Small Amount Of Sample Research Articles

Large margin-learning methodology from time-frequency maps and its physically interpretable weights for simultaneous machine health monitoring and fault diagnosis

Artificial intelligence (AI) enables machine health monitoring including fault detection and diagnosis that are becoming prevalent and have been actively investigated during recent years. Nonetheless, poor interpretation and black-box characteristics hinder their performance in machine condition monitoring. Specifically, abstract features extracted from AI models are difficult to physically interpret and correlate with fault mechanisms. In this paper, to enrich interpretation of learned features, a large margin-learning methodology from time-frequency maps is newly proposed. The original idea is to construct a health indicator (HI) for degradation process tracking in a feature extraction module and it is defined as the sum of element-wise products between a time–frequency map and a weight matrix. Here, the weight matrix can indicate fundamental components that always exist in healthy and faulty signals and newly generated components that are frequency components caused by machine faults. Moreover, the significance of the two-dimensional weight matrix can clearly show how weights are varied with time and indicate a cyclo-stationarity behavior of repetitive transients existing in fault vibration signals, which results in a new perspective for revisiting time–frequency maps for intelligent large margin-learning. Following, thanks to the physically interpretable feature matrix, a single-hidden layer network in a decision-making module is seamlessly designed for immediate machine fault detection, in which weights between an input layer and a hidden layer are tactfully set to the physically interpretable feature. At last, since the proposed methodology is based on convex optimization, it only needs a small amount of samples for training and realizing the physically interpretable weight matrix to understand a significant difference between different time–frequency maps for machine health monitoring and diagnosis. Experiments verify the effectiveness and superiority of the proposed large margin-learning methodology for simultaneous machine health monitoring and fault diagnosis.

Joint 2-D Sparse ISAR Imaging and Autofocusing by Using 2-D-IADIANet

Compressive sensing (CS) based methods have been widely used for sparse inverse synthetic aperture radar (ISAR) imaging. However, many CS-based methods are sensitive to the selection of model parameters, and the residual phase error of the echo also causes trouble for imaging and autofocusing. To address these problems, a novel deep learning approach, named as 2D-IADIANet, is proposed to achieve 2D sparse ISAR imaging with 2D phase error estimation in this paper. First, a 2D ISAR sparse echo model with 2D phase error into account is established, and a 2D-ADMM frame-work-based method, dubbed as 2D-IADIA, is presented to solve this compound reconstruction problem. Second, 2D-IADIA is further unfolded and mapped into a deep network form by integrating with 2D phase error compensation network. Moreover, all adjustable parameters can be learned adaptively by training the network through back propagation algorithm in complex domain directly. At last, experiment results verify that the well-learned 2D-IADIANet, which is only trained by a small amount of simulation samples, can also be generalized to measured data application. Especially, owing to the good performance of the network, the proposal has a superior reconstruction performance than 2D-IADIA under the low 2D sample rate and/or signal-to-noise ratio scenarios.

A method to produce low lead blank silicon dioxide gel as an emitter for isotopic analysis of sub-nanogram lead sample

Lead (Pb) isotopes have been widely used in isotopic dating and geochemical tracing. The rapid development in Earth sciences requires high precision and accuracy of isotopic measurements of low Pb contents or small amounts of samples. However, low ionization efficiency can significantly affect the sensitivity and precision of the measurement. Emitters, such as silicon dioxide (SiO2) gel used in the thermal ionization mass spectrometer (TIMS) measurement of Pb isotopes, can reduce Pb loss at the low-temperature stage and improve Pb ionization efficiency at the high-temperature stage, but they inevitably introduce Pb blank and affect the quality of the results. Therefore, the emitters should possess the features of both high ionization efficiency and low Pb blank. In the present study, a SiO2 gel solution was produced via a double-bottle method and then purified by the Sr-spec® resin. We further measured Pb blank value of this emitter using the isotopic dilution method and examined its ionization efficiency via measuring isotopic composition of standard reference materials of Pb solution and rock powders using different amounts of Pb. Analytical data show that Pb blank values of the twice-purified SiO2 gel solution are lower than 1 pg/μL (lowest value of ∼0.3 pg/μL). Moreover, it can effectively improve Pb ionization, and maintain high and stable ion signal intensity during the measurement runs. Analytical results of Pb isotopic compositions, obtained from nano- to subnano-gram Pb amounts of reference materials, all fall in the ranges of their reference values, meeting the requirements in precision and accuracy for the measurements on micro-samples. This emitter is useful for Pb isotopic measurement of micro-samples and predictable to promote the application of Pb isotopic geochemistry.

Determination of phytocannabinoids in cannabis samples by ultrasound-assisted solid-liquid extraction and high-performance liquid chromatography with diode array detector analysis

The characterisation of cannabis plants, especially the determination of specific phytocannabinoids, has gained enormous importance in the last decade, mainly due to the recent changes in cannabis control in several countries or states. This is particularly relevant for the forensic, medical or recreative industry to have a rapid, inexpensive, and reliable methodology to identify and quantify phytocannabinoids. Furthermore, spiking cannabis products with Δ8-tetrahydrocannabinol (THC) is a contemporary trend that demands improving or replacing current methods to include this cannabinoid. The current study presents an ultrasound-assisted solid-liquid extraction followed by high-performance liquid chromatography with diode array detection (HPLC-DAD) methodology to identify and quantify Δ9-THC, Δ8-THC, cannabidiol, cannabinol, Δ9-tetrahydrocannabinolic acid and cannabidiolic acid in cannabis products. The herbal samples were extracted with ethanol:acetonitrile (50:50, v:v) by ultrasonication using only 50 mg of sample. The plant oils were diluted in ethanol. The optimised procedure allowed ≈100% extraction efficiency of the target cannabinoids. The validation assays showed that the method is linear (R2 > 0.997), selective, sensitive, precise and accurate, with suitable limits of detection (0.125–0.250 µg mL−1) and quantification (0.500 µg mL−1). The method was successfully applied to cannabis samples, demonstrating its suitability for routine analyses. This contribution follows the current demand for fast and straightforward analysis services of this plant and its derivatives, using small amounts of sample. The present study compares very favourably against other works, particularly in regards to the extraction efficiency, speed of the overall procedure, method sensitivity, and ability to monitor Δ8-THC spiked samples using a novel solvent mixture.

Mass photometry: A powerful tool for carbohydrates-proteins conjugation monitoring and glycoconjugates molecular mass determination.

Glycoconjugate vaccines are important additions to the existing means for prevention of diseases caused by bacterial and viral pathogens. Conjugating carbohydrates to proteins is a crucial step in the development of these vaccines. Traditional mass spectrometry techniques, such as MALDI-TOF and SELDI-TOF, have difficulties in detecting glycoconjugates with high molecular masses. Mass photometry (MP) is a single-molecule technique that has been recently developed, which allows mass measurements of individual molecules and generates mass distributions based on hundreds to thousands of these measurements. In this study, we evaluated the performance of MP in monitoring carbohydrate-protein conjugation reactions and characterization of conjugates. Three different glycoconjugates were prepared from carrier protein BSA, and one from a large protein complex, a virus capsid with 3.74MDa molecular mass. The masses measured by MP were consistent with those obtained by SELDI-TOF-MS and SEC-MALS. The conjugation of BSA dimer to carbohydrate antigen was also successfully characterized. This study shows that the MP technique is a promising alternative to methods developed earlier for monitoring glycoconjugation reactions and characterization of glycoconjugates. It measures intact molecules in solution and it is highly accurate over a wide mass range. MP requires only a very small amount of sample and has no specific buffer constraints. Other MP advantages include minimal cost of consumables and rapid data collection and analysis. Its advantages over other methods make it a valuable tool for researchers in the glycoconjugation field.

Evaluation of SARS-CoV-2 Detection Systems Using Clinical Samples and Standard Material: A Comparative Study.

Due to the decreasing trends in daily confirmed COVID-19 cases and daily confirmed tests, there is a need for a new testing system capable of quickly and efficiently testing small amounts of samples. Therefore, we compared and evaluated the testing performance of the Aptima SARS-CoV-2 assay, an automated testing system that allows continuous loading of samples, and the Real-Q Direct SARS-CoV-2 detection kit that is currently being used in our laboratory. We compared the results of the two testing systems using 259 residual individual nasopharyngeal specimens and 91 residual pooled nasopharyngeal specimens that were submitted for COVID-19 testing in January and February 2023. The 95% limit of detection (LoD) for the Aptima SARS-CoV-2 assay determined using reference material for SARS-CoV-2 nucleic acid was confirmed to be 17.793 copies/mL, while the LoD for the Real-Q Direct SARS-CoV-2 detection kit was determined to be 131.842 copies/mL for the RdRP gene and 241.77 copies/mL for the E gene. The comparative study using clinical specimens showed almost perfect agreement. Our data showed that the Aptima SARS-CoV-2 assay has a very low LoD. In addition, the Aptima SARS-CoV-2 assay and Real-Q Direct detection kit have comparable clinical performance for SARS-CoV-2 for individual and pooled samples.

Microfluidics potential for developing food-grade microstructures through emulsification processes and their application

The food sector continues to face challenges in developing techniques to increase the bioavailability of bioactive chemicals. Utilising microstructures capable of encapsulating diverse compounds has been proposed as a technological solution for their transport both in food and into the gastrointestinal tract. The present review discusses the primary elements that influence the emulsification process in microfluidic systems to form different microstructures for food applications. In microfluidic systems, reactions occur within small reaction channels (1–1000 μm), using small amounts of samples and reactants, ca. 102–103 times less than conventional assays. This geometry provides several advantages for emulsion and encapsulating structure production, like less waste generation, lower cost and gentle assays. Also, from a food application perspective, it allows the decrease in particle dispersion, resulting in a highly repeatable and efficient synthesis method that also improves the palatability of the food products into which the encapsulates are incorporated. However, it also entails some particular requirements. It is important to obtain a low Reynolds number (Re < approx. 250) for greater precision in droplet formation. Also, microfluidics requires fluid viscosity typically between 0.3 and 1400 mPa s at 20 °C. So, it is a challenge to find food-grade fluids that can operate at the micro-scale of these systems. Microfluidic systems can be used to synthesise different food-grade microstructures: microemulsions, solid lipid microparticles, microgels, or self-assembled structures like liposomes, niosomes, or polymersomes. Besides, microfluidics is particularly useful for accurately encapsulating bacterial cells to control their delivery and release on the action site. However, despite the significant advancement in these systems' development over the past several years, developing and implementing these systems on an industrial scale remains challenging for the food industry.

Quantitative Evaluation of Interleukin-4 by Immunowall Devices Made of Gelatin Methacryloyl Hydrogel.

Immunoassays, which use antigen-antibody reactions, are the primary techniques used to selectively quantify specific disease markers in blood. Conventional immunoassays, such as the microplate-based enzyme-linked immunosorbent assay (ELISA) and paper-based immunochromatography, are widely used, but they have advantages and disadvantages in terms of sensitivity and operating time. Therefore, in recent years, microfluidic-chip-based immunoassay devices with high sensitivity, rapidity and simplicity, which are compatible with whole blood assays and multiplex assays, have been actively investigated. In this study, we developed a microfluidic device using gelatin methacryloyl (GelMA) hydrogel to form a wall-like structure in a microfluidic channel and perform immunoassays inside the wall-like structure, which can be used for rapid and highly sensitive multiplex assays with extremely small sample amounts of ~1 μL. The characteristics of GelMA hydrogel, such as swelling rate, optical absorption and fluorescence spectra, and morphology, were carefully studied to adapt the iImmunowall device and immunoassay. Using this device, a quantitative analysis of interleukin-4 (IL-4), a biomarker of chronic inflammatory diseases, was performed and a limit of detection (LOD) of 0.98 ng/mL was achieved with only 1 μL sample and 25 min incubation time. The superior optical transparency over a wide range of wavelengths and lack of autofluorescence will help to expand the application field of the iImmunowall device, such as to a simultaneous multiple assay in a single microfluidic channel, and provide a fast and cost-effective immunoassay method.

A Comparison of Analytical Methods for the Determination of Soil pH: Case Study on Burned Soils in Northern Portugal

Wildfires can cause serious imbalances in ecosystems, primarily at the soil level, making it vulnerable to degradation processes such as erosion. During and after a fire, changes occur in soil properties, including pH, which affects the solubility and availability of nutrients. Currently, there is a great diversity of protocols, some involving normalized standards, to determine soil pH, but there is no consensual or universal analytical method for this parameter, especially in burned soils, in which mineral and organic fractions could have been modified. Therefore, the objective of the present work is to evaluate the effect that variations in these analytical protocols may have on pH results. For this, five methods commonly found in the international bibliography for the analysis of pH of soil in water (pHH2O) were selected and compared to propose the most precise procedure. The analytical methods were applied to 43 soil samples, collected in a plot subjected to prescribed burning in the Parque Natural de Montesinho (Northern Portugal). The studied methods differ in the following protocol items: water suspension ratio (1:2.5 or 1:5), mechanical stirring time in the suspension (10 min or 1 h), and in the resting time for the solid particles to settle (15 min or 8 h). The obtained results point to the suitability of the five methods used for soil pH analysis, indicating that there are no statistically significant differences. However, results also allow suggesting a more appropriate method concerning practical reasons, such as labor in a lab. Thus, to make the analysis process more profitable, M2 is a good option because it uses a small amount of sample (5 g), short agitation (10 min) and settling time (15 min). In turn, M1 and M5, which use a lower proportion of soil (1:2.5) show lower pH variation in the measurements. This fact may be explained by a smaller dilution effect. Considering that these two methods differ in the settling time, it is suggested to apply M1, because only 15 min are required. Therefore, the main conclusion reached with this work is that the measurement of soil pH using M1, i.e., a soil:water ratio of 1:2.5, with agitation of 10 min and settling time of 15 min, is a robust and more expeditious protocol to be applied to soil samples after a fire.

Recurrent ConFormer for WiFi Activity Recognition

Dear Editor, Human activity recognition (HAR) using WiFi signals has been a significant task due to its potential applications in for example, healthcare services and smart homes. This letter deals with the WiFi channel state information (CSI)-based HAR task. To capture the dynamics of human activities well from CSI without using a huge number of training samples, we propose a recurrent model of convolution blocks and transformer encoders. Firstly, the model utilizes the convolution blocks to capture local variation and the self-attention mechanism in transformer encoders to characterize long-range dependencies. Secondly and more importantly, the recurrent architecture models the context information well within CSI signals and allows the network to deepen without scale increase, making it particularly suited to learning from a small amount of CSI samples.

Green extraction of Commiphora leptophloeos Mart. – J. B. Gillett aiming to increase the content of hinokinin, an “emerging bioactive”

Hinokinin is a lignan considered an “emerging bioactive” by several therapeutic effects. Thus, this study aimed to develop a method of extraction of hinokinin from the dried bark of the Commiphora leptophloeos Mart. – J. B. Gillett, using the extractor EDGE® and analyzes by GC-MS. Four solvents (hexane, dichloromethane, ethyl acetate, and ethanol) were used in the first part of the work in conditions of 80 °C and 5 min of hold time. Of these, ethanol presented a better yield (7.4%) in total extract and %hinokinin in the relative area (58.5%). Central Composite Design using ethanol, ranging the temperature (51.7–108 °C), and the hold time (from 1.5 to 8.5 min) was carried out. The analysis of variance (ANOVA) showed statistical significance for the temperature parameter, where the linear and quadratic factors were significant for the hinokinin GC-MS response, while the linear factor was significant for the mass yield. Thus, the better hold time and temperature were 6.85 min and 108 °C, respectively, increasing the mass yield from 6.4% to 17.9%, and the hinokinin content, estimated by the ratio hinokinin/Internal standard increased from 6.7 to 11.1. Therefore, the EDGE® method demonstrated good efficiency in the extraction, as well as the use of small sample quantities (2 g), green solvent, low extraction time, and few sample manipulations.

Mass spectrometric approaches in discovering lipid biomarkers for COVID-19 by lipidomics:Future challenges and perspectives.

Coronavirus disease 2019 (COVID-19) has emerged as a global health threat and has rapidly spread worldwide. Significant changes in the lipid profile before and after COVID-19 confirmed the significance of lipid metabolism in regulating the response to viral infection. Therefore, understanding the role of lipid metabolism may facilitate the development of new therapeutics for COVID-19. Owing to their high sensitivity and accuracy, mass spectrometry (MS)-based methods are widely used for rapidly identifying and quantifying of thousands of lipid species present in a small amount of sample. To enhance the capabilities of MS for the qualitative and quantitative analysis of lipids, different platforms have been combined to cover a wide range of lipidomes with high sensitivity, specificity, and accuracy. Currently, MS-based technologies are being established as efficient methods for discovering potential diagnostic biomarkers for COVID-19 and related diseases. As the lipidome of the host cell is drastically affected by the viral replication process, investigating lipid profile alterations in patients with COVID-19 and targeting lipid metabolism pathways are considered to be crucial steps in host-directed drug targeting to develop better therapeutic strategies. This review summarizes various MS-based strategies that have been developed for lipidomic analyzes and biomarker discoveries to combat COVID-19 by integrating various other potential approaches using different human samples. Furthermore, this review discusses the challenges in using MS technologies and future perspectives in terms of drug discovery and diagnosis of COVID-19.

Determination of 39 fatty acids in liver of rats by gas chromatography-mass spectrometry

Fatty acids not only form phospholipids that contribute to the formation of cell membranes but also participate in many metabolic activities, such as energy storage and cell signal transduction. The liver plays a key role in the synthesis and metabolism of fatty acids. The composition and contents of fatty acids in the liver are closely related to body health. Most fatty acid-detection methods require a large sample size and can detect only a small number of fatty acids. Therefore, a sensitive and efficient method to determine fatty acids in the liver is urgently required. Herein, a method based on gas chromatography-mass spectrometry (GC-MS) was established for the simultaneous determination of 39 fatty acids in 1.1 mg of liver tissue. Different extraction methods and derivatization conditions were compared to develop an optimal sample-treatment method. The performance of two different columns in separating the target fatty acids were also compared. A total of 10 mg of liver was added to 450 μL of normal saline and ground at -35 ℃ to obtain a homogenate. Next, 50 μL of the homogenate (equivalent to 1.1 mg of liver) was added with 750 μL of chloroform-methanol (1∶2, v/v) to extract total fatty acids. The fatty acid extracts were dried under nitrogen, and then derivatized at 100 ℃ for 90 min after being added with methanol containing 5% sulfuric acid. The fatty acid methyl esters were extracted with hexane and then separated on an SP-2560 capillary column (100 m×0.25 mm×0.2 μm; Supelco, USA) via GC-MS. The results revealed that all 39 fatty acid methyl esters detected had good linearities in the certain mass concentration ranges with correlation coefficients (R2) greater than 0.9940. The limits of detection (LOD) and quantification (LOQ) of these methyl esters in the liver were 2-272 ng/mg and 7-906 ng/mg, respectively. The accuracy and precision of the method were evaluated by spiking the liver homogenate with tridecylic acid and eicosanoic acid at low (0.09 μg/mg), moderate (0.90 μg/mg), and high (5.40 μg/mg) concentration levels. The recoveries ranged from 82.4% to 101.0% with an intraday relative standard deviations (RSDs) (n=5) of 3.2%-12.0% and interday RSDs (n=3) of 5.4%-13.4%. The method was successfully applied to detect fatty acids in the livers of four healthy male Sprague-Dawley (SD) rats and four male SD rats with abnormal liver function induced by perfluorooctane sulfonate (PFOS). PFOS is a persistent organic pollutant. Twenty-six fatty acids were detected in the livers of both groups. Among the fatty acids investigated, pentadecanoic acid (C15∶0), γ-linolenic acid (C18∶3n6), and elaidic acid (C18∶1n9t) cannot be detected by the methods reported in the literature. By contrast, the method developed in this study could separate the isomers of oleic acid (elaidic acid, C18∶1n9t; oleic acid, C18∶1n9c) and linolenic acid (linolelaidic acid, C18∶2n6t; linoleic acid, C18∶2n6c). In conclusion, the developed method is simple and can detect a large number of fatty acids using small sample amounts and few reagents. More importantly, it could successfully separate fatty acid isomers. These findings indicate that the developed method is suitable for the detection of fatty acid composition and contents in the liver in clinical and experimental research.

Microfluidic systems as a novel approach for microalgal bioprocess

Challenges such as controlling parameters for microalgal bioprocess optimization, increased need for inoculum and chemicals with the increasing number of experiments, long procedures and high production costs make it difficult to commercialize high value-added bioactive compounds from microalgae. Furthermore, downstream processes comprise the majority of the total production costs and increase the amount of energy consumed, depending on the desired purity percentage and the biochemical features of the material. So, it is important to maximize the effectiveness, quality, and economic factors of both upstream and downstream processes. Due to their micro-scale size, diluted cultures and controlled operational parameters, reduced sample and material utilization, increased mass and heat transfer, better species interaction, and high-throughput cell/reagent processing capabilities, microfluidic devices are becoming increasingly used in microalgal bioprocess studies for both fundamental research and industrial applications. Additionally, microfluidic devices outperform conventional techniques in their capacity to carry out a lot of functions, including the separation and more sensitive analysis of small amounts of samples. In this review, diverse microfluidic platforms for microalgal cultivation, purification and separation processes, sorting and high-throughput screening of microalgae, and emerging studies of microfluidic technologies in various microalgal processes are discussed.

Gear contact fatigue life prediction based on transfer learning

The gear contact fatigue test is characterised by extraordinarily high costs and a long period of testing. A transfer learning algorithm was applied to develop a gear contact fatigue life prediction strategy to fully use other low-cost fatigue test data, such as twin-disc test data. The twin-disc contact fatigue test data were incorporated into the neural network model to explore the combined effects of surface integrity and stress level on fatigue life, which was further transferred for gear contact fatigue life prediction. The results indicate that this method enables an effective gear fatigue life prediction under minor gear sample conditions. With a small sample amount of 7, the prediction error in the fatigue life of the model with transfer learning is 46.33%, while the typical back-propagation neural network (BPNN) model without transfer learning is 101.66%. To control life prediction error to within 50%, the model without transfer learning requires at least 17 gear samples, while the transfer model calls for only 7 gear samples. The proposed data transfer learning framework can be used to predict the gear contact fatigue S-N curve under minor sample conditions and is straightforwardly applied to extended applications.

"Usefulness of the Acute Phase Reactants (APR) Score: Early Detection of Delayed Onset of Sepsis in Extremely Low Birth Weight Infants by APR Score"

The production of acute phase reactants (APRs) in the liver is stimulated by increased inflammatory cytokines. Therefore, inflammatory cytokines are more advantageous than APRs for early diagnosis of neonatal sepsis. There is a machine Latessier TM that can produce results after about 3 minutes with a small amount of sample of 10 μL each at the same time of C-reactive protein (CRP), α1 acid glycoprotein (AGP), and haptoglobin (Hp).

Abstract 2282: Immune modulation of the T cell repertoire in mice following immunotherapy and chemotherapy combination treatments

Abstract Background: Immune checkpoint blockade therapeutics have revolutionized cancer therapy. However, most patients are either unresponsive or develop acquired resistance. Understanding patient-specific temporal T cell repertoires in the context of immune interventions will contribute to a better understanding of potential improvement strategies for better T cell anti-tumor immunity. Current methods to understand the T cell repertoire changes over time are limited due to the limited amount of material and prohibitive cost. In this study, we designed and performed longitudinal TCR sequencing in mice treated with multiple therapies. Methods: C57BL/6 mice were used in each treatment group, with blood drawn overtime before, during and after treatment. Mice were treated with a combination of immunotherapeutic agents and OVA peptide immunization, 100µl blood was drawn at multiple pre-, on- and post-treatment time points followed subsequently by TCR sequencing. Cyclophosphamide (CTX) is known to cause lymphodepletion followed by homeostatic proliferation. Thus, we also treated B16-F10 tumor bearing mice with CTX, and performed TCR sequencing on blood draws pre-, on-, and post-treatment to track TCR clone diversity and clonality over time. Results: We find that our method is sensitive enough to detect effects of immunotherapies on TCR diversity in small sample quantities. Using our method, we discovered that certain immunotherapeutic agents, most evidently CD40, have a significant but transient effect on the diversity of the T cell repertoire. We observed an initial increase in repertoire clonality, seven days post CD40 treatment followed by contraction. We show how we can identify antigen specific T cells and follow reacting T cell clones. In addition, we find that CTX treatment is associated with increased clonality in tumor bearing mice particularly in the week following treatment reflecting changes in the TCR repertoire. Conclusion: We have developed a method by which we can follow the TCR repertoire in mice treated with immunotherapy or chemotherapy. This enabled us to isolate and study the effects of different immune modulatory drugs of the endogenous T cell repertoire overtime. Citation Format: Yuval Elhanati, Mariam M. George, Hyejin Choi, Rachana Maniyar, Linda Hamadane, Neeman Mohibullah, Benjamin D. Greenbaum, Taha Merghoub. Immune modulation of the T cell repertoire in mice following immunotherapy and chemotherapy combination treatments [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2282.

Abstract 4486: Proof of principle for pharmacogenomic-guided precision oncology for pediatric malignancy

Abstract Childhood cancers are rare and clinically diverse. They are typically associated with few driver mutational events than adult cancers, constituting potential targets for patient-specific precision therapy approaches. Here, we evaluated the feasibility of using a patient-derived tumor cell (PDC) based drug screening system and integrated multi-omics data to achieve precision oncology for pediatric patients. We established a PDC library derived from a few passage-cultured tumor cells from surgically resected tumor specimens and conducted chemical screening, which composed of various target agents of major oncogenic pathways (e.g. receptor tyrosine kinase inhibitor, proteasome inhibitor and histone deacetylase etc.). Next Generation Sequencing was performed to characterize the genomic and transcriptomic traits of tumors. Overall, success of establishing PDCs of pediatric cancers was high (80.4%) and comparable to adult cancers. The amount of obtained tissue was an important factor for the success of PDC establishment; the estimated optimal weight for PDC establishment was small (1.14g) and it is noteworthy that a small amount of tumor sample is sufficient to identify the potential hit(s) of parental tumors. The platform provided therapeutic options to pediatric tumors regardless of actionable targets. Our PDC approach identified several potential gene-drug associations, including anti-PI3K/Akt agents for neuroblastomas and anti-SHH agents for sarcomas with EWSR1 fusion. Given that a considerable proportion of pediatric tumors still lack actionable targets with matched treatment options, PDC-based drug screening profiles can be an optimal therapeutic strategy for these cases. Collectively, our analysis confirmed the feasibility of PDC-based in vitro drug screening systems to guide the therapeutic strategy for pediatric patients. This approach will accelerate the preclinical research for pediatric tumors to understand their pathophysiology and investigate the potential therapeutic strategies to fulfill the future precision oncology. Citation Format: Gi Ju Lee, Seung-Won Choi, Seung Ah Choi, Hee-Jin Cho, Robyn Gartrell, Ji Won Lee, Joo Whan Kim, Nam-Gu Her, Raul Rabadan, Ki Woong Sung, Do-Hyun Nam, Seung-Ki Kim. Proof of principle for pharmacogenomic-guided precision oncology for pediatric malignancy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4486.

Measurement of trace elements in murine liver tissue samples: Comparison between ICP-MS/MS and TXRF

BackgroundTrace elements exhibit essential functions in many physiological processes. Thus, for research focusing on trace element homeostasis and metabolism analytical methods allowing for multi-element analyses are fundamental. Small sample amounts may be a big challenge in trace element analyses especially if also other end points want to be addressed in the same sample. Therefore, the aim of the present study was to examine trace elements (iron, copper, zinc, and selenium) in murine liver tissue prepared by a RIPA buffer-based lyses method. Methods and resultsAfter centrifugation, lysates and pellets were obtained and trace elements were analyzed with TXRF in liver lysates. The results were compared to that obtained by a standard microwave-assisted acidic digestion with subsequent ICP-MS/MS analysis of the same liver tissue, liver lysates, and remaining pellets. In addition, trace element concentrations, determined in murine serum with both methods, were compared. For serum samples, both TXRF and ICP-MS/MS provide similar and highly correlating results. Furthermore, in liver lysate samples prepared with RIPA buffer, comparable trace element concentrations were measured by TXRF as with the standard digestion technique and ICP-MS/MS. Only marginal amounts of trace elements were detected in the pellets. ConclusionTaken together, the results obtained by the present study indicate that the RIPA buffer-based method is suitable for sample preparation for trace element analyses via TXRF, at least for the here investigated murine liver samples.

Development of qualitative GC MS method for simultaneous identification of PM-CCM a modified illicit drugs preparation and its modern-day application in drug-facilitated crimes

Prescriptions for psychoactive substances such as Pregabalin, Methamphetamine, Caffeine, Clonazepam and Mirtazapine (PM-CCM) are common in the treatment of a variety of disorders. Indeed, the PM-CCM has been used in different therapeutic areas, including insomnia, anxiety, seizure disorders, etc. Unfortunately, these psychoactive substances are present in the illegal street market, leading to a lot of drug abuse among some addicted users, road insecurity and suicide. Hence, it has become essential to validate and develop a rapid and effective method to analyze the PM-CCM, a modified illicit drug, for drug abuse in the forensic sciences. A simple, rapid, specific and sensitive Gas Chromatography-Mass Spectrometry(GC-MS) method has been developed for the identification of Pregabalin, Methamphetamine, Caffeine, Clonazepam and Mirtazapine (PM-CCM) in forensic exhibits. At room temperature, the sample was ultrasonicated for 5 minutes before being extracted with methanol. A highly precise auto-injector is used to inject a very small quantity of samples for analysis. Helium is used as a carrier gas with a flow rate of 1 ml/min. The separation of PM-CCM was performed on SH-RXi-5 MS, ID.25 mm, film thickness. 25 µm, length of 30 m column. The constituents of PM-CCM were identified by the mass-to-charge ratio (m/z ratio) of fragments of the parent compound by comparing them with the NIST-17 MS Library. Separation and identification of PM-CCM were achieved within a 15-minute run. The proposed method has been successfully used for the routine analysis of PM-CCM in complex illicit drug preparations and in forensic exhibits as well. The application of above discussed qualitative analysis method and screening of PM-CCM, modified illicit drug samples demonstrates the potential and applicability of the technique to the fast chemical profiling of illicit samples.