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Data for In Situ Sequestration of Per- and Polyfluoroalkyl Substances in Aquifer Materials Using Polydiallyldimethyl Ammonium Chloride-Stabilized Powdered Activated Carbon
(2025-03-27) Simcik, Matt; Longo, William; msimcik@umn.edu; Simcik, Matt; University of Minnesota School of Public Health
The widespread use of aqueous film-forming foams (AFFF) for firefighting and fire fighter training activities has led to groundwater contamination with per- and polyfluoroalkyl substances (PFAS). PFAS can be effectively sorbed onto powdered activated carbon (PAC) and the aqueous cationic polymer, polydiallyldimethyl ammonium chloride (PDM). These sorbents form a stable suspension (S-PAC) that can be injected into the subsurface to create a permeable adsorptive barrier (PAB), providing the basis for field-scale in situ PFAS sequestration. A series of bench-scale one-dimensional column experiments were performed to assess the transport and sorption of PFAS in aquifer materials from two field sites with PFAS-contaminated groundwater. Experiments included testing the effect of pre-treatment with PDM and sequential injections of individual PFAS and mixtures. In all experiments, S-PAC enhanced PFAS sorption on site media from > 2-fold (e.g. perfluorohexanoic acid) to > 100-fold (e.g. perfluorooctance sulfonic acid) depending on headgroup, chain length, and influent concentration. Pretreatment of influent with PDM alone increased total PFAS sorption for compounds with sulfonic acid and sulfonamido headgroups by up to ~2-fold relative to S-PAC treatment without PDM pretreatment. Results also demonstrated competition for sorption sites with long-chain PFAS displacing shorter chain length PFAS from the S-PAC, an effect that can potentially be addressed by expanding the treatment zone. S-PAC is a viable treatment for in situ sequestration of PFAS and upstream injection of PDM may enhance removal. Competitive displacement by more strongly sorbed PFAS should be a design consideration when implementing this technology in the field.
Supplemental Data and R File of Material Property Data used in Compression and Fit Modelling Studies
(2025-03-27) Beaudette, Eric; Dunne, Lucy; eric.p.beaudette@gmail.com; Beaudette, Eric; University of Minnesota Wearable Technology Lab
Supplemental record of fabric thickness, weight, and tensile data used for compression modeling. Fabric thickness and fabric weight were averaged across 5 samples for 3 synthetic textiles in various material assemblies to use for compression modeling applications. Each row in these files represents datapoint for either a single layer (textile only), two layer (textile + silicone backed elastic) or three layer (textile + elastic + textile) sample. Samples used for material testing were cut to tensile testing specifications (200 mm by 50 mm strips) and, for two- and three-layer samples, assembled into the appropriate sample type. Fabric weight and thickness (following ASTM D1777-96, 2019) were found before testing for tensile strength (following ISO 13934-1:2013). Testing was conducted across four days with an average temperature of 21.81 C (+/- 0.58 C) and a humidity of 24.13% (+/- 2.03%).
Steroid levels following experimentally induced mating in gray treefrogs during 2024 breeding season (Carver Park Reserve, MN)
(2025-03-27) Freiler, Megan K; Halstead, Liam N; Bee, Mark A; Baugh, Alexander T; megan.k.freiler@gmail.com; Freiler, Megan; University of Minnesota Animal Communication Lab
During amplexus, male frogs clasp a female for several hour prior to gamete release. In this experiment, we tested the hypothesis that amplexus can cause changes in circulating levels of steroid hormones in Cope's gray tree frogs ('Hyla chrysoscelis'). Frogs were collected in breeding ponds in Carver Park Reserve in Minnesota in May and June of 2024. An amplexed pair and two single males were collected in quick succession and brought to the edge of the pond for each experimental trial. In each trial, we quantified levels of testosterone, estradiol, and corticosterone after 90 minutes in four treatment groups: males allowed to enter amplexus with a newly provided female ("amplexus induced"), paired males removed from their mate ("amplexus terminated"), unpaired control males, and the female that was removed from the amplexus terminated male and given to the amplexus induced male.
Data for Detection of 15N-labeled Metabolites in Microbial Extracts using AI-Designed Broadband Pulses for 1H, 15N Heteronuclear NMR Spectroscopy
(2025-03-24) Veliparambil Subrahmanian, Manu; Veglia, Gianluigi; Tonelli, Marco; Bell, Bailey; Sharma, Alok K; S. Bugni, Tim; vegli001@gmail.com; Veglia, Gianluigi; Veglia Lab
This dataset contains the pulse sequence and radiofrequency (RF) shapes for a novel 2D 1H–15N Broadband Heteronuclear Single Quantum Coherence (BB-HSQC) NMR experiment. The data includes an optimized Bruker pulse sequence (bbhsqcetf3gpsi2.3) and AI-designed broadband RF pulse shapes that significantly enhance spectral sensitivity across the full range of 15N chemical shifts. Approximately 40% of bacterial and mammalian metabolites contain nitrogen-based moieties (amides, amines, imines), making their detection crucial for comprehensive metabolomics studies. Traditional NMR experiments face challenges at high magnetic fields due to the difficulty of achieving uniform excitation across the wide 15N chemical shift range. Our AI-designed universal 180° pulse for both inversion and refocusing operations overcomes these limitations. The value of this data lies in its ability to improve the identification and quantification of nitrogen-containing metabolites in biological samples. We've demonstrated its effectiveness by analyzing crude extracts of Micromonospora sp. WMMC264, a microbial strain that produces siderophores for iron absorption. We are releasing this data to advance metabolomics research and provide the scientific community with improved tools for studying nitrogen-containing compounds. The implementation of these AI-designed pulses in 2D 1H–15N BB-HSQC experiments will contribute to more sensitive and accurate analysis of complex biological fluids and cell extracts, expanding the catalog of NMR-detected metabolites.
Data associated with manuscript on the Nonlinear viscoelasticity of the upper mantle to be submitted to JGR: Solid Earth in March 2025
(2025-03-20) Hein, Diede; Hansen, Lars N; hein0477@umn.edu; Hein, Diede; University of Minnesota Rock and Mineral Physics laboratory
This entry contains the energy-dispersive X-ray diffraction data and X-ray radiography of deformation-DIA experiments performed at beamline 6-BM-B of the Advanced Photon Source at Argonne National Lab performed to study the nonlinear viscoelasticity of polycrystalline olivine as well as electron back-scatter diffraction (EBSD) data of the samples and electron microscope images and annotated electron microscope images of decorated dislocations in the samples.
Data, Code (STATA and R) and Supplementary materials for JDS paper: A randomized controlled trial to evaluate the effect of 2 hoof trimming methods at dry-off on hoof lesion and lameness occurrence in dairy cattle
(2025-03-18) Stoddard, Grant; Cook, Nigel; Wagner, Sarah; Solano, Laura; Shepley, Elise; Cramer, Gerard; gcramer@umn.edu; Cramer, Gerard; Cramer Foot Health Lab
Despite hoof trimming (HT) being a recommended procedure for hoof lesion and lameness prevention, there is limited data on the efficacy of different HT methods. Our objective was to compare the effects of HT cows at dry-off with the functional method that uses a little model (LIT) to an adaptation with bigger modeling (BIGM) of the higher load-bearing hoof on the occurrence of new hoof lesions and the risk for lameness in the next lactation. Cows scheduled for their regular HT at dry-off were enrolled weekly from 3 sand-bedded freestall housed herds located in Wisconsin (n = 2) and Minnesota (n = 1). Cows were eligible for enrollment if they did not have hoof horn lesions at their dry-off HT. Cows were allocated to either LIT or BIGM weekly. Locomotion scores were collected on a biweekly basis from 2 herds, once before enrollment and until their subsequent HT or up to 165 DIM. Two trained hoof trimmers collected hoof lesion data either during the cow’s scheduled midlactation HT between 100 and 165 DIM or during an HT prompted by identification as a lame cow by farm personnel. Data were analyzed using multivariable logistic regression, with the presence of any hoof lesion as the outcome of interest and multivariable Cox proportional hazards models, with the presence of lameness as the outcome of interest. A total of 1,556 cows were enrolled, with 790 (51%) cows in the LIT treatment and 766 (49%) cows in the BIGM treatment. The average DIM at the cow’s next HT was 113 (95% CI: 111–114 DIM). A total of 205 (16.2%) of 1,265 cows were identified with a lesion before 165 DIM. A total of 501 (43%) of 1,167 cows were identified as lame following enrollment. There was no evidence of a difference between the LIT and BIGM groups overall when presence of any hoof lesion was considered as the outcome. The median time to lameness was 193 d for LIT and 203 d for BIGM. For the hazard of lameness outcome there was no evidence of a difference between the LIT and BIGM groups overall. However, for both the presence of any hoof lesion and lameness outcomes, a cow’s lactation group modified the effect of BIGM. First-lactation cows trimmed with BIGM had reduced risk of any hoof lesion and specifically reduced risk for hoof horn lesions (risk difference 6.1%, 95% CI: 9.6%–2.5%) and odds 76% (odds ratio 0.24, 95% CI: 0.10%–0.58%). In addition, first-lactation cows and cows with an enrollment locomotion score <3 had a lower hazard of becoming lame in the following lactation if they were allocated to the BIGM treatment, compared with cows trimmed with LIT. In summary, the effect of the BIGM trimming method was modified by factors related to parity and prior lameness status, possibly influenced by bone exostosis on the third phalanx. Therefore, the BIGM HT method should be considered to prevent lameness and hoof lesions when animals are trimmed at their first-lactation dry-off trim.
Controlling Magnetism and Transport at Perovskite Cobaltite Interfaces via Strain-Tuned Oxygen Vacancy Ordering
(2025-03-11) Leighton, Chris; Bose, Shameek; Sharma, Manish; Torija, Maria A; Walter, Jeff; Nandakumaran, Nileena; Dewey, John; Schmitt, Josh; Gazquez, Jaume; Varela, Maria; Zhernenkov, Mikhail; Fitzsimmons, Michael R; Ambaye, Haile; Lauter, Valeria; Hovoka, Ondrej; Berger, Andreas; leighton@umn.edu; Leighton, Chris; Leighton Electronic and Magnetic Materials Lab
Complex oxides such as perovskite cobaltites exhibit rich phenomena at interfaces due to the complex interplay between their structural, defect, electronic, and magnetic degrees of freedom. We study this here in the ferromagnetic metallic cobaltite La1-xSrxCoO3-, using specific substrates to systematically vary both the heteroepitaxial strain (compressive vs. tensile) and growth orientation ((001) vs. (110)). Transmission electron microscopy, electron energy-loss spectroscopy, high-resolution X-ray diffraction, magnetometry, polarized neutron reflectometry, and electronic magnetotransport measurements are applied. Lattice mismatch and growth orientation are found to precisely control interfacial oxygen vacancy ordering in La1-xSrxCoO3-, thus dictating strain relaxation and chemical depth profiles, and in turn controlling thickness-dependent magnetic and electronic properties. In particular, compressive strain and (110) orientations are found to minimize deleterious magnetic/electronic dead layer effects, leading to optimization of interfacial magnetism and transport. Strain and orientation tuning of oxygen vacancy ordering are thus established as powerful means to control physical properties at cobaltite-based interfaces, of relevance to several fields.
Data for Electronic transport across the insulator-metal transition in Co-doped pyrite FeS₂ single crystals
(2025-03-11) Das, Bhaskar; Voigt, Bryan; Moore, William; Lee, Yeon; Maiti, Moumita; Chaturvedi, Vipul; Haugstad, Greg; Manno, Michael; Aydil, Eray; Leighton, Chris; leighton@umn.edu; Leighton, Chris; Leighton Electronic and Magnetic Materials Lab; Department of Chemical Engineering and Materials Science, University of Minnesota
Pyrite FeS₂ is a low-cost, sustainable, non-toxic, 1-eV-band-gap semiconductor with unrealized potential in several application arenas, including photovoltaics. From the fundamental perspective, issues such as surface conduction and the deep-donor nature of S vacancies have hindered the study of low-temperature electronic phenomena in pyrite, including the insulator-metal transition (IMT). Here, we leverage a recently developed CoS₂-based contact scheme in tandem with wide-range doping via shallow Co donors to directly access low-temperature bulk FeS₂ transport properties and thus probe the IMT. Thoroughly characterized FeS₂:Co single crystals are studied over broad ranges of temperature (0.4 – 400 K) and Hall electron density (8.6 × 10¹⁶ – 2.0 × 10²⁰ cm⁻³) through resistivity, Hall effect, and magnetoresistance measurements. The IMT is found to occur near 2 × 10¹⁷ cm⁻³, with Efros-Shklovskii variable-range hopping below this, weak-localization-corrected metallic conductivity above this, and the onset of magnetic effects at the highest doping levels. Most significantly, unexpected additional phenomena are found in the vicinity of the IMT, including a non-linear Hall effect with non-monotonic temperature and doping dependence, and a non-saturating, linear positive magnetoresistance at low temperatures. Quantitative analysis of these phenomena points to unusually strong effect disorder effects in the vicinity of the IMT, further elucidating the electronic behavior of this unique semiconductor.
Data and R-code for "Aquatic Macrophyte and Water Quality Response to Aluminum Sulfate Treatments"
(2025-03-05) Hembre, Kaitlyn; Newman, Raymond M; Bajcz, Alex W; Berg, Matt; James, William; newma004@umn.edu; Newman, Raymond; Minnesota Aquatic Invasive Species Research Center (MAISRC); water
This study examines data from 6 lakes in Minnesota and 2 in Wisconsin to assess the response of aquatic plants and water quality to aluminum sulfate (alum) treatments. The dataset spans from 2011 to 2023 and includes measurements of total epilimnetic phosphorus, Secchi depths, and the frequency of native and invasive macrophyte species. Data were collected directly by project personnel but we also include data provided by project collaborators that were used in the formal analysis. Additional data collected by project personnel, including all point intercept aquatic plant data, temperature, light and dissolved oxygen profiles, and additional water chemistry data are included to facilitate further analysis in the future. Results indicate a marked reduction in total epilimnetic phosphorus levels and improved water clarity (Secchi) after alum treatment, with notable increases in native macrophyte occurrence. Invasive species such as curly-leaf pondweed decreased after alum treat, while Eurasian watermilfoil exhibited variable responses. This comprehensive dataset highlights the effectiveness of alum treatments in enhancing water quality and supporting macrophyte health, with considerations for ongoing invasive species management.
COU: Common Objects Underwater
(2025-02-27) Sattar, Junaed; Mukherjee, Rishi; Singh, Sakshi; McWilliams, Jack; junaed@umn.edu; Sattar, Junaed; Interactive Robotics and Vision Lab
We introduce COU: Common Objects Underwater, an instance-segmented image dataset of commonly found man-made objects in multiple aquatic and marine environments. COU contains approximately 10K segmented images, annotated from images collected during a number of underwater robot field trials in diverse locations. COU has been created to address the lack of datasets with robust class coverage curated for underwater instance segmentation, which is particularly useful for training light-weight, real-time capable detectors for Autonomous Underwater Vehicles (AUVs). In addition, COU addresses the lack of diversity in object classes since the commonly available aquatic image datasets focus only on marine life. Currently, COU contains images from both closed-water (pool) and open-water (lakes and oceans) environments, of 24 different classes of objects including marine debris, dive tools, and AUVs To assess the efficacy of COU in training underwater object detectors, we use three state-of-the-art models to evaluate its performance and accuracy, using a combination of standard accuracy and efficiency metrics. The improved performance of COU-trained detectors over those solely trained on terrestrial data demonstrates the clear advantage of the availability of annotated underwater images.
The experimental and modeled resonance Raman and absorption dataset for pentacene polaritons measured at various angles taken in the Frontiera lab at the University of Minnesota in 2023
(2025-02-24) Alam, Shahzad; Liu, Yicheng; Holmes, Russell J; Frontiera, Renee R; rrf@umn.edu; Frontiera, Renee R.; University of Minnesota Frontiera Research Lab
This dataset contains resonance Raman measurements and angle-resolved reflectivity data for two optical cavities with pentacene layers of 27 nm and 39 nm thickness, as well as a 27 nm pentacene thin film at various angles. Additionally, it includes results from resonance Raman intensity analysis, comprising modeled absorption cross-section and Raman cross-section profiles for the same three systems.
Supporting Dataset for "RT-QuIC Optimization for Prion Detection in Two Minnesota Soil Types" and "Detection of Chronic Wasting Disease Prions in Soil at an Illegal White-tailed Deer Carcass Disposal Site"
(2025-02-24) Grunklee, Madeline K; Bartz, Jason C; Karwan, Diana L; Lichtenberg, Stuart S; Lurndahl, Nicole A; Larsen, Peter A; Schwabenlander, Marc D; Rowden, Gage R; Li, E Anu; Yuan, Qi; Wolf, Tiffany M; wolfx305@umn.edu; Wolf, Tiffany M; Minnesota Center for Prion Research and Outreach (MNPRO)
These data describe prion detections in soil using real-time quaking-induced conversion (RT-QuIC) assay with various metric calculations common to RT-QuIC. The Soil_Cntrl_Expmts_Data.xlsx file contains data from a series of control experiments aimed at optimizing and applying RT-QuIC for the detection of chronic wasting disease prions in environmental soil samples. We focused negative control experiments on refining RT-QuIC and sample processing to use on Minnesota native soils, which included limiting background noise from the samples. Starting on 2023-05-08, we used spiked soil control experiments to distinguish true prion signal from background noise and validate detection reliability. Following soil control experiments, the Soil_Test_Samples_Data.xlsx file describes our sample testing in RT-QuIC collected from our study site, an illegal white-tailed deer (Odocoileus virginianus, WTD) carcass disposal site and a nearby captive WTD farm in Beltrami County, Minnesota. We analyzed study site soil samples for prion presence to assess potential environmental contamination associated with improper carcass disposal practices.
Data in support of "Phenology, food webs, and fish: the effects of loss of lake ice across multiple trophic levels"
(2025-02-21) Rounds, Christopher I; Manske, John; Feiner, Zachary S; Walsh, Jake R; Polik, Catherine A; Hansen, Gretchen J A; round060@umn.edu; Rounds, Christopher; University of Minnesota Fisheries Systems Ecology Lab
This dataset and associated analyses are made to accompany the manuscript, "Phenology, food webs, and fish: the effects of loss of lake ice across multiple trophic levels". Accompanying data is split into components with distinct analyses (lake ice-off, phytoplankton, zooplankton, walleye spawning, walleye young-of-year recruitment, and walleye abundance). Plankton data is collected from Ramsey County, MN, USA lakes and filtered only to include open water season. Walleye spawning is collected by DNR staff as part of egg-take operations in the spring, walleye young-of-year recruitment is indexed by fall electrofishing and was filtered according to (Kundel et al. 2023). Walleye adult abundance is indexed through gillnets during the open water season and has minimum effort and sampling time of year filtering (see MNDNR 2017), unaged fish were applied a HALK to allow for cohort effects to be modeled (based on Frater et al. 2024). All analyses are done using the package mgcv in R and visualized using ggplot2.
Whitewater River Planform Change Analysis
(2025-02-21) England, Hendrick O; Brown, Andrew A; Larson, Phillip H; Hilgendorf, Zach T; Rowen, Jayda K; phillip.larson@mnsu.edu; Larson, Phillip H; MNiMorph (mnimorph.science)
These data include the output of the LCCMR-ENRTF Whitewater River project with specific focus on river channel change and planform analysis.
Anomalous Transport in Dissolving Porous Media: Transitions Between Fickian and Non-Fickian Regimes
(2025-02-17) Deng, Jingxuan; Sharma, Rishabh; Szymczak, Piotr; Kang, Peter K; pkkang@umn.edu; Kang, Peter K; University of Minnesota Kang Research Lab
Mineral dissolution is a key geologic process with broad impacts on natural processes and human activities. Depending on the interplay between advection, diffusion, and reaction rates, mineral dissolution can produce various dissolution patterns, such as wormholing and uniform dissolution. The resulting changes in pore structure directly influence the flow field, which in turn control solute transport behavior. In this study, we conducted numerical modeling of mineral dissolution and solute transport in pore networks to investigate how initial network heterogeneity and dissolution regimes affect transport dynamics. Our findings show that wormholing increases network heterogeneity by creating preferential flow paths and stagnation zones, resulting in a transition from Fickian to non-Fickian transport. Conversely, uniform dissolution extensively homogenizes the pore network and the flow field, leading to a transition from non-Fickian to Fickian transport, even in networks with high initial heterogeneity. Based on the initial heterogeneity and Damköhler number, transitions can be predicted.
Data for Unbiased Clustering of Residues Undergoing Synchronous Motions in Proteins using NMR Spin Relaxation Data
(2025-02-13) Veliparambil Subrahmanian, Manu; Veglia, Gianluigi; Melacini, Giuseppe; L Kovrigin, Evgenii; Loria, J Patrick; mvelipar@umn.edu; Veliparambil Subrahmanian, Manu; Veglia Lab
Carr-Purcell-Meiboom-Gill Relaxation Dispersion (CPMG-RD) experiments are highly effective for probing micro- to millisecond conformational exchange processes in proteins. By performing experiments at multiple magnetic field strengths , one can extract dynamic parameters such as exchange rates, population fractions, and chemical shift differences. PySyncDyn is a comprehensive Python-based toolkit that automates the entire workflow from raw data processing to the generation of Dynamic Correlation (SyncDyn) maps. The workflow includes the calculation of effective transverse relaxation rates , pairwise fitting using the Carver-Richards model, generation of correlation maps, and computation of a SyncDyn Score that quantifies the extent of correlated dynamics across the protein. In addition, the Score2Pymol.py script allows visualization of these scores on the three-dimensional structure of the protein in PyMOL.
Data for Reflection instructions influence 7- to 9-year-olds' metacognition and executive function at the levels of task performance and neural processing
(2025-02-13) Drexler, Colin; Zelazo, Philip David; cdrexler@umn.edu; Drexler, Colin; UMN Developmental Social Cognitive Neuroscience Lab
Though research on metacognitive development has historically remained independent from research on executive function (EF) skills, the two constructs share numerous theoretical similarities. Namely, the skill of reflection, or the ability to consciously reprocess information in real-time, may influence children’s awareness of their own use of EF skills. The present study examined the relations among implicit and explicit forms of metacognition in the Dimensional Change Card Sort (DCCS; Zelazo et al., 2012), while experimentally manipulating the propensity to reflect in 7- to 9-year-olds. Results showed that instructions to reflect led to improved task accuracy and better metacognitive control, but only younger children, as older children were likely reflecting spontaneously. Individual differences in trait mindfulness related to a similarly reflective mode of responding characterized by improved task accuracy and metacognitive control. In contrast, articulatory suppression impaired children’s task accuracy and metacognitive control. Additionally, simply asking children to make metacognitive judgments without extra instructions decreased the amplitude of neural indices of error monitoring, namely the error-related negativity (ERN) and N2 ERP components. Finally, individual differences in trait anxiety were related to larger Pe amplitudes. Taken together, the current findings reinforce theoretical frameworks integrating metacognition and EF, and highlight the shared influence of reflection across multiple levels of analysis.
Supporting data for 3D Printed Anisotropic Tissue Simulants with Embedded Fluid Capsules for Medical Simulation and Training
(2025-02-10) Somayaji, Adarsh; Lawler, Matthew S; Gong, Alex T; Fuenning , Zachary M; Roach, Victoria A; B S, Athira ; Traina, David J; Speich, Jason R; Wang, Ruikang K; Hackett, Matthew G; Hananel, David M; Sweet , Robert M; McAlpine, Michael C; mcalpine@umn.edu; McAlpine, Michael C.; McAlpine Research Group
Human tissues are primarily composed of collagen and elastin fiber networks that exhibit directional mechanical properties which are not replicable by conventional tissue simulants manufactured via casting. Here, we 3D print tissue simulants which incorporate anisotropic mechanical properties through the manipulation of infill voxel shape and dimensions. A mathematical model for predicting the anisotropy of single and multi-material structures with orthogonal infill patterns is developed. We apply this methodology to generate conformal printing toolpaths for replicating the structure and directional mechanics observed in native tissue within 3D printed tissue simulants. Further, a method to embed fluid-filled capsules within the infill structure of these tissue simulants to mimic blood is also presented. The improvements in simulation quality when using 3D printed anisotropic tissue simulants over conventional tissue simulants is demonstrated via a comparative acceptability study. These advances open new avenues for the manufacture of next-generation tissue simulants with high mechanical fidelity for enhanced medical simulation and training.
Supporting data for Renewable Lactam Monomer for Tunable and Processable Polyamides
(2025-02-06) Häkkinen, Satu; Krajovic, Daniel; Chamberlain, Kari; Shippee, Joshua; Biswas, Arpan; Zhang, Honghu; Felsenthal, Lillian; Dichtel, William; Hillmyer, Marc; hillmyer@umn.edu; Hillmyer, Marc; Hillmyer Group
This work aimed to improve the processability and application scope of polyamides by introducing a bio-derivable lactam co-monomer to controllably reduce the polyamides' crystallinity. Tuning the co-monomer composition modulated crystallinity, water uptake, and mechanical properties while achieving newfound solubilities, 3D printability, and structural adhesion properties.
Data for Detection of Exchangeable Protons in NMR Metabolomic Analysis using AI-Designed Water Irradiation Devoid Pulses
(2025-02-06) Veliparambil Subrahmanian, Manu; Veglia, Gianluigi; Vuckovic, Ivan; Macura, Slobodan; mvelipar@umn.edu; Manu, Veliparambil Subrahmanian; Veglia Lab
1H NMR spectroscopy has enabled the quantitative profiling of metabolites in various biofluids, emerging as a possible di-agnostic tool for metabolic disorders and other diseases. To boost the signal-to-noise ratio and detect proton resonances near the water signal, current 1H NMR experiments require solvent suppression schemes (e.g., presaturation, jump-and-return, WATERGATE, excitation sculpting, etc.). Unfortunately, these techniques affect the quantitative assessment of analytes containing exchangeable protons. To address this issue, we introduce two new1D 1H NMR techniques that eliminates the water signal, preserving the intensities of exchangeable protons. Using GENETICS-AI, a software that combines an evolutionary algorithm and artificial intelligence, we tailored new WAter irradiation DEvoid (WADE) pulses and optimized 1D 1H NOESY sequence for metabolomics analysis. When applied to human urine samples, kidney tissue extract, and plasma, the WADE technique allowed for accurate measurement of typical metabolites and direct quantification of urea, which is usually challenging to measure using standard NMR experiments. We anticipate that these new NMR techniques will significantly improve the accuracy and reliability of metabolite quantitative assessment for a wide range of biological fluids.