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At least 289 records · Page 16

Evolutionary Origins of Metabolic Reprogramming in Cancer

Metabolic changes that facilitate tumor growth are one of the hallmarks of cancer. These changes are not specific to tumors but also take place during the physiological growth of tissues. Indeed, the cellular and tissue mechanisms present in the tumor have their physiological counterpart in the repair of tissue lesions and wound healing. These molecular mechanisms have been acquired during metazoan evolution, first to eliminate the infection of the tissue injury, then to enter an effective regenerative phase. Cancer itself could be considered a phenomenon of antagonistic pleiotropy of the genes involved in effective tissue repair. Cancer and tissue repair are complex traits that share many intermediate phenotypes at the molecular, cellular, and tissue levels, and all of these are integrated within a Systems Biology structure. Complex traits are influenced by a multitude of common genes, each with a weak effect. This polygenic component of complex traits is mainly unknown and so makes up part of the missing heritability. Here, we try to integrate these different perspectives from the point of view of the metabolic changes observed in cancer.

60 APPLIED LIFE SCIENCES↗

Temporal dynamics of the multi-omic response to endurance exercise training

Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood. Here, the Molecular Transducers of Physical Activity Consortium profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository (https://motrpac-data.org/).

59 BASIC BIOLOGICAL SCIENCES↗

Localized growth and remodelling drives spongy mesophyll morphogenesis

The spongy mesophyll is a complex, porous tissue found in plant leaves that enables carbon capture and provides mechanical stability. Unlike many other biological tissues, which remain confluent throughout development, the spongy mesophyll must develop from an initially confluent tissue into a tortuous network of cells with a large proportion of intercellular airspace. How the airspace in the spongy mesophyll develops while the tissue remains mechanically stable is unknown. Here, we use computer simulations of deformable polygons to develop a purely mechanical model for the development of the spongy mesophyll tissue. By stipulating that cell wall growth and remodelling occurs only near void space, our computational model is able to recapitulate spongy mesophyll development observed in Arabidopsis thaliana leaves. We find that robust generation of pore space in the spongy mesophyll requires a balance of cell growth, adhesion, stiffness and tissue pressure to ensure cell networks become porous yet maintain mechanical stability. The success of this mechanical model of morphogenesis suggests that simple physical principles can coordinate and drive the development of complex plant tissues like the spongy mesophyll.

Science & Technology - Other Topics↗

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testisspecific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

59 BASIC BIOLOGICAL SCIENCES↗

A microCT-based platform to quantify drug targeting

Abstract Background Heterotopic ossification (HO) is a frequent and debilitating complication of traumatic musculoskeletal injuries and orthopedic procedures. Prophylactic dosing of botulinum toxin type A (BTxA) holds potential as a novel treatment option if accurately distributed throughout soft-tissue volumes where protection is clinically desired. We developed a high-resolution, microcomputed tomography (microCT)-based imaging strategy to assess drug distribution and validated this platform by quantifying distribution achieved via a prototype delivery system versus a single-bolus injection. Methods We injected an iodine-containing contrast agent (iodixanol 320 mg I/mL) into dissected rabbit musculature followed by microCT imaging and analysis. To contrast the performance of distributed versus bolus injections, a three-dimensional (3D) 64-cm 3 -printed soft-tissue holder was developed. A centered 2-cm 3 volume of interest (VOI) was targeted with a single-bolus injection or an equal volume distributed injection delivered via a 3D-printed prototype. VOI drug coverage was quantified as a percentage of the VOI volume that was < 1.0 mm from the injected fluid. Results The microCT-based approach enabled high-resolution quantification of injection distribution within soft tissue. The distributed dosing prototype provided significantly greater tissue coverage of the targeted VOI (72 ± 3%, mean ± standard deviation) when compared to an equal volume bolus dose (43 ± 5%, p = 0.031) while also enhancing the precision of injection targeting. Conclusions A microCT-based imaging technique precisely quantifies drug distribution within a soft-tissue VOI, providing a path to overcome a barrier for clinical translation of prophylactic inhibition of HO by BTxA. Relevance statement This platform will facilitate rapid optimization of injection parameters for clinical devices used to effectively and safely inhibit the formation of heterotopic ossification. Key points • MicroCT provides high-resolution quantification of soft-tissue drug distribution. • Distributed dosing is required to maximize soft-tissue drug coverage. • Imaging platform will enable rapid screening of 3D-printed drug distribution prototypes. Graphical Abstract

Ausk, Brandon J. (ORCID:0000000335338303)↗

Data for Identifying the best high-biomass sorghum hybrids based on biomass yield potential and feedstock quality affected by nitrogen fertility management under various environments

Data were collected from agronomy fields in Urbana and Ewing, IL, during the 2022 and 2023 growing seasons. The dataset includes dry biomass yield, nitrogen, phosphorus, and potassium concentrations and removals, and chemical composition elements (cellulose, hemicellulose, lignin, and soluble fractions) for 13 high-biomass sorghum hybrids. data_sharing.xlsx contains 20 columns and 104 rows. Below is the explanation of all variables in the file: Year: 2022; 2023 Location: Urbana, IL; Ewing, IL N rate (kg-N/ha): 0; 112 Hybrid #: H1-H13 Pedigree: Pedigree for 13 hybrids Dry biomass yield (Mg/ha): Aboveground dry biomass yield N (g/kg): Nitrogen concentration in plant tissue P (g/kg): Phosphorus concentration in plant tissue K (g/kg): Potassium concentration in plant tissue N (kg/ha): Nitrogen removal by aboveground biomass P (kg/ha): Phosphorus removal by aboveground biomass K (kg/ha): Potassium removal by aboveground biomass Cellulose (g/kg): Cellulose concentration in plant tissue Hemicellulose (g/kg): Hemicellulose concentration in plant tissue Lignin (g/kg): Lignin concentration in plant tissue Soluble (g/kg): Soluble concentration in plant tissue Cellulose (Mg/ha): Cellulose content in aboveground biomass Hemicellulose (Mg/ha): Hemicellulose content in aboveground biomass Lignin (Mg/ha): Lignin content in aboveground biomass Soluble (Mg/ha): Soluble content in aboveground biomass

environmental adaptability↗

Identification of integrated proteomics and transcriptomics signature of alcohol-associated liver disease using machine learning

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

60 APPLIED LIFE SCIENCES↗

Systems, devices, and methods for contact measurement and modulation of material properties

Materials and devices are provided for the sensing and manipulation of biomechanical and physiochemical properties of tissues or tissue surfaces. Examples of use include soft tissues such as skin or adipose tissues or more dense tissues such as muscle or heart or dense tissues such as bone. The materials and devices provide for in vivo measurements of biomechanical properties at the tissue surface, e.g. near surface regions of the epidermis or dermis or underlying structures. The devices can be non-invasive and/or non-destructive to the material and, especially for the biomaterials, can be biocompatible and/or biodegradable. The materials and devices can use ultrathin, stretchable networks of mechanical actuators and sensors constructed with nanoribbons of piezoelectric materials.

Dagdeviren, Canan↗

An effective QWBA/UHPLC-MS/tissue punch approach: solving a pharmacokinetic issue via quantitative Met-ID

Methods to provide absolute quantitation of the administered drug and corresponding metabolites in tissue in a spatially resolved manner is a challenging but much needed necessity in pharmaceutical research. Quantitative whole-body autoradiography (QWBA) after a single-dose intravenous (3 mg/kg) and extravascular (30 mg/kg) administrations of an in vitro metabolically stable test compound (structure not reported here) indicated quick tissue distribution and excretion. Good bioavailability and short in vivo half-lives were determined formerly for the same test compound. For closing gaps in the understanding of pharmacokinetic data and in vitro results, radioactive hot spots on whole-body tissue sections had been profiled. Punches from selected tissue regions containing high radioactivity in the tissue sections previously analyzed by QWBA were extracted by a highly organic solvent and analyzed without any consecutive sample preparation step, applying ultra high performance liquid chromatography-mass spectrometry (UHPLC-MS) and off-line radioanalysis to maximize signal levels for metabolite identification and profiling. The analysis revealed that the test compound was metabolized intensively by phase I reactions in vivo and the metabolites formed were excreted in bile and in urine. The predominant metabolites showed abundant signal intensities both by MS and by radioanalysis but the MS signal intensities generally underestimated the real abundances of metabolites relative to the unchanged drug. In this work we illustrate that maximizing the sensitivity of tissue punch radioanalysis and the combination with UHPLC-MS leads to a better insight of pharmacokinetic processes by providing quantitative data with high molecular selectivity.

60 APPLIED LIFE SCIENCES↗

Advanced Methodology and Preliminary Measurements of Molecular and Mechanical Properties of Heart Valves under Dynamic Strain

Mammalian heart valves are soft tissue assemblies with multi-scale material properties. This is because they are constructs comprising both muscle and non-contractile extracellular matrix proteins (such as collagens and proteoglycans) and transition regions where one form of tissue structure becomes another, significantly different form. The leaflets of the mitral and tricuspid valves are connected to chordae tendinae which, in turn, bind through papillary muscles to the cardiac wall of the ventricle. The transition regions between these tissue subsets are complex and diffuse. Their material composition and mechanical properties have not been previously described with both micro and nanoscopic data recorded simultaneously, as reported here. Annotating the mechanical characteristics of these tissue transitions will be of great value in developing novel implants, improving the state of the surgical simulators and advancing robot-assisted surgery. We present here developments in multi-scale methodology that produce data that can relate mechanical properties to molecular structure using scanning X-ray diffraction. We correlate these data to corresponding tissue level (macro and microscopic) stress and strain, with particular emphasis on the transition regions and present analyses to indicate points of possible failure in these tissues.

valve failure↗

Nematic cell alignment directs calcium waves in an epithelial monolayer

Tissues rely on supracellular signals to coordinate their cells over a long range. Two such tissuescale cues are calcium waves and patterns of cell-cell alignment or nematic order. During wound healing, for example, calcium waves propagate across a tissue to guide directed cell migration and reepithelialization. Defects in long-range cell-cell alignment, or nematic orientation, can act to localize morphogenetic events in a tissue. Although these two cues have been considered in isolation, we demonstrate a relationship in epithelial tissue between long-range calcium signaling and the cell’s nematic order: The speed of a wound-induced calcium wave depends monotonically on the angle between the wave vector and cell axis, with maximal wave speed occurring perpendicular to the tissue’s orientation. Including anisotropic di↵usive coupling between cells in a canonical reactiondi↵usion model recapitulates our measured calcium wave dynamics. Our model demonstrates how orientation defects can desynchronize information propagation across a tissue. A calcium wave front is bent around nematic defects, therefore cells the same distance from a wound can receive the calcium signal at di↵erent times. Our work elucidates how spatial patterns in global cell alignment can control collective communication via calcium signaling during development, wound healing, and disease.

Winterstrain, Annemarie C. [Brandeis University, W↗

Investigating the FLASH Effect in a Rat Brain Organotypic Model With a Novel High-Energy Electron Beam

Ultrahigh dose rate (FLASH) radiation therapy is reported to reduce normal tissue toxicity while maintaining tumor control; however, mechanism(s) remain obscure. To study FLASH mechanisms in brain tissue, we developed a novel experimental platform featuring a specialized high-energy electron linear accelerator, High Intensity Gamma Ray Source (HIGS), paired with an organotypic ex vivo brain metastasis model. We varied interpulse spacing to modulate the mean dose rate (MDR) of our unique 35 MeV electron beam, while maintaining extremely high instantaneous dose rate (IDR). We characterized dosimetry and targeting accuracy of the FLASH beam with film dosimetry. We combined this FLASH beam with an organotypic rat brain slice/breast carcinoma coculture model of brain metastasis to assess effects on normal and neoplastic tissues. Live-cell and bioluminescence imaging demonstrated cancer cell growth effects, whereas normal tissue responses and immune activation were assessed using live-cell imaging, cytokine profiles, and confocal microscopy. Here, we performed comparison experiments with 20 MeV electrons from a Varian clinical linear accelerator (VCLA) using conventional dose rates. The highest IDR of the FLASH beam to date was 20.7 ± 0.6 MGy/s, with maximum MDR of 20.7 MGy/s delivered in 1 pulse of 1 µs duration. Beam targeting was accurate to <1 mm and reproducible. HIGS-FLASH and VCLA dose rates equivalently decreased cancer cell growth. HIGS-FLASH irradiation significantly increased tumor necrosis factor α and fractalkine levels and confocal microscopy revealed distinct changes in microglial morphology slices suggesting microglia activation. Our novel experimental platform produces extremely high dose rates and rapid normal/neoplastic tissue readouts for mechanistic research into the effects of FLASH radiation in the brain. HIGS-FLASH irradiation induces comparable cancer cell growth inhibition but differential effects on cytokines and microglial morphology, suggesting that acute innate immune responses may be involved in FLASH normal tissue effects in the brain.

Kay, Tyler V. [Duke University, Durham, NC (United↗

Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10 × 10 –6 ) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61 × 10 –6 ) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25 × 10 –6 ) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in a TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a GWAS. Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability of >0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.

60 APPLIED LIFE SCIENCES↗

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated $\underline{w}et$ $\underline{c}ollection$ of single microscale tissue voxels and $\underline{S}urfactant$$-assisted$ $\underline{O}ne$-$\underline{P}ot$ voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of a single voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of ~900 and ~4,600 proteins for single voxels at 20 µm × 20 µm × 10 µm (close to single cells) and 200 µm × 200 µm × 10 µm (~100 cells) from fresh frozen human spleen tissue, respectively. 100s-1000s of protein signatures were spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. To evaluate its broad applicability, we applied wcSOP-MS to two commonly accessible, OCT-embedded and FFPE, human archived tissues. It enabled to identify spatially resolved proteome changes and enriched pathways between diseased (breast cancer tumor or AD amyloid plaque) and adjacent normal regions. Antibody-based CODEX and IHC imaging validated label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

59 BASIC BIOLOGICAL SCIENCES↗

Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation

A comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3' RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of timeseries transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. Our data confirm that DroNcseq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.

59 BASIC BIOLOGICAL SCIENCES↗

Specific absorbed fractions for a revised series of the UF/NCI pediatric reference phantoms: internal photon sources

Assessment of radiation absorbed dose to internal organs of the body from the intake of radionuclides, or in the medical setting through the injection of radiopharmaceuticals, is generally performed based upon reference biokinetic models or patient imaging data, respectively. Biokinetic models estimate the time course of activity localized to source organs. The time-integration of these organ activity profiles are then scaled by the radionuclide S-value, which defines the absorbed dose to a target tissue per nuclear transformation in various source tissues. S-values are computed using established nuclear decay information (particle energies and yields), and a parameter termed the specific absorbed fraction (SAF). The SAF is the ratio of the absorbed fraction—fraction of particle energy emitted in the source tissue that is deposited in the target tissue—and the target organ mass. While values of the SAF may be computed using patient-specific or individual-specific anatomic models, they have been more widely available through the use of computational reference phantoms. In this study, we report on an extensive series of photon SAFs computed in a revised series of the University of Florida and the National Cancer Institute pediatric reference phantoms which have been modified to conform to the specifications embodied in the ICRP reference adult phantoms of Publication 110 (e.g. organs modeled, organ ID numbers, blood contribution to elemental compositions). Following phantom anatomical revisions, photon radiation transport simulations were performed using MCNPX v2.7 in each of the ten phantoms of the series—male and female newborn, 1 year old, 5 year old, 10 year old, and 15 year old—for 60 different tissues serving as source and/or target regions. A total of 25 photon energies were considered from 10 keV to 10 MeV along a logarithm energy grid. Detailed analyses were conducted of the relative statistical errors in the Monte Carlo target tissue energy deposition tallies at low photon energies and over all energies for source–target combinations at large intra-organ separation distances. Based on these analyses, various data smoothing algorithms were employed, including multi-point weighted data smoothing, and log–log interpolation at low energies (1 keV and 5 keV) using limiting SAF values based upon target organ mass to bound the interpolation interval. The final dataset is provided in a series of ten electronic supplemental files in MS Excel format. Finally, the results of this study were further used as the basis for assessing the radiative component of internal electron source SAFs as described in our companion paper (Schwarz et al 2021) for this same pediatric phantom series.

61 RADIATION PROTECTION AND DOSIMETRY↗

Specific absorbed fractions for a revised series of the UF/NCI pediatric reference phantoms: internal electron sources

Assessment of radiation absorbed dose to internal organs of the body from the intake of radionuclides, or in the medical setting through the injection of radiopharmaceuticals, is generally performed based upon reference biokinetic models or patient imaging data, respectively. Biokinetic models estimate the time course of activity localized to source organs. The time-integration of these organ activity profiles are then scaled by the radionuclide S-value, which defines the absorbed dose to a target tissue per nuclear transformation in various source tissues. S-values are computed using established nuclear decay information (particle energies and yields), and a parameter termed the specific absorbed fraction (SAF). The SAF is the ratio of the absorbed fraction—fraction of particle energy emitted in the source tissue that is deposited in the target tissue—and the target organ mass. While values of the SAF may be computed using patient-specific or individual-specific anatomic models, they have been more widely available through the use of computational reference phantoms. In this study, we report on an extensive series of photon SAFs computed in a revised series of the University of Florida and the National Cancer Institute pediatric reference phantoms which have been modified to conform to the specifications embodied in the ICRP reference adult phantoms of Publication 110 (e.g. organs modeled, organ ID numbers, blood contribution to elemental compositions). Following phantom anatomical revisions, photon radiation transport simulations were performed using MCNPX v2.7 in each of the ten phantoms of the series—male and female newborn, 1 year old, 5 year old, 10 year old, and 15 year old—for 60 different tissues serving as source and/or target regions. A total of 25 photon energies were considered from 10 keV to 10 MeV along a logarithm energy grid. Detailed analyses were conducted of the relative statistical errors in the Monte Carlo target tissue energy deposition tallies at low photon energies and over all energies for source–target combinations at large intra-organ separation distances. Based on these analyses, various data smoothing algorithms were employed, including multi-point weighted data smoothing, and log–log interpolation at low energies (1 keV and 5 keV) using limiting SAF values based upon target organ mass to bound the interpolation interval. The final dataset is provided in a series of ten electronic supplemental files in MS Excel format. Finally, the results of this study were further used as the basis for assessing the radiative component of internal electron source SAFs as described in our companion paper (Schwarz et al 2021) for this same pediatric phantom series.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evolutionary analysis of the LORELEI gene family in plants reveals regulatory subfunctionalization

Abstract A signaling complex comprising members of the LORELEI (LRE)-LIKE GPI-anchored protein (LLG) and Catharanthus roseus RECEPTOR-LIKE KINASE 1-LIKE (CrRLK1L) families perceive RAPID ALKALINIZATION FACTOR (RALF) peptides and regulate growth, reproduction, immunity, and stress responses in Arabidopsis (Arabidopsis thaliana). Genes encoding these proteins are members of multigene families in most angiosperms and could generate thousands of signaling complex variants. However, the links between expansion of these gene families and the functional diversification of this critical signaling complex as well as the evolutionary factors underlying the maintenance of gene duplicates remain unknown. Here, we investigated LLG gene family evolution by sampling land plant genomes and explored the function and expression of angiosperm LLGs. We found that LLG diversity within major land plant lineages is primarily due to lineage-specific duplication events, and that these duplications occurred both early in the history of these lineages and more recently. Our complementation and expression analyses showed that expression divergence (i.e. regulatory subfunctionalization), rather than functional divergence, explains the retention of LLG paralogs. Interestingly, all but one monocot and all eudicot species examined had an LLG copy with preferential expression in male reproductive tissues, while the other duplicate copies showed highest levels of expression in female or vegetative tissues. The single LLG copy in Amborella trichopoda is expressed vastly higher in male compared to in female reproductive or vegetative tissues. We propose that expression divergence plays an important role in retention of LLG duplicates in angiosperms.

Plant Sciences↗