Quality Reference Research Articles

Low-Field MRI for Dental Imaging in Pediatric Patients With Supernumerary and Ectopic Teeth: A Comparative Study of 0.55 T and Ultra-Low-Dose CT.

This study sought to elucidate the diagnostic performance of 0.55 T magnetic resonance imaging (MRI) for pediatric dental imaging, specifically in terms of the image quality (IQ) for detecting ectopic and/or supernumerary teeth, compared with routine ultra-low-dose computed tomography (ULD-CT) of the jaw. A total of 16 pediatric patients (mean age: 12.4 ± 2.6 years, range: 9-17 years) with ectopic and/or supernumerary teeth screened from January 2023 to January 2024 were enrolled in this prospective, single-center study. All patients underwent ULD-CT as the clinical reference standard and 0.55 T MRI as the study scan on the same day. A 0.6-mm isotropic 3-dimensional T1w FLASH sequence was developed with a dedicated field of view of the upper and lower jaws. ULD-CT was performed using a new single-source computed tomography (CT) scanner equipped with a tin filter (Sn100, slice thickness: 1 mm, quality reference mAs: 24). The IQ for the tooth axis, the tooth length, the tooth root, root resorptions, cysts, the periodontal ligament space, and the mandibular canal was evaluated twice by 3 senior readers using a 5-point Likert scale (LS) (LS score of 1: insufficient, 3: reduced IQ but sufficient for clinical use, and 5: perfect) and compared between both methods. Subsequently, the results were dichotomized into nonvalid (LS score of ≤2) and valid (LS score of ≥3) for clinical use. A total of 49 ectopic and/or supernumerary teeth in 16 pediatric patients were investigated using ULD-CT (CTDI: 0.43 ± 0.09 mGy) and 0.55 T MRI. The mean MRI acquisition time was 9:45 minutes. Motion artifacts were nonsignificantly different between 0.55 T MRI and ULD-CT (P = 0.126). The IQ for the tooth axis, the tooth root, root resorptions, and cysts was similar between the methods. The IQ for the periodontal ligament space and tooth length favored ULD-CT by 14% (confidence interval [CI]: 4.3%-24%) and 7.5% (CI: 1.8%-13%), respectively, whereas that for the mandibular canal favored 0.55 T MRI by -35% (CI: -54%-16%). Sufficient IQ was found especially for cystic lesions (CT: 100% sufficient, MRI: 95% sufficient), the tooth root (CT: 100%, MRI: 98%), root resorptions (CT: 94%; MRI: 85%), the tooth axis (CT: 100%; MRI: 98%), and the tooth length (CT: 99%; MRI: 91%). The findings indicate that 0.55 T MRI is a feasible, radiation-free technique for delineating ectopic and/or supernumerary teeth in pediatric patients. Nevertheless, to date, 0.55 T MRI has not yet been able to provide an optimal IQ for all anatomical tooth and jaw structures. In cases of advanced clinical indications that require optimal spatial resolution, high-resolution CT or cone-beam CT may still be necessary.

Machine learning-aided microRNA discovery for olive oil quality.

MicroRNAs (miRNAs) are key regulators of gene expression in plants, influencing various biological processes such as oil quality and seed development. Although, our knowledge about miRNAs in olive (Olea europaea L.) is progressing, with several miRNAs being identified in previous studies, but most of these reported miRNAs have been predicted without the aid of a reference genome, primarily due to limited genome accessibility at the time. However, significant knowledge gaps still need to be improved in this area. This study addresses the complexities of miRNA detection in olive, using a high quality reference genome and a combination of genomics and machine learning-based methods. By leveraging random forest and support vector machine algorithms, we successfully identified 56 novel miRNAs in olive, surpassing the limitations of conventional homology-based methods. Our subsequent analysis revealed that some of these miRNAs are implicated in the regulation of key genes involved in oil quality. Within the context of oil biosynthesis pathways, the novel miRNA Oeu124369 regulates fatty acid biosynthesis by targeting acetyl-CoA acyltransferase 1 and palmitoyl-protein thioesterase, thereby influencing the production of acetyl-CoA and palmitic acid, respectively. These findings underscore the power of machine learning in unraveling the complex miRNA regulatory network in olive and provide a high quality miRNA resource for future research aimed at improving olive oil production by exploring the target genes of the identified miRNAs to understand their role and their biological processes.

How to Better Qualify ICT Graduates to Support Digital Education: A contribution from CALOHEE Tuning project qualifications framework

The Information and Communications Technology subject area is a broad multidisciplinary field of academic research and professional practice covering many topics ranging from electronics to system and network administration, to software development, cyber security, VR, AR, IoT and AI. Due to its nature, it cooperates closely with diverse areas, most notably eLearning and digital education. As contemporary educational institutions undergo a digital transformation, by which its processes are reengineered to take most of the possibilities offered by the emerging technologies, the contribution of the ICT field has become transversal and consequently of critical importance. The term ICT which refers to this wide multidisciplinary field differentiates from IT, which applies specifically to the management and use of computer systems to store, retrieve, transmit, and manipulate data. The continuous expansion of the field to new territories of practice such as education is requiring additional knowledge, skills and wider competences acquisition. In addition, high volatility of the job market creates the need for very adaptable professional profiles. As a result, there is a pressure from the job market for shorter and more job-oriented programmes, but also for competence frameworks which may serve as references for quality higher education and training. In this paper we present the Tuning Quality Reference Framework (QRF) for ICT which was developed as part of the CALOHEE Erasmus+ funded project. A multidisciplinary team with experts from 12 different countries (Portugal, Lithuania, Germany, Italy, Spain, Austria, Belgium, Greece, Turkey, Finland, Ireland and Romania) took part in the task. The QRF is built in a way to flexibly address all the mentioned complexity and continuously emerging new requirements including educational institutions and non-formal education organisations. The approach used also supports innovation in learning, teaching and assessment practices in ICT degrees, fostering open and digital education.

Preparation of polystyrene microplastic particles by solvent-dissolution-precipitation

The reliable characterisation of the physicochemical properties of micro-sized plastic particles requires quality reference materials for establishing, calibrating, and validating methods. Heterogeneity in particle size, shape and surface chemistry are important factors for reference materials for them to mimic environmental microplastics. This paper introduces a method for preparing model polystyrene micro and nano plastic reference materials using a solvent dissolution-precipitation approach. Polystyrene microplastic particles with mean particle sizes of 0.35, 15.7, 30.0 and 52.3 micron were produced using solvent precipitation under different synthesis conditions with the particle present in a well dispersed and partially dispersed system. The particle size can be controlled by reducing the initial polystyrene-cyclohexane concentration and adjusting the volume of methanol. At a fixed polystyrene-cyclohexane ratio, particles within the specified size range were consistently produced. Chemical analysis using pyrolysis-gas chromatography-mass spectrometry revealed that synthesized microplastics maintain their chemical properties, aligning with the original composition of virgin polystyrene pellets. A similar conclusion was drawn after examining the surface chemistry of the virgin and synthesised microplastic particles using ATR-FTIR analysis. The polystyrene particles produced in this way may be of use as reference materials and might be of interest for toxicological studies.

Assessing background levels of trace elements in soils of Mato Grosso (Brazil) for environmental and food security

The State of Mato Grosso, Brazil, presents a great diversity of soils and landscapes, and many areas of agriculture and mining. However, the natural content of trace elements in the soil are still little known, which represents a great gap for studies and/or regulations concerning soil and food security. This study proposes to establishing quality reference values ​​(QRVs) for trace elements in Mato Grosso soils. Soil sampling was carried out to cover the geodiversity of soils in this region, considering geology, geomorphology, lithology, pedology and biomes, in addition to summarizing the data available in the literature to form the database for this study. The soil was analyzed for the contents of Fe, Mn, Cu, Zn, Ni, Cr, Ba, Pb, As, Cd and Hg, according to the USEPA 3051A methodology. Trace element results based on soil geodiversity contributed to a general description of how levels of these elements may be related to the environmental factors studied. The levels of main elements related to the environmental factors were Mn and Zn to geology; Mn, Cr, Ba, Zn, As and Cd to geomorphology; Mn to lithology; Mn and Cr to pedology; and Mn, As, Cd and Hg to the biome. It was not possible to propose QRVs grouped by environmental factors for the State of Mato Grosso, especially due to the large territorial extension covered. Thus, the QRVs were proposed in the 90th percentile, in mg kg−1, as follows: Fe 23,128; Mn 351; Cu 16.50; Zn 29.24; Ni 8.86; Cr 52.73; Ba 84.45; Pb 13.42; As 7.60; Cd 0.87; and Hg 0.10. Mercury, Cd, and As levels require careful regional monitoring, as some environments, such as the Amazon biome, may present naturally high levels, and small alterations in the bioavailability of such elements might represent a risk to health or the environment.

Sales mode selection considering the consumer reference quality effect

AbstractThis work investigates a two‐tier supply chain in which a supplier adjusts product quality and prices and distributes the products through a retailer or directly to consumers with the reference quality (RQ) effect. The supplier can choose from three, that is, traditional sales (TS), dual‐channel (DC), and online‐to‐offline (O2O), sales modes. In the O2O sales mode, the retailer is allowed to open an online channel. The market demands are determined by the consumer utility consisting of two parts, a part depending on the consumer RQ effect and the other depending on the retail price and product quality. The profit maximization, that is, the Stackelberg game, models involving the consumer RQ effect are developed using prospect theory, wherein the supplier has the first mover advantage. The analytical optimal solutions are obtained through backward induction. The optimal quality and pricing decisions and the optimal profits of the supply chain members are compared among the three sales modes. A practical application is analyzed to verify the theoretical results of the proposed models. The results show that the consumer RQ effect benefits the two supply chain members under certain conditions. The optimal quality and pricing decisions are significantly affected by the consumer RQ effect except those of the supplier under the O2O sales mode. When consumers have the RQ effect, the DC sales mode is the best choice for the supplier, is a win–win mode for the two supply chain members under certain conditions, and benefits the consumers the most among the three sales modes.

Evaluation of the accuracy of remote emission sensing measurements via real-world vehicle dynamic tests

To evaluate the measurement accuracy of horizontal and vertical remote emission sensing (RES) equipment, a real-world dynamic test was carried out in Chengdu by using electric vehicles equipped with various concentrations of standard gases. In addition, a new Image-based Spectral Processing Algorithm (ISPA) for vertical remote sensing spectral data was developed to improve the measurement capability. The results showed that the ISPA provided a greater percentage of valid data and lower relative errors; thus, our new algorithm could more effectively analyze the spectral data to measure vehicle emission levels. The percentages of valid horizontal and vertical RES data were 71% and 84%, respectively. The mean relative errors of CO2, CO, HC and NO measured by the vertical RES were about 5%, 20%, 20% and 40%, respectively, and those of CO2, CO and NO measured by the horizontal RES were 3%, 13% and 15%, respectively. For the common vehicle emission concentration, the percentage of valid data for the two RES types increased with increasing gas concentration. As the vehicle speed increased, the relative errors of the horizontal RES equipment showed an increasing trend for the same concentration of gas. Furthermore, for the same speed segment, the relative errors of the horizontal RES equipment increased as the simulated emission concentration decreased. The vertical RES equipment did not exhibit a consistent trend in terms of changes. This study provides a data quality reference for further RES applications.

Comparative evaluation of two clinical sampling techniques for HPV detection in male genital sites: a randomized controlled study.

The optimal sampling methods for detecting human papillomavirus (HPV) in male genital sites remain unclear. This study aimed to assess the performance, acceptability, and comfort of two sampling techniques for male genital HPV detection. A total of 490 men aged 18-45 were randomly assigned in a 1:1 ratio to undergo either the rub-brush (nail file followed by swab) or brush-only method (swab only) for sampling at external genitalia sites (PGS) and perineum/perianal (PA) sites. HPV distribution, specimen validity (β-globin as a quality reference), and participant acceptability and comfort were evaluated between the two sampling methods. The brush-only method demonstrated non-inferiority in detecting 14 high-risk HPV types (16/18/31/33/35/39/45/51/52/56/58/59/66/68) compared to the rub-brush method in both PGS (18.9%vs. 16.9%) and PA (10.5%vs. 11.9%). Although no significant differences were observed in positive rates for other HPV types, the brush-only method had a significantly higher invalid rate in PA (8.5%vs. 1.5%). Approximately 85.0% of participants reported good acceptability and comfort with both sampling methods, regardless of anatomical sites. This study suggests comparable performance, acceptability and comfort between the two sampling techniques for HPV detection. However, the rub-brush method may offer an advantage in higher sample validity.

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

EU surveys insights: analytical tools, future directions, and the essential requirement for reference materials in wastewater monitoring of SARS-CoV-2, antimicrobial resistance and beyond

BackgroundWastewater surveillance (WWS) acts as a vigilant sentinel system for communities, analysing sewage to protect public health by detecting outbreaks and monitoring trends in pathogens and contaminants. To achieve a thorough comprehension of present and upcoming practices and to identify challenges and opportunities for standardisation and improvement in WWS methodologies, two EU surveys were conducted targeting over 750 WWS laboratories across Europe and other regions. The first survey explored a diverse range of activities currently undertaken or planned by laboratories. The second survey specifically targeted methods and quality controls utilised for SARS-CoV-2 surveillance.ResultsThe findings of the two surveys provide a comprehensive insight into the procedures and methodologies applied in WWS. In Europe, WWS primarily focuses on SARS-CoV-2 with 99% of the survey participants dedicated to this virus. However, the responses highlighted a lack of standardisation in the methodologies employed for monitoring SARS-CoV-2. The surveillance of other pathogens, including antimicrobial resistance, is currently fragmented and conducted by only a limited number of laboratories. Notably, these activities are anticipated to expand in the future. Survey replies emphasise the collective recognition of the need to enhance the accuracy of results in WWS practices, reflecting a shared commitment to advancing precision and effectiveness in WWS methodologies.ConclusionsThese surveys identified a lack of standardised common procedures in WWS practices and the need for quality standards and reference materials to enhance the accuracy and reliability of WWS methods in the future. In addition, it is important to broaden surveillance efforts beyond SARS-CoV-2 to include other emerging pathogens and antimicrobial resistance to ensure a comprehensive approach to protecting public health.

A Ranking Tool for "Category Killer" Microbial Biobanks.

Microbial biobanks preserve and provide microbial bioresources for research, training, and quality control purposes. They ensure the conservation of biodiversity, contribute to taxonomical research, and support scientific advancements. Microbial biobanks can cover a wide range of phylogenetic and metabolic diversity ("category killers") or focus on specific taxonomic, thematic, or disease areas. The strategic decisions about strain selection for certain applications or for the biobank culling necessitate a method to support prioritization and selection. Here, we propose an unbiased scoring approach based on objective parameters to assess, categorize, and assign priorities among samples in stock in a microbial biobank. We describe the concept of this ranking tool and its application to identify high-priority strains for whole genome sequencing with two main goals: (i) genomic characterization of quality control, reference, and type strains; (ii) genome mining for the discovery of natural products, bioactive and antimicrobial molecules, with focus on human diseases. The general concept of the tool can be useful to any biobank and for any ranking or culling needs.

A DNA barcoding framework for taxonomic verification in the Darwin Tree of Life Project.

Biodiversity genomics research requires reliable organismal identification, which can be difficult based on morphology alone. DNA-based identification using DNA barcoding can provide confirmation of species identity and resolve taxonomic issues but is rarely used in studies generating reference genomes. Here, we describe the development and implementation of DNA barcoding for the Darwin Tree of Life Project (DToL), which aims to sequence and assemble high quality reference genomes for all eukaryotic species in Britain and Ireland. We present a standardised framework for DNA barcode sequencing and data interpretation that is then adapted for diverse organismal groups. DNA barcoding data from over 12,000 DToL specimens has identified up to 20% of samples requiring additional verification, with 2% of seed plants and 3.5% of animal specimens subsequently having their names changed. We also make recommendations for future developments using new sequencing approaches and streamlined bioinformatic approaches.

Mn 2p and O 1s X-ray absorption spectroscopy of manganese oxides

Manganese oxides (MnOx) are used as electrode materials in many different energy storage applications such as batteries and supercapacitors. X-ray spectromicroscopy, using near edge X-ray absorption spectra (NEXAFS) for chemical speciation, is a powerful tool to study reduction and oxidation processes in such systems. High quality reference spectra are required for both qualitative identification and quantitative mapping of MnOx species. Here we present accurate, quantitative Mn 2p and O 1s NEXAFS spectra of MnO, MnSO4, Mn3O4, Mn2O3, α-MnO2, β-MnO2, and KMnO4, measured using both transmission and total electron yield X-ray absorption techniques. An example of the use of these reference spectra in a study of Zn/MnO2 batteries is given.

Haplotype-resolved chromosome-level genome assembly of Huyou (Citrus changshanensis)

Huyou (Citrus changshanensis) is a significant citrus species that originated in Zhejiang Province, China, where it is also primarily cultivated. It is valued for its distinctive flavor and notable health benefits, owing to its high content of bioactive compounds like naringin and limonin. However, the absence of a high quality reference genome has limited the exploration of these health-promoting compounds in Huyou and hindered research into the mechanisms behind its medicinal properties. In this study, we present a phased chromosome-level genome assembly of Huyou. By combining PacBio and Hi-C sequencing, we generated a primary genome assembly and two haplotypes, comprising nine pseudo-chromosomes, with sizes of 339.91 Mb, 323.51 Mb, and 311.89 Mb, respectively. By integrating transcriptome data and annotations of homologous species, we identified a total of 29,775 protein-coding genes in the genome of Huyou. Additionally, we detected lots of structural variants between the two haplotypes. This represents the first reference genome of Huyou, providing a valuable resource for future studies on its agricultural characteristics and medicinal applications.

Abstract PO4-25-12: Improving HER2 Low Scoring Consistency and Accuracy: Insights from the Australian HER2 Low Concordance Study for Invasive Breast Cancer

Abstract Introduction: The Destiny Breast-04 Trial (DB-04) demonstrated the survival benefits of Trastuzumab Deruxtecan (T-DXd) for women with metastatic HER2 Low breast cancer, characterised by 1+ or 2+ IHC staining without amplification. While the DB-04 study applied the standard 2018 ASCO CAP IHC scoring criteria, in clinical practice, distinguishing HER2 0 from 1+ cancers is challenging as i) HER2 Low is not a biologically distinct subset of breast cancer, ii) there are no reference standards for HER2 Low cancers, iii) second-tier test, like ISH, are not applicable, and iv) there are no known controls for cases that have 0 or 1+ HER2 scores. For two decades this distinction was clinically immaterial, but now differentiating between HER2 0 and 1+ has now become crucial for determining patient eligibility for T-DXd therapy. Concerns regarding the subjectivity, imprecision and poor concordance between pathologists in scoring IHC in HER2 Low cancers raise the potential for misalignments in patient treatment. Ensuring pathologists have access to focused training for interpreting IHC scores at the low end of the HER2 expression spectrum, quality assurance procedures and reference sets are essential steps to help pathologists assess HER2 Low breast cancers more accurately and consistently. Design: In this study, a group of 9 experienced breast pathologists compiled a deidentified set of 60 breast cancer core biopsies from 3 laboratories. The Ventana 4B5 HER2 assay had been used for evaluation and the local laboratories had scored the samples as HER2 0 or 1+. We teased out the ASCO CAP 2018 criteria and used our collective expertise of reporting HER2 IHC for many years to specify HER2 Low-focused scoring conventions, including some potential pitfalls. Subsequently, using these conventions, each pathologist reviewed digitized whole slide images of the IHC slides and scored HER2 expression for each case. At a consensus workshop, the cases were jointly reviewed to establish consensus scores and determine the percentage of HER2-expressing tumor cells in each case. We then evaluated the concordance between individual pathologists' HER2 scores and the consensus opinion and ascertained reasons for discordance. Results: Among the cases discussed during the consensus conference, 43 out of 60 (71.7%) were classified as HER2 Low, with 40 cases designated as 1+ and three as 2+ (known to be not amplified). The consensus score matched the majority opinion of the pathologists' independent scores in 93.3% (56 out of 60) of the cases. Utilizing the HER2 Low-focused IHC scoring conventions, 7 out of 17 (41.2%) cases locally reported as HER2 0 were reclassified as HER2 Low. Conversely, among the 32 cases with local scores of 1+, 7 (21.8%) were reclassified as ultralow or null. When compared to the consensus score, individual pathologists' scores demonstrated concordance levels ranging from 71.7% to 91.7%, with a mean concordance rate of 81.3%. Cases with less than 20% of tumor cells expressing HER2 had lower inter observer concordance. This reference set of cases with expert consensus HER2 scores obtained through our study will be invaluable for peer training and the development of external quality assurance programs for HER2 Low cancers, including the quality assurance program of the Royal College of Pathologists of Australasia. Conclusion: This study revealed that when breast pathologists were provided explicit instructions on scoring pitfalls and HER2 Low-focused scoring conventions, their HER2 scores were concordant with expert consensus scores in 71.7% to 91.7% of cases. Discordant cases primarily involved cases with less than 20% of tumor cells expressing HER2. Utilising such an approach, peer training and quality assurance procedures will improve the accuracy and consistency of HER2 IHC assessment for better patient care. Reassessing older cases using HER2 Low focused scoring conventions may result in revisions of HER2 scores from HER2 Low to zero, and vice versa. Table. Individual pathologists' concordance with the consensus HER2 IHC score Applying our HER2 Low-focused IHC scoring conventions in a set of 60 core biopsies of invasive breast cancer with low or 0 HER2 protein expression. Citation Format: Gelareh Farshid, Beena Kumar, Nirmala Pathmanathan, Hema Mahajan, Ben Dessauvagie, Jane Armes, Cameron Snell, Amardeep Gilhotra. Improving HER2 Low Scoring Consistency and Accuracy: Insights from the Australian HER2 Low Concordance Study for Invasive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-25-12.

Comparative analysis of sediment quality indices using different reference values in an environmental protection area in Southeastern Brazil.

Contamination of aquatic ecosystems by potentially toxic elements (PTEs) is a concerning environmental issue, given their persistence, toxicity potential, and ability to accumulate in living organisms. Several studies have been conducted to assess the contamination of aquatic ecosystems by PTEs, using pollution and ecological risk indices that rely on the concentration of these elements in aquatic sediments. However, many of these studies use global reference values for calculating the indices, which can lead to misleading interpretations due to substantial variations in PTEs concentrations influenced by the geological characteristics of each region. Therefore, the use of regional reference values is more appropriate when available. This study aimed to investigate variations in the results of five indices, employing global, regional, and quality reference values, based on sediment samples collected from rivers in the Ipanema National Forest, a protected area in Brazil exposed to various anthropogenic pressures. The results revealed that elements such as Al, Fe, and Mn exceeded the limits allowed by legislation in water samples, while As and Cr surpassed the limits in sediment samples. Comparative analysis highlighted significant discrepancies in the results of the indices when global reference values were used compared to regional and quality reference values, especially for As and Ba. Thus, this study underscores the importance of establishing specific regional values for an accurate assessment of sediment quality and the risks associated with contamination by PTEs in different regions worldwide.

Geochemical background and geopedological interactions of selenium in soils from Piauí state, Northeastern Brazil

ABSTRACT Although Selenium (Se) plays a role as a micronutrient for humans through vegetable consumption, it is also recognized as toxic when present in excessive quantities. Therefore, quantifying Se contents in soils can prevent diseases influenced by crop Se deficiency or excess. We aimed to measure background contents, establish quality reference values (QRV) for Se in soils from two Brazilian biomes (Cerrado and Caatinga), and assess how geopedological factors affect Se content and spatial variability. Two hundred and eight composite topsoil samples were analyzed for Se content, covering an area of about 251,578 km². Sampling sites were under the minimal anthropogenic influence to represent Se background contents. Selenium contents were determined by hydride generation atomic absorption spectroscopy (HGAAS), ranging from 0.002 to 4.78 mg kg -1 . Most soils had contents below the world average of 0.44 mg kg -1 but still above the soil content that causes human Se deficiency (0.125 mg kg -1 ). Soils from Cerrado and Caatinga biomes showed similar average contents of Se, 0.41 and 0.47 mg kg -1 , respectively. Organic carbon content and soil particle size (clay fraction) were the main factors governing Se content in the soils. Our results contribute to understanding the Se content and spatial distribution in tropical soils and the factors governing them. They also provide a tool for agriculture and environmental decision-makers to plan public policies regarding the management of Se levels in these and similar tropical soils in the world.

Abstract 3520: A scalable single cell RNA-seq pipeline leveraging machine learning and high-quality references for cell-type prediction

Abstract Single cell RNA-seq (scRNA-seq) technology transformed our understanding of biology at the cell level. Inferring cell types provide insights into the relative abundance of, and genomic differences between, different cell types. Current methods leverage known cell type markers and genomic similarity measures to attribute cell types to groups of cells. We present a scalable machine learning-based pipeline that can leverage high quality reference annotation data to infer cell types quickly for multiple scRNA-seq experimental samples. This pipeline leverages two machine learning technologies: variational autoencoders (VAE) to create a low-dimensional representation of the reference transcriptome; and, supervised learning methods that use this representation to learn cell types from the reference data. This pipeline can quickly score new experimental data using GPU-enabled computing platforms and provide probabilities of a cell being each cell type present in the reference data. This novel pipeline is evaluated using 5 public reference data sets. We evaluate whether VAE-based representations benefit supervised learning, compared to PCA and t-SNE. We next evaluate different supervised learning methods for predictive performance. Finally, we compare the pipeline’s performance with commonly-used cell type prediction algorithms (Seurat, scANVI). We find that using a VAE is generally better than both PCA and t-SNE for feature generation to predict cell type. Using the VAE representation, there is no significant difference in accuracy between logistic regression and other supervised learning algorithms. Finally, using logistic regression as the learning machine, this pipeline is as accurate as Seurat and better than scANVI, while running about 2-5x faster than Seurat. Table 1 Balanced accuracy (%) from leave-one-subject-out cross-validation across 5 public data sets. Intervals are the range of the metric across the cross-validation folds. Algorithm PBMC (10X) HLCA Eraslan snRNA Blueprint Breast Blueprint Lung Our pipeline 92 (87-95) 92 (88-93) 93 (90-97) 89 (80-96) 97 (95-99) Seurat 96 (95-97) 90 (94-98) 94 (93-97) 96 (87-98) 98 (94-99) scANVI 91 (84-95) 72 (78-86) 92 (88-96) 94 (80-97) 88 (86-100) Citation Format: Abhijit Dasgupta, Grant Duclos, Ricardo Miragaia, Brychan Manry, Etai Jacob, Natasha Markuzon, Asaf Rotem. A scalable single cell RNA-seq pipeline leveraging machine learning and high-quality references for cell-type prediction [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 3520.

A 10.5 ppm/°C Modified Sub-1 V Bandgap in 28 nm CMOS Technology with Only Two Operating Points

Reference voltage/current generation is essential to the Analog circuit design. There have been several ways to generate quality reference voltage using bandgap reference (BGR) and there are mainly two types: current mode and voltage mode. The current-mode bandgap reference (CBGR) is widely accepted in industry due to having an output voltage which is below 1 V. However, its drawbacks include a lack of proportional to absolute temperature (PTAT) current availability, a large silicon area, multiple operating points, and a large temperature coefficient (TC). In this paper, various operating points are explained in detail with diagrams. Similar to the conventional voltage mode bandgap reference (VBGR) circuits, modifications of the existing circuits with only two operating points have also been proposed. Moreover, the proposed BGR occupies a much smaller area due to eliminating the complimentary to absolute temperature (CTAT) current-generating resistor. A new self-biased opamp was introduced to operate from a 1.05 V supply, reducing systematic offset and TC of the BGR. The proposed solution has been implemented in 28 nm CMOS TSMC technology, and extraction simulations were performed to prove the robustness of the proposed circuit. The targeted mean BGR output is 500 mV, and across the industrial temperature range (−40 to 125 °C), the simulated TC is approximately 10.5 ppm/°C. The integrated output noise within the observable frequency band is 19.6 µV (rms). A 200-point Monte Carlo simulation displays a histogram with a 2.6 mV accuracy of 1.2% (±3-sigma). The proposed BGR circuit consumes 32.8 µW of power from a 1.05 V supply in a fast process and hot (125 °C) corner. It occupies a silicon area of 81 × 42 µm (including capacitors). This design can aim for use in biomedical and sensor applications.

Effect of kilovoltage and quality reference mAs on CT-based attenuation correction in 177Lu SPECT/CT imaging: a phantom study

IntroductionCT-based attenuation correction (CT-AC) plays a major role in accurate activity quantification by SPECT/CT imaging. However, the effect of kilovoltage peak (kVp) and quality-reference mAs (QRM) on the attenuation coefficient image (μ-map) and volume CT dose index (CTDIvol) have not yet been systematically evaluated. Therefore, the aim of this study was to fill this gap and investigate the influence of kVp and QRM on CT-AC in 177Lu SPECT/CT imaging.MethodsSeventy low-dose CT acquisitions of an Electron Density Phantom (seventeen inserts of nine tissue-equivalent materials) were acquired using various kVp and QRM combinations on a Siemens Symbia Intevo Bold SPECT/CT system. Using manufacturer reconstruction software, 177Lu μ-maps were generated for each CT image, and three low-dose CT related aspects were examined. First, the μ-map-based attenuation values (μmeasured) were compared with theoretical values (μtheoretical). Second, changes in 177Lu activity expected due to changes in the μ-map were calculated using a modified Chang method. Third, the noise in the μ-map was assessed by measuring the coefficient of variation in a volume of interest in the homogeneous section of the Electron Density Phantom. Lastly, two phantoms were designed to simulate attenuation in four tissue-equivalent materials for two different source geometries (1-mL and 10-mL syringes). 177Lu SPECT/CT imaging was performed using three different reconstruction algorithms (xSPECT Quant, Flash3D, STIR), and the SPECT-based activities were compared against the nominal activities in the sources.ResultsThe largest relative errors between μmeasured and μtheoretical were observed in the lung inhale insert (range: 18%-36%), while it remained below 6% for all other inserts. The resulting changes in 177Lu activity quantification were -3.5% in the lung inhale insert and less than -2.3% in all other inserts. Coefficient of variation and CTDIvol ranged from 0.3% and 3.6 mGy (130 kVp, 35 mAs) to 0.4% and 0.9 mGy (80 kVp, 20 mAs), respectively. The SPECT-based activity quantification using xSPECT Quant reconstructions outperformed all other reconstruction algorithms.ConclusionThis study shows that kVp and QRM values in low-dose CT imaging have a minimum effect on quantitative 177Lu SPECT/CT imaging, while the selection of low values of kVp and QRM reduce the CTDIvol.