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At least 1,189 records · Page 66

VRC34-Antibody Lineage Development Reveals How a Required Rare Mutation Shapes the Maturation of a Broad HIV-Neutralizing Lineage

Rare mutations have been proposed to restrict the development of broadly neutralizing antibodies against HIV-1, but this has not been explicitly demonstrated. We hypothesized that such rare mutations might be identified by comparing broadly neutralizing and non-broadly neutralizing branches of an antibody-developmental tree. Because sequences of antibodies isolated from the fusion peptide (FP)-targeting VRC34-antibody lineage suggested it might be suitable for such rare mutation analysis, we carried out next-generation sequencing (NGS) on B cell transcripts from donor N123, the source of the VRC34 lineage, and functionally and structurally characterized inferred intermediates along broadly neutralizing and poorly neutralizing developmental branches. The broadly neutralizing VRC34.01 branch required the rare heavy-chain mutation Y33P to bind FP, whereas the early bifurcated VRC34.05 branch did not require this rare mutation and evolved less breadth. Our results demonstrate how a required rare mutation can restrict development and shape the maturation of a broad HIV-1-neutralizing antibody lineage.

59 BASIC BIOLOGICAL SCIENCES↗

A new version of the RDP (Ribosomal Database Project)

The Ribosomal Database Project (RDP-II), previously described by Maidak et al. [ Nucleic Acids Res. (1997), 25, 109-111], is now hosted by the Center for Microbial Ecology at Michigan State University. RDP-II is a curated database that offers ribosomal RNA (rRNA) nucleotide sequence data in aligned and unaligned forms, analysis services, and associated computer programs. During the past two years, data alignments have been updated and now include >9700 small subunit rRNA sequences. The recent development of an ObjectStore database will provide more rapid updating of data, better data accuracy and increased user access. RDP-II includes phylogenetically ordered alignments of rRNA sequences, derived phylogenetic trees, rRNA secondary structure diagrams, and various software programs for handling, analyzing and displaying alignments and trees. The data are available via anonymous ftp (ftp.cme.msu. edu) and WWW (http://www.cme.msu.edu/RDP). The WWW server provides ribosomal probe checking, approximate phylogenetic placement of user-submitted sequences, screening for possible chimeric rRNA sequences, automated alignment, and a suggested placement of an unknown sequence on an existing phylogenetic tree. Additional utilities also exist at RDP-II, including distance matrix, T-RFLP, and a Java-based viewer of the phylogenetic trees that can be used to create subtrees.

Non-NASA Center↗

Transcriptome sequencing of three Pseudo-nitzschia species reveals comparable gene sets and the presence of Nitric Oxide Synthase genes in diatoms

Diatoms are among the most diverse eukaryotic microorganisms on Earth, they are responsible for a large fraction of primary production in the oceans and can be found in different habitats. Pseudo-nitzschia are marine planktonic diatoms responsible for blooms in coastal and oceanic waters. We analyzed the transcriptome of three species, Pseudo-nitzschia arenysensis, Pseudo-nitzschia delicatissima and Pseudo-nitzschia multistriata, with different levels of genetic relatedness. These species have a worldwide distribution and the last one produces the neurotoxin domoic acid. We were able to annotate about 80% of the sequences in each transcriptome and the analysis of the relative functional annotations allowed comparison of the main metabolic pathways, pathways involved in the biosynthesis of isoprenoids (MAV and MEP pathways) and pathways putatively involved in domoic acid synthesis. The search for homologous transcripts among the target species and other congeneric species resulted in the discovery of a sequence annotated as Nitric Oxide Synthase (NOS), found uniquely in Pseudo-nitzschia multistriata. The predicted protein product contained all the domains of the canonical metazoan sequence. Putative NOS sequences were found in other available diatom datasets, supporting a role for nitric oxide as signaling molecule in this group of microalgae.

59 BASIC BIOLOGICAL SCIENCES↗

A Search for Vector Magnetic Field Variations Associated with the M-Class Flares of 1991 June 10 in AR 6659

A careful analysis of a 6-hour time sequence of vector magnetograms of AR 6659, observed on 1991 June 10 with the MSFC vector magnetograph, has revealed only minor changes in the vector magnetic field azimuths in the vicinity of two M-class flares, and the association of these changes with the flares is not unambiguous. In this paper we present our analysis of the data which includes comparison of vector magnetograms prior to and during the flares, calculation of distributions of the rms variation of the azimuth at each pixel in the field of view of the active region, and examination of the variation with time of the azimuths at every pixel covered by the main flare emissions as observed with the H-alpha telescope coaligned with the vector magnetograph. We also present results of an analysis of evolutionary changes in the azimuth over the field of view of the active region.

Hagyard, Mona J.↗

A Search for Vector Magnetic Field Variations Associated with the M-Class Flares of 1991 June 10 in AR 6659

A careful analysis of a 6-hour time sequence of vector magnetograms of AR 6659, observed on 1991 June 10 with the MSFC vector magnetograph, has revealed only minor changes in the vector magnetic field azimuths in the vicinity of two M-class flares, and the association of these changes with the flares is not unambiguous. In this paper we present our analysis of the data which includes comparison of vector magnetograms prior to and during the flares, calculation of distributions of the rms variation of the azimuth at each pixel in the field of view of the active region, and examination of the variation with time of the azimuths at every pixel covered by the main flare emissions as observed with the H-alpha telescope coaligned with the vector magnetograph. We also present results of an analysis of evolutionary changes in the azimuth over the field of view of the active region.

Hagyard, Mona J.↗

Single-base-pair discrimination of terminal mismatches by using oligonucleotide microarrays and neural network analyses

The effects of single-base-pair near-terminal and terminal mismatches on the dissociation temperature (T(d)) and signal intensity of short DNA duplexes were determined by using oligonucleotide microarrays and neural network (NN) analyses. Two perfect-match probes and 29 probes having a single-base-pair mismatch at positions 1 to 5 from the 5' terminus of the probe were designed to target one of two short sequences representing 16S rRNA. Nonequilibrium dissociation rates (i.e., melting profiles) of all probe-target duplexes were determined simultaneously. Analysis of variance revealed that position of the mismatch, type of mismatch, and formamide concentration significantly affected the T(d) and signal intensity. Increasing the concentration of formamide in the washing buffer decreased the T(d) and signal intensity, and it decreased the variability of the signal. Although T(d)s of probe-target duplexes with mismatches in the first or second position were not significantly different from one another, duplexes with mismatches in the third to fifth positions had significantly lower T(d)s than those with mismatches in the first or second position. The trained NNs predicted the T(d) with high accuracies (R(2) = 0.93). However, the NNs predicted the signal intensity only moderately accurately (R(2) = 0.67), presumably due to increased noise in the signal intensity at low formamide concentrations. Sensitivity analysis revealed that the concentration of formamide explained most (75%) of the variability in T(d)s, followed by position of the mismatch (19%) and type of mismatch (6%). The results suggest that position of the mismatch at or near the 5' terminus plays a greater role in determining the T(d) and signal intensity of duplexes than the type of mismatch.

Non-NASA Center↗

Development of Computational Environmental Microbiome Workflows for the Laboratory and the International Space Station

Identification of microorganisms in the spaceflight environment is critical for crew health risk assessment on the International Space Station (ISS). Since 2017, nanopore sequencing technology has been used to support thein situ identification of microbial species during spaceflight. Beginning in 2018, a culture-independent, swab-to-sequencer method was implemented onboard the ISS to provide a more thorough insight of the ISS microbiome. Eliminating microbial culture enables identification of difficult-to-culture organisms, reduces risks associated with potentially pathogenic cultures, and could significantly reduce the time from sample-to-answer. However, this molecular-based approach generates large metagenomic datasets that require substantial computational resources for analysis. To process nanopore-generated sequencing data, the JSC Microbiology Laboratory established a bioinformatics workflow on Amazon EC2 under the security guidance of the NASA Science Managed Cloud Environment (SMCE).This resource allows for the development, testing, and accessing of computational tools for processing large and complex datasets. The work described here will address the downlinking of data from the ISS, the automated pipeline developed to identify targeted bacterial and fungal organisms, and the time from sampling onboard to microbial identification. The pipelines have been enhanced to address high and low biomass samples using optimization based on sample source (air, water, or surface) and type of collection (filter, colony, or swab).The resulting microbiome data can be assessed beyond microbial identifications to gain understanding toward population changes over time, potential selective environmental pressures, and evaluating correlations with a wide range of additional data sets. Metagenome analysis pipelines in development could allow for simultaneous identification of microbial species, gene function, and gene pathways present in the environment. Beyond the ground processing, the developed analysis pipeline is currently deployed onboard the ISS to allow for near real-time assessments of the ISS microbiome. This study serves as a critical foundation for exploration missions, where rapid microbiome analyses will be required.

G. Marie Sharp↗

Genomic analysis of six new Geobacillus strains reveals highly conserved carbohydrate degradation architectures and strategies

In this work we report the whole genome sequences of six new Geobacillus xylanolytic strains along with the genomic analysis of their capability to degrade carbohydrates. The six sequenced Geobacillus strains described here have a range of GC contents from 43.9% to 52.5% and clade with named Geobacillus species throughout the entire genus. We have identified a ~200 kb unique super-cluster in all six strains, containing five to eight distinct carbohydrate degradation clusters in a single genomic region, a feature not seen in other genera. The Geobacillus strains rely on a small number of secreted enzymes located within distinct clusters for carbohydrate utilization, in contrast to most biomass-degrading organisms which contain numerous secreted enzymes located randomly throughout the genomes. All six strains are able to utilize fructose, arabinose, xylose, mannitol, gluconate, xylan, and α-1,6-glucosides. The gene clusters for utilization of these seven substrates have identical organization and the individual proteins have a high percent identity to their homologs. The strains show significant differences in their ability to utilize inositol, sucrose, lactose, α-mannosides, α-1,4-glucosides and arabinan.

59 BASIC BIOLOGICAL SCIENCES↗

Development of peptoid-based ligands for the removal of cadmium from biological media

Cadmium poisoning poses a serious health concern due to cadmium's increasing industrial use, yet there is currently no recommended treatment. The selective coordination of cadmium in a biological environment—i.e. in the presence of serum ions, small molecules, and proteins—is a difficult task. To address this challenge, a combinatorial library of peptoid-based ligands has been evaluated to identify structures that selectively bind to cadmium in human serum with minimal chelation of essential metal ions. Eighteen unique ligands were identified in this screening procedure, and the binding affinity of each was measured using metal titrations monitored by UV-vis spectroscopy. To evaluate the significance of each chelating moiety, sequence rearrangements and substitutions were examined. Analysis of a metal–ligand complex by NMR spectroscopy highlighted the importance of particular residues. Depletion experiments were performed in serum mimetics and human serum with exogenously added cadmium. These depletion experiments were used to compare and demonstrate the ability of these peptoids to remove cadmium from blood-like mixtures. In one of these depletion experiments, the peptoid sequence was able to deplete the cadmium to a level comparable to the reported acute toxicity limit. Evaluation of the metal selectivity in buffered solution and in human serum was performed to verify minimal off-target binding. These studies highlight a screening platform for the identification of metal–ligands that are capable of binding in a complex environment. They additionally demonstrate the potential utility of biologically-compatible ligands for the treatment of heavy metal poisoning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cacao pod transcriptome profiling of seven genotypes identifies features associated with post-penetration resistance to Phytophthora palmivora

Abstract The oomycete Phytophthora palmivora infects the fruit of cacao trees ( Theobroma cacao ) causing black pod rot and reducing yields. Cacao genotypes vary in their resistance levels to P. palmivora , yet our understanding of how cacao fruit respond to the pathogen at the molecular level during disease establishment is limited. To address this issue, disease development and RNA-Seq studies were conducted on pods of seven cacao genotypes (ICS1, WFT, Gu133, Spa9, CCN51, Sca6 and Pound7) to better understand their reactions to the post-penetration stage of P. palmivora infection. The pod tissue- P. palmivora pathogen assay resulted in the genotypes being classified as susceptible (ICS1, WFT, Gu133 and Spa9) or resistant (CCN51, Sca6 and Pound7). The number of differentially expressed genes (DEGs) ranged from 1625 to 6957 depending on genotype. A custom gene correlation approach identified 34 correlation groups. De novo motif analysis was conducted on upstream promoter sequences of differentially expressed genes, identifying 76 novel motifs, 31 of which were over-represented in the upstream sequences of correlation groups and associated with gene ontology terms related to oxidative stress response, defense against fungal pathogens, general metabolism and cell function. Genes in one correlation group (Group 6) were strongly induced in all genotypes and enriched in genes annotated with defense-responsive terms. Expression pattern profiling revealed that genes in Group 6 were induced to higher levels in the resistant genotypes. An additional analysis allowed the identification of 17 candidate cis -regulatory modules likely to be involved in cacao defense against P. palmivora . This study is a comprehensive exploration of the cacao pod transcriptional response to P. palmivora spread after infection. We identified cacao genes, promoter motifs, and promoter motif combinations associated with post-penetration resistance to P. palmivora in cacao pods and provide this information as a resource to support future and ongoing efforts to breed P. palmivora -resistant cacao.

60 APPLIED LIFE SCIENCES↗

Establishing Data Analysis Pipeline for Bulk ATAC-Seq Datasets

We developed an analysis pipeline for transposase-accessible chromatin sequencing (ATAC-Seq) data derived from bulk samples, which brings together publicly available R packages in addition to command-line tools designed for analysis of bulk ATAC-Seq data and can be run on any computer running a Linux-like operating system such as Ubuntu or Apple OSX.

97 MATHEMATICS AND COMPUTING↗

Emerging Trends and Technologies Used for the Identification, Detection, and Characterisation of Plant-Parasitic Nematode Infestation in Crops

Accurate identification and estimation of the population densities of microscopic, soil-dwelling plant-parasitic nematodes (PPNs) are essential, as PPNs cause significant economic losses in agricultural production systems worldwide. This study presents a comprehensive review of emerging techniques used for the identification of PPNs, including morphological identification, molecular diagnostics such as polymerase chain reaction (PCR), high-throughput sequencing, meta barcoding, remote sensing, hyperspectral analysis, and image processing. Classical morphological methods require a microscope and nematode taxonomist to identify species, which is laborious and time-consuming. Alternatively, quantitative polymerase chain reaction (qPCR) has emerged as a reliable and efficient approach for PPN identification and quantification; however, the cost associated with the reagents, instrumentation, and careful optimisation of reaction conditions can be prohibitive. High-throughput sequencing and meta-barcoding are used to study the biodiversity of all tropical groups of nematodes, not just PPNs, and are useful for describing changes in soil ecology. Convolutional neural network (CNN) methods are necessary to automate the detection and counting of PPNs from microscopic images, including complex cases like tangled nematodes. Remote sensing and hyperspectral methods offer non-invasive approaches to estimate nematode infestations and facilitate early diagnosis of plant stress caused by nematodes and rapid management of PPNs. This review provides a valuable resource for researchers, practitioners, and policymakers involved in nematology and plant protection. It highlights the importance of fast, efficient, and robust identification protocols and decision-support tools in mitigating the impact of PPNs on global agriculture and food security.

Plant Sciences↗

Study of the Microbial Diversity of a Newly Discovered East Antarctic Freshwater Lake, L27C, and of a Perennially Ice-Covered Lake Untersee

The microbial communities that reside within freshwater lakes of Schirmacher and Untersee Oases in East Antarctica must cope with extreme conditions that may include cold temperature, annual freeze-thaw cycles, exposure to UV radiation, especially during the austral summer months, low light beneath thick ice-cover, followed by seasonal darkness. The objective of this study was to assess the microbial biodiversity and distribution from samples taken from two freshwater lakes (L27C and Lake Untersee) that were collected during the Tawani 2008 International Antarctic Expedition that conducted research in this region of Antarctica. L27C is a small, previously unreported lake residing 2 km WNW of Maitri Station at Schirmacher Oasis. Biodiversity and distribution of microorganisms within the lake were studied using both culture-independent and culture-dependent methodologies based upon the analysis of eubacterial 16S rRNA gene sequences. Lake Untersee, a perennially ice-covered, ultra-oligotrophic, lake in the Otto-von-Gruber-Gebirge (Gruber Mountains) of central Dronning Maud Land was also sampled and the microbial diversity was analyzed by eubacterial 16S rRNA gene sequences derived from pure cultures. Direct culturing of water samples from each lake on separate R2A growth medium exhibited a variety of microorganisms including: Janthinobacterium, Hymenobacter, Sphingamonas, Subtercola, Deinococcus, Arthrobacter, Flavobacterium, Polaromonas, Rhodoferax and Duganella. The evaluation of samples from L27C through culture-independent methodology identified a rich microbial diversity consisting of six different phyla of bacteria. The culture-independent analysis also displayed the majority of bacteria (56%) belonged to the Class gamma-proteobacteria within the phylum Proteobacteria. Within the Class gamma-proteobacteria, Acinetobacter dominated (48%) the total microbial load. Overall, L27C exhibited 7 different phyla of bacteria and 20 different genera. Statistical analysis (Shannon-Weaver Diversity Index and Simpson Diversity Index) of the biodiversity of L27C displayed a moderately rich and diverse community. Investigations of the biodiversity and distribution of microorganisms in these lakes will help further our understanding of how the physical environment impact the structure and function within these microbially dominated ecosystems.

Huang, Jonathan P.↗

Space Flown Rodent Liver RNA Sequencing Data for Machine Learning in Space Biology Research

High-throughput nucleic acid sequencing (DNA-seq, RNA-seq) has become widespread in biomedical research due to the growing availability and affordability of these assays. Data analysis has been accelerated in recent years by the adoption of artificial intelligence (AI) and machine learning (ML) techniques by biomedical researchers. In space biology research, RNAseq datasets from space-flown experimental samples are critical for characterizing the gene expression aberrations associated with exposure to spaceflight stressors. However, space biological experiments tend to be very low sample size, so identifying proper AI/ML algorithms for sequencing data analysis is an ongoing challenge since these algorithms typically require large sample size. The NASA Science Mission Directorate (SMD) has started the “Benchmark Initiative for AI/ML”, focused on creating datasets meant for three main applications: 1) scientific benchmarking, which finds the best algorithm for a specific problem; 2) application benchmarking, which measures algorithm performance against a set of parameters; and 3) system benchmarking, which evaluates performance of hardware and software architecture. These scientific benchmarks consist of an AI-ready dataset and a reference implementation on a specific scientific question. In this work, we focused on generating standardized datasets to allow the scientific community to benchmark AI/ML algorithms in the domain of space biology. We present here a standardized, AI-ready, publicly available benchmark dataset for space biology RNA-seq data as a collaboration between the NASA AI4LS (Artificial Intelligence for Life Sciences) working group. and NASA’s SMD. This dataset consists of space-flown and ground control mouse liver found in the NASA GeneLab omics database. However, to amplify the small sample number (n=112 samples) for ML purposes, we employ Gaussian noise and a generative adversarial network to extend this dataset to 6,000 synthetic samples, matching the original gene expression characteristics.

James Casaletto↗

Metagenomics, metatranscriptomics and single cell genomics reveal functional response of active Oceanospirillales to Gulf oil spill

The Deepwater Horizon oil spill in the Gulf of Mexico resulted in a deep-sea hydrocarbon plume that caused a shift in the indigenous microbial community composition with unknown ecological consequences. Early in the spill history, a bloom of uncultured, thus uncharacterized, members of the Oceanospirillales was previously detected, but their role in oil disposition was unknown. Here our aim was to determine the functional role of the Oceanospirillales and other active members of the indigenous microbial community using deep sequencing of community DNA and RNA, as well as single-cell genomics. Shotgun metagenomic and metatranscriptomic sequencing revealed that genes for motility, chemotaxis and aliphatic hydrocarbon degradation were significantly enriched and expressed in the hydrocarbon plume samples compared with uncontaminated seawater collected from plume depth. In contrast, although genes coding for degradation of more recalcitrant compounds, such as benzene, toluene, ethylbenzene, total xylenes and polycyclic aromatic hydrocarbons, were identified in the metagenomes, they were expressed at low levels, or not at all based on analysis of the metatranscriptomes. Isolation and sequencing of two Oceanospirillales single cells revealed that both cells possessed genes coding for n-alkane and cycloalkane degradation. Specifically, the near-complete pathway for cyclohexane oxidation in the Oceanospirillales single cells was elucidated and supported by both metagenome and metatranscriptome data. The draft genome also included genes for chemotaxis, motility and nutrient acquisition strategies that were also identified in the metagenomes and metatranscriptomes. These data point towards a rapid response of members of the Oceanospirillales to aliphatic hydrocarbons in the deep sea.

09 BIOMASS FUELS↗

Hybrid Technique in SCALE for Fission Source Convergence Applied to Used Nuclear Fuel Analysis

The new hybrid SOURCE ConveRgence accelERator (SOURCERER) sequence in SCALE deterministically computes a fission distribution and uses it as the starting source in a Monte Carlo eigenvalue criticality calculation. In addition to taking the guesswork out of defining an appropriate, problem-dependent starting source, the more accurate starting source provided by the deterministic calculation decreases the probability of producing inaccurate tally estimates associated with undersampling problems caused by inadequate source convergence. Furthermore, SOURCERER can increase the efficiency of the overall simulation by decreasing the number of cycles that has to be skipped before the keff accumulation. SOURCERER was applied to a representative example for a used nuclear fuel cask utilized at the Maine Yankee storage site {Scaglione and Ilas}. Because of the time constraints of the Used Fuel Research, Development, and Demonstration project, it was found that using more than 30,000 neutrons per cycle will lead to inaccurate Monte Carlo calculation of keff due to the inevitable decrease in the number of skipped and active cycles used with this problem. For a fixed uncertainty objective and by using 30,000 neutron per cycle, the use of SOURCERER increased the efficiency of the keff calculation by 60%compared to a Monte Carlo calculation that used a starting source distributed uniformly in fissionable regions, even with the inclusion of the extra computational time required by the deterministic calculation. Additionally, the use of SOURCERER increased the reliability of keff calculation using any number of skipped cycles below 350.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Microbial community diversity changes during voltage reversal repair in a 12-unit microbial fuel cell

Microbial fuel cell stacks (MFC-Stack) are often confronted with voltage reversals, likely due to an interplay between microbial community dynamics and insufficient electric circuit balancing. Herein, we provide new insight into voltage reversals by examining the microbiomes of twelve MFC units of a 12-liter Pilot-MFC-Stack during repair. Different biofilm repair methods (self-healing, electrostimulation, and re-acclimatization upon cross-inoculation) were used to evaluate the microbial community response. In addition, MFC-Stack simulation was performed based on Kirchhoff’s Second Law to predict values for source potentials and post-evaluate internal resistances. Analysis of the 16S rRNA amplicon sequencing data suggests that the biofilm repair methods could slowly heal damaged biofilms. Notably, severely voltage reversed MFC units had low electrogen relative abundances (18%) and positive anode potentials, while strong bioanodes and contained more than 50% electrogens and had negative anode potentials. Between-community analyses (beta diversity ordination and multinomial regression) of the voltage reversed MFC units revealed differences among biofilms in contrast to healthy/strong MFC units. Permutational multivariate analysis of variance (PERMANOVA) confirmed that reversed biofilms were, indeed, significantly (p < 0.05) different from stronger ones. Overall, these analyses demonstrated the utility of combining electrotechnical and microbial community analyses, especially beta diversity ordination and multinomial regression, to understand problematic MFC units and the potential success of a biofilm repair method. Finally, thicker biofilms were usually healthier and stronger, although thickness was no guarantee for proper structure and power function as all factors were interdependent. There was an evolutionary trend that strong anodes became stronger/healthier and others weaker. This spontaneous trend has to be considered to avoid irreversible voltage reversals and to repair electrogenic biofilms in an MFC-Stack.

59 BASIC BIOLOGICAL SCIENCES↗

Entry Dispersion Analysis for the Genesis Sample Return Capsule

Genesis will be the first mission to return samples from beyond the Earth-Moon system. The spacecraft will be inserted into a halo orbit about the L1 (Sun- Earth) libration point where it will remain for two years collecting solar wind particles. Upon Earth return, the sample return capsule, which is passively controlled, will descend under parachute to Utah. The present study describes the analysis of the entry, descent, and landing scenario of the returning sample capsule. The robustness of the entry sequence is assessed through a Monte Carlo dispersion analysis where the impact of off-nominal conditions is ascertained. The dispersion results indicate that the capsule attitude excursions near peak heating and drogue chute deployment are within Genesis mission limits. Additionally, the size of the resulting 3-sigma landing ellipse is 47.8 km in downrange by 15.2 km in crossrange, which is within the Utah Test and Training Range boundaries.

Desai, Prasun N.↗