Variation In Growth Rate Research Articles

Fungal community composition predicts forest carbon storage at a continental scale.

Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack of paired data on microbiome diversity and in situ observations of forest carbon accumulation and storage. Here, we investigated the relationship between soil microbiomes and forest carbon across 238 forest inventory plots spanning 15 European countries. We show that the composition and diversity of fungal, but not bacterial, species is tightly coupled to both forest biotic conditions and a seven-fold variation in tree growth rates and biomass carbon stocks when controlling for the effects of dominant tree type, climate, and other environmental factors. This linkage is particularly strong for symbiotic endophytic and ectomycorrhizal fungi known to directly facilitate tree growth. Since tree growth rates in this system are closely and positively correlated with belowground soil carbon stocks, we conclude that fungal composition is a strong predictor of overall forest carbon storage across the European continent.

Filtrasyonun oligotrofik deniz balık çiftliği ortamındaki fitoplankton dinamikleri üzerindeki etkisine dair ön çalışma

Fish farms play a crucial role in meeting the escalating demand for fish in human diets, yet their nutrient releases pose potential environmental risks. This study explores the influence of a fish farm in the eastern Aegean Sea on local phytoplankton dynamics, serving as an indicator of nutrient abundance. Designing a phytoplankton bioassay near the fish farm, natural phytoplankton communities were incubated within dialysis membrane bags, creating a confined environment for accessing farm-released nutrients before dispersing into surrounding seawater. Consequently, higher growth rates within the bags were anticipated compared to the ambient seawater. However, natural interactions within phytoplankton communities involve predator-prey dynamics, influencing the net growth rates of phytoplankton. To investigate different grazing pressures on the incubated phytoplankton, five experimental groups were established. Four of these groups involved filtering seawater through various mesh sizes (40 µm, 56 µm, 100 µm, and 150 µm) and then filling the dialysis membrane bags with the filtered water. The fifth group contained seawater without any filtration. Despite the oligotrophic nature of the ambient seawater, a remarkable increase in phytoplankton growth was observed inside the bags. Variable growth rates were observed among the groups, with unfiltered and 150 µm mesh-filtered bags exhibiting the highest growth rates, suggesting copepod absence may contribute. Although the species composition within the bags differed from that of the ambient seawater, the overall species diversity remained limited. A total of 33 phytoplankton taxa were identified in the seawater samples taken from the study site, comprising 17 diatom and 16 dinoflagellate species. Pronoctiluca spinifera (Lohmann) Schiller 1932 was documented for the first time along the Aegean Sea coast of Türkiye. This study enhances our understanding of how fish farming can impact phytoplankton communities and underscores the necessity for further investigations into the complex interactions between aquaculture and marine ecosystems in oligotrophic environments.

Stability analysis of electro-osmotic flow in a rotating microchannel

We investigate the linear stability analysis of rotating electro-osmotic flow in confined and unconfined configurations by appealing to the Debye–Hückel approximation. Pertaining to flow in confined and unconfined domains, the stability equations are solved using the Galerkin method to obtain the stability picture. Both qualitative and quantitative aspects of Ekman spirals are examined in stable and unstable scenarios within the unconfined domain. Within the confined domain, the variation of the real growth rate and the transition to instability are analysed using the modified Routh–Hurwitz criteria, employed for the first time in this context. The stability of the underlying flow, characterized by the number of roots with a positive real part, is determined by establishing a Routhian table. The inferences of this analysis show that the velocity plane produces intriguing closed Ekman spirals, which diminish in size with an increase in the rotation speed $\omega$ . The Ekman spirals in the stable region exhibit a distinct discontinuity, indicating the dissipation of disturbances over time. In the confined domain, the flow appears consistently stable for a set of involved parameters pertinent to this analysis, such as electrokinetic parameter $K=1.5$ and rotational parameter $\omega$ approximately up to $6$ . However, the flow instabilities become evident for $K=1.5$ and $\omega \geq 6$ .

Fracture Behaviour of Aluminium Alloys under Coastal Environmental Conditions: A Review

Aluminium alloys have been integral to numerous engineering applications due to their favourable strength, weight, and corrosion resistance combination. However, the performance of these alloys in coastal environments is a critical concern, as the interplay between fracture toughness and fatigue crack growth rate under such conditions remains relatively unexplored. This comprehensive review addresses this research gap by analysing the intricate relationship between fatigue crack propagation, fracture toughness, and challenging coastal environmental conditions. In view of the increasing utilisation of aluminium alloys in coastal infrastructure and maritime industries, understanding their behaviour under the joint influences of cyclic loading and corrosive coastal atmospheres is imperative. The primary objective of this review is to synthesise the existing knowledge on the subject, identify research gaps, and propose directions for future investigations. The methodology involves an in-depth examination of peer-reviewed literature and experimental studies. The mechanisms driving fatigue crack initiation and propagation in aluminium alloys exposed to saltwater, humidity, and temperature variations are elucidated. Additionally, this review critically evaluates the impact of coastal conditions on fracture toughness, shedding light on the vulnerability of aluminium alloys to sudden fractures in such environments. The variability of fatigue crack growth rates and fracture toughness values across different aluminium alloy compositions and environmental exposures was discussed. Corrosion–fatigue interactions emerge as a key contributor to accelerated crack propagation, underscoring the need for comprehensive mitigation strategies. This review paper highlights the pressing need to understand the behaviour of aluminium alloys under coastal conditions comprehensively. By revealing the existing research gaps and presenting an integrated overview of the intricate mechanisms at play, this study aims to guide further research and engineering efforts towards enhancing the durability and safety of aluminium alloy components in coastal environments.

Functional genomic screens with death rate analyses reveal mechanisms of drug action.

A common approach for understanding how drugs induce their therapeutic effects is to identify the genetic determinants of drug sensitivity. Because 'chemo-genetic profiles' are performed in a pooled format, inference of gene function is subject to several confounding influences related to variation in growth rates between clones. In this study, we developed Method for Evaluating Death Using a Simulation-assisted Approach (MEDUSA), which uses time-resolved measurements, along with model-driven constraints, to reveal the combination of growth and death rates that generated the observed drug response. MEDUSA is uniquely effective at identifying death regulatory genes. We apply MEDUSA to characterize DNA damage-induced lethality in the presence and absence of p53. Loss of p53 switches the mechanism of DNA damage-induced death from apoptosis to a non-apoptotic death that requires high respiration. These findings demonstrate the utility of MEDUSA both for determining the genetic dependencies of lethality and for revealing opportunities to potentiate chemo-efficacy in a cancer-specific manner.

Ocean-driven interannual variability in atmospheric CO2 quantified using OCO-2 observations and atmospheric transport simulations

Interannual variability (IAV) in the atmospheric CO2 growth rate is caused by variation in the balance between uptake by land and ocean and accumulation of anthropogenic emissions in the atmosphere. While variations in terrestrial fluxes are thought to drive most of the observed atmospheric CO2 IAV, the ability to characterize ocean impacts has been limited by the fact that most sites in the surface CO2 monitoring network are located on coasts or islands or within the continental interior. NASA’s Orbiting Carbon-Observatory 2 (OCO-2) mission has observed the atmospheric total column carbon dioxide mole fraction (XCO2) from space since September 2014. With a near-global coverage, this dataset provides a first opportunity to directly observe IAV in atmospheric CO2 over remote ocean regions. We assess the impact of ocean flux IAV on the OCO-2 record using atmospheric transport simulations with underlying gridded air-sea CO2 fluxes from observation-based products. We use three observation-based products to bracket the likely range of ocean air-sea flux contributions to XCO2 variability (over both land and ocean) within the GEOS-Chem atmospheric transport model. We find that the magnitude of XCO2 IAV generated by the whole ocean is between 0.08-0.12 ppm throughout the world. Depending on location and flux product, between 20-80% of the IAV in the simulations is caused by IAV in air-sea CO2 fluxes, with the remainder due to IAV in atmospheric winds, which modulate the atmospheric gradients that arise from climatological ocean fluxes. The Southern Hemisphere mid-latitudes and low-latitudes are the dominant ocean regions in generating the XCO2 IAV globally. The simulation results based on all three flux products show that even within the Northern Hemisphere atmosphere, Southern Hemisphere ocean fluxes are the dominant source of variability in XCO2. Nevertheless, the small magnitude of the air-sea flux impacts on XCO2 presents a substantial challenge for detection of ocean-driven IAV from OCO-2. Although the IAV amplitude arising from ocean fluxes and transport is 20 to 50% of the total observed XCO2 IAV amplitude of 0.4 to 1.6 ppm in the Southern Hemisphere and the tropics, ocean-driven IAV represents only 10% of the observed amplitude in the Northern Hemisphere. We find that for all three products, the simulated ocean-driven XCO2 IAV is weakly anti-correlated with OCO-2 observations, although these correlations are not statistically significant (p>0.05), suggesting that even over ocean basins, terrestrial IAV obscures the ocean signal.

Analisis Pengaruh Pertumbuhan Ekonomi, Inflasi, Dan Nilai Tukar Mata Uang Asing Terhadap Profitabilitas Bank Umum Syariah Di Indonesia Periode 2016-2020

This study aims to determine the effect of macroeconomic variables, namely economic growth, inflation and foreign exchange rates on the profitability of Islamic banks in Indonesia. The data sources for macroeconomic variables in this study are secondary data published by BPS and SEKI, while the profitability data for 14 Islamic banks in Indonesia are taken from the OJK Sharia Banking Statistics. The research method used in this study is a quantitative method with panel data analysis. The results showed that there was no significant effect of macroeconomic variables, namely economic growth, inflation and exchange rate variables on the profitability of Islamic banks partially, but simultaneously significant.

Plant seedlings of peas, tomatoes, and cucumbers exude compounds that are needed for growth and chemoattraction of Rhizobium leguminosarum bv. viciae 3841 and Azospirillum brasilense Sp7.

This study characterizes seedling exudates of peas, tomatoes, and cucumbers at the level of chemical composition and functionality. A plant experiment confirmed that Rhizobium leguminosarum bv. viciae 3841 enhanced growth of pea shoots, while Azospirillum brasilense Sp7 supported growth of pea, tomato, and cucumber roots. Chemical analysis of exudates after 1 day of seedling incubation in water yielded differences between the exudates of the three plants. Most remarkably, cucumber seedling exudate did not contain detectable sugars. All exudates contained amino acids, nucleobases/nucleosides, and organic acids, among other compounds. Cucumber seedling exudate contained reduced glutathione. Migration on semi solid agar plates containing individual exudate compounds as putative chemoattractants revealed that R. leguminosarum bv. viciae was more selective than A. brasilense, which migrated towards any of the compounds tested. Migration on semi solid agar plates containing 1:1 dilutions of seedling exudate was observed for each of the combinations of bacteria and exudates tested. Likewise, R. leguminosarum bv. viciae and A. brasilense grew on each of the three seedling exudates, though at varying growth rates. We conclude that the seedling exudates of peas, tomatoes, and cucumbers contain everything that is needed for their symbiotic bacteria to migrate and grow on.

Variation in growth rates between cultures hinders the cultivation of ammonia-oxidizing bacteria.

Ammonia-oxidizing bacteria, key players in the nitrogen cycle, have been the focus of extensive research. Numerous novel species have been isolated and their growth dynamics were studied. Despite these efforts, controlling their growth to obtain diverse physiological findings remains a challenge. These bacteria often fail to grow, even under optimal conditions. This unpredictable growth pattern could be viewed as a survival strategy. Understanding this heterogeneous behavior could enhance our ability to culture these bacteria. In this study, the variation in the growth rate was quantified for the ammonia-oxidizing bacterium Nitrosomonas mobilis Ms1. Our findings revealed significant growth rate variation under low inoculum conditions. Interestingly, higher cell densities resulted in more stable cultures. A comparative analysis of three Nitrosomonas species showed a correlation between growth rate variation and culture failure. The greater the variation in growth rate, the higher the likelihood of culture failure.

Eco-Engineering Mangrove Restoration at Gazi Bay, Kenya

Mangroves offer a range of globally acknowledged advantages, yet they continue to be lost and degraded. Efforts to restore lost mangroves using conventional techniques in high-energy areas result in low success rates due to the removal of seedlings via wave action. We assessed the efficacy of using modified Riley Encasement Methods in the restoration of mangroves in high-energy areas in Gazi Bay, Kenya. Vegetation and soil baseline data were collected in 49 square plots of 100 m2, which were established along belt transects perpendicular to the shoreline. The following mangrove vegetation data was collected: species composition, tree height (m), and stem diameter (cm). From these, the importance value index (IV), basal area, and standing density (stems/ha) were derived. Sediment cores were made in the center of each square plot for carbon and grain size analysis. Mangrove (Rhizophora mucronata) planting adopted a randomized complete block design (RCBD) in which the planting area was divided into three blocks (A, B, C). Within each block, treatments (bamboo and different-sized PVC pipes) were randomly assigned locations. The results of the study reveal significant variations in survival and growth rates among treatments. Higher survival rates were recorded for seedlings grown within PVC encasements (43%), surpassing bamboo (1%) and control groups (4%). Our findings suggest that PVC pipes were efficient in supporting and protecting seedlings from external forces. We expound on the implications of the results and highlight potential enhancements for the effectiveness of encasement technique in mangrove restoration.

Trade dependence of Mexico on barley (Hordeum vulgare L.)

Objective: To determine the degree of trade dependence of the Mexican market on, imported barley from 1994 to 2021.Design/Methodology/Approach: The growth rates of the barley production variables in the domestic market were estimated, the relative trade balance was calculated, and the trade dependence was determined.Results: The production variables had growth rates in the analysis period, the relative trade balance was -1, and the trade dependence was close to 0.Study Limitations/Implications: There is no correlation between the barley market and the brewing industry in Mexico.Findings/Conclusions: Mexico is a net importer of barley despite the positive growth rates of the production variables. Nevertheless, this grain does not have a trade dependence on the foreign market.

Costs of ribosomal RNA stabilization affect ribosome composition at maximum growth rate

Ribosomes are key to cellular self-fabrication and limit growth rate. While most enzymes are proteins, ribosomes consist of 1/3 protein and 2/3 ribonucleic acid (RNA) (in E. coli).Here, we develop a mechanistic model of a self-fabricating cell, validated across diverse growth conditions. Through resource balance analysis (RBA), we explore the variation in maximum growth rate with ribosome composition, assuming constant kinetic parameters.Our model highlights the importance of RNA instability. If we neglect it, RNA synthesis is always cheaper than protein synthesis, leading to an RNA-only ribosome at maximum growth rate. Upon accounting for RNA turnover, we find that a mixed ribosome composed of RNA and proteins maximizes growth rate. To account for RNA turnover, we explore two scenarios regarding the activity of RNases. In (a) degradation is proportional to RNA content. In (b) ribosomal proteins cooperatively mitigate RNA instability by protecting it from misfolding and subsequent degradation. In both cases, higher protein content elevates protein synthesis costs and simultaneously lowers RNA turnover expenses, resulting in mixed RNA-protein ribosomes. Only scenario (b) aligns qualitatively with experimental data across varied growth conditions.Our research provides fresh insights into ribosome biogenesis and evolution, paving the way for understanding protein-rich ribosomes in archaea and mitochondria.

Credit Scoring Modelling For Corporate Banking Institutions

This research aims to build a credit scoring modeling simulation of bank corporate loans. The credit scoring model is used in assessing creditworthiness in credit decisions. This model determines whether or not a company is eligible for the corporate credit facility it proposes. Observations were made of 100 companies included in the list of Kompas100 Index formers on the Indonesia Stock Exchange (IDX) that have the potential to apply for loans/credits to Bank Financial Institutions (IKB) in optimizing the corporate capital structure through bank debt facilities in the period 2022. Analysis was conducted on five financial aspects consisting of 14 research variables, including (i) liquidity aspects, including current ratio and quick ratio variables; (ii) solvency aspects, including debt asset ratio and equity ratio variables; (iii) profitability aspects including return on net assets, operating profit ratio, price to earnings ratio variables, (iv) activity aspects including total asset turnover, accounts receivable turnover, inventory turnover, current assets turnover, and (v) growth aspects including operating income growth rate, total assets growth rate, and operating profit growth rate variables. The analysis tool uses Logistic Regression through an assessment conducted on the company's credit rating as a proxy for the dependent variable, worth one if the credit application is feasible and worth 0 if the credit application is not feasible with a cut-off point of 0.5. The results show that credit scoring modeling for corporate credit is significantly formed from liquidity (CR) and solvency (DER) aspects. Out of 61 companies classified as not eligible for credit facilities, 58 companies were classified correctly, and out of 39 companies classified as eligible, 29 companies were classified correctly. The overall percentage shows 68.0, meaning that the logistic regression model has an accuracy of 68%.

Macroeconomic and financial mixed frequency factors in a big data environment

Abstract In this paper, we evaluate the predictive content of 3 new business condition indexes and uncertainty measures that are estimated using high-frequency financial and low-frequency macroeconomic time series data. More specifically, our measures are defined as latent factors that are extracted from a state space model that includes multiple different frequencies of non-parametrically estimated components of quadratic variation, as well as mixed frequency macroeconomic variables. When forecasting growth rates of various monthly financial and macroeconomic variables, use of our new mixed frequency factors is shown to result in significant improvement in predictive performance, relative to a number of benchmark models. Additionally, when used to forecast corporate yields, predictive gains associated with the use of our measures are shown to be monotonically increasing, as one moves from predicting higher to lower rated bonds. This is consistent with the existence of a natural pricing channel wherein financial risk (as measured using our volatility factors) contains more predictive information for lower grade bonds. We also find that a variety of extant risk factors including the Aruoba et al. [(2009a). Real-time measurement of business conditions. Journal of Business & Economic Statistics, 27(4), 417427] business conditions index also contain marginal predictive content for the variables that we examine, although their inclusion does not reduce the usefulness of our measures.

Effect of basket height and stocking density on production of the sea urchin Tripneustes gratilla: insights and recommendations

Basket height and stocking density are crucial and related factors for successful commercial sea urchin aquaculture, but these factors have not been definitively determined for production of Tripneustes gratilla. This study investigated the effects of varying basket heights (deep 30 cm vs. shallow 15 cm) and stocking densities (4, 6 and 8 kg.m−2 or 13, 19 and 24% coverage of available basket surface area) on aquacultural production of T. gratilla. Contrary to previous suggestions, reduced consumption was identified as the cause of decreased production in deeper baskets. Consumption was significantly higher in shallow baskets than deep baskets for both the fresh seaweed, Ulva lacinulata, (W = 38, p = 0.026) and formulated feed (W = 76.5, p = 0.007). Consequently, baskets of approximately 15 cm deep are recommended to enhance production of T. gratilla and possibly other urchin species. Two subsequent trials assessed production of T. gratilla at different stocking densities. Trial 1 aimed to maximize urchin size over a three-month grow-out period using fresh U. lacinulata, while trial 2 focused on enhancing gonad production over two months using formulated feed. Although greater stocking density significantly reduced the specific growth rates of individual urchin mass in both trials (p < 0.044), there was no significant impact on mortality, net production or gonad size and quality. The variations in growth rates were attributed to spine loss resulting from negative behavioural interactions (F2, 9 = 9.551; p = 0.005). Based on the objectives of both grow-out and gonad-enhancement phases, we recommend a stocking density of approximately 20% coverage.

Modeling Physical and Physiological Processes Reveals the Role of Turbulence in the Prerequisites for Microcystis Blooms

AbstractHarmful algal blooms of Microcystis have become a global problem. Turbulence, a determining factor affecting blooms, not only disperses surface scum but also controls the growth of Microcystis. Numerous studies have analyzed the effects of turbulence on the growth and colony size of Microcystis in laboratories, but the turbulence thresholds for Microcystis growth and colony disaggregation in the field are difficult to determine due to the complex environment. In addition, the quantitative contribution of turbulence‐driven blooms and the intrinsic mechanisms of the spatial distribution responding to turbulence are unclear. In this study, a fully integrated filed scale computational model focusing on turbulence‐driven blooms was developed, which incorporates physical processes (turbulence‐induced vertical mixing, VMT) and physiological processes such as buoyancy‐controlling transport (BCT), turbulence‐induced colony size variation (CSV), and growth rate variation (GRV). We performed model sensitivity analysis and evaluated the effects of turbulence intensity and duration on the biomass and vertical distribution of Microcystis. The results show that the optimal turbulence dissipation rate for Microcystis growth in the field is 1.0 × 10−5 m2/s3 and the critical turbulence dissipation rate for aggregation distribution is 3.81 × 10−6 m2/s3 in shallow lakes. A quantitative comparison of the effects of physical/physiological processes on blooms shows that physiological processes (CSV, GRV, and BCT) are critical for biomass enrichment, and the accumulation of Microcystis at the water surface is dominated by physical processes (VMT). This study reveals the mechanisms of turbulence‐driven Microcystis blooms and provides new insights for algal bloom prediction and control.

Demography and threats to population growth of Cirsium pitcheri, a threatened dune plant, in Wisconsin.

Multi-year and multi-site demographic data for rare plants allow researchers to observe threats and project population growth rates and thus long-term persistence of the species, generating knowledge, which allows for effective conservation planning. Demographic studies across more than a decade are extremely rare but allow for the effects of threats to be observed and assessed within the context of interannual environmental variation. We collected demographic data on the Threatened plant Cirsium pitcheri in two sites from 2011-2022. These sites were chosen because one exhibited the presence of non-native seed predators while the other did not, and we hypothesized that we would see declines and potentially extinction of the population threatened by predation. Over the course of our study, we observed additional threats, such as human trampling and high lake levels, which led to significant erosion, sand burial, and storm damage to plants. We find high interannual variation in vital rates and population growth rates for both populations, which mask the overall effects of predation. We observed dramatic declines in plant survivorship and population growth rates in both sites in the years with high lake levels. We conclude that high lake levels, which are expected to become more frequent with climate change, pose a significant threat to all near-shore populations of C. pitcheri.

Abstract IA016: Bayesian phylodynamics to quantify cancer growth across space and time

Abstract Phylogenetics has traditionally inferred shared genetic histories of species over macroevolutionary time. With the expansion of cancer multi-region and single-cell sequencing, phylogenetic approaches have found new uses mapping the evolutionary histories of tumors as well. Recently developed “phylodynamic” methods that integrate phylogenetic and population dynamic modeling offer further promise - uncovering cancer growth dynamics from the topologies and branch lengths of tumor trees. Here, I discuss two recent efforts in this area: 1) Heterogeneous growth rates across a tumor become encoded in the branching patterns of phylogenetic trees built from multi-region sequencing. We introduce a cancer-specific extension to a class of multi-state birth-death models to infer these growth rate differences across space. We apply our model (SDevo) to a sample of hepatocellular carcinomas and infer that these tumor peripheries grow 2-6 times faster than their interiors. 2) Tumors experience differential growth rates over time as they acquire new driver mutations and invade their surrounding tissues, and these growth dynamics similarly leave characteristic signatures in their phylogenies. We employ Bayesian skyline models to dissect tumor growth dynamics from a dataset of diverse cancers and reveal variation in cancer growth rates over time. As cancer sequencing continues to proliferate, phylodynamic approaches are poised to reveal new quantitative insights into cancer growth dynamics across time and space. Citation Format: Maya Lewinsohn, Trevor Bedford, Nicola F. Müller, Alison Feder. Bayesian phylodynamics to quantify cancer growth across space and time [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA016.

Abstract A027: Detecting and modeling frequency-dependent evolution in serially passaged primary triple negative breast cancer patient derived xenografts

Abstract Tumor evolution is a contributing factor to most failed cancer treatments. The intratumor heterogeneity of cellular phenotypes found in the tumor microenvironment acts as an evolutionary substate for cancer cells during tumorigenesis, subsequent growth, and after the patient is in the clinic. Selective forces imposed by certain medications can cause the emergence of a tumor with a resistant phenotype. Chemotherapies that target rapidly dividing cells will select for slower dividing ones which are less sensitive to such agents. However, many selective pressures acting on the tumor microenvironment are yet to be elucidated. For example, the effect one cancer cell has on another’s growth through competitive (i.e., the struggle for resources) or cooperative (e.g., exchange of growth factors) interactions remains poorly understood. Our central hypothesis is that cancer cells with distinct karyotypes will have a varying growth rate influenced by the karyotype landscape of the entire tumor. That is, we expect the fitness of a cancer cell to be largely determined by its karyotype and the karyotypes of its neighbors. Thus, we predict that frequency-dependent selection has a significant impact on clonal evolution in cancer. To test this, we have developed two novel methods for respectively identifying likely instances of frequency-dependent selection and modeling the long-term evolutionary trajectory in such cases. To detect frequency-dependent effects, we investigate the relationship between the frequency of one clone and the growth rate of all others (including itself). If a statistically significant correlation can be found, we proceed to modeling clonal evolution. To do this, we use a penalized least squares method and find the best-fitting parameterization of the replicator equation to the clonally resolved frequency data. This provides us with a payoff matrix describing the intensity of competition between each pair of clones. Furthermore, it allows us to model the long-term evolutionary dynamics of the tumor and to make predictions regarding co-existence of clones or clonal sweeps. Recently, investigators serially passaged primary triple negative breast cancer (TNBC) patient derived xenograft (PDX) tumors in NRG mice for over a year, inferring clonal frequencies at multiple timepoints using single cell whole genome (scWGS) and RNA sequencing (scRNA-seq). From this data, we were able to detect statistically significant frequency-dependent effects in the majority of serially passaged PDX tumors. Of these, most are predicted to result in a clonal sweep. Three of the PDX tumors were treated with cisplatin which revealed clone-specific drug response. This presents an opportunity for adaptive therapy scheduling which takes advantage of fitness tradeoffs under different contexts. A greater understanding of the effects frequency-dependent selection has on tumor evolution will contribute to the design of therapies intended to preclude or delay the emergence of resistance to treatment. Citation Format: Thomas A. Veith, Richard Beck, Noemi Andor. Detecting and modeling frequency-dependent evolution in serially passaged primary triple negative breast cancer patient derived xenografts [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A027.

Microstructure and growth rate variability in a giant clam (Tridacna maxima) from the Lakshadweep Archipelago, India: implications for their use as biological monitors to trace extreme weather events

Microstructure and growth rate variability in a giant clam (Tridacna maxima) from the Lakshadweep Archipelago, India: implications for their use as biological monitors to trace extreme weather events