Fine Characterization Research Articles

Abstract 5141: Using single cell gene expression to develop treatment response predictions in multiple myeloma

Abstract The promise of precision medicine in oncology is to identify the ideal treatment for each patient, eliminating failed treatment cycles and reducing treatment burdens on patients and payors. While gene sequencing can predict effective treatment options in some cases, studies have estimated that only 10-15% of cancer patients are treated with genotype matched drugs. Additional treatment selection tools for predicting patient response thus remains a critical clinical need. While gene sequencing has clear utility in predicting therapeutic response, gene expression is less commonly used in clinical tests to guide treatment selection. Gene expression is theoretically attractive to predicting therapeutic response because, unlike mutational analysis, it provides a direct readout of the dysregulated biochemical activities in the cells which may be targeted by particular therapies. One of the major problems with conventional approaches to using gene expression to predict therapeutic response is tumor heterogeneity; that is, a biopsied tumor contains multiple cells types and even different tumor clones that can confound a conventional bulk gene expression analysis. More recently, single-cell RNA expression analysis technologies have grown in popularity. These technologies enable the fine characterization of tumors and their cellular makeup and hold the promise of increasing the power of gene expression measurements for identifying therapy response prediction tools. Here we show the application of single cell gene expression analysis with Proteona’s MapResponse™ machine-learning algorithms to developing a predictive classifier for patient response to Daratumumab treatment in multiple myeloma. Starting with publicly available data (Cohen et al. Nat. Medicine 2021), we developed a classifier that accurately predicted the response of 94% of subjects in the published study. This classifier was able to accurately predict response in an independent cohort of Daratumumab-treated patients. In contrast, the classifier performed poorly in a cohort of patients who did not receive Daratumumab. Together these data suggest the classifier has specificity to predicting response to Daratumumab and is not a general prognostic signature. These early findings point to the potential value of combining single-cell RNA sequencing with machine-learning methods such as MapResponse™ to bring precision medicine to more patients. Citation Format: Jonathan Scolnick, Stacy Xu, Sanjay de Mel, Cinnie Yentia Soekojo, Wee Joo Chng. Using single cell gene expression to develop treatment response predictions in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5141.

Three-dimensional modeling and analysis of fractal characteristics of rupture source combined acoustic emission and fractal theory

Deep mining exploration and the sustainable use of enormous data via acoustic emission (AE) systems is a major experimental approach for fulfilling the perception, characterization, and forecasting for rock engineering catastrophes such mines, tunnels, and water conservation. To carry out the fine numerical characterization of the nonlinear and disordered time-space-energy information in the AE system, we use the fractal theory to analyzing. The key elements such as time, space, and energy of the fracturing source are comprehensively extracted. The fractal dimension statistical framework and its optimal dimension are designed, and the three-dimensional (3D) analysis model that can characterize the actual failure and instability process is constructed. The AE experimental data and numerical simulation are used to obtain the spatial clustering and energy dissipation fractal dimension characteristics of regional AE events in the time domain. The model is optimized and verified on the spot. The results show that the time-space-energy parameters of AE can be characterized by fractal dimension. The fractal dimension analysis model can transform and finely characterize the failure anomaly data. The distribution results of the fractal dimension value field can be consistent with the actual failure. Through iterative optimization and comprehensive verification of the scientificity and applicability of the fractal dimension analysis model, a comprehensive fractal dimension representation method of time-space-energy of fracture source in rock failure process is formed, which can provide guidance for the service and analysis of existing monitoring systems in mines, and provide theoretical support and technical conditions for fine judgment of rock mass failure in mines.

Fine mapping and characterization of the dominant gene SmFTSH10 conferring non-photosensitivity in eggplant (Solanum melongena L.).

A candidate non photosensitive gene S m F TS H10 was identified by combining bulked segregant analysis and map‑based cloning. Low light condition often leads to poor coloration of photosensitive eggplant. Here, we obtained a non-photosensitive eggplant that can synthesize large amount of anthocyanin under shading conditions. Genetic analysis of F1 and F2 populations revealed that the phenotype of non-photosensitivity was regulated by a single dominant nuclear gene, herein temporarily designated SmFTSH10. Through Bulked segregant analysis (BSA), SNP haplotyping and fine genetic mapping delimited SmFTSH10 to a 290kb region of eggplant chromosome 10 flanking by markers dCAPS21 and dCAPS32. Sequence analysis revealed C-base deletion in the fourth exon of SmFTSH10 resulted in premature termination of translation. The expression level of SmFTSH10 decreased significantly in anthocyanin-rich parts of mutant '145' compared with the wild-type 'LSHX'. Sequencing of 10 recombinants revealed that the C-base deletion in the 4th exon of SmFTSH10 was co-segregated with the non-photosensitive phenotype, and the sequencing analysis of the natural population of eggplant also showed that the Indel in SmFTSH10 had a high accuracy in the identification of the photosensitivity of eggplant. Light-responsive expression patterns analysis suggests that it has the same expression trend as the genes involved in eggplant anthocyanin biosynthesis, which supports SmFTSH10 as the most possible candidate gene of non-photosensitivity. These findings provide a new insight into understanding the molecular mechanisms of anthocyanin biosynthesis in non-photosensitive eggplant.

Genetic variation in CaTIFY4b contributes to drought adaptation in chickpea.

SummaryChickpea production is vulnerable to drought stress. Identifying the genetic components underlying drought adaptation is crucial for enhancing chickpea productivity. Here, we present the fine mapping and characterization of ‘QTL‐hotspot’, a genomic region controlling chickpea growth with positive consequences on crop production under drought. We report that a non‐synonymous substitution in the transcription factor CaTIFY4b regulates seed weight and organ size in chickpea. Ectopic expression of CaTIFY4b in Medicago truncatula enhances root growth under water deficit. Our results suggest that allelic variation in ‘QTL‐hotspot’ improves pre‐anthesis water use, transpiration efficiency, root architecture and canopy development, enabling high‐yield performance under terminal drought conditions. Gene expression analysis indicated that CaTIFY4b may regulate organ size under water deficit by modulating the expression of GRF‐INTERACTING FACTOR1 (GIF1), a transcriptional co‐activator of Growth‐Regulating Factors. Taken together, our study offers new insights into the role of CaTIFY4b and on diverse physiological and molecular mechanisms underpinning chickpea growth and production under specific drought scenarios.

Fine mapping and characterization of the Crinkled Dwarf gene in cotton

Cotton (Gossypium) is an important natural fiber crop worldwide. Plant height, which is an important commercial cotton breeding trait, is also useful for plant architecture research. Crinkled Dwarf (cr), a natural mutant of Sea Island cotton (Gossypium barbadense L.), simultaneously displays crinkled leaves and dwarfing. However, the genes controlling cr have not been characterized, and the molecular mechanism of the trait remains unknown. In this study, genetic analysis indicated that cr was likely controlled by a major recessive gene, although the cr phenotype was sensitive to environmental factors, including light intensity. Using bulked-segregant analysis and recombinant methods, the cr gene was mapped to a 35.8-kbp genomic interval on chromosome D03 that contained three annotated protein-coding genes. Comparative transcriptome analysis showed that cr enhanced stress/disease resistance and repressed plant development/growth. Endogenous phytohormone measurements showed that most auxin compounds were decreased in the cr mutant. Although the cr mutation was insensitive to exogenous auxin, gibberellin and cytokinin treatments promoted and repressed main stem elongation, respectively. However, no hormone treatment could fully rescue the crinkled leaf phenotype. These findings will contribute to the breeding of cotton lines with improved plant architecture or yield, and aid in the dissection of the genetic basis of cr.

Pore closure in thick aluminum plate: From industrial hot rolling to individual pore observation

Pores are often present in large aluminum ingots after casting. To ensure the mechanical reliability of the final thick plates, these pores must be closed during the forming process, hot rolling in the present case. This study aims at understanding the effects of rolling parameters on the volume evolution of pores. To do so, X-ray microtomography is used to track real casting pores during deformation. Nevertheless, thick plates are too large to enable a fine characterization of the evolution of pores during the process. The size and shape of the samples as well as the mechanical boundary conditions must be optimized to meet imaging constraints. This paper focuses on the reproduction of complex loading paths. Multi-scale FE simulations are used to reproduce the loading conditions of thick plate rolling with uniaxial tests on samples of a few millimeters. Uniaxial tests are then characterized with tomography on a synchrotron X-ray beamline. In each sample, tens of pores are individually tracked, giving access to their volume evolution. The local loading path experienced by each pore is determined with FE simulation. It is shown that the volume evolution of a real pore correlates with the hydrostatic integration which is the integral of stress triaxiality along cumulated strain. This confirms that the closure of complex casting pores is enhanced by a high relative reduction and high values of L/H ratio during rolling similarly to what was observed numerically on simpler shapes.

Coordination of Ethylamine on Small Silver Clusters: Structural and Topological (ELF, QTAIM) Analyses.

Amine ligands are expected to drive the organization of metallic centers as well as the chemical reactivity of silver clusters early growing during the very first steps of the synthesis of silver nanoparticles via an organometallic route. Density functional theory (DFT) computational studies have been performed to characterize the structure, the atomic charge distribution, and the planar two-dimensional (2D)/three-dimensional (3D) relative stability of small-size silver clusters (Agn, 2 ≤ n ≤ 7), with or without an ethylamine (EA) ligand coordinated to the Ag clusters. The transition from 2D to 3D structures is shifted from n = 7 to 6 in the presence of one EA coordinating ligand, and it is explained from the analysis of the Ag-N and Ag-Ag bond energies. For fully EA saturated silver clusters (Agn-EAn), the effect on the 2D/3D transition is even more pronounced with a shift between n = 4 and 5. Subsequent electron localization function (ELF) and quantum theory of atoms in molecules (QTAIM) topological analyses allow for the fine characterization of the dative Ag-N and metallic Ag-Ag bonds, both in nature and in strength. Electron transfer from ethylamine to the coordinated silver atoms induces an increase of the polarization of the metallic core.

Poly(d,l-lactide)-Grafted Bioactive Glass Nanoparticles: From Nanobricks to Freeze-Cast Scaffolds for Bone Substitution

This paper focuses on an integrative “bricks-and-mortar” approach involving bioactive glass nanoparticles (bricks) covalently functionalized with a customized polymer (mortar) combined with the freeze-casting process. With the aim of obtaining a macroporous composite for bone substitution, composed of a spatially homogeneous assembly of nanoscale objects, we establish a method for the systematic elaboration of nanocomposite scaffolds. It was implemented through several steps from the synthesis of functionalized poly(d,l-lactide) (PDLLA) and SiO2–CaO binary bioactive glass nanoparticles (diameter around 164 nm) to the unidirectional freeze-casting process. The different stages include the first description of controlled PDLLA (Mn 8400 g·mol–1) grafting onto bioactive glass nanoparticle surfaces, their fine characterization and grafting quantification, and their mixing with free PDLLA chains (83 400 g·mol–1) during suspension formulation. This paper emphasizes the effect of the working temperature during the freeze-casting process on the multiscale spatial organization of resulting scaffolds such as the porosity morphology (lamellar and tubular), size (from 30 to 380 μm), anisotropy, and orientation. In addition to porosity, our results demonstrate a rosary-like organization of PDLLA-grafted nanoparticles in pore walls. The higher homogeneity in the spatial distribution of grafted nanoparticles over the height of scaffolds and at a micron scale confirms the validity of the “bricks-and-mortar” concept to prevent or limit aggregation. In particular, this study highlights the correlation between nanoparticle functionalization and mechanical properties, especially the recovery rate after compression tests. These results lay the foundation for the development of tunable materials for bone substitution, via potential enhancement of bioactivity and cell colonization.

Classification of underwater photogrammetry data for temperate benthic rocky reef mapping

The fine characterization of the substrate is a baseline to thoroughly investigate the relations between organisms and their biotopes. Cutting edge spatial technologies now provide access to accurate information on biotopes and biocenoses both in terrestrial and in marine environments. Photogrammetry is one of them and has recently been applied in submarine environments especially in shallow clear water. In this study, we investigated the potential of photogrammetry to characterise benthic habitats in turbid environments. Although more challenging, turbid environments are more frequent in temperate marine coastal areas. We selected two rocky sites in the bay of Saint-Malo (Brittany, France), differentiated by their level of turbidity, one being a marine site exposed to natural tides (Buharats), while the other (Bizeux) is subjected to both natural tides and artificial currents created by the functioning of a hydroelectric dam. The different substrates observed were classified into eight classes at a centimetre resolution using photogrammetry-based spatial and multispectral predictors. The spatial benthic terrain predictors were derived from a digital surface model (DSM) at various spatial scales, and the multispectral predictors were retrieved from the red-green-blue (RGB, natural colours) orthomosaic imagery. An overall classification was computed for Buharats and Bizeux, with accuracies of 84.76% and 79.54% respectively, revealing a good quality of the substrate classification. The combination of RGB, DSM, and several spatial benthic terrain variables, with a pixel resolution of 5 and 10 mm, and a kernel size of 30, 60 and 90 pixels leads to the best benthic substrate classification (highest overall accuracy). At the class scale, producer's (PA) and user's (UA) accuracy showed that big boulders and field material were correctly distinguished. Small boulders and cobbles, having similar sizes, showed the lowest classification performances. This classification methodology provides new perspectives for mesoscale (100 m2 to 1 km2) semi-automatic mapping of the fine resolution (1 cm) relationship between benthic organisms and their substrate.

The dynamics and mechanism of JP-10 thermal oxidative deposition

High-energy–density (HED) fuels (like JP-10) have drawn more and more attention for volume-limited aerospace vehicles to extend the flight range and/or increase the payload. However, their thermal oxidation and deposition performance are still ambiguous. In this work, the dynamics and mechanism of JP-10 thermal oxidative deposition were investigated by the jet fuel thermal oxidation stability tester (JFTOT), ellipsometric tube rater (ETR) and comprehensive two-dimensional gas chromatography coupled with mass spectrometry and flame ionization detector (GC × GC–MS/FID). The results reveal that both the peak deposit thickness and total deposits volume of JP-10 increase with increasing temperature with the apparent deposition activation energy of approximately 71.2 kJ/mol. The deposits on the tube surface have globular structure, and they undergo particle formation, growth, adherence, agglomeration and size reduction during thermal stress. The fine characterizations of liquid products after JFTOT test confirm that the thermal oxidative deposition of JP-10 occurs via a series of radical reactions, such as oxidative decomposition and radical addition, which will be significantly accelerated at higher temperature. Importantly, the stability of alkoxy radical seems to be a significant factor affecting the thermal oxidation stability of HED fuels. This work may shed light on the possible deposition mechanism of HED fuels and will guide the rational design of HED fuels with high thermal oxidation stability.

Fine Mapping of Two Interacting Loci for Transmission Ratio Distortion in Rice (Oryza sativa L.)

Transmission ratio distortion (TRD) denotes the observed allelic or genotypic frequency deviation from the expected Mendelian segregation ratios in the offspring of a heterozygote. TRD can severely hamper gene flow between and within rice species. Here, we report the fine mapping and characterization of two loci (TRD4.1 and TRD4.2) for TRD using large F2 segregating populations, which are derived from rice chromosome segment substitution lines, each containing a particular genomic segment introduced from the japonica cultivar Nipponbare (NIP) into the indica cultivar Zhenshan (ZS97). The two loci exhibited a preferential transmission of ZS97 alleles in the derived progeny. Reciprocal crossing experiments using near-isogenic lines harboring three different alleles at TRD4.1 suggest that the gene causes male gametic selection. Moreover, the transmission bias of TRD4.2 was diminished in heterozygotes when they carried homozygous TRD4.1ZS97. This indicates an epistatic interaction between these two loci. TRD4.2 was mapped into a 35-kb region encompassing one candidate gene that is specifically expressed in the reproductive organs in rice. These findings broaden the understanding of the genetic mechanisms of TRD and offer an approach to overcome the barrier of gene flow between the subspecies in rice, thus facilitating rice improvement by introgression breeding.

Efficient and universal characterization of atomic structures through a topological graph order parameter

A graph-based order parameter, based on the topology of the graph itself, is introduced for the characterization of atomistic structures. The order parameter is universal to any material/chemical system and is transferable to all structural geometries. Four sets of data are used to validate both the generalizability and accuracy of the algorithm: (1) liquid lithium configurations spanning up to 300 GPa, (2) condensed phases of carbon along with nanotubes and buckyballs at ambient and high temperature, (3) a diverse set of aluminum configurations including surfaces, compressed and expanded lattices, point defects, grain boundaries, liquids, nanoparticles, all at nonzero temperatures, and (4) eleven niobium oxide crystal phases generated with ab initio molecular dynamics. We compare our proposed method to existing, state-of-the-art methods for the cases of aluminum and niobium oxide. Our order parameter uniquely classifies every configuration and outperforms all studied existing methods, opening the door for its use in a multitude of complex application spaces that can require fine structure-level characterization of atomistic graphs.

Fine Mapping and Characterization of a Major Gene Responsible for Chlorophyll Biosynthesis in Brassica napus L.

Rapeseed (Brassica napus L.) is mainly used for oil production and industrial purposes. A high photosynthetic efficiency is the premise of a high yield capable of meeting people’s various demands. Chlorophyll-deficient mutants are ideal materials for studying chlorophyll biosynthesis and photosynthesis. In a previous study, we obtained the mutant yl1 for leaf yellowing throughout the growth period by ethyl methanesulfonate mutagenesis of B. napus. A genetic analysis showed that the yl1 chlorophyll-deficient phenotype was controlled by one incompletely dominant gene, which was mapped on chromosome A03 by a quantitative trait loci sequencing analysis and designated as BnA03.Chd in this study. We constructed an F2 population containing 5256 individuals to clone BnA03.Chd. Finally, BnA03.Chd was fine-mapped to a 304.7 kb interval of the B. napus ‘ZS11’ genome containing 58 annotated genes. Functional annotation, transcriptome, and sequence variation analyses confirmed that BnaA03g0054400ZS, a homolog of AT5G13630, was the most likely candidate gene. BnaA03g0054400ZS encodes the H subunit of Mg-chelatase. A sequence analysis revealed a single-nucleotide polymorphism (SNP), causing an amino-acid substitution from glutamic acid to lysine (Glu1349Lys). In addition, the molecular marker BnaYL1 was developed based on the SNP of BnA03.Chd, which perfectly cosegregated with the chlorophyll-deficient phenotype in two different F2 populations. Our results provide insight into the molecular mechanism underlying chlorophyll synthesis in B. napus.

Characterizing stream morphological features important for fish habitat using airborne laser scanning data

Understanding changes in salmonid populations and their habitat is a critical issue given changing climate, their importance as a keystone species, and their cultural significance. Terrain features such as slope, gradient, and morphology, as well as forest structure attributes including canopy cover, height, and presence of on ground coarse wood, all influence the quality and quantity of salmonid habitat in forested ecosystems. The increasing availability of Airborne Laser Scanning (ALS) data for forest applications offers an opportunity to utilize these data for assessing the quality and quantity of habitat, which is often costly and difficult to characterize. ALS data provides detailed and accurate Digital Elevation Models (DEMs) under forest canopies, which in turn enable the characterization of detailed stream networks, as well as stream and terrain attributes important to salmonids. At the Nahmint watershed on Vancouver Island, British Columbia, Canada, we sampled six, 200 m long stream reaches, describing a range of terrain and stream features following standard data collection protocols. Our objective in this research was to use ALS data to estimate three attributes from the 3D point cloud and DEM that are known to be important for salmonids, including bankfull width,instream wood and discrete stream morphological units. Results indicate that ALS-based estimates had strong, significant, correlations with field-measured attributes (with Pearson's correlation of 0.80 and 0.81 for bankfull width and instream wood, respectively). Bankfull width was slightly underestimated using the ALS data (Bias = −1.01 m; MAD = 1.89 m; RMSD = 2.05 m) and 80% of instream wood pieces were detected. Using ALS-derived predictors in a Random Forest model, discrete stream morphological units (i.e. pools, riffles, glides, cascades) were classified with an overall accuracy of 85%, with pools having the highest user's class accuracy at 96%. Results presented herein indicate that ALS data can be used to provide a fine scale characterization of stream attributes that are required to identify salmonid habitat, providing critical information for sustainable forest management decision making, and providing a foundation for advanced salmonid habitat modeling.

Biomass derived Fe-N/C catalyst for efficiently catalyzing oxygen reduction reaction in both alkaline and neutral pH conditions

Fe-N/C is a promising oxygen reduction reaction (ORR) catalyst to substitute the current widely used precious metal platinum. Cost-effectively fabricating the Fe-N/C material with high catalytic activity and getting in-depth insight into the responsible catalytic site are of great significance. In this work, we proposed to use biomass, tea leaves waste, as the precursor to prepare ORR catalyst. By adding 5% FeCl3 (wt%) into tea precursor, the pyrolysis product (i.e., 5%Fe-N/C) exhibited an excellent four-electron ORR activity, whose onset potential was only 10 mV lower than that of commercial Pt/C. The limiting current density of 5%Fe-N/C (5.75 mA/cm2) was even higher than Pt/C (5.44 mA/cm2). Compared with other biomass or metal organic frameworks derived catalysts, 5%Fe-N/C showed similar ORR activity. Also, both the methanol tolerance and material stability performances of as-prepared 5%Fe-N/C catalyst were superior to that of Pt/C. X-ray adsorption fine structure characterization revealed that the FeN4O2 might be the possible catalytic site. An appropriate amount of iron chloride addition not only facilitated catalytic site formation, but also enhanced material conductivity and reaction kinetics. The results of this work may be useful for the Fe based transition metal ORR catalyst design and application.

Study on Fine Characterization Method of Super-stripping Line of Sha 2 Formation in Bonan Area of Jiyang Depression

Study on Fine Characterization Method of Super-stripping Line of Sha 2 Formation in Bonan Area of Jiyang Depression

Correlation between Flotation and Rheology of Fine Particle Suspensions

This paper summarizes and discusses previous investigations into the correlation between the rheology and flotation process of fine particle suspensions. This summary provides a better understanding of the challenges and current status of this subject and useful feedback based on the revision of relevant theories and practical implications for fine particle characterization and processing. Such processes include the sustainable beneficiation of complex ores and wastes for valuable material extraction and the segregation of toxic substances. For example, there has been increasing demand for the beneficiation of complex ores often carrying the values (e.g., critical raw materials) in fine grains, due to the noticeable decrease in the accessibility of high-grade and easily extractable ores. To maintain the sustainable use of limited resources, the effective beneficiation of complex ores is urgently required. It can be successfully achieved only with selective particle/mineral dispersion/liberation and the assistance of mineralogical and fine particle characterization including a proper understanding of the rheological behavior of complex ores in the context of fine particle separation/processing. In correlating flotation with suspension rheology, previous works were summarized and we found that the modeling of their correlations as well as comprehensive contributions of pulp and froth rheology on flotation performance have been studied very limitedly, and comprehensive developments in these aspects are thus strongly suggested.

ELISA-Based Analysis Reveals an Anti-SARS-CoV-2 Protein Immune Response Profile Associated with Disease Severity

Since the start of the COVID-19 pandemic, many studies have investigated the humoral response to SARS-CoV-2 during infection. Studies with native viral proteins constitute a first-line approach to assessing the overall immune response, but small peptides are an accurate and valuable tool for the fine characterization of B-cell epitopes, despite the restriction of this approach to the determination of linear epitopes. In this study, we used ELISA and peptides covering a selection of structural and non-structural SARS-CoV-2 proteins to identify key epitopes eliciting a strong immune response that could serve as a biological signature of disease characteristics, such as severity, in particular. We used 213 plasma samples from a cohort of patients well-characterized clinically and biologically and followed for COVID-19 infection. We found that patients developing severe disease had higher titers of antibodies mapping to multiple specific epitopes than patients with mild to moderate disease. These data are potentially important as they could be used for immunological profiling to improve our knowledge of the quantitative and qualitative characteristics of the humoral response in relation to patient outcome.

Comparative elemental characterization of atmospheric fine and coarse PM samples by PIXE and ICP-MS/MS: results from a one-year measurement campaign in a coal-powered thermal power plant city

Method matters! Precise elemental characterization of PM is crucial to air quality studies. Here, we compared the elemental concentrations of fine and coarse PM, quantified by both PIXE and ICP-MS/MS in a thermal power plant affected city.

Quantifying the Fine Particle Characterization and Source Origins by Applying Positive Matrix Factorization Based on a Regional Background Site in the Yangtze River Delta Region, China

Quantifying the Fine Particle Characterization and Source Origins by Applying Positive Matrix Factorization Based on a Regional Background Site in the Yangtze River Delta Region, China