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Consistent structures and interactions by density functional theory with small atomic orbital basis sets

A density functional theory (DFT) based composite electronic structure approach is proposed to efficiently compute structures and interaction energies in large chemical systems. It is based on the well-known and numerically robust Perdew-Burke-Ernzerhoff (PBE) generalized-gradient-approximation in a modified global hybrid functional with a relatively large amount of non-local Fock-exchange. The orbitals are expanded in Ahlrichs-type valence-double zeta atomic orbital (AO) Gaussian basis sets, which are available for many elements. In order to correct for the basis set superposition error (BSSE) and to account for the important long-range London dispersion effects, our well-established atom-pairwise potentials are used. In the design of the new method, particular attention has been paid to an accurate description of structural parameters in various covalent and non-covalent bonding situations as well as in periodic systems. Together with the recently proposed three-fold corrected (3c) Hartree-Fock method, the new composite scheme (termed PBEh-3c) represents the next member in a hierarchy of “low-cost” electronic structure approaches. They are mainly free of BSSE and account for most interactions in a physically sound and asymptotically correct manner. PBEh-3c yields good results for thermochemical properties in the huge GMTKN30 energy database. Furthermore, the method shows excellent performance for non-covalent interaction energies in small and large complexes. For evaluating its performance on equilibrium structures, a new compilation of standard test sets is suggested. These consist of small (light) molecules, partially flexible, medium-sized organic molecules, molecules comprising heavy main group elements, larger systems with long bonds, 3d-transition metal systems, non-covalently bound complexes (S22 and S66×8 sets), and peptide conformations. For these sets, overall deviations from accurate reference data are smaller than for various other tested DFT methods and reach that of triple-zeta AO basis set second-order perturbation theory (MP2/TZ) level at a tiny fraction of computational effort. Periodic calculations conducted for molecular crystals to test structures (including cell volumes) and sublimation enthalpies indicate very good accuracy competitive to computationally more involved plane-wave based calculations. PBEh-3c can be applied routinely to several hundreds of atoms on a single processor and it is suggested as a robust “high-speed” computational tool in theoretical chemistry and physics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping

Abstract High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. As an extension of a previous study testing 44 chemicals, HTTr was used to screen an additional 1,751 unique chemicals from the EPA’s ToxCast collection in MCF7 cells using 8 concentrations and an exposure duration of 6 h. We hypothesized that concentration-response modeling of signature scores could be used to identify putative molecular targets and cluster chemicals with similar bioactivity. Clustering and enrichment analyses were conducted based on signature catalog annotations and ToxPrint chemotypes to facilitate molecular target prediction and grouping of chemicals with similar bioactivity profiles. Enrichment analysis based on signature catalog annotation identified known mechanisms of action (MeOAs) associated with well-studied chemicals and generated putative MeOAs for other active chemicals. Chemicals with predicted MeOAs included those targeting estrogen receptor (ER), glucocorticoid receptor (GR), retinoic acid receptor (RAR), the NRF2/KEAP/ARE pathway, AP-1 activation, and others. Using reference chemicals for ER modulation, the study demonstrated that HTTr in MCF7 cells was able to stratify chemicals in terms of agonist potency, distinguish ER agonists from antagonists, and cluster chemicals with similar activities as predicted by the ToxCast ER Pathway model. Uniform manifold approximation and projection (UMAP) embedding of signature-level results identified novel ER modulators with no ToxCast ER Pathway model predictions. Finally, UMAP combined with ToxPrint chemotype enrichment was used to explore the biological activity of structurally related chemicals. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points of departure, predicting chemicals’ MeOA and grouping chemicals with similar bioactivity profiles.

Toxicology↗

AI Model Benchmarking for Nonproliferation Applications: Steel Thread Benchmarking Task Force Technical Report (Rev. 2)

Steel Thread is a NA-22 venture that seeks to build trustworthy, reliable AI models that can be used in a wide variety of nonproliferation tasks. A key aspect of building these models is developing appropriate benchmarks and evaluation methods, which will enable the venture to identify and adapt models to provide the most value in the nonproliferation domain. Benchmarks must be relevant to key tasks in this domain, such as question answering, information retrieval, document summarization and classification, consensus analysis, and image and data analysis. This report 1) provides an overview of benchmark design, evaluation, and challenges; 2) reviews a variety of open benchmarks, with a focus on language models and tasks; and 3) identifies benchmarks that are most relevant to Steel Thread. This report is intended to serve as a basis for further efforts to classify and evaluate benchmarks and their correlation with success on nonproliferation-specific tasks. The Steel Thread venture has defined benchmarks to be a particular combination of a dataset (or datasets) and a metric (or metrics) conceptualized as representing one or more specific tasks or sets of abilities for a specific modality. It is adopted by a research community as a shared framework for comparing methods.1 It includes 1) Data: Labeled (a designated subset not used for training, which could be all the data), 2) Metric: A way to quantify performance, 3) Task/Ability: What the benchmark is testing, 4) Protocol: A structured and repeatable evaluation process, 5) Baseline/Reference Model: For comparison; could be statistical, rule-based, SME-derived, or another model, and 6) Maintenance Plan: to update with new information over time; important for long-term utility. For further clarity, the definition includes what a benchmark, in this context, is not. It is not a corpus of training data, specific to a model (it is intended to apply to a range of models), a universal evaluation of performance, a guarantee that the ‘top’ model on the leaderboard will be the best fit for every specific use case, an all-encompassing proof of a model’s universal quality, nor is it a one-size-fits-all measure of success. It does not cover every real-world constraint (like operational, ethical, or cost considerations), a systems integration test, or a unit test. This definition was inspired by and resulted from discussions within the Steel Thread Benchmarking Task Force. This group was formed to define what we would mean as a benchmark within Steel Thread but persisted as the need to develop a thorough understanding of the large and expanding existing benchmarking space. This technical report is a result of the group’s divide and conquer approach to exploring this space. The release of benchmarks might not be progressing as quickly as model development, but it is moving very fast, as many benchmarks quickly become saturated, when state-of-the-art models score so close to the benchmark’s ceiling that their results are virtually indistinguishable. At that point, the test no longer differentiates between new systems, so researchers usually stop reporting scores as the benchmark no longer informs about improvements from the next generation of models. In the OpenAI announcement of GPT-5, they reported results on six flagship public benchmarks (AIME 2025, SWE-bench Verified, Aider Polyglot, MMMU, HealthBench Hard, GPQA) but the full system-card covers roughly thirty-five separate evaluations, comprising hundreds of test task items in total. There have been some efforts to summarize benchmarks in specific fields, like for text-to-image generation, but these surveys have had a narrow methodology scope. Therefore, a comprehensive survey of all benchmarks or even all benchmarks that could be relevant to Steel Thread is outside of the scope of this report. We chose some specific benchmarks to investigate in detail.

97 MATHEMATICS AND COMPUTING↗

PET/CT in brachytherapy early response evaluation of pancreatic ductal adenocarcinoma xenografts: comparison with apparent diffusion coefficient from diffusion-weighted MR imaging

Objective: To evaluate the feasibility of using PET/CT and diffusion-weighted magnetic resonance imaging (DW-MRI) to monitor the early response of pancreatic ductal adenocarcinoma (PDAC) xenografts to brachytherapy, and to determine whether maximum standardized uptake value (SUVmax) correlate with apparent diffusion coefficient (ADC). Materials and Methods: SW1990 human PDAC were subcutaneously implanted in 20 nude mice. They were randomly divided into 125-Iodine ({sup 125}I) seeds and blank seeds group. PET/CT and DW-MRI were performed at pretreatment and 5 days after therapy. SUVmax and ADC values were calculated, respectively. The correlation between SUVmax and ADC values was analyzed by the Pearson correlation test. Results: The SUVmax were significantly decreased between pretreatment and 5 days after {sup 125}I seeds treatment (p < 0.001) and between two groups (p < 0.001). And the ADC values were significantly increased between pretreatment and 5 days after {sup 125}I seeds treatment (p < 0.001) and between two groups (p < 0.001). While in the bank seeds group, there were no significantly difference between pretreatment and after treatment in SUVmax and ADC values (p = 0.057; p = 0.397). SUVmax and ADC correlated significantly and negatively before treatment in both groups (r = − 0.964, R{sup 2} = 0.929, p < 0.001; r = − 0.917, R{sup 2} = 0.841, p < 0.001) and after treatment in the blank seeds group (r = − 0.944, R{sup 2} = 0.891, p < 0.001). But after {sup 125}I seeds treatment there was no significant correlation between SUVmax and ADC (r = − 0.388, R{sup 2} = 0.151, p = 0.268). Conclusion: The PET/CT and DW-MRI are capable of monitoring the early response of PDAC xenografts to brachytherapy. The significantly inverse correlation between pretreatment SUVmax and ADC suggests that PET/CT and DW-MRI might play complementary roles for therapy assessment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Pitting fatigue characteristics of AISI M-50 and super nitralloy spur gears

Two groups of 3.50-in. pitch-diameter spur gears, without tip relief, made from consumable-electrode vacuum-melted (CVM) AISI M-50 steel and CVM super nitralloy (5Ni-2A1) were tested under conditions which produced fatigue pitting. The M-50 gears had fatigue lives approximately 50 percent longer than the super nitralloy gears. Both groups of gears failed by classical rolling-element fatigue at the pitch circle. When the gears were overrun past initial spall formation, the spalled M-50 gear teeth failed by fatigue fracture. The M-50 material had higher wear than the super nitralloy material. Differences in fatigue life and wear were not considered statistically significant.

Townsend, D. P.↗

Resistance exercise prevents plantar flexor deconditioning during bed rest

Because resistance exercise (REX) and unloading induce opposing neuromuscular adaptations, we tested the efficacy of REX against the effects of 14 d of bed rest unloading (BRU) on the plantar flexor muscle group. Sixteen men were randomly assigned to no exercise (NOE, N = 8) or REX (N = 8). REX performed 5 sets x 6-10 repetitions to failure of constant resistance concentric/eccentric plantar flexion every other day during BRU. One-repetition maximum (1RM) strength was tested on the training device. The angle-specific torque-velocity relationship across 5 velocities (0, 0.52, 1.05, 1.75, and 2.97 rad.s-1) and the full range-of-motion power-velocity relationship were assessed on a dynamometer. Torque-position analyses identified strength changes at shortened, neutral, and stretched muscle lengths. Concentric and eccentric contractile work were measured across ten repetitions at 1.05 rad.s-1. Maximal neural activation was measured by surface electromyography (EMG). 1RM decreased 9% in NOE and improved 11% in REX (P < 0.05). Concentric (0.52 and 1.05 rad.s-1), eccentric (0.52 and 2.97 rad.s-1), and isometric angle-specific torques decreased (P < 0.05) in NOE, averaging 18%, 17%, and 13%, respectively. Power dropped (P < 0.05) in NOE at three eccentric (21%) and two concentric (14%) velocities. REX protected angle-specific torque and average power at all velocities. Concentric and eccentric strength decreased at stretched (16%) and neutral (17%) muscle lengths (P < 0.05) in NOE while REX maintained or improved strength at all joint positions. Concentric (15%) and eccentric (11%) contractile work fell in NOE (P < 0.05) but not in REX. Maximal plantar flexor EMG did not change in either group. In summary, constant resistance concentric/eccentric REX completely prevented plantar flexor performance deconditioning induced by BRU. The reported benefits of REX should prove useful in prescribing exercise for astronauts in microgravity and for patients susceptible to functional decline during bed- or chair-bound hospital stays.

NASA Discipline Musculoskeletal↗

A novel targeted plugging and fracture‐adaptable gel used as a diverting agent in fracturing

Abstract Diverting agents that could plug a targeted location and fill different shapes of fractures have attracted an increasing attention in the field of fracturing. In this study, a series of novel diverting agents were prepared by mixing aldehyde sodium alginate (ASA) and amino gelatin (AG) through a Schiff base reaction to form a primary network, polylactic acid (PLA) fibers were added to produce a 3D network, and Ca 2+ was mixed in as an ionic cross‐linking agent to strengthen the cross‐linking points. It was found that gelation time, swelling behavior, and mechanical performance could be controlled by varying the content of aldehyde groups and amino groups. Gelation time could be controlled in 1‐10 minutes. Plugging behavior and degradation tests demonstrated that the hydrogel could suit fractures with various shapes and plug effectively under high temperatures and pressures, and it could eventually become acidic fluid to help clean the wellbore. This novel ASA/AG/PLA hydrogel constitutes a promising environmentally friendly diverting agent in the application of diversion fracturing.

Zhang, Yuyuan↗

Weakly-interacting massive particles in non-supersymmetric SO(10) grand unified models

Here, non-supersymmetric SO(10) grand unified theories provide a framework in which the stability of dark matter is explained while gauge coupling unification is realized. In this work, we systematically study this possibility by classifying weakly interacting dark matter candidates in terms of their quantum numbers of SU(2) L Ⓧ U(1) Y , B – L, and SU(2) R . We consider both scalar and fermion candidates. We show that the requirement of a sufficiently high unification scale to ensure a proton lifetime compatible with experimental constraints plays a strong role in selecting viable candidates. Among the scalar candidates originating from either a 16 or 144 of SO(10), only SU(2) L singlets with zero hypercharge or doublets with Y = 1/2 satisfy all constraints for SU(4) C Ⓧ SU(2) L Ⓧ SU(2) R and SU(3) C Ⓧ SU(2) L Ⓧ SU(2) R Ⓧ U(1) B–L intermediate scale gauge groups. Among fermion triplets with zero hypercharge, only a triplet in the 45 with intermediate group SU(4) C Ⓧ SU(2) L Ⓧ SU(2) R leads to solutions with M GUT > M int and a long proton lifetime. We find three models with weak doublets and Y = 1/2 as dark matter candidates for the SU(4) C Ⓧ SU(2) L Ⓧ SU(2) R and SU(4) C Ⓧ SU(2) L Ⓧ U(1) R intermediate scale gauge groups assuming a minimal Higgs content. We also discuss how these models may be tested at accelerators and in dark matter detection experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Influence of H 2 O and H 2 S on the composition, activity, and stability of sulfided Mo, CoMo, and NiMo supported on MgAl 2 O 4 for hydrodeoxygenation of ethylene glycol

Here in this work, density functional theory (DFT), catalytic activity tests, and in-situ X-ray absorption spectroscopy (XAS) was performed to gain detailed insights into the activity and stability of MoS 2 , Ni-MoS 2 , and Co-MoS 2 catalysts used for hydrodeoxygenation (HDO) of ethylene glycol upon variation of the partial pressures of H 2 O and H 2 S. The results show high water tolerance of the catalysts and highlight the importance of promotion and H 2 S level during HDO. DFT calculations unraveled that the active edge of MoS 2 could be stabilized against SO exchanges by increasing the partial pressure of H 2 S or by promotion with either Ni or Co. The Mo, NiMo, and CoMo catalysts of the present study were all active and fairly selective for ethylene glycol HDO at 400 °C, 27 bar H 2 , and 550–2200 ppm H 2 S, and conversions of ≈50–100%. The unpromoted Mo/MgAl 2 O 4 catalyst had a lower stability and activity per gram catalyst than the promoted analogues. The NiMo and CoMo catalysts produced ethane, ethylene, and C1 cracking products with a C 2 /C 1 ratio of 1.5–2.0 at 550 ppm H 2 S. This ratio of HDO to cracking could be increased to ≈2 at 2200 ppm H 2 S which also stabilized the activity. Removing H 2 S from the feed caused severe catalyst deactivation. Both DFT and catalytic activity tests indicated that increasing the H 2 S concentration increased the concentration of SH groups on the catalyst, which correspondingly activated and stabilized the catalytic HDO performance. In-situ XAS further supported that the catalysts were tolerant towards water when exposed to increasing water concentration with H2O/H2S ratios up to 300 at 400–450 °C. Raman spectroscopy and XAS showed that MoS2 was present in the prepared catalysts as small and highly dispersed particles, probably owing to a strong interaction with the support. Linear combination fitting (LCF) analysis of the X-ray absorption near edge structure (XANES) spectra obtained during in-situ sulfidation showed that Ni was sulfided faster than Mo and CoMo, and that Mo was sulfided faster when promoted with Ni. Extended X-ray absorption fine structure (EXAFS) results showed the presence of MoS 2 in all sulfided catalysts. Lastly, sulfided CoMo was present as a mixture of CoMoS and Co 9 S 8 , whereas sulfided NiMo was present as NiMoS.

09 BIOMASS FUELS↗

Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay

Highlights: • We have modelled household waste generation in Biscay municipalities. • We have identified relevant characteristics regarding household waste generation. • Factor models are used in order to identify the best subset of explicative variables. • Biscay’s municipalities are grouped by means of hierarchical clustering. - Abstract: The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The present works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Elevated temperature alters proteomic responses of individual organisms within a biofilm community

Microbial communities that underpin global biogeochemical cycles will likely be influenced by elevated temperature associated with environmental change. In this paper, we test an approach to measure how elevated temperature impacts the physiology of individual microbial groups in a community context, using a model microbial-based ecosystem. The study is the first application of tandem mass tag (TMT)-based proteomics to a microbial community. We accurately, precisely and reproducibly quantified thousands of proteins in biofilms growing at 40, 43 and 46 °C. Elevated temperature led to upregulation of proteins involved in amino-acid metabolism at the level of individual organisms and the entire community. Proteins from related organisms differed in their relative abundance and functional responses to temperature. Elevated temperature repressed carbon fixation proteins from two Leptospirillum genotypes, whereas carbon fixation proteins were significantly upregulated at higher temperature by a third member of this genus. Leptospirillum group III bacteria may have been subject to viral stress at elevated temperature, which could lead to greater carbon turnover in the microbial food web through the release of viral lysate. Finally, overall, these findings highlight the utility of proteomics-enabled community-based physiology studies, and provide a methodological framework for possible extension to additional mixed culture and environmental sample analyses.

59 BASIC BIOLOGICAL SCIENCES↗

A study of poplar organosolv lignin after melt rheology treatment as carbon fiber precursors

Lignins from various poplar genotypes were isolated by using organosolv fractionation and subjected to rheological treatment at various temperatures. Physicochemical characterization of the lignin variants shows a broad distribution of glass transition temperatures, melt viscosity, and pyrolysis char residues. Rheological treatment at 170 °C induces lignin repolymerization accompanied with an increase in condensed linkages, molecular weights, and viscosities. In contrast, rheology testing at 190 °C results in the decrease in lignin aliphatic and phenolic hydroxyl groups, β-O-aryl ether linkages, molecular weights, and viscosity values. Lignin under air cooling generates more oxygenated and condensed compounds, but lower amounts of ether linkages than lignin cooled under nitrogen. Here, lignin with a lower syringyl/guaiacyl ratio tends to form more cross-linkages along with higher viscosity values, higher molecular weight and larger amounts of condensed bonds.

36 MATERIALS SCIENCE↗

Do triatomic molecules echo atomic periodicity?

Demonstrations of periodicity among triatomic-molecular spectroscopic constants underscore the role of the periodic law as a foundation of chemistry. The objective of this work is to prepare for another test using vibration frequencies ν{sub 1} of free, ground-state, main-group triatomic molecules. Using data from four data bases and from computation, we have collected ν{sub 1} data for molecules formed from second period atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine-Resilience

Here, we study a setting where a group of agents, each receiving partially informative private signals, seek to collaboratively learn the true underlying state of the world (from a finite set of hypotheses) that generates their joint observation profiles. To solve this problem, we propose a distributed learning rule that differs fundamentally from existing approaches, in that it does not employ any form of “belief-averaging”. Instead, agents update their beliefs based on a min-rule. Under standard assumptions on the observation model and the network structure, we establish that each agent learns the truth asymptotically almost surely. As our main contribution, we prove that with probability 1, each false hypothesis is ruled out by every agent exponentially fast, at a network-independent rate that is strictly larger than existing rates. We then develop a computationally-efficient variant of our learning rule that is provably resilient to agents who do not behave as expected (as represented by a Byzantine adversary model) and deliberately try to spread misinformation.

42 ENGINEERING↗

Miniaturize the Redox Flow Battery for Accelerated Materials Discovery and Development

Redox flow batteries are a promising technology for grid-scale energy storage. The aqueous organic redox flow battery is of particular interest for its potentially low material cost and sustainability. Developing novel organic active material for flow battery electrolytes typically entails molecular engineering toward desired properties, necessitating organic synthesis. In a research laboratory setting, the synthesis of specifically designed organic molecules featuring targeted functional groups is time and resources intensive. In the past, synthesizing materials required for battery testing has often required gram-scale production, presenting considerable constraints on the pace of novel organic material discovery. In this report, we introduce a miniaturized cell design that mandates only milligram-scale material synthesis while yielding testing outcomes equivalent or superior to those reported with other commercially available or homemade flow cells in the literature. The test results under various pH conditions validate the scale-down strategy to accelerate the flow battery material discovery and development using the newly designed mini cell. This approach offers researchers an efficient means to notably reduce the time and resources required to develop novel materials for flow batteries.

25 ENERGY STORAGE↗

Quasioptical modeling of wave beams with and without mode conversion: II. Numerical simulations of single-mode beams

This work continues a series of papers where we propose an algorithm for quasioptical modeling of electromagnetic beams with and without mode conversion. The general theory was reported in the first paper of this series, where a parabolic partial differential equation was derived for the field envelope that may contain one or multiple modes with close group velocities. Here, we present a corresponding code PARADE (PAraxial RAy DEscription) and its test applications to single-mode beams in vacuum and also in inhomogeneous magnetized plasma. The numerical results are compared, respectively, with analytic formulas from Gaussian-beam optics and also with cold-plasma ray tracing. Quasioptical simulations of mode-converting beams are reported in the next, third paper of this series.

ECRH↗

BubbleCluster v4

The BubbleCluster algorithm was developed to help address the limitations of traditional genetic mapping tools when presented with large amounts of data. The BubbleCluster software is a tool for the initial stage in the genetic mapping pipeline -- clustering genetic markers into linkage groups. BubbleCluster was designed to tackle large genetic marker data sets, and has been tested on input of up to 1.6M markers. Input format is identical to that of the popular MSTMap package, aiding useability.

Buluc, Aydin↗

A Versatile Click-Compatible Monolignol Probe to Study Lignin Deposition in Plant Cell Walls

Here, lignin plays important structural and functional roles in plants by forming a hydrophobic matrix in secondary cell walls that enhances mechanical strength and resists microbial decay. While the importance of the lignin matrix is well documented and the biosynthetic pathways for monolignols are known, the process by which lignin precursors or monolignols are transported and polymerized to form this matrix remains a subject of considerable debate. In this study, we have synthesized and tested an analog of coniferyl alcohol that has been modified to contain an ethynyl group at the C-3 position. This modification enables fluorescent tagging and imaging of this molecule after its incorporation into plant tissue by click chemistry-assisted covalent labeling with a fluorescent azide dye, and confers a distinct Raman signature that could be used for Raman imaging. We found that this monolignol analog is incorporated into in vitro -polymerized dehydrogenation polymer (DHP) lignin and into root epidermal cell walls of 4-day-old Arabidopsis seedlings. Incorporation of the analog in stem sections of 6-week-old Arabidopsis thaliana plants and labeling with an Alexa-594 azide dye revealed the precise locations of new lignin polymerization. Results from this study indicate that this molecule can provide high-resolution localization of lignification during plant cell wall maturation and lignin matrix assembly.

59 BASIC BIOLOGICAL SCIENCES↗