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At least 127 records · Page 7

Evolutionary engineering reveals amino acid substitutions in Ato2 and Ato3 that allow improved growth of Saccharomyces cerevisiae on lactic acid

ABSTRACT In Saccharomyces cerevisiae, the complete set of proteins involved in transport of lactic acid across the cell membrane has not been determined. In this study, we aimed to identify transport proteins not previously described to be involved in lactic acid transport via a combination of directed evolution, whole-genome resequencing and reverse engineering. Evolution of a strain lacking all known lactic acid transporters on lactate led to the discovery of mutated Ato2 and Ato3 as two novel lactic acid transport proteins. When compared to previously identified S. cerevisiae genes involved in lactic acid transport, expression of ATO3T284C was able to facilitate the highest growth rate (0.15 ± 0.01 h-1) on this carbon source. A comparison between (evolved) sequences and 3D models of the transport proteins showed that most of the identified mutations resulted in a widening of the narrowest hydrophobic constriction of the anion channel. We hypothesize that this observation, sometimes in combination with an increased binding affinity of lactic acid to the sites adjacent to this constriction, are responsible for the improved lactic acid transport in the evolved proteins.

Baldi, Nicolò↗

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗

Heterothermic Migration Strategies in Flying Vertebrates

Migration is a widespread and highly variable trait among animals. Population-level patterns arise from individual-level decisions, including physiological and energetic constraints. Many aspects of migration are influenced by behaviors and strategies employed during periods of stopover, where migrants may encounter variable or unpredictable conditions. Thermoregulation can be a major cost for homeotherms which largely encounter ambient temperatures below the lower critical temperature during migration, especially during the rest phase of the daily cycle. In this review we describe the empirical evidence, theoretical models, and potential implications of bats and birds that use heterothermy to reduce thermoregulatory costs during migration. Torpor-assisted migration is a strategy described for migrating temperate insectivorous bats, whereby torpor can be used during periods of inactivity to drastically reduce thermoregulatory costs and increase net refueling rate, leading to shorter stopover duration, reduced fuel load requirement, and potential consequences for broad-scale movement patterns and survival. Hummingbirds can adopt a similar strategy, but most birds are not capable of torpor. However, there is an increasing recognition of the use of more shallow heterothermic strategies by diverse bird species during migration, with similarly important implications for migration energetics. A growing body of published literature and preliminary data from ongoing research indicate that heterothermic migration strategies in birds may be more common than traditionally appreciated. We further take a broad evolutionary perspective to consider heterothermy as an alternative to migration in some species, or as a conceptual link to consider alternatives to seasonal resource limitations. There is a growing body of evidence related to heterothermic migration strategies in bats and birds, but many important questions related to the broader implications of this strategy remain.

bats↗

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SIF-based GPP modeling for evergreen forests considering the seasonal variation in maximum photochemical efficiency

Solar-induced chlorophyll fluorescence (SIF) has shown great potential in estimating gross primary production (GPP). However, their quantitative relationship is not invariant, which undermines the reliability of empirical SIF-based GPP estimation at fine spatiotemporal scales, especially under extreme conditions. In this study, we developed a parsimonious mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) by employing the Mechanistic Light Response framework and Eco-Evolutionary theory to describe the light and dark reactions during photosynthesis, respectively. Specifically, we found that considering the seasonal variation in a key parameter of the MLR framework, the maximum photochemical efficiency of photosystem II (Φ PSIImax ), can avoid the GPP overestimation in winter and early spring due to the relatively low environmental sensitivity of SIF. Compared to the estimates from other benchmark models, our GPP estimates were closer to the 1: 1 line and had higher accuracy (average R 2 = 0.86, RMSE=1.99 μmol m -2 s -1 ) across sites. Furthermore, the changes in the relationship between SIF and J (refers to the electron transport rate) contribute a lot to the dynamic SIF–GPP relationship in this study, while the J–GPP relationship is less variant when the temperature drops. Further, the seasonal variation in the SIF–J relationship, especially the reduction in its slope at low temperatures, is found largely explained by the Φ PSIImax . These results indicate the importance of the uncertainty caused by the variation in the SIF–J relationship for SIF-based GPP estimation, and the consideration of changes in Φ PSIImax under extreme conditions (such as severe winter in this study) is crucial for the improvement of GPP estimation via SIF.

59 BASIC BIOLOGICAL SCIENCES↗

Retrospective analysis of biochemical limitations to photosynthesis in 49 species: C 4 crops appear still adapted to pre‐industrial atmospheric [ CO 2 ]

Abstract Leaf CO 2 uptake ( A ) in C 4 photosynthesis is limited by the maximum apparent rate of PEPc carboxylation ( V pmax ) at low intercellular [CO 2 ] ( c i ) with a sharp transition to a c i ‐saturated rate ( V max ) due to co‐limitation by ribulose‐1:5‐bisphosphate carboxylase/oxygenase (Rubisco) and regeneration of PEP. The response of A to c i has been widely used to determine these two parameters. V max and V pmax depend on different enzymes but draw on a shared pool of leaf resources, such that resource distribution is optimized, and A maximized, when V max and V pmax are co‐limiting. We collected published A / c i curves in 49 C 4 species and assessed variation in photosynthetic traits between phylogenetic groups, and as a function of atmospheric [CO 2 ]. The balance of V max ‐ V pmax varied among evolutionary lineages and C 4 subtypes. Operating A was strongly V max ‐limited, such that re‐allocation of resources from V pmax towards V max was predicted to improve A by 12% in C 4 crops. This would not require additional inputs but rather altered partitioning of existing leaf nutrients, resulting in increased water and nutrient‐use efficiency. Optimal partitioning was achieved only in plants grown at pre‐industrial atmospheric [CO 2 ], suggesting C 4 crops have not adjusted to the rapid increase in atmospheric [CO 2 ] of the past few decades.

Pignon, Charles P.↗

Abiotic selection of microbial genome size in the global ocean

Abstract Strong purifying selection is considered a major evolutionary force behind small microbial genomes in the resource-poor photic ocean. However, very little is currently known about how the size of prokaryotic genomes evolves in the global ocean and whether patterns reflect shifts in resource availability in the epipelagic and relatively stable deep-sea environmental conditions. Using 364 marine microbial metagenomes, we investigate how the average genome size of uncultured planktonic prokaryotes varies across the tropical and polar oceans to the hadal realm. We find that genome size is highest in the perennially cold polar ocean, reflecting elongation of coding genes and gene dosage effects due to duplications in the interior ocean microbiome. Moreover, the rate of change in genome size due to temperature is 16-fold higher than with depth up to 200 m. Our results demonstrate how environmental factors can influence marine microbial genome size selection and ecological strategies of the microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

The influence of incubation temperature on offspring traits varies across northern and southern populations of the American alligator ( Alligator mississippiensis )

Maternal provisioning and the developmental environment are fundamental determinants of offspring traits, particularly in oviparous species. However, the extent to which embryonic responses to these factors differ across populations to drive phenotypic variation is not well understood. Here, we examine the contributions of maternal provisioning and incubation temperature to hatchling morphological and metabolic traits across four populations of the American alligator (Alligator mississippiensis), encompassing a large portion of the species' latitudinal range. Our results show that whereas the influence of egg mass is generally consistent across populations, responses to incubation temperature show population-level variation in several traits, including mass, head length, head width, and residual yolk mass. Additionally, the influence of incubation temperature on developmental rate is greater at northern populations, while the allocation of maternal resources toward fat body mass is greater at southern populations. Overall, our results suggest that responses to incubation temperature, relative to maternal provisioning, are a larger source of interpopulation phenotypic variation and may contribute to the local adaptation of populations.

59 BASIC BIOLOGICAL SCIENCES↗

Comparison of the Core-collapse Evolution of Two Nearly Equal-mass Progenitors

Abstract We compare the core-collapse evolution of a pair of 15.8 M ☉ stars with significantly different internal structures, a consequence of the bimodal variability exhibited by massive stars during their late evolutionary stages. The 15.78 and 15.79 M ☉ progenitors have core masses (masses interior to an entropy of 4 k B baryon −1 ) of 1.47 and 1.78 M ☉ and compactness parameters ξ 1.75 of 0.302 and 0.604, respectively. The core-collapse simulations are carried out in 2D to nearly 3 s postbounce and show substantial differences in the times of shock revival and explosion energies. The 15.78 M ☉ model begins exploding promptly at 120 ms postbounce when a strong density decrement at the Si–Si/O shell interface, not present in the 15.79 M ☉ progenitor, encounters the stalled shock. The 15.79 M ☉ model takes 100 ms longer to explode but ultimately produces a more powerful explosion. Both the larger mass accretion rate and the more massive core of the 15.79 M ☉ model during the first 0.8 s postbounce time result in larger ν e / ν ¯ e luminosities and RMS energies along with a flatter and higher-density heating region. The more-energetic explosion of the 15.79 M ☉ model resulted in the ejection of twice as much 56 Ni. Most of the ejecta in both models are moderately proton rich, though counterintuitively the highest electron fraction ( Y e = 0.61) ejecta in either model are in the less-energetic 15.78 M ☉ model, while the lowest electron fraction ( Y e = 0.45) ejecta in either model are in the 15.79 M ☉ model.

79 ASTRONOMY AND ASTROPHYSICS↗

Shedding far-ultraviolet light on the donor star and evolutionary state of the neutron-star LMXB Swift J1858.6−0814

ABSTRACT The evolution of accreting X-ray binary systems is closely coupled to the properties of their donor stars. Consequently, we can constrain the evolutionary track a system is by establishing the nature of its donor. Here, we present far-ultraviolet (far-UV) spectroscopy of the transient neutron-star low-mass X-ray binary J1858 in different accretion states (low-hard, high-hard, and soft). All of these spectra exhibit anomalous N v, C iv, Si iv, and He ii lines, suggesting that its donor star has undergone CNO processing. We also determine the donor’s effective temperature, Td ≃ 5700 K, and radius, Rd ≃ 1.7 R⊙, based on photometric observations obtained during quiescence. Lastly, we leverage the transient nature of the system to set an upper limit of $\dot{M}_{\rm acc} \lesssim 10^{-8.5}~{\rm M}_{\odot }~\mathrm{ yr}^{-1}$ on the present-day mass-transfer rate. Combining these with the orbital period of the system, Porb = 21.3 h, we search for viable evolution paths. The initial donor masses in the allowed solutions span the range 1 M⊙ ≲ Md,i ≲ 3.5 M⊙. All but the lowest masses in this range are consistent with the strong CNO-processing signature in the UV line ratios. The present-day donor mass in the permitted tracks are 0.5 M⊙ ≲ Md,obs ≲ 1.3 M⊙, higher than suggested by eclipse modelling. Since Porb is close to the so-called bifurcation period, both converging and diverging binary tracks are permitted. If the former is confirmed, J1858 will end its life as an ultracompact system with a substellar donor.

Castro Segura, N. (ORCID:0000000258700443)↗

Exposure to ionizing radiation disrupts normal epigenetic aging in Japanese medaka

Alterations to the epigenome are a hallmark of biological aging and age-dependent patterning of the DNA methylome (“epigenetic aging”) can be modeled to produce epigenetic age predictors. Rates of epigenetic aging vary amongst individuals and correlate to the onset of age-related disease and all-cause mortality. Yet, the origins of epigenetic-to-chronological age discordance are not empirically resolved. Here, we investigate the relationship between aging, DNA methylation, and environmental exposures in Japanese medaka (Oryzias latipes). We find age-associated DNA methylation patterning enriched in genomic regions of low CpG density and that, similar to mammals, most age-related changes occur during early life. We construct an epigenetic clock capable of predicting chronological age with a mean error of 61.1 days (~8.4% of average lifespan). To test the role of environmental factors in driving epigenetic age variation, we exposed medaka to chronic, environmentally relevant doses of ionizing radiation. Because most organisms share an evolutionary history with ionizing radiation, we hypothesized that exposure would reveal fundamental insights into environment-by-epigenetic aging interactions. Radiation exposure disrupted epigenetic aging by accelerating and decelerating normal age-associated patterning and was most pronounced in cytosines that were moderately associated with age. These findings empirically demonstrate the role of DNA methylation in integrating environmental factors into aging trajectories.

60 APPLIED LIFE SCIENCES↗

Sodium azide mutagenesis induces a unique pattern of mutations

The nature and effect of mutations are of fundamental importance to the evolutionary process. The generation of mutations with mutagens has also played important roles in genetics. Applications of mutagens include dissecting the genetic basis of trait variation, inducing desirable traits in crops, and understanding the nature of genetic load. Previous studies of sodium azide-induced mutations have reported single nucleotide variants (SNVs) found in individual genes. To characterize the nature of mutations induced by sodium azide, we analyze whole-genome sequencing (WGS) of 11 barley lines derived from sodium azide mutagenesis, where all lines were selected for diminution of plant fitness owing to induced mutations. We contrast observed mutagen-induced variants with those found in standing variation in WGS of 13 barley landraces. Here, we report indels that are two orders of magnitude more abundant than expected based on nominal mutation rates. We found induced SNVs are very specific, with C → T changes occurring in a context followed by another C on the same strand (or the reverse complement). The codons most affected by the mutagen include the sodium azide-specific CC motif (or the reverse complement), resulting in a handful of amino acid changes and few stop codons. The specific nature of induced mutations suggests that mutagens could be chosen based on experimental goals. Sodium azide would not be ideal for gene knockouts but will create many missense mutations with more subtle effects on protein function.

Genetics & Heredity↗

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Soni, Vivak (ORCID:0000000294969562)↗

P finder: genomic and metagenomic annotation of RNase P RNA gene (rnpB)

Abstract Background The rnpB gene encodes for an essential catalytic RNA (RNase P). Like other essential RNAs, RNase P’s sequence is highly variable. However, unlike other essential RNAs (i.e. tRNA, 16 S, 6 S,...) its structure is also variable with at least 5 distinct structure types observed in prokaryotes. This structural variability makes it labor intensive and challenging to create and maintain covariance models for the detection of RNase P RNA in genomic and metagenomic sequences. The lack of a facile and rapid annotation algorithm has led to the rnpB gene being the most grossly under annotated essential gene in completed prokaryotic genomes with only a 24% annotation rate. Here we describe the coupling of the largest RNase P RNA database with the local alignment scoring algorithm to create the most sensitive and rapid prokaryote rnpB gene identification and annotation algorithm to date. Results Of the 2772 completed microbial genomes downloaded from GenBank only 665 genomes had an annotated rnpB gene. We applied P Finder to these genomes and were able to identify 2733 or nearly 99% of the 2772 microbial genomes examined. From these results four new rnpB genes that encode the minimal T-type P RNase P RNAs were identified computationally for the first time. In addition, only the second C-type RNase P RNA was identified in Sphaerobacter thermophilus . Of special note, no RNase P RNAs were detected in several obligate endosymbionts of sap sucking insects suggesting a novel evolutionary adaptation. Conclusions The coupling of the largest RNase P RNA database and associated structure class identification with the P Finder algorithm is both sensitive and rapid, yielding high quality results to aid researchers annotating either genomic or metagenomic data. It is the only algorithm to date that can identify challenging RNAse P classes such as C-type and the minimal T-type RNase P RNAs. P Finder is written in C# and has a user-friendly GUI that can run on multiple 64-bit windows platforms (Windows Vista/7/8/10). P Finder is free available for download at https://github.com/JChristopherEllis/P-Finder as well as a small sample RNase P RNA file for testing.

59 BASIC BIOLOGICAL SCIENCES↗

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

Abstract Background and Aims New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae. Methods We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally. Key Results Using sliding-window population genetic analyses we find that differentiation is concentrated within ‘islands’ of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap. Conclusions We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth’s climate rapidly changes.

58 GEOSCIENCES↗

Photometric and Spectroscopic Analysis of Four Contact Binaries

We present the photometric and spectroscopic analysis of four W UMa binaries J015829.5+260333 (hereinafter as J0158), J030505.1+293443 (hereinafter as J0305), J102211.7+310022 (hereinafter as J1022), and KW Psc. The VR {sub c} I {sub c} band photometric observations are carried out with the 1.3 m Devasthal Fast Optical Telescope (DFOT). For low-resolution spectroscopy, we used the 2 m Himalayan Chandra Telescope (HCT) as well as the archival data from the 4 m LAMOST survey. The systems J0158 and J0305 show a period increase rate of 5.26( ± 1.72) × 10{sup −7} days yr{sup −1} and 1.78( ± 1.52) × 10{sup −6} days yr{sup −1}, respectively. The period of J1022 is found to be decreasing with a rate of 4.22 ( ± 1.67) × 10{sup −6} days yr{sup −1}. The period analysis of KW Psc displays no change in its period. The PHOEBE package is used for the light-curve modeling and basic parameters are evaluated with the help of the GAIA parallax. The asymmetry of light curves is explained with the assumption of cool spots at specific positions on one of the components of the system. On the basis of temperatures, mass ratios, fill-out factors, and periods, the system J1022 is identified as a W-subtype system while the others show some mixed properties. To probe the chromospheric activities in these W UMa binaries, their spectra are compared with the known inactive stars’ spectra. The comparison shows emission in H {sub α}, H {sub β}, and Ca II. To understand the evolutionary status of these systems, the components are plotted in mass–radius and mass–luminosity planes with other well characterized binary systems. The secondary components of all the systems are away from ZAMS, which indicates that the secondary is more evolved than the primary component.

47 OTHER INSTRUMENTATION↗

Checking It Twice: Using [C/N] Masses and Asteroseismic Masses as a Diagnostic of Mass Loss and Transfer on the Red Giant Branch

Red giants experience significant mass loss, but the mechanism is poorly understood. The surface [C/N] of red giants is correlated with birth mass but not directly impacted by mass loss. Exploiting this, we compare asteroseismic masses of red giants with the same [C/N] but different evolutionary states. We find bulk differences between stars at the beginning of the red giant branch (RGB) and in the subsequent evolutionary phase, the red clump, providing a direct constraint on the strength of net RGB mass loss in field stars. We find that net mass loss decreases with metallicity and mass, matching recent studies for field giants but contradicting expectations from the widely used Reimers’s mass-loss formula. We propose a mass- and metallicity-dependent Reimers’s η calibration that reproduces the empirical trends that we see. In addition, we identify 200 stars (3.12% of our sample) that are clear outliers from their population in these birth mass bins, which we believe are likely candidates for mass transfer events. These stars do not show any obvious discrepancies in abundances or binary properties from their counterparts. This population should be accounted for in Galactic archeological studies. Further follow-up is required to quantify their occurrence rate and origin.

Roberts, John D. [The Ohio State Univ., Columbus, ↗