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At least 271 records · Page 15

A network of soil moisture, soil temperature, air temperature, net radiation, ground heat flux and ground water for Chicago, Illinois

This dataset contains environmental monitoring data collected using solar-powered Multi-Function Research (MFR) Long Range Wide Area (LoRaWAN)-enabled nodes at 11 sites in Chicago, Illinois, as part of the DOE Urban Integrated Field Lab CROCUS project. The MFR node system consists of an Input/Output Digital Input Module (IB8) interface box (ICT International) providing wired connections for environmental sensors and an MFR-Node-L data logger that manages power, data processing, and LoRaWAN communication. The wireless data are ingested via Sage network (https://sagecontinuum.org/) nodes that contain LoRaWAN antennae. Measurements were collected from 11 MFR nodes deployed across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), West Woodlawn "Blacks in Green" (BIG), and Indian Boundary Prairies (IBP). Each MFR node supports a consistent suite of sensors measuring atmospheric, soil, and hydrological variables. Atmospheric measurements include 2m air temperature (°C), 2m vapor pressure deficit (kPa), and 2m shortwave/longwave radiation (incoming and outgoing, W/m²) measured using ATH-VPD and Apogee SN500 sensors. Soil measurements include volumetric water content (VWC, %) and temperature (°C) at four depths (15, 30, 45, and 60 cm below surface) using Meter Teros54 sensors, and heat flux (W/m²) at 10 cm depth using Huske HFP01-05 sensors. At selected locations, Meter Hydros21 sensors measure groundwater depth (mm), specific conductivity (dS/m), and temperature (°C). The dataset includes timestamps, site identifiers with location names, device IDs, Global Positioning System (GPS) coordinates, variable names with units, measurement depths, values, sensor names, and Sage node identifiers. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 6-bit binary system indicating physical range violations, step spikes, 24-hour flat-line conditions, 6-hour jitter, 7-day ultra-low variance, and persistent high offset. Data is provided in CSV and CF-compliant NetCDF formats. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Sap Flow Meter (SFM1x) sensors.

Chicago↗

Application of cyclic fluorocarbon/argon discharges to device patterning

With increasing demands on device patterning to achieve smaller critical dimensions and pitches for the 5 nm node and beyond, the need for atomic layer etching (ALE) is steadily increasing. In this work, a cyclic fluorocarbon/Ar plasma is successfully used for ALE patterning in a manufacturing scale reactor. Self-limited etching of silicon oxide is observed. The impact of various process parameters on the etch performance is established. The substrate temperature has been shown to play an especially significant role, with lower temperatures leading to higher selectivity and lower etch rates, but worse pattern fidelity. The cyclic ALE approach established with this work is shown to have great potential for small scale device patterning, showing self-limited etching, improved uniformity and resist mask performance.

36 MATERIALS SCIENCE↗

Routing performance analysis and optimization within a massively parallel computer

An apparatus, program product and method optimize the operation of a massively parallel computer system by, in part, receiving actual performance data concerning an application executed by the plurality of interconnected nodes, and analyzing the actual performance data to identify an actual performance pattern. A desired performance pattern may be determined for the application, and an algorithm may be selected from among a plurality of algorithms stored within a memory, the algorithm being configured to achieve the desired performance pattern based on the actual performance data.

97 MATHEMATICS AND COMPUTING↗

Clinical–Pathologic Stage Discrepancy in Bladder Cancer Patients Treated With Radical Cystectomy: Results From the National Cancer Data Base

Purpose: To examine the accuracy of clinical staging and its effects on outcome in bladder cancer (BC) patients treated with radical cystectomy (RC), using a large national database. Methods and Materials: A total of 16,953 patients with BC without distant metastases treated with RC from 1998 to 2009 were analyzed. Factors associated with clinical–pathologic stage discrepancy were assessed by multivariate generalized estimating equation models. Survival analysis was conducted for patients treated between 1998 and 2004 (n=7270) using the Kaplan-Meier method and Cox proportional hazards models. Results: At RC 41.9% of patients were upstaged, whereas 5.9% were downstaged. Upstaging was more common in females, the elderly, and in patients who underwent a more extensive lymphadenectomy. Downstaging was less common in patients treated at community centers, in the elderly, and in Hispanics. Receipt of preoperative chemotherapy was highly associated with downstaging. Five-year overall survival rates for patients with clinical stages 0, I, II, III, and IV were 67.2%, 62.9%, 50.4%, 36.9%, and 27.2%, respectively, whereas those for the same pathologic stages were 70.8%, 75.8%, 63.7%, 41.5%, and 24.7%, respectively. On multivariate analysis, upstaging was associated with increased 5-year mortality (hazard ratio [HR] 1.80, P<.001), but downstaging was not associated with survival (HR 0.88, P=.160). In contrast, more extensive lymphadenectomy was associated with decreased 5-year mortality (HR 0.76 for ≥10 lymph nodes examined, P<.001), as was treatment at an National Cancer Institute–designated cancer center (HR 0.90, P=.042). Conclusions: Clinical–pathologic stage discrepancy in BC patients is remarkably common across the United States. These findings should be considered when selecting patients for preoperative or nonoperative management strategies and when comparing the outcomes of bladder sparing approaches to RC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A stable and highly selective metalloporphyrin based framework for the catalytic oxidation of cyclohexene

A new metalloporphyrin framework of molybdenum Mo 2 O 4 (C 48 H 28 N 4 O 8 )·(CH 3 ) 2 NH·5H 2 O·2DMF (Mo 2 TCPP) was synthesized from tetrakis(4-carboxyphenyl)porphyrin (H 4 TCPP) and sodium molybdate dihydrate by a hydrothermal method. Mo 2 TCPP is a 3D network with two sub-units, in which both TCPP ligands and each Mo 2 dimer act as four connection nodes. The crystal structure was determined by single crystal analysis and further characterized by FTIR, SEM, EDX, PXRD, XPS and TGA. Here cumene hydrogen peroxide and hydrogen peroxide were used as oxidants to study the catalytic activity of new metalloporphyrins in the oxidation of cyclohexene at different temperatures. The conversion rate of cyclohexene and the selectivity of epoxycyclohexane were both higher than 99%, which was better than the previously published research results. The stability of the catalyst before and after the reaction was further tested for 10 runs without obvious degradation. The catalyst was stable in different solutions such as acidic, water and alkaline. These results shed light on the future development of new catalytic materials based on metalloporphyrin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlling guided modes in plasmonic metal/dielectric multilayer waveguides

We investigate the mode properties of planar dielectric aluminum-quinoline (Alq{sub 3}) multilayer waveguides comprising one single or three equally spaced embedded nanometer-thin (∼10 nm thick) Alq{sub 3}-Mg{sub 0.9}:Ag{sub 0.1} composite metal-island layers. The plasmonic waveguides were fabricated by organic molecular beam deposition. Transverse magnetic (TM) and transverse electric (TE) modes were selectively excited using the m-line method. The symmetric plasmonic TM{sub 0} mode was launched in all waveguides and—in addition—two higher order plasmonic TM{sub 1} and TM{sub 2} modes were generated in waveguides comprising three metal layers. Other TM modes have hybrid dielectric-plasmonic characters, showing an increased effective refractive index when one electric field antinode is close to a metallic layer. TM modes which have all their antinode(s) in the dielectric layers propagate essentially like dielectric modes. TE modes with antinode(s) at the position of the metal layer(s) are strongly damped while the losses are low for TE modes comprising a node at the position of the composite metal film(s). The possibility to control the effective refractive index and the losses for individual hybrid plasmonic-dielectric TM and dielectric TE modes opens new design opportunities for mode selective waveguides and TM-TE mode couplers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Grain boundary slip transfer classification and metric selection with artificial neural networks

An artificial neural network is used to evaluate the effectiveness of six metrics and their combinations to assess whether slip transfers across grain boundaries in coarse-grained oligocrystalline Al foils. This approach extends the one- or two-dimensional projections formerly applied to analyze slip transfer. The accuracy of this binary classification reaches around 87% for the best single metric and around 90% when considering two or more metrics simultaneously. Here, the results suggest slip transfer mostly depends on the geometric relationship between grains. Training a double-layer network having 10 nodes per hidden layer with 40 measurements is sufficient to render the maximum accuracy.

36 MATERIALS SCIENCE↗

Design of metal-mediated protein assemblies via hydroxamic acid functionalities

The self-assembly of proteins into sophisticated multicomponent assemblies is a hallmark of all living systems and has spawned extensive efforts in the construction of novel synthetic protein architectures with emergent functional properties. Protein assemblies in nature are formed via selective association of multiple protein surfaces through intricate noncovalent protein-protein interactions, a challenging task to accurately replicate in the de novo design of multiprotein systems. In this protocol, we describe the application of metal-coordinating hydroxamate (HA) motifs to direct the metal-mediated assembly of polyhedral protein architectures and 3D crystalline protein frameworks (protein-MOFs). This strategy has been implemented using an asymmetric cytochrome cb562 monomer through selective, concurrent association of Fe 3+ and Zn 2+ ions to form polyhedral cages. Furthermore, the use of ditopic HA linkers as bridging ligands with metal-binding protein nodes has allowed the construction of crystalline 3D protein-MOF lattices. The protocol is divided into two major sections: (1) the development of a Cys-reactive HA molecule for protein derivatization and self-assembly of protein-HA conjugates into polyhedral cages and (2) the synthesis of ditopic HA bridging ligands for the construction of ferritin-based protein-MOFs using symmetric metal-binding protein nodes. Furthermore, protein cages can be analyzed using analytical ultracentrifugation (AUC), transmission electron microscopy (TEM) and single-crystal X-ray diffraction (sc-XRD) techniques. HA-mediated protein-MOFs are formed in sitting-drop vapor diffusion crystallization trays and are probed via sc-XRD and multi-crystal small-angle X-ray scattering (SAXS) measurements. Ligand synthesis, construction of HA-mediated assemblies, and post-assembly analysis as described in this protocol can be performed by a graduate-level researcher within six weeks.

36 MATERIALS SCIENCE↗

Message passing with queues and channels

In an embodiment, a send thread receives an identifier that identifies a destination node and a pointer to data. The send thread creates a first send request in response to the receipt of the identifier and the data pointer. The send thread selects a selected channel from among a plurality of channels. The selected channel comprises a selected hand-off queue and an identification of a selected message unit. Each of the channels identifies a different message unit. The selected hand-off queue is randomly accessible. If the selected hand-off queue contains an available entry, the send thread adds the first send request to the selected hand-off queue. If the selected hand-off queue does not contain an available entry, the send thread removes a second send request from the selected hand-off queue and sends the second send request to the selected message unit.

97 MATHEMATICS AND COMPUTING↗

Development of a Multicomponent Prediction Model for Acute Esophagitis in Lung Cancer Patients Receiving Chemoradiotherapy

Purpose: To construct a model for the prediction of acute esophagitis in lung cancer patients receiving chemoradiotherapy by combining clinical data, treatment parameters, and genotyping profile. Patients and Methods: Data were available for 273 lung cancer patients treated with curative chemoradiotherapy. Clinical data included gender, age, World Health Organization performance score, nicotine use, diabetes, chronic disease, tumor type, tumor stage, lymph node stage, tumor location, and medical center. Treatment parameters included chemotherapy, surgery, radiotherapy technique, tumor dose, mean fractionation size, mean and maximal esophageal dose, and overall treatment time. A total of 332 genetic polymorphisms were considered in 112 candidate genes. The predicting model was achieved by lasso logistic regression for predictor selection, followed by classic logistic regression for unbiased estimation of the coefficients. Performance of the model was expressed as the area under the curve of the receiver operating characteristic and as the false-negative rate in the optimal point on the receiver operating characteristic curve. Results: A total of 110 patients (40%) developed acute esophagitis Grade {>=}2 (Common Terminology Criteria for Adverse Events v3.0). The final model contained chemotherapy treatment, lymph node stage, mean esophageal dose, gender, overall treatment time, radiotherapy technique, rs2302535 (EGFR), rs16930129 (ENG), rs1131877 (TRAF3), and rs2230528 (ITGB2). The area under the curve was 0.87, and the false-negative rate was 16%. Conclusion: Prediction of acute esophagitis can be improved by combining clinical, treatment, and genetic factors. A multicomponent prediction model for acute esophagitis with a sensitivity of 84% was constructed with two clinical parameters, four treatment parameters, and four genetic polymorphisms.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗

Ion-Electron Coupling-Driven Redox Behavior in Metal–Organic Frameworks

Redox-active metal–organic frameworks (MOFs) have long been proposed as electronic transport platforms, yet the microscopic origin of their conductivity remains debated. A theoretical demonstration reveals charge transport in a Zn(pyrazole–naphthalene diimide (NDI)) MOF arising not from delocalized band-like states but from redox hopping between discrete linker sites. Using ab initio molecular dynamics simulations combined with electronic structure analysis, we established a direct link among electron injection, structural reorganization, and transport. Electron accumulation proceeds sequentially and site-selectively from imide and carbonyl groups of the NDI core progressively involving pyrazole N atoms at higher reduction states, through a hierarchy of redox-active sites. In contrast, Zn nodes remain essentially redox-inactive, which confirms their structural role. Density-of-states analysis corroborates a transport regime dominated by linker-centered states with evolving p-character upon reduction, resulting in dynamically reconfigured conduction networks. Real-time trajectories reveal anisotropic linker-to-linker electron transfer modulated by counterion coordination. This cooperative ion–electron regime emerges from potential energy surface collapse into a single low-barrier transition (ΔG ‡ ≈ 45 meV), where ionic and electronic motions evolve adiabatically on the same free-energy landscape. Elucidating redox conductivity in Zn(pyrazole–NDI) MOFs provides a theoretical framework for use in neuromorphic computing and related technologies.

Charge transfer↗

SU-C-BRD-02: A Team Focused Clinical Implementation and Failure Mode and Effects Analysis of HDR Skin Brachytherapy Using Valencia and Leipzig Surface Applicators

Purpose: and Leipzig applicators (VLAs) are single-channel brachytherapy surface applicators used to treat skin lesions up to 2cm diameter. Source dwell times can be calculated and entered manually after clinical set-up or ultrasound. This procedure differs dramatically from CT-based planning; the novelty and unfamiliarity could lead to severe errors. To build layers of safety and ensure quality, a multidisciplinary team created a protocol and applied Failure Modes and Effects Analysis (FMEA) to the clinical procedure for HDR VLA skin treatments. Methods: team including physicists, physicians, nurses, therapists, residents, and administration developed a clinical procedure for VLA treatment. The procedure was evaluated using FMEA. Failure modes were identified and scored by severity, occurrence, and detection. The clinical procedure was revised to address high-scoring process nodes. Results: Several key components were added to the clinical procedure to minimize risk probability numbers (RPN): -Treatments are reviewed at weekly QA rounds, where physicians discuss diagnosis, prescription, applicator selection, and set-up. Peer review reduces the likelihood of an inappropriate treatment regime. -A template for HDR skin treatments was established in the clinical EMR system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planning physicist, and increases the detectability of an error during the physics second check. -A screen check was implemented during the second check to increase detectability of an error. -To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display. This facilitates data entry and verification. -VLAs are color-coded and labeled to match the EMR prescriptions, which simplifies in-room selection and verification. Conclusion: Multidisciplinary planning and FMEA increased delectability and reduced error probability during VLA HDR Brachytherapy. This clinical model may be useful to institutions implementing similar procedures.

60 APPLIED LIFE SCIENCES↗

If We Build Them, They Will Run: Automated HPC Apps Deployment and Profiling with eBPF in Cloud

The high performance computing (HPC) community is in a period of transition. The rise of AI/ML coupled with a changing landscape of resources deems portability a new metric of performance, and methods to move between on-premises and cloud environments and assess compatibility are paramount. Here we design and test a strategy for bridging the gap between traditional HPC and Kubernetes environments – first containerizing applications, providing automated orchestration to run studies, and packaging the setup with automated means to assess performance using low overhead eXtended Berkeley Packet Filter (eBPF) programs. We first assess different designs for eBPF collection, demonstrating a tradeoff between number of programs deployed on a node and overhead added. We develop 5 low overhead eBPF programs that combine with streaming ML models to assess CPU, futex, TCP, shared memory, and file access across four different builds of an HPC application for CPU and GPU. We use eBPF data to generate insights into the possible underlying etiology of scaling issues. We then assess compatibility of a well-known benchmark, HPCG, across matrices of micro-architectures and optimization levels (217 containers across 24 instance types and over 7500 runs). We provide to the community 30 applications to deploy in our automated setup and perform a scaling study from 4 to a maximum of 256 nodes for both CPU and GPU applications. Finally, we use our gained knowledge about performance to generate compatibility artifacts that are used by a newly developed Kubernetes controller to intelligently select instance type based on optimizing a figure of merit. Along with insights to scaling in this environment with a collection of applications and templates to work from, we provide an overall strategy for approaching HPC application deployment and image selection based on compatibility in cloud.

Computer science↗

Biomass yield in a genetically diverse Miscanthus sacchariflorus germplasm panel phenotyped at five locations in Asia, North America, and Europe

Abstract Miscanthus is a high‐yielding bioenergy crop that is broadly adapted to temperate and tropical environments. Commercial cultivation of Miscanthus is predominantly limited to a single sterile triploid clone of Miscanthus × giganteus , a hybrid between Miscanthus sacchariflorus and M. sinensis. To expand the genetic base of M. × giganteus , the substantial diversity within its progenitor species should be used for cultivar improvement and diversification. Here, we phenotyped a diversity panel of 605 M. sacchariflorus from six previously described genetic groups and 27 M. × giganteus genotypes for dry biomass yield and 16 yield‐component traits, in field trials grown over 3 years at one subtropical location (Zhuji, China) and four temperate locations (Foulum, Denmark; Sapporo, Japan; Urbana, Illinois; and Chuncheon, South Korea). There was considerable diversity in yield and yield‐component traits among and within genetic groups of M. sacchariflorus , and across the five locations. Biomass yield of M. sacchariflorus ranged from 0.003 to 34.0 Mg ha −1 in year 3. Variation among the genetic groups was typically greater than within, so selection of genetic group should be an important first step for breeding with M. sacchariflorus . The Yangtze 2x genetic group (=ssp. lutarioriparius ) of M. sacchariflorus had the tallest and thickest culms at all locations tested. Notably, the Yangtze 2x genetic group's exceptional culm length and yield potential were driven primarily by a large number of nodes (>29 nodes culm −1 average over all locations), which was consistent with the especially late flowering of this group. The S Japan 4x, the N China/Korea/Russia 4x, and the N China 2x genetic groups were also promising genetic resources for biomass yield, culm length, and culm thickness, especially for temperate environments. Culm length was the best indicator of yield potential in M. sacchariflorus . These results will inform breeders' selection of M. sacchariflorus genotypes for population improvement and adaptation to target production environments.

59 BASIC BIOLOGICAL SCIENCES↗

SU-F-R-14: PET Based Radiomics to Predict Outcomes in Patients with Hodgkin Lymphoma

Purpose: To identify PET-based radiomics features associated with high refractory/relapsed disease risk for Hodgkin lymphoma patients. Methods: A total of 251 Hodgkin lymphoma patients including 19 primary refractory and 9 relapsed patients were investigated. All patients underwent an initial pre-treatment diagnostic FDG PET/CT scan. All cancerous lymph node regions (ROIs) were delineated by an experienced physician based on thresholding each volume of disease in the anatomical regions to SUV>2.5. We extracted 122 image features and evaluated the effect of ROI selection (the largest ROI, the ROI with highest mean SUV, merged ROI, and a single anatomic region [e.g. mediastinum]) on classification accuracy. Random forest was used as a classifier and ROC analysis was used to assess the relationship between selected features and patient’s outcome status. Results: Each patient had between 1 and 9 separate ROIs, with much intra-patient variability in PET features. The best model, which used features from a single anatomic region (the mediastinal ROI, only volumes>5cc: 169 patients with 12 primary refractory) had a classification accuracy of 80.5% for primary refractory disease. The top five features, based on Gini index, consist of shape features (max 3D-diameter and volume) and texture features (correlation and information measure of correlation1&2). In the ROC analysis, sensitivity and specificity of the best model were 0.92 and 0.80, respectively. The area under the ROC (AUC) and the accuracy were 0.86 and 0.86, respectively. The classification accuracy was less than 60% for other ROI models or when ROIs less than 5cc were included. Conclusion: This study showed that PET-based radiomics features from the mediastinal lymph region are associated with primary refractory disease and therefore may play an important role in predicting outcomes in Hodgkin lymphoma patients. These features could be additive beyond baseline tumor and clinical characteristics, and may warrant more aggressive treatment.

60 APPLIED LIFE SCIENCES↗

DIMPLES: Distributed Influence Maximization for Pandemic pLanning on Exascale Systems

We study exascale parallel algorithms for the selection of intervention or monitoring strategies in massive realistic socio-technical networks through scalable Influence Maximization (InfMax) algorithms. We employ novel techniques to enable efficient scaling on up to 8k nodes of OLCF Frontier, with 65k AMD GPUs and 458k AMD CPU cores. Current state-of-the-art InfMax tools are limited to networks with only a few million actors (vertices) and a few hundred million interactions (edges). By overcoming these limitations, we show that our approach is capable of processing a realistic social contact network of the United States with 285 million nodes and about 8 billion edges. This two orders-of-magnitude improvement over the previous state-of-the-art is obtained by leveraging algorithmic advancements for the InfMax problem and designing several problem-specific approaches to overlap communication with computation, improve GPU efficiency, and lower the application’s memory requirements. We evaluate strong scaling for computing 10k most influential seeds using up to 8k nodes of an exascale system, and weak scaling from 128 to 8k system nodes for seed sets ranging from 625 to 40k seeds. We achieve the fastest-known runtime of 25 minutes while performing 48 million diffusion simulations totaling 2.31 petabytes to identify 40k influential seeds using 8k nodes, and take 5.75 minutes to identify 10k seeds while using 4k nodes.

Minutoli, Marco [Pacific Northwest National Labora↗

Defining the Environmental Adaptations of Genus Devosia: Insights into its Expansive Short Peptide Transport System and Positively Selected Genes

Devosia are well known for their dominance in soil habitats contaminated with various toxins and are best characterized for their bioremediation potential. In this study, we compared the genomes of 27 strains of Devosia with aim to understand their metabolic abilities. The analysis revealed their adaptive gene repertoire which was bared from 52% unique pan-gene content. A striking feature of all genomes was the abundance of oligo- and di-peptide permeases (oppABCDF and dppABCDF) with each genome harboring an average of 60.7±19.1 and 36.5±10.6 operon associated genes respectively. Apart from their primary role in nutrition, these permeases may help Devosia to sense environmental signals and in chemotaxis at stressed habitats. Through sequence similarity network analyses, we identified 29 Opp and 19 Dpp sequences that shared very little homology with any other sequence suggesting an expansive short peptidic transport system within Devosia. The substrate determining components of these permeases viz. OppA and DppA further displayed a large diversity that separated into 12 and 9 homologous clusters respectively in addition to large number of isolated nodes. We also dissected the genome scale positive evolution and found genes associated with growth (exopolyphosphatase, HesB_IscA_SufA family protein), detoxification (moeB, nifU-like domain protein, alpha/beta hydrolase), chemotaxis (cheB, luxR) and stress response (phoQ, uspA, luxR, sufE) were positively selected. The study highlights the genomic plasticity of the Devosia spp. for conferring adaptation, bioremediation and the potential to utilize a wide range of substrates. The widespread toxin-antitoxin loci and ‘open’ state of the pangenome provided evidence of plastic genomes and a much larger genetic repertoire of the genus which is yet uncovered.

59 BASIC BIOLOGICAL SCIENCES↗