering, resulting in five distinct classes based on their mineral composition. These classes showed significant differences in clay and sand contents. With the use of ComDim-PAM, samples were labeled for classification via Partial-least Squares-Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) using NIR spectra (spectral range: 908–1676 nm) from two handheld instruments (Hand 1 and Hand 2). The SVM models outperformed the PLS-DA models, especially by including variable selection for Hand 1, with test accuracy exceeding 90%. These findings highlight the method's advantages for fast and cost-effective assessment, classification, and soil mapping based on their mineral and particle-size distribution.

Crossroads of vibrational (infrared and Raman) spectroscopy and X-ray powder diffraction in identification and characterization of some minerals – advantages and limitations. A review

Many analytical methods have been successfully employed for the study of minerals, in particular, vibrational infrared (FTIR) and Raman spectroscopies and X-ray powder diffraction (XRPD). The advantages of the vibrational spectroscopic techniques for identifying and characterizing minerals include: rapid and versatile use; qualitative and quantitative chemical signatures; distinctive chemical fingerprint of a material; indirect determination of the crystal features (polymorphism, isomorphism, coordination, degree of deformation of structural polyhedra); small sample quantity (area less than 1 μm2 for Raman); wide coverage of 4,000 – 50 cm−1 region in a single scan; in situ and direct measurements without sample preparation; nondestructive use; etc. On the other hand, XRPD is a destructive technique that, depending on the method used and the density of the material, requires from a few micrograms up to around 5 grams of sample quantity for analysis. In spite of that, it is a rapid and powerful technique used in mineral studies with relatively straightforward interpretation of the results. During the last decade, portable X-ray powder diffractometers for the nondestructive analysis of art and archeological materials have been developed along with the portable and hand-held vibrational spectroscopy instrument. Here, some advantages and limitations in the process of the complementary use of FTIR and Raman vibrational spectroscopy and XRPD for identification and characterization of minerals are outlined.

Continuous Leaf Area Index (LAI) Observation in Forests: Validation, Application, and Improvement of LAI-NOS

The leaf area index (LAI) is one of the core parameters reflecting the growth status of vegetation. The continuous long-term observation of the LAI is key when assessing the dynamic changes in the energy exchange of ecosystems and the vegetation’s response indicators to climate change. The errors brought about by non-standard operations in manual LAI measurements hinder the further research utilization of this parameter. The long-term automatic LAI observation network is helpful in reducing errors from manual measurements. To further test the applicability of automatic LAI observation instruments in forest environments, this study carried out comparative validation research of the LAI-NOS (LAI automatic network observation system) at the Wanglang Mountain Ecological Remote Sensing Comprehensive Observation Station, China, comparing it with the results measured by the LAI-2200 Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA), the LAI-probe handheld instrument, and a fisheye lens digital camera (DHP method). Instead of using the original “smoothest window” method, a new method, the “sunrise–sunset” method, is used to extract daily LAI-NOS LAI, and the corresponding confidence level is used to filter the data. The results of the data analysis indicate the following: LAI-NOS has a high data stability. The automatically acquired daily data between two consecutive days has a small deviation and significant correlations. Single-angle/multi-angle LAI measurement results of the LAI-NOS have good correlations with the LAI-2200 (R2 = 0.512/R2 = 0.652), the LAI-probe (R2 = 0.692/R2 = 0.619), and the DHP method (R2 = 0.501/R2 = 0.394). The daily LAI obtained from the improved method, when compared to the original method, both show the same vegetation growth trend. However, the improved method has a smaller dispersion. This study confirms the stability and accuracy of automatic observation instruments in mountainous forests, demonstrating the distinct advantages of automatic measurement instruments in the long-term ground observation of LAIs.

A novel technique for the removal of retained Kirschner wires utilizing a cannulated drill bit

A 35 year-old male with past history of severe open femur and tibia injury presented years after fracture fixation with a symptomatic retained Kirschner wire in his proximal tibia. A cannulated drill bit was used for removal after unsuccessful attempts using hand-held instruments. This case presents a technique for removal of a k-wire retained in bone for several years. This technique can be replicated in similar settings with cannulated drill bits from other commonly used orthopaedic device companies. Intraoperative removal of k-wires can be problematic, however, this technique offers a solution that balances implant removal and limiting destruction of surrounding tissue.

Implementing A Flexible Sensor to Identify Forces during Instrument-Assisted Soft Tissue Mobilization

Instrument-assisted soft tissue mobilization (IASTM) techniques use specialized hand-held instruments for applying controlled mechanical forces to the body with the goal of facilitating healing, improving range of motion, and reducing pain. Nevertheless, an optimal range of forces for achieving clinical outcomes has yet to be established. A barrier to advancing research on IASTM force optimization is the lack of commercially available instruments that quantify treatment forces. The aim of the current study was to assess the feasibility of attaching a flexible force sensor to a commercially available IASTM instrument to obtain valid force measurements. The validity of this novel approach was assessed by comparing data between the flexible force sensor and a force plate during a simulated treatment. Intraclass correlation coefficients, linear regression models, and Bland Altman plots all indicated excellent agreement between the force plate and flexible sensor when the instrument was used at 45°, 65°, and 90° treatment angles. Agreement between measures decreased when the instrument was held at 30°. Thus, commercially available instruments with attached sensors could make force measurement more accessible and feasible for a wider range of research settings, facilitating the advancement of IASTM research and ultimately informing clinical decision-making to improve patient care.

Thermal radiation of tongue surface as a human computer interaction diagnostics technique based on image classification with software interface

Backgroundand Purpose: Thermal radiation plays a pivotal role in addressing recognition limitations encountered by traditional Chinese medicine's tongue diagnosis. Modern thermal radiation diagnostic instruments offer enhanced objectivity, and in this study, we strive to further improve the diagnostic process through the integration of Human-Computer Interaction (HCI) principles. Our objective is to introduce the thermal radiation DenseNet ensemble model, synergizing the strengths of Convolutional Neural Networks (CNNs) and HCI principles to advance tongue image recognition in healthcare. This approach aims to enhance classification accuracy, even when faced with limited training data. MethodologyTransfer learning, utilizing fine-tuned CNNs and DenseNet, is employed for precise classification, with a specific focus on distinguishing tooth-marked tongues. A portable hand-held thermal radiation diagnostic instrument, seamlessly integrated with HCI, is developed for both clinical use and research. Experimental resultsMeticulously curated datasets, formed through the annotation of thermal radiation images, confirm the superior performance of the DenseNet architecture in tooth mark and tongue feature recognition. The proposed tooth mark tongue recognition model exhibits a significant accuracy improvement of approximately 25% compared to similar tasks in existing studies. Additionally, an AI health detector tailored for Traditional Chinese Medicine (TCM) thermal radiation image recognition is introduced, showcasing the seamless integration of HCI principles into healthcare applications. This innovative tool not only assesses users' health but also provides personalized health recommendations, illustrating the transformative potential of combining technology and healthcare. Discussion and conclusionIn addressing the limitations of traditional tongue diagnosis, thermal radiation emerges as a key factor enhancing objectivity and accuracy. The thermal radiation DenseNet ensemble model, along with HCI integration through the portable hand-held device, proves effective for improved TCM thermal radiation image identification in healthcare. The fusion of technology and HCI principles underscores the potential to elevate health assessments and offer valuable guidance to users.

Abstract 2575: GD2 targeted dual-labeled intraoperative molecular imaging probe for neuroblastoma

Abstract Neuroblastoma (NB) is the most common pediatric extracranial solid tumor, with a 5-year survival rate under 50% for those with high-risk disease. Complete surgical resection is essential for these patients and is associated with improved outcomes. However, NB resection presents significant technical challenges due to encasement of vital structures that must be preserved, as well as remote deposits of disease. The current approach to find and safely resect tumor depends on the surgeon’s eyes and hands alone. Fluorescence tracers allow enhanced tumor visualization, but most are not molecularly targeted which leads to poor tumor to background signal. Further, fluorescent signal does not penetrate more than a few millimeters, a limitation that can be overcome by inclusion of a radiotracer. We, therefore, generated and evaluated a dual radio and fluorescent antibody-based probe targeting the GD2 tumor antigen to improve the identification of NB with widely available intraoperative handheld instruments. We generated an intraoperative probe (111In-αGD2-IRDye800CW) with retained affinity and stability. In vivo- Nu/j mice were injected with SK-N-BE(2) NB cells. After tumors grew for five weeks, mice were given tail vein injections of the probe. Gamma and optical biodistribution studies were performed to determine the specificity of binding and tumor to background signal four- and six-days post probe injection. Probe uptake was compared to an isotype. Gross dissections and surgeries aimed at improving completeness of resection were performed using a handheld fluorescent camera (SPY-PHI) and a gamma probe (Neoprobe). The handheld gamma probe detected xenografts with great sensitivity (average in vivo 818 cps of In111 in tumor region versus 34.8 cps in the tail). The fluorescent imaging showed high specific binding to the tumor region. Gamma biodistribution results indicated high accumulation within tumor (13.5 %ID/g) with lower accumulation in blood (3.49 %ID/g) and muscle (0.45 %ID/g). Uptake of the probe greatly exceeded isotype control antibody on days 4 and 6 post-agent injection, for both gamma and optical biodistributions. Initial tumor resection using 111In-DTPA-aGD2-IRDye800CW in an NB bearing mouse identified residual disease left behind when resection was performed using white light alone; the residual disease was then removed, guided by fluorescence imaging. Our dual-labeled probe demonstrated antigen specificity and allowed for the sensitive detection and visualization of NB in vivo with widely available intraoperative tools. This targeted probe could provide a means to improve surgical NB resection, by enabling localization of the all regions of tumor using radio-guidance, followed by clear definition of tumor margins with fluorescent signal, to maximize preservation of vital tissues. Ultimately, we believe this approach can improve safety, extent of NB resection, and patient outcomes. Citation Format: ReidAnn E. Sever, Lauren Taylor Rosenblum, Kayla C. Stanley, Dominic M. Menendez, W Barry Edwards, Marcus M. Malek, Gary Kohanbash. GD2 targeted dual-labeled intraoperative molecular imaging probe for neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2575.