Small Amount Of Sample Research Articles

RNA Isolation from Human Stem Cell-Derived Retinal Organoids.

RNA isolation is an essential first step for many types of molecular analyses, including reverse transcription PCR (RT-PCR)/quantitative RT-PCR (qRT-PCR), Northern blotting, microarrays, and RNA-sequencing. While many RNA purification methods have been reported, it can be challenging to extract sufficient quantity, and suitable quality, of RNA from very small amounts of tissue and/or samples containing low numbers of cells. Here we outline a total RNA isolation method that reproducibly yields high-quality RNA from human stem cell-derived retinal organoids for downstream transcriptomic analysis.

Image-free recognition of moderate ROP from mild with machine learning algorithm on plasma Raman spectrum

The retinopathy of prematurity (ROP) can cause serious clinical consequences and, fortunately, it is remediable while the time window for treatment is relatively narrow. Therefore, it is urgent to screen all premature infants and diagnose ROP degree timely, which has become a large workload for pediatric ophthalmologists. We developed a retinal image-free procedure using small amount of blood samples based on the plasma Raman spectrum with the machine learning model to automatically classify ROP cases before medical intervention was performed. Statistical differences in infrared Raman spectra of plasma samples were found among the control, mild (ZIIIS1), moderate (ZIIIS2 & ZIIS1), and advanced (ZIIS2) ROP groups. With the different wave points of Raman spectra as the inputs, the outputs of our support vector machine showed that the area under the curves in the receiver operating characteristic (AUC) were 0.763 for the pair comparisons of the control with the mild groups, 0.821 between moderate and advanced groups (ZIIS2), while more than 90% in comparisons of the other four pairs: control vs. moderate (0.981), control vs. advanced (0.963), mild vs. moderate (0.936), and mild vs. advanced (0.953), respectively. Our study could advance principally the ROP diagnosis in two dimensions: the moderate ROPs have been classified remarkably from the mild ones, which leaves more time for the medical treatments, and the procedure of Raman spectrum with a machine learning model based on blood samples can be conveniently promoted to those hospitals lacking of the pediatric ophthalmologists with experience in reading retinal images.

Use of hyperspectral imaging devices for the measurement of small granular samples: Evaluation of grape seed protein concentrates

Hyperspectral imaging is a well-known technique for quality control of food and agricultural products. This technique is often applied to the measurement of large and heterogeneous samples, where chemical imaging is extremely useful. In addition, when the amount of sample is limited by different factors (price, other analyses, sample production, etc.) hyperspectral imaging is an alternative to traditional spectroscopes for acquiring its spectral information.In this study, a new and specific methodology to acquire hyperspectral information from small amounts of granular samples has been developed. For this purpose, two different hyperspectral devices (400–1100 nm, 900–1700 nm) have been used. A statistical procedure has been followed to test the proposed method. In grape seed protein concentrates, NIR radiation (900–1700 nm) penetrates deeper into the sample than VisNIR radiation (400–1100 nm). Therefore, the minimum amount of sample needed to measure in the NIR range is larger than that needed to measure in the VisNIR range. Finally, different calibration models have been developed for the control of protein content in the tested samples. Standard errors of prediction obtained in external validation are similar to those reported in the literature when sample amount is not an issue (9–10 %).

МЕТОД АДАПТИВНОГО ОПРЕДЕЛЕНИЯ ПОРОГА ПРИНЯТИЯ РЕШЕНИЙ ПРИ КЛАССИФИКАЦИИ СЛАБО-ОПРЕДЕЛЕННЫХ ДАННЫХ

When solving the classification problem, many methods require knowledge of the threshold for belonging a vector to a class. The decision on whether a new vector belongs to a given class is made after comparing the distance from the vector to the class with the accepted threshold. If the threshold is not exceeded, the vector is considered classified. The article proposes a method for the adaptive calculation of such a threshold, called the confidence threshold, for the case of rarely occurring data in the presence of distortions in measurements (poorly defined data). The method includes the sequential determination of the confidence interval for the distances of previously classified vectors to their class with a given confidence probability. The right confidence limit is selected as the confidence threshold of the class. Since poorly defined data are characterized by small and ultra-small amounts of data samples, it is proposed to determine the confidence interval in two ways: for a small sample size, its normal distribution is assumed, and the Laplace distribution quantile is used; for an ultra-small volume, the Student distribution and the quantiles of the t-distribution are used. During classification, the distance from the new vector to the class is calculated, and the vector is considered classified with a given confidence probability if this distance does not exceed the confidence threshold. The distance can be determined by any known metric. The paper presents both the algorithm of the method itself and computational experiments that have shown the applicability and effectiveness of the proposed technique.

Chromatographic Separation and Quantitation of Sphingolipids from the Central Nervous System or Any Other Biological Tissue.

Chromatographic separation and purification of an individual lipid to homogeneity have long been introduced. Using this concept, a more precise method has been developed to identify and characterize the sphingolipid composition(s) using a small amount (30mg) of biological sample. Sphingolipids (lipids containing sphingosine or dihydrosphingosine) are well-known regulators of the central nervous system development and play a critical role in neurodegenerative diseases. Introducing a silicic acid column chromatography, sphingolipid components have been separated to individual fractions such as ceramide, glucosyl/galactosylceramide, other neutral and acidic glycosphingolipids, including (dihydro)sphingosine and psychosine; as well as phospholipids from which individual components are quantified employing a single or combination of other advanced chromatography procedures such as thin-layer chromatography, gas chromatography-mass spectrometry, and high-performance liquid chromatography-mass spectrometry.

The Effect of High Molecular Weight Glutenin Subunit Encoded by Glu-B1k Allele on Bread-Making Quality of Near-Isogenic Lines of Bread Wheat

: In this study, the effect of the 22 glutenin subunit encoded by the Glu-B1k allele on the chromosome B on the quality of wheat was investigated. Nevzatbey and a genotype of Triticum aestivum L. subsp. sphaerococcum were used as parents and produced the near-isogenic lines (NILs) in the generation of BC4F3. Plant morphological traits and protein content, sedimentation volume, lactic acid solvent retention capacity (SRC), and glutenin swelling index (GSI) of the NILs were determined. The mean protein content of the NILs carrying 22 glutenin subunit was higher than that of the NILs carrying the 7+9 glutenin subunit (20.4% and 16.2%, respectively). In contrast, the NILs with 22 glutenin subunit had a lower sedimentation volume than those of the NILs with 7+9 glutenin subunits. The 22 glutenin subunit decreased the sedimentation volume from 19.47 to 13.49 mL. The average GSI value of the NILs carrying 7+9 glutenin subunits was higher than that of the NILs carrying 22 glutenin subunit (3.05 and 2.92). In conclusion, in this study we were able to detect a quality difference between NILs with 22 and 7+9 glutenin subunits in a small amount of samples. These findings suggest that glutenin subunit 22 may be associated with low gluten strength.

ACETONE PRECIPITATION OF PROTEINS FOR DETERMINATION OF THE OF ENZYMES ACTIVITY IN MEDICINAL PLANTS

Plant phenolic compounds are widely used in medicine and agriculture. The study of the mechanisms of their biosynthesis and accumulation is a complex task. It is also true for the determination of the activity of the key plant enzymes such as shikimate dehydrogenase. At the same time, the isolation of proteins and enzymes from plant is complicated by the presence of phenolic compounds and pigments. The aim of the research was to evaluate the feasibility of the acetone precipitation of proteins of leaf extracts of plants to determine the activity of shikimate dehydrogenase. The object of the study was the leaves of sea buckthorn (H. rhamnoides) and silky dogwood (C. sericea). The proteins were precipitated from the crude extract with cold (-20 °C) acetone in varying ratio followed by washing three times with acetone and final dissolution in buffer. The activity of shikimate dehydrogenase was determined at pH=10.0 and expressed in ncat per mg of protein. Protein fractions with different activity of shikimate dehydrogenase were isolated from the leaves of sea buckthorn (H. rhamnoides) and silky dogwood (C. sericea). It was shown that the protein fraction with a ratio of 1 : 1.5 of extract : acetone (60% saturation) is most convenient to work with, has a high enzyme activity and does not contain colored impurities. This method of protein isolation and pre-purification is fast, requires a small amount of sample, and suitable for screening studies of the activity of various enzymes in medicinal plants.

Ink in secular and religious documents from the Pelliot collection (BnF, Paris): A study of ingredients and uses of ink in1st millennium Tocharian, Sanskrit and Chinese manuscripts from the Kucha and Dunhuang regions

This paper presents the study of ink from first millennium manuscripts discovered in the Kucha and Dunhuang regions (West China) from the “Pelliot collection” stored at the Bibliothèque nationale de France (Paris, France). The sixteen analyzed manuscripts written in black ink were selected partly because of their diverse characteristics (script, type, etc.) and partly because of the high possibility for their accurate dating between 4th to the 8th century. This period is defined by an important economic growth as well as cultural and artistic activities, facilitated by the fact that Kucha and Dunhuang played a key role in the passage of the Silk Road network connecting China, India and western Central Asia.FTIR and Raman spectroscopies were first employed as they are non-destructive and non-invasive methods. They indicated that the ink present on the manuscripts was composed of soot and protein binder, however they did not provide direct insight on the precise origin of the soot (e.g pine soot or lampblack) and the protein binder used in the fabrication of inks. The analysis of the inked manuscripts by pyrolysis-comprehensive two-dimensional gas chromatography/mass spectrometry (Py-GCxGC-MS) – for which only a small amount of sample (microgram quantities) is required - and the exploration of the obtained multivariate datasets combining Hierarchical Clustering and PCA provide invaluable information on Asian inks, their manufacture and use in different historical periods. Our research suggests that the majority of the inks were made with pine soot. Furthermore, our results reveal different chemical signatures that may be indicators of difference in the production of pine soot (use of various species of pine wood, combustion parameters, etc.). Moreover, diverse proteinaceous binders and additives, known to have been used in ancient Chinese ink manufacture to ensure ink’s consistency and for their antimicrobial and aromatic properties, were identified.

Arsenic speciation analysis in cow's milk and plant-based imitation milks by HPLC-ICP-MS

Imitation milks based on vegetables have become relevant in recent years as a substitute for cow´s milk. Total and inorganic content of arsenic (As) determination in food is of utmost importance due to toxicological concerns. This study aimed to (1) optimize and validate a methodology for speciation analysis using anion exchange high performance liquid chromatography coupled to plasma mass spectrometry and (2) analyze the arsenic content in milk and imitation milks. Determination of As (III) and As (V) was done following a simple and innovative treatment, which consisted on the dilution of a small volume of sample in mobile phase and further filtration. Furthermore, acid microdigestion for total As determination with small amounts of acid and sample was optimized. The detection limits of the method ranged from 0.2 to 0.7 µg L−1. Regarding to arsenic content we found that imitation milks based on peanuts and nuts presented the lowest inorganic As content (between 1.7 and 1 µg L−1) whereas the highest values were found in imitations based on soy, rice and vetch (27.3, 13 and 8 µg L−1, respectively). The cow’s milk presented intermediate levels of inorganic As (4 µg L−1). Also, almond- and quinoa-based imitation milks showed inorganic As values below detection limits, so these imitation milks may be the safest to consume with respect to arsenic content.

Fast and sensitive smartphone colorimetric detection of whole blood samples on a paper-based analytical device

BackgroundMethods based on paper-based analytical devices (PAD) and smartphone photographic colorimetric detection have become representative instrument-independent point-of-care testing (POCT) platforms due to their low cost and simplicity. However, the detection of target components from whole blood sample still presents challenges in terms of field preparation of small amounts of blood sample and detection sensitivity. This paper presents a rapid online processing method for whole blood samples on PAD based on plasma separation membrane (PSM), and combined with electrokinetic stacking and selective chromatic reaction. Real-time smartphone-based colorimetric detection of free hemoglobin (FHb) and human serum albumin (HSA) was successfully demonstrated. ResultsWith the proposed method, both detections for low and high concentration analytes could be implemented. The limits of detection of 16.6 mg L-1 for FHb and 0.67 g L-1 for HSA were obtained, respectively, with RSD below 8 %. The reliability of the method was verified by the recovery test and desktop spectrophotometric method. The detection results for real blood samples were in agreement with that by clinical methods. Significance and noveltyThe PAD method is inexpensive, simple and fast, and detection of a whole blood sample of 5 μL can be finished in 5 min. This work shows that POCT of biomarkers from whole blood with PAD is possible without using any desktop facilities.

Identification of Central Nervous System Oncologic Disease Biomarkers in EVs from Cerebrospinal Fluid (CSF) of Pediatric Patients: A Pilot Neuro-Proteomic Study.

Cerebrospinal fluid (CSF) is a biochemical-clinical window into the brain. Unfortunately, its wide dynamic range, low protein concentration, and small sample quantity significantly limit the possibility of using it routinely. Extraventricular drainage (EVD) of CSF allows us to solve quantitative problems and to study the biological role of extracellular vesicles (EVs). In this study, we implemented bioinformatic analysis of our previous data of EVD of CSF and its EVs obtained from congenital hydrocephalus with the aim of identifying a comprehensive list of potential tumor and non-tumor biomarkers of central nervous system diseases. Among all proteins identified, those enriched in EVs are associated with synapses, synaptosomes, and nervous system diseases including gliomas, embryonal tumors, and epilepsy. Among these EV-enriched proteins, given the broad consensus present in the recent scientific literature, we validated syntaxin-binding protein 1 (STXBP1) as a marker of malignancy in EVD of CSF and its EVs from patients with pilocytic astrocytoma and medulloblastoma. Our results show that STXBP1 is negatively enriched in EVs compared to non-tumor diseases and its downregulation correlates with adverse outcomes. Further experiments are needed to validate this and other EV markers in the blood of pediatric patients for translational medicine applications.

Optimization and validation of a micro–QuEChERS method for phthalates detection in small samples of cetacean blubber

In this study, an innovative method was developed to detect and quantify phthalates in fresh cetacean blubber. An adaptation of the ammonium formate QuEChERS method was used and adapted as a micro-extraction for small quantities of samples. Significantly, this technique utilized minimal quantities of reagents and salts, with the additional implementation of rigorous Quality Assurance/Quality Control protocols to further reduce background contamination. To ensure the reliability of this method, comprehensive validation procedures were conducted, with a specific focus on two widely studied cetacean species: the common bottlenose dolphin (Tursiops truncatus) and the short-finned pilot whale (Globicephala macrorhynchus). Determination coefficients (R2) for matrix-matched calibration were >0.93 with limits of quantifications (LOQ) of the method in the range of 5–10 ng/g. Mean recovery values were between 40 and 100 %. This novel methodology holds particular relevance for environmental research studies, offering the capability to detect emerging contaminants with minimal sample requirements. This aspect is particularly valuable in investigations that involve free-ranging animals and rely on biopsy sampling. It allows for the assessment of contaminant levels in healthy individuals within wild populations, enhancing our understanding of ecological impacts and potential conservation measures.•A micro-extraction adaptation of the ammonium formate QuEChERS method was developed and applied to a small quantity of fresh cetacean blubber to detect phthalates.•Small quantities of reagents and salts were used, and additional Quality Assurance/ Quality Control procedures were taken to further minimize background contamination.•Method validation was carried out for two cosmopolitan and extensively studied cetacean species: the common bottlenose dolphin (Tursiops truncatus) and the short-finned pilot whale (Globicephala macrorhynchus).

Mobility-Modulated Sequential Dissociation Analysis Enables Structural Lipidomics in Mass Spectrometry Imaging.

Spatial lipidomics based on mass spectrometry imaging (MSI) is a powerful tool for fundamental biology studies and biomarker discovery. But the structure-resolving capability of MSI is limited because of the lack of multiplexed tandem mass spectrometry (MS/MS) method, primarily due to the small sample amount available from each pixel and the poor ion usage in MS/MS analysis. Here, we report a mobility-modulated sequential dissociation (MMSD) strategy for multiplex MS/MS imaging of distinct lipids from biological tissues. With ion mobility-enabled data-independent acquisition and automated spectrum deconvolution, MS/MS spectra of a large number of lipid species from each tissue pixel are acquired, at no expense of imaging speed. MMSD imaging is highlighted by MS/MS imaging of 24 structurally distinct lipids in the mouse brain and the revealing of the correlation of a structurally distinct phosphatidylethanolamine isomer (PE 18 : 1_18 : 1) from a human hepatocellular carcinoma (HCC) tissue. Mapping of structurally distinct lipid isomers is now enabled and spatial lipidomics becomes feasible for MSI.

Mobility‐Modulated Sequential Dissociation Analysis Enables Structural Lipidomics in Mass Spectrometry Imaging

AbstractSpatial lipidomics based on mass spectrometry imaging (MSI) is a powerful tool for fundamental biology studies and biomarker discovery. But the structure‐resolving capability of MSI is limited because of the lack of multiplexed tandem mass spectrometry (MS/MS) method, primarily due to the small sample amount available from each pixel and the poor ion usage in MS/MS analysis. Here, we report a mobility‐modulated sequential dissociation (MMSD) strategy for multiplex MS/MS imaging of distinct lipids from biological tissues. With ion mobility‐enabled data‐independent acquisition and automated spectrum deconvolution, MS/MS spectra of a large number of lipid species from each tissue pixel are acquired, at no expense of imaging speed. MMSD imaging is highlighted by MS/MS imaging of 24 structurally distinct lipids in the mouse brain and the revealing of the correlation of a structurally distinct phosphatidylethanolamine isomer (PE 18 : 1_18 : 1) from a human hepatocellular carcinoma (HCC) tissue. Mapping of structurally distinct lipid isomers is now enabled and spatial lipidomics becomes feasible for MSI.

Riemannian geometric and ensemble learning for decoding cross-session motor imagery electroencephalography signals

Objective. Brain–computer interfaces (BCIs) enable a direct communication pathway between the human brain and external devices, without relying on the traditional peripheral nervous and musculoskeletal systems. Motor imagery (MI)-based BCIs have attracted significant interest for their potential in motor rehabilitation. However, current algorithms fail to account for the cross-session variability of electroencephalography signals, limiting their practical application. Approach. We proposed a Riemannian geometry-based adaptive boosting and voting ensemble (RAVE) algorithm to address this issue. Our approach segmented the MI period into multiple sub-datasets using a sliding window approach and extracted features from each sub-dataset using Riemannian geometry. We then trained adaptive boosting (AdaBoost) ensemble learning classifiers for each sub-dataset, with the final BCI output determined by majority voting of all classifiers. We tested our proposed RAVE algorithm and eight other competing algorithms on four datasets (Pan2023, BNCI001-2014, BNCI001-2015, BNCI004-2015). Main results. Our results showed that, in the cross-session scenario, the RAVE algorithm outperformed the eight other competing algorithms significantly under different within-session training sample sizes. Compared to traditional algorithms that involved a large number of training samples, the RAVE algorithm achieved similar or even better classification performance on the datasets (Pan2023, BNCI001-2014, BNCI001-2015), even when it did not use or only used a small number of within-session training samples. Significance. These findings indicate that our cross-session decoding strategy could enable MI-BCI applications that require no or minimal training process.

Enhancing the Yield of a Lab-on-a-Disk-Based Single-Image Parasite Quantification Device.

The recently proposed single-image parasite quantification (SIMPAQ) platform based on a Lab-on-a-Disc (LOD) device was previously successfully tested in field conditions, demonstrating its efficiency in soil-transmitted helminth (STH) egg detection and analysis on the level delivered by the current state-of-the-art methods. Furthermore, the SIMPAQ provides relatively quick diagnostics and requires small amounts of sample and materials. On the other hand, in a recent related study, it was revealed that the performance of the SIMPAQ method can be limited due to the action of the tangential Euler and Coriolis forces, and the interaction of the moving eggs with the walls of the LOD chamber. Here, we propose a new improved design that allows us to overcome these limitations and enhance the yield of the SIMPAQ LOD device, as demonstrated in experiments with a synthetic particle model system and real parasite eggs. Despite the simplicity, the proposed design modification is demonstrated to allow a substantial improvement in the yield of the SIMPAQ device, i.e., above 90% of parasite eggs and 98% of synthetic model particles were transported to the field of view. The new design proposed here will be further examined in the new generation of SIMPAQ devices within ongoing research on STH egg detection in field conditions.

Study on the Feasibility of the TG Method for Maximum Water Content Measurement of Waterlogged Archaeological Wood

ABSTRACT Thermogravimetry (TG) is used to measure the change of sample mass versus temperature or time under a program controlling temperature. It is a common thermal analysis tool with a precise built-in balance, and accurate data can be obtained through a small amount of sample at the level of milligrams. The feasibility of the TG method for determining maximum water content (MWC) measurement of waterlogged archaeological wood was studied. Simulated waterlogged wood and waterlogged archaeological wood were used to determine the test condition for the TG method. MWC data obtained through the oven-dry and TG methods with different mass gradients from 0–10 mg to >50 mg were analyzed statistically. Deviation, error bar, and coefficient of variation were evaluated. According to the results, when sample mass is no less than 30 mg, and holding time at 105°C is no less than 40 min, data deviation between these two methods is less than 5%. Effect of sampling depth and presence of inorganic deposits were also investigated. Specimens were taken from an archaeological wood with a sampling depth from 2 to 6 mm, then MWC was measured through the TG method. The results indicate MWC of the samples taken from a depth of 2–4 mm is higher than that taken from a depth of 0–2 mm and is lower than that taken from a depth of 4–6 mm, which is related to inorganic deposits. The presence of deposits was verified through SEM-EDX. MWC of three archaeological wood samples from China and five archaeological wood samples from Italy were measured to verify the effectiveness of the TG method when wood species and degradation degree are different.

A Novel Optical Fiber Terahertz Biosensor Based on Anti-Resonance for The Rapid and Nondestructive Detection of Tumor Cells.

The sensitive and accurate detection of tumor cells is essential for successful cancer therapy and improving cancer survival rates. However, current tumor cell detection technologies have some limitations for clinical applications due to their complexity, low specificity, and high cost. Herein, we describe the design of a terahertz anti-resonance hollow core fiber (THz AR-HCF) biosensor that can be used for tumor cell detection. Through simulation and experimental comparisons, the low-loss property of the THz AR-HCF was verified, and the most suitable fiber out of multiple THz AR-HCFs was selected for biosensing applications. By measuring different cell numbers and different types of tumor cells, a good linear relationship between THz transmittance and the numbers of cells between 10 and 106 was found. Meanwhile, different types of tumor cells can be distinguished by comparing THz transmission spectra, indicating that the biosensor has high sensitivity and specificity for tumor cell detection. The biosensor only required a small amount of sample (as low as 100 μL), and it enables label-free and nondestructive quantitative detection. Our flow cytometry results showed that the cell viability was as high as 98.5 ± 0.26% after the whole assay process, and there was no statistically significant difference compared with the negative control. This study demonstrates that the proposed THz AR-HCF biosensor has great potential for the highly sensitive, label-free, and nondestructive detection of circulating tumor cells in clinical samples.

Simultaneous Determination of 12 Preservatives in Pastries Using Gas Chromatography-Mass Spectrometry.

(1) Background: Preservatives may pose a potential threat to human health. To ensure food safety, this study has devised a method that concurrently detects a dozen preservatives (acetic acid, propionic acid, dehydroacetic acid, benzoic acid, sorbic acid, dimethyl fumarate, methyl parahydroxybenzoate, ethyl parahydroxybenzoate, propyl parahydroxybenzoate, isopropyl parahydroxybenzoate, butyl parahydroxybenzoate, and isobutyl parahydroxybenzoate) in pastry, utilizing gas chromatography-mass spectrometry. (2) Methods: The pastry samples were acidified with hydrochloric acid, extracted with acetonitrile via vortexing, purified by hexane and saturated with sodium chloride solution to remove lipids and impurities, and then concentrated via nitrogen blowing. The method was then quantitatively analyzed using GC-MS with the internal standard method after methanol re-dissolution. (3) Results: The results showed that the content of the 12 preservatives had good linearity within the range of 1.0-50 μg/mL, with correlation coefficients all greater than 0.99. The method detection limit was 0.04-2.00 mg/kg and the quantification limit was 0.12-6.67 mg/kg. The average recovery rates of the samples at three different spiked concentrations of low, medium, and high were 70.18-109.22%, and the relative standard deviations were 1.82-9.79% (n = 6). (4) Conclusions: This method requires a small amount of sample, has high sensitivity, and is simple and fast to operate, making it suitable for the simultaneous determination of 12 preservatives in pastry. This approach contributes to the effective surveillance and regulation of preservative usage in pastries, thereby safeguarding public well-being.

THU597 Po2-guided Adrenal Vein Sampling In Primary Aldosteronism

Abstract Disclosure: K. Omata: None. Y. Tezuka: None. Y. Ono: None. F. Satoh: None. Background: Accurate laterality diagnosis of adrenal aldosterone over-secretion is crucial in determining specific treatment for primary aldosteronism. Although adrenal vein sampling (AVS) is considered as the gold standard method for lateralization, successful canulation to right adrenal vein (RAV) has been reported to be difficult since RAV usually empties directly into inferior vena cava (IVC). In addition, the entrance of RAV is close to that of hepatic vein (HV) or opens to a common trunk with HV in up to 20% of the patients with PA. Cortisol step-up and other proposed indices are not always available during the procedure. Method: AVS was performed in confirmed PA patients between January 2021 and March 2022 at Tohoku University Hospital. During AVS, a small portion (0.3mL) of the sampled veins (RAV, IVC and HV) were analyzed with a blood gas analyzer for partial pressure of oxygen (pO2) measurement. Result: A total of 113 AVS was performed. After excluding inappropriate samples, further analyzed were 113 samples of IVC, 100 of RAV, 109 of HV before cosyntropin stimulation, and 113 samples of IVC, 110 of RAV, 108 of HV after cosyntropin stimulation. We observed an average of 22 mmHg increase of pO2 in RAV than IPV, and 27 mmHg increase than HV before stimulation. The difference between RAV and IPV was 15 mmHg in average and that of RAV and HV was 21 mmHg after stimulation. Similar pO2 step-up was also observed between left adrenal vein and left inferior phrenic vein. Discussion: Here we first describe prominent pO2 step-up in both adrenal veins compared to neighboring non-adrenal veins and peripheral blood. pO2 measurement is easier, faster, less expensive, and requires a very small amount of sample, can be performed by routine equipments in angiography suite, compared to other selectivity indices of successful canulation in AVS. This could also contribute to reducing unnecessary blood sampling, radiation exposure and repeat AVS. pO2 step-up in adrenal vein suggests low oxygen consumption in adrenal glands, which potentially contributes to survival advantage in systemic hypoxic conditions. We propose the novel pO2-guided AVS especially in patients with difficult RAV anatomy and in unexperienced centers. Presentation: Thursday, June 15, 2023