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DOE OSTI2019

SNAPPy: A snakemake pipeline for scalable HIV-1 subtyping by phylogenetic pairing

Abstract Human immunodeficiency virus 1 (HIV-1) genome sequencing is routinely done for drug resistance monitoring in hospitals worldwide. Subtyping these extensive datasets of HIV-1 sequences is a critical first step in molecular epidemiology and evolution studies. The clinical relevance of HIV-1 subtypes is increasingly recognized. Several studies suggest subtype-related differences in disease progression, transmission route efficiency, immune evasion, and even therapeutic outcomes. HIV-1 subtyping is mainly done using web-servers. These tools have limitations in scalability and potential noncompliance with data protection legislation. Thus, the aim of this work was to develop an efficient method for large-scale local HIV-1 subtyping. We designed SNAPPy: a snakemake pipeline for scalable HIV-1 subtyping by phylogenetic pairing. It contains several tasks of phylogenetic inference and BLAST queries, which can be executed sequentially or in parallel, taking advantage of multiple-core processing units. Although it was built for subtyping, SNAPPy is also useful to perform extensive HIV-1 alignments. This tool facilitates large-scale sequence-based HIV-1 research by providing a local, resource efficient and scalable alternative for HIV-1 subtyping. It is capable of analyzing full-length genomes or partial HIV-1 genomic regions (GAG, POL, and ENV) and recognizes more than ninety circulating recombinant forms. SNAPPy is freely available at: https://github.com/PMMAraujo/snappy/releases.

Araújo, Pedro M. M.↗

DOE OSTI2025

Pulse and Polarization Structures in Axion-Converted X-Rays from Pulsars

Neutron stars (NSs) with their strong magnetic fields and hot dense cores could be powerful probes of axions, a classic benchmark of feebly coupled new particles, through abundant production of axions with the axion-nucleon coupling and subsequent conversion into x-rays due to the axion-photon coupling. In this Letter, we point out that the pulsation structures in both the intensity and polarization of x-rays from NSs could provide us additional information about axions and their couplings. We develop new analytical formalisms of pulsation-polarization structure applicable to a wide range of NSs in the axion scenario and argue that they hold in complicated astrophysical environments. As a case study, we apply our formalism to a representative X-ray Dim Isolated Neutron Star, RX J1856.6-3754, with an unexpected hard x-ray excess which might be axion induced. We show with an updated fit that the axion explanation is compatible with both the intensity and pulsation data available, and combining the pulsation data does not shift the posterior by more than 1⁢𝜎. Yet, the preferred parameter space is close to being excluded by other astrophysical constraints. With a 75% reduction of the uncertainties in the pulsation data, we could potentially draw a definite conclusion on the axion-induced x-rays at more than 3⁢𝜎 level.

Axions↗

DOE OSTI2020

Tailoring Spin-Wave Channels in a Reconfigurable Artificial Spin Ice

Artificial spin ices are ensembles of geometrically arranged interacting nanomagnets that have shown promising potential for the realization of reconfigurable magnonic crystals. Such systems allow for the manipulation of spin waves on the nanoscale and their potential use as information carriers. However, there are presently two general obstacles to the realization of artificial spin-ice-based magnonic crystals: the magnetic state of artificial spin ices is difficult to reconfigure and the magnetostatic interactions between the nanoislands are often weak, preventing mode coupling. We demonstrate, using micromagnetic modeling, that coupling a reconfigurable artificial spin-ice geometry made of weakly interacting nanomagnets to a soft magnetic underlayer creates a complex system exhibiting dynamically coupled modes. These give rise to spin-wave channels in the underlayer at well-defined frequencies, based on the artificial spin-ice magnetic state, which can be reconfigured. Finally, these findings open the door to the realization of reconfigurable magnonic crystals with potential applications for data transport and processing in magnonic-based logic architectures.

25 ENERGY STORAGE↗

DOE OSTI2021

Detecting hidden layers from spreading dynamics on complex networks

When dealing with spreading processes on networks it can be of the utmost importance to test the reliability of data and identify potential unobserved spreading paths. In this paper we address these problems and propose methods for hidden layer identification and reconstruction. We also explore the interplay between difficulty of the task and the structure of the multilayer network describing the whole system where the spreading process occurs. Our methods stem from an exact expression for the likelihood of a cascade in the susceptible-infected model on an arbitrary graph. We then show that by imploring statistical properties of unimodal distributions and simple heuristics describing joint likelihood of a series of cascades one can obtain an estimate of both existence of a hidden layer and its content with success rates far exceeding those of a null model. Furthermore, we conduct our analyses on both synthetic and real-world networks providing evidence for the viability of the approach presented.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Steps in the Development of Nuclear Thermal Propulsion Fuels

Due to the recent increased interest in Mars and deep-space missions it has been determined to be feasible to revisit the ability for the United States to build a Nuclear Thermal Propulsion (NTP) system. The need to make and qualify a NTP fuel that meets mission performance requirements is an essential first step. Graphite fuels and cermet fuels are of particular interest since these fuels have shown significant advantages over other fuel types. This paper will address the history of NTP fuel fabrication technology as related to the NERVA, GE 710, and Argonne National Laboratory’s Nuclear Fuel Programs as well as recent efforts in recapturing heritage fuels and develop new NTP fuels. Substantial experimental databases and supporting documentation exists for the composite fuel. Some irradiation and high temperature test data is available for cermet fuels, but cermet fuels were never tested at prototypic NTP conditions. A first step in the development effort will be a fuel fabrication recapture effort to provide samples to show that the technology works and performance of the fuel is acceptable. Advances in fuel fabrication, materials processing, and coating technology are expected to improve and/or enhance future fuel development, maturation and certification efforts. The current plan is to perform, non-nuclear separate-effects and integrated tests to provide additional test data and insight into the capabilities of each fuel and to use that data to evaluate potential performance within a NTP engine stage.

Qualls, A↗

DOE OSTI2019

Analysis of a GaN-Based CRM Totem-Pole PFC Converter Considering Current Sensing Delay

High-frequency soft-switched gallium-nitride (GaN) based critical conduction mode (CRM) totem-pole power factor correction (PFC) converter is one of the most potential candidates in data center power supplies. However, the high-speed cycle-by-cycle zero current detection (ZCD) brings challenges to zero-voltage-switching (ZVS) control. Current sensing delay (CSD) exists, and the ZCD circuit is sensitive to high di/dt switching noise. In this paper, mechanisms of the ZCD time error are elaborated, and impacts of the current sensing delay on converter switching frequency, inductor current, input current third harmonic distortion (THD), and power loss are analyzed. Qualification time is added within the controller for immunity to the swiching noise, and a CSD embedded converter model is proposed to compensate the ZCD time delay. Also, loss modeling of the CRM totem-pole PFC is conducted to aid in analysis of the proposed theory. A 1.5 kW single-phase CRM totem-pole PFC prototype is tested. Experimental results validiate the analysis, modeling, and the proposed compensation method for current sensing delay.

Sun, Jingjing↗

DOE OSTI2026

Atomistic Simulation of Glasses and Amorphous Materials: Challenges and Opportunities for the Next Decade

Atomistic simulations have become indispensable tools for understanding glass structure, dynamics, and properties, yet persistent challenges limit their predictive power. This perspective examines three interconnected issues, namely glass formation procedures, interatomic potential development, and machine learning applications, which emerged from the 5th International Workshop on Challenges of Atomistic Simulations of Glasses and Amorphous Materials. We identify convergent community priorities for (i) standardized validation protocols, (ii) curated benchmark datasets with complete metadata, and (iii) open repositories for glasses. A systematic was forward is provided by a hierarchical validation framework for assessing the structural fidelity, property prediction, and behavioral realism of simulation techniques. Looking ahead, transformative advances are promised by the fusion of classical techniques with machine learning based approaches, for instance, by integrating swap Monte Carlo with machine-learning (ML) potentials, leveraging foundation models through transfer learning, and finetuning ML potentials with experimental data. Progress depends on the community committing to validated models, reproducible protocols, and sustained data sharing.

Krishnan, N. M. Anoop↗

DOE OSTI2022

Genome-wide DNA methylation patterns harbour signatures of hatchling sex and past incubation temperature in a species with environmental sex determination

Conservation of thermally sensitive species depends on monitoring organismal and population-level responses to environmental change in real time. Epigenetic processes are increasingly recognized as key integrators of environmental conditions into developmentally plastic responses, and attendant epigenomic data sets hold potential for revealing cryptic phenotypes relevant to conservation efforts. Here, we demonstrate the utility of genome-wide DNA methylation (DNAm) patterns in the face of climate change for a group of especially vulnerable species, those with temperature-dependent sex determination (TSD). Due to their reliance on thermal cues during development to determine sexual fate, contemporary shifts in temperature are predicted to skew offspring sex ratios and ultimately destabilize sensitive populations. Using reduced-representation bisulphite sequencing, we profiled the DNA methylome in blood cells of hatchling American alligators (Alligator mississippiensis), a TSD species lacking reliable markers of sexual dimorphism in early life stages. We identified 120 sex-associated differentially methylated cytosines (DMCs; FDR < 0.1) in hatchlings incubated under a range of temperatures, as well as 707 unique temperature-associated DMCs. We further developed DNAm-based models capable of predicting hatchling sex with 100% accuracy (in 20 training samples and four test samples) and past incubation temperature with a mean absolute error of 1.2°C (in four test samples) based on the methylation status of 20 and 24 loci, respectively. Though largely independent of epigenomic patterning occurring in the embryonic gonad during TSD, DNAm patterns in blood cells may serve as nonlethal markers of hatchling sex and past incubation conditions in conservation applications. These findings also raise intriguing questions regarding tissue-specific epigenomic patterning in the context of developmental plasticity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

A treatment planning study to assess the feasibility of laser-driven proton therapy using a compact gantry design

Purpose: Laser-driven proton acceleration is suggested as a cost- and space-efficient alternative for future radiation therapy centers, although the properties of these beams are fairly different compared to conventionally accelerated proton beams. The laser-driven proton beam is extremely pulsed containing a very high proton number within ultrashort bunches at low bunch repetition rates of few Hz and the energy spectrum of the protons per bunch is very broad. Moreover, these laser accelerated bunches are subject to shot-to-shot fluctuations. Therefore, the aim of this study was to investigate the feasibility of a compact gantry design for laser-driven proton therapy and to determine limitations to comply with. Methods: Based on a published gantry beam line design which can filter parabolic spectra from an exponentially decaying broad initial spectrum, a treatment planning study was performed on real patient data sets. All potential parabolic spectra were fed into a treatment planning system and numerous spot scanning proton plans were calculated. To investigate limitations in the fluence per bunch, the proton number of the initial spectrum and the beam width at patient entrance were varied. A scenario where only integer shots are delivered as well as an intensity modulation from shot to shot was studied. The resulting plans were evaluated depending on their dosimetric quality and in terms of required treatment time. In addition, the influence of random shot-to-shot fluctuations on the plan quality was analyzed. Results: The study showed that clinically relevant dose distributions can be produced with the system under investigation even with integer shots. For small target volumes receiving high doses per fraction, the initial proton number per bunch must remain between 1.4 × 10{sup 8} and 8.3 × 10{sup 9} to achieve acceptable delivery times as well as plan qualities. For larger target volumes and standard doses per fraction, the initial proton number is even more restricted to stay between 1.4 × 10{sup 9} and 2.9 × 10{sup 9}. The lowest delivery time that could be reached for such a case was 16 min for a 10 Hz system. When modulating the intensity from shot to shot, the delivery time can be reduced to 6 min for this scenario. Since the shot-to-shot fluctuations are of random nature, a compensation effect can be observed, especially for higher laser shot numbers. Therefore, a fluctuation of ±30% within the proton number does not translate into a dosimetric deviation of the same size. However, for plans with short delivery times these fluctuations cannot cancel out sufficiently, even for ±10% fluctuations. Conclusions: Under the analyzed terms, it is feasible to achieve clinically relevant dose distributions with laser-driven proton beams. However, to keep the delivery times of the proton plans comparable to conventional proton plans for typical target volumes, a device is required which can modulate the bunch intensity from shot to shot. From the laser acceleration point of view, the proton number per bunch must be kept under control as well as the reproducibility of the bunches.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Thermal annealing of Stone–Wales defects in fullerenes and nanotubes

The thermally activated annealing of topological Stone–Wales defects in carbon fullerenes and nanotubes is studied via molecular dynamics. The temperature dependences of characteristic times are shown to obey the Arrhenius law. The values of the relevant activation energies and frequency factors are found. The results are compared with the simulated potential energy surface data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Beam charge asymmetries for deeply virtual Compton scattering off the proton

The unpolarized and polarized Beam Char\-ge Asymmetries (BCAs) of the $\overrightarrow{e}^{\pm}p \to e^{\pm}p \gamma$ process off unpolarized hydrogen are discussed. The measurement of BCAs with the CLAS12 spectrometer at the Thomas Jefferson National Accelerator Facility, using polarized positron and electron beams at 10.6 GeV is investigated. This experimental configuration allows to measure azimuthal and $t$-dependences of the unpolarized and polarized BCAs over a large $(x_B,Q^2)$ phase space, providing a direct access to the real part of the Compton Form Factor (CFF) ${\mathcal H}$. Additionally, these measurements confront the Bethe-Heitler dominance hypothesis and eventual effects beyond leading twist. The impact of potential positron beam data on the determination of CFFs is also investigated within a local fitting approach of experimental observables. Finally, positron data are shown to strongly reduce correlations between CFFs and consequently improve significantly the determination of $\Re {\rm e} [\mathcal{H}]$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Pion electroproduction measurements in the nucleon resonance region

Here, we report new pion electroproduction measurements in the $\Delta (1232)$ resonance, utilizing the SHMS - HMS magnetic spectrometers of Hall C at Jefferson Lab. The data focus on a region that exhibits a strong and rapidly changing interplay of the mesonic cloud and quark-gluon dynamics in the nucleon. The results are in reasonable agreement with models that employ pion cloud effects and chiral effective field theory calculations, but at the same time they suggest that an improvement is required to the theoretical calculations and provide valuable input that will allow their refinements. The data illustrate the potential of the magnetic spectrometers setup in Hall C towards the study the $\Delta (1232)$ resonance. These first reported results will be followed by a series of measurements in Hall C, that will expand the studies of the $\Delta (1232)$ resonance offering a high precision insight within a wide kinematic range from low to high momentum transfers.

13.60.Fz Transition Form Factors↗

DOE OSTI2021

Automatic Traffic Queue-End Identification using Location-Based Waze User Reports

Traffic queues, especially queues caused by non-recurrent events such as incidents, are unexpected to high-speed drivers approaching the end of queue (EOQ) and become safety concerns. Though the topic has been extensively studied, the identification of EOQ has been limited by the spatial-temporal resolution of traditional data sources. This study explores the potential of location-based crowdsourced data, specifically Waze user reports. It presents a dynamic clustering algorithm that can group the location-based reports in real time and identify the spatial-temporal extent of congestion as well as the EOQ. The algorithm is a spatial-temporal extension of the density-based spatial clustering of applications with noise (DBSCAN) algorithm for real-time streaming data with an adaptive threshold selection procedure. Here, the proposed method was tested with 34 traffic congestion cases in the Knoxville, Tennessee area of the United States. It is demonstrated that the algorithm can effectively detect spatial-temporal extent of congestion based on Waze report clusters and identify EOQ in real-time. The Waze report-based detection are compared to the detection based on roadside sensor data. The results are promising: The EOQ identification time of Waze is similar to the EOQ detection time of traffic sensor data, with only 1.1 min difference on average. In addition, Waze generates 1.9 EOQ detection points every mile, compared to 1.8 detection points generated by traffic sensor data, suggesting the two data sources are comparable in respect of reporting frequency. The results indicate that Waze is a valuable complementary source for EOQ detection where no traffic sensors are installed.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Assessing the reliability of medical resource demand models in the context of COVID-19

Abstract Background Numerous medical resource demand models have been created as tools for governments or hospitals, aiming to predict the need for crucial resources like ventilators, hospital beds, personal protective equipment (PPE), and diagnostic kits during crises such as the COVID-19 pandemic. However, the reliability of these demand models remains uncertain. Methods Demand models typically consist of two main components: hospital use epidemiological models that predict hospitalizations or daily admissions, and a demand calculator that translates the outputs of the epidemiological model into predictions for resource usage. We conducted separate analyses to evaluate each of these components. In the first analysis, we validated various hospital use epidemiological models using a recent validation framework designed for epidemiological models. This allowed us to quantify the accuracy of the models in predicting critical aspects such as the date and magnitude of local COVID-19 peaks, among other factors. In the second analysis, we evaluated a range of demand calculators for ventilators, medical gowns, and COVID-19 test kits. To achieve this, we decoupled these demand calculators from the underlying epidemiological models and provided ground truth data for their inputs. This approach enabled a direct comparison of the demand calculators, comparing them against each other and actual usage data when available. The code is available athttps://doi.org/10.5281/zenodo.13712387. Results Performance varied greatly across the epidemiological models, with greater variability in COVID-19 hospital use predictions than for COVID-19 deaths as analyzed previously. Some models did not have any peaks. Among those that did, the models under-estimated date of peak approximately as often as they over-estimated, but were more likely to under-estimate magnitude of peak, with typical relative errors around 50%. Regarding demand calculator predictions, there was significant variability, including five-fold differences in predictions for gown models. Validation against actual or surrogate usage data illustrated the potential value of demand models while demonstrating their limitations. Conclusions The emerging field of demand modeling holds promise in averting medical resource shortages during future public health emergencies. However, achieving this potential necessitates focused efforts on standardization, transparency, and rigorous model validation before placing reliance on demand models in critical public health decision-making.

Medical Informatics↗

DOE OSTI2023

Engineering transcriptional regulation of pentose metabolism in Rhodosporidium toruloides for improved conversion of xylose to bioproducts

Abstract Efficient conversion of pentose sugars remains a significant barrier to the replacement of petroleum-derived chemicals with plant biomass-derived bioproducts. While the oleaginous yeast Rhodosporidium toruloides (also known as Rhodotorula toruloides ) has a relatively robust native metabolism of pentose sugars compared to other wild yeasts, faster assimilation of those sugars will be required for industrial utilization of pentoses. To increase the rate of pentose assimilation in R. toruloides, we leveraged previously reported high-throughput fitness data to identify potential regulators of pentose catabolism. Two genes were selected for further investigation, a putative transcription factor (RTO4_12978, Pnt1) and a homolog of a glucose transceptor involved in carbon catabolite repression (RTO4_11990). Overexpression of Pnt1 increased the specific growth rate approximately twofold early in cultures on xylose and increased the maximum specific growth by 18% while decreasing accumulation of arabitol and xylitol in fast-growing cultures. Improved growth dynamics on xylose translated to a 120% increase in the overall rate of xylose conversion to fatty alcohols in batch culture. Proteomic analysis confirmed that Pnt1 is a major regulator of pentose catabolism in R. toruloides. Deletion of RTO4_11990 increased the growth rate on xylose, but did not relieve carbon catabolite repression in the presence of glucose. Carbon catabolite repression signaling networks remain poorly characterized in R. toruloides and likely comprise a different set of proteins than those mainly characterized in ascomycete fungi.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Data for Adoption of Perennial Energy Crops in the U.S. Midwest, Causal and Heterogeneous Determinants

The success of a bioenergy policy relies largely on the wide adoption of perennial energy crops at the farm scale. This study uses survey data to examine potential adoption decisions by farmers in the U.S. Midwest and the causal effects of various direct and indirect influencing factors, especially heterogeneous preferences of farmers. A Bayesian network (BN) model is developed to delineate the causal relationship between farmers adoption decisions and the influencing factors. We find a dominating role of economic factors and a non-negligible impact of non-economic factors, such as the perceived environmental benefits and the extent of familiarity with perennial energy crops. To examine the effect of heterogeneity in farmer preferences, we classify the surveyed farmers into four categories based on their attitudes toward the economic, social, and environmental dimensions of perennial energy crops. We identified statistically significant between-group differences in the responses of the four types of farmers to the various influencing factors. Our findings contribute to disentangling the complicated motivations that will influence perennial energy crop adoption decisions and provide implications for more targeted policy development that need to consider the heterogeneous drivers of farmer decisions about land use.

Modeling↗

DOE OSTI2022

Health Physics Research Reactor Criticality Accident Alarm System Benchmark Overview

From the countless critical experiments performed in the world during the past century, high-quality integral benchmarks experiments have been collected and gathered into the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook), managed by the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Working Group. This information preservation and dissemination effort is crucial for reactor licensing as well as criticality and radiation transport modeling validation. This summary reports on the status of a tentative benchmark addition to the ICSBEP Handbook. The proposed benchmark arises from legacy operation data of the Oak Ridge National Laboratory (ORNL) Health Physics Research Reactor (HPRR). The HPRR was a small, unmoderated, unshielded fast burst reactor that was used for research in health physics and radiobiology as well as teaching and training. As part of a comprehensive investigation of the available HPRR operation data and characteristics, different possibilities for use of the valuable results were studied. A critical experiment benchmark evaluation was performed, analyzing data coming from sub-critical and critical operation of the HPRR during operator training, steady-state irradiation of samples and before critical bursts. The results of the evaluation do not satisfy for the ICSBEP standards as the benchmark relative standard uncertainty is of about 4% for k eff , and the relative difference between sample calculations and expected k eff results is of about 1.5%. Due to those unsatisfactory results, it was decided not to pursue critical experiments evaluation of the HPRR presently and to focus instead on shielding type data for the creation of a criticality accident alarm system (CAAS) and shielding category benchmark, which is currently very scarce in the ICSBEP handbook—especially concerning critical, pulsed assembly, or reactor operation data. Several dosimetry and shielding experiments from HPRR burst operation were evaluated, with different benchmark metrics as sulfur fluence, Element 57 dose, or neutron fluence at different distances and under different shield materials conditions. An evaluation focusing on the Element 57 neutron dose as a benchmark metric was submitted to the ICSBEP Technical Review Group (TRG) meeting in October 2021, and the inclusion of the evaluation in the ICSBEP Handbook was deferred. The main change proposed by the international experiment evaluation experts is to use the neutron fluence measured by Bonner spheres as a benchmark metric. This represents a quantity closer to that actually measured by the experimentalists of the HPRR compared to the Element 57 dose, which adds another step of data transformation, thus potentially adding uncertainty to the benchmark. The evaluation has been updated and will be submitted to the 2022 ICSBEP TRG meeting for inclusion in the 2023 edition of the ICSBEP Handbook. The evaluation is performed using the KENO and MAVRIC combination from the SCALE 6.2.4 code suite which was previously used in similar CAAS benchmarks to allow for the use of variance reduction techniques.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

Molecular Dissection of Induced Platinum Resistance through Functional and Gene Expression Analysis in a Cell Culture Model of Bladder Cancer

Here, we report the development, functional and molecular characterization of an isogenic, paired bladder cancer cell culture model system for studying platinum drug resistance. The 5637 human bladder cancer cell line was cultured over ten months with stepwise increases in oxaliplatin concentration to generate a drug resistant 5637R sub cell line. The MTT assay was used to measure the cytotoxicity of several bladder cancer drugs. Liquid scintillation counting allowed quantification of cellular drug uptake and efflux of radiolabeled oxaliplatin and carboplatin. The impact of intracellular drug inactivation was assessed by chemical modulation of glutathione levels. Oxaliplatin- and carboplatin-DNA adduct formation and repair was measured using accelerator mass spectrometry. Resistance factors including apoptosis, growth factor signaling and others were assessed with RNAseq of both cell lines and included confirmation of selected transcripts by RT-PCR. Oxaliplatin, carboplatin, cisplatin and gemcitabine were significantly less cytotoxic to 5637R cells compared to the 5637 cells. In contrast, doxorubicin, methotrexate and vinblastine had no cell line dependent difference in cytotoxicity. Upon exposure to therapeutically relevant doses of oxaliplatin, 5637R cells had lower drug-DNA adduct levels than 5637 cells. This difference was partially accounted for by pre-DNA damage mechanisms such as drug uptake and intracellular inactivation by glutathione, as well as faster oxaliplatin-DNA adduct repair. In contrast, both cell lines had no significant differences in carboplatin cell uptake, efflux and drug-DNA adduct formation and repair, suggesting distinct resistance mechanisms for these two closely related drugs. The functional studies were augmented by RNAseq analysis, which demonstrated a significant change in expression of 83 transcripts, including 50 known genes and 22 novel transcripts. Most of the transcripts were not previously associated with bladder cancer chemoresistance. This model system and the associated phenotypic and genotypic data has the potential to identify some novel details of resistance mechanisms of clinical importance to bladder cancer.

59 BASIC BIOLOGICAL SCIENCES↗