Michigan Technological University

This laboratory-scale study presents the development and validation of a hydraulic fracturing technique to directly measure the tensile strength of cemented paste backfill (CPB), providing an alternative to traditional strength testing methods. Fracture initiation pressure (FIP) was used as the primary measure of CPB strength. Experimental results were compared with traditional benchmark measures such as uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and critical Mode-I fracture toughness (K Ic ). Regression analysis of experimental results revealed a strong linear relationship between FIP and these benchmark strength measures, indicating that FIP can be used as a reliable predictor of CPB strength. However, traditional linear elastic failure models did not adequately explain the observed FIP values, as they significantly over-predicted the CPB tensile strength. To address this, the Point Stress (PS) model was applied, which provided a more accurate prediction of tensile strength, especially in cases involving small boreholes. The PS model explained observed effects of borehole size on the material’s response to hydraulic pressurization. This study confirms that hydraulic fracturing, interpreted through the PS model, is an effective method for determining CPB strength and provides a practical alternative measure to conventional testing methods.

Purpose. Selecting patients with high-risk intracranial aneurysms (IAs) is of clinical importance. Recent work in machine learning-based (ML) predictive modeling has demonstrated that lesion-specific hemodynamics within IAs can be combined with other information to provide critical insights for assessing rupture risk. However, how the adoption of blood rheology models (i.e., Newtonian and Non-Newtonian blood models) may influence ML-based predictive modeling of IA rupture risk has not been investigated. Methods and Materials. In this study, we conducted transient CFD simulations using Newtonian and non-Newtonian rheology (Carreau-Yasuda [CY]) models on a large cohort of ‘patient-specific’ IA geometries (>100) under pulsatile flow conditions to investigate how each blood model may affect the characterization of the IAs’ rupture status. Key hemodynamic parameters were analyzed and compared, including wall shear stress (WSS) and vortex-based parameters. In addition, velocity-informatics features extracted from the flow velocity were utilized to train a support vector machine (SVM) model for rupture status prediction. Results. Our findings demonstrate significant differences between the two models (i.e., Newtonian versus CY) regarding the WSS-related metrics. In contrast, the parameters derived from the flow vortices and velocity informatics agree. Similar to other studies, using a non-Newtonian CY model results in lower peak WSS and higher oscillatory shear index (OSI) values. Furthermore, integrating velocity informatics and machine learning achieved robust performance for both blood models (area under the curve [AUC] ˃0.85). Conclusions. Our preliminary study found that ML-based rupture status prediction derived from velocity informatics and geometrical parameters yielded comparable results despite differences observed in aneurysmal hemodynamics using two blood rheology models (i.e., Newtonian versus CY).

Plants have evolved a complex regulatory network to cope with heat stress (HS), which includes microRNAs (miRNAs). However, the roles of the entire miRNA biogenesis machinery in HS responses remain unclear. Here, we show that HS induces the majority of miRNAs primarily through the enhanced nuclear localization of HYPONASTIC LEAVES 1 (HYL1), rather than by upregulating MIR gene transcription in Arabidopsis (Arabidopsis thaliana). Disruption of miRNA biogenesis increases plant susceptibility to HS. We also demonstrate that HYL1 phosphorylation modulates its nuclear localization during HS, which is critical for miRNA induction and thermotolerance. MAP KINASE3 (MPK3) phosphorylates and stabilizes the phosphatase C-TERMINAL DOMAIN PHOSPHATASE-LIKE 1 (CPL1), while CPL1 inhibits MPK3 activity, creating a feedback loop that regulates HYL1 phosphorylation. Disruption of MPK3 function results in increased nuclear HYL1 levels and miRNA production, conferring enhanced HS tolerance to mpk3 mutants. These findings reveal a mechanism by which plants enhance miRNA biogenesis during HS, offering insights into the regulatory networks that govern plant thermotolerance.

Thermal convection in a closed chamber is driven by a warm bottom, a cold top, and side walls at various temperatures. Although wall fluxes are the source of convection energy, accurately modeling these fluxes (i.e., the wall model) is challenging. In large-eddy simulations (LESs), many wall models are traditionally derived from the canonical boundary layer, which may be unsuitable for thermal convection bounded by both horizontal and vertical walls. This study conducts a model intercomparison of dry convection in a cubic-meter chamber using three direct numerical simulations (DNSs) and four LESs with different wall models. The LESs employ traditional wall models, a new wall model employing physics-aware neural networks, and a refined grid near the walls. The experiment involves four cases with varying sidewall temperatures. Our results show that LESs capture the main flow features and the trends of mean fluxes. The physics-aware neural networks and refined wall grids can improve the temporally averaged local fluxes when the large-scale circulation has a preferred direction. Even without the local improvement of wall fluxes, the LES flow quantities (temperature and velocities) can still largely match those in DNSs, provided the mean flux largely matches the DNSs. Additionally, DNSs reveal that a variation in corner treatments has minimal impacts on the flow quantities away from corners. Finally, LESs underestimate the mean fluxes of the entire wall due to their inability to resolve corner regions, but their mean flux away from the corner can better match DNS.

The application of noninvasive genetic methods toward the field of conservation has increased our understanding of many wildlife populations that are difficult to sample, allowing for better management. In molecular ecology, the use of noninvasive sampling became widely feasible with the advent of microsatellites, a highly polymorphic, short‐length marker that could be genotyped from low‐quality DNA sources. Despite decades of use, many microsatellite panels continue to suffer from high genotyping error rates, allelic dropout, and limited reproducibility across laboratories. To address these issues, single nucleotide polymorphisms (SNPs) offer advantages such as lower genotyping error rates, avoidance of allelic dropout due to consistent allele length, and automated calling through bioinformatic pipelines, reducing human subjectivity and error. Given the advantages SNPs provide relative to microsatellites as a molecular marker, the use of SNP panels and specifically, the method of genotyping‐in‐thousands by sequencing (GTseq) has gained popularity. Here, we developed a GTseq panel for western Great Lakes canids comprised of 196 loci, capable of species identification, accurately inferring sex (97.2%), identifying unique individuals (probability of identity = 6.71e⁻⁴¹), assigning relationships (false positive rate = 9.34e⁻¹⁴), and assigning genotypes with low error (0.39%). In an attempt to improve genotyping success with low‐quality samples, we found that while increasing the number of PCR cycles yielded a higher percentage of genotyped loci, it also increased on‐target reads in negative PCR controls. We suggest approaching this manipulation with caution and emphasize the importance of including and reporting negative PCR controls. Further, quantitative PCR was a powerful method to estimate host‐specific DNA concentrations, enabling conservative sample selection for library preparation with respect to GTseq affordability.

This study aimed to (i) characterize municipal solid waste (MSW) sourced from Utah and Michigan transfer stations and (ii) upcycle, produce, and evaluate composites derived from this MSW. Composition analysis showed that the MSW was composed of a variety of commodity plastics, paper/cardboard, and inorganic materials. Detailed chemical analysis for lignin, cellulose, hemicellulose, and lipids was performed. The plastics identified were mainly polyethylene, polypropylene, polystyrene, and poly (ethylene terephthalate). The compoundability of the MSW was assessed by torque rheometry. Composites were prepared by compounding the MSW in an extruder. A composite flexural strength of 29 MPa and a modulus of 1.0 GPa was achieved. The thermal properties of the composites were also determined. The melt flow behavior of the MSW composites at 190 °C was comparable to wood plastic composite formulations.

Biomaterials with inherent anti‐inflammatory properties and the ability to foster a pro‐regenerative environment hold significant promise for enhancing cell transplantation and tissue regeneration. Fucoidan, a sulfated polysaccharide with well‐documented immune‐regulatory and antioxidant capabilities, offers strong potential for creating such biomaterials. Yet, there is a lack of engineered fucoidan hydrogels that are injectable and provide tunable physicochemical properties. In this study, the ability of fucoidan to undergo periodate‐mediated oxidation is leveraged to introduce aldehydes into backbone (oxidized fucoidan, OFu), enabling the formation of reversible, imine‐crosslinks with amine‐containing molecules such as gelatin. The imine‐crosslinked OFu‐gelatin hydrogel provided excellent control over gelation rate and mechanical properties. Counter‐intuitively, OFu‐gelatin hydrogel exhibited excellent long‐term stability (≥28 days), even though imine crosslinks are known to be relatively less stable. Moreover, the OFu‐gelatin hydrogels are self‐healing, injectable, and biocompatible, supporting cell culture and encapsulation. Furthermore, fucoidan hydrogels displayed immune‐modulatory properties both in vitro and in vivo. This innovative injectable fucoidan hydrogel presents a versatile platform for applications in tissue engineering and regenerative medicine.

A chemical method suitable for the synthesis of RNAs containing modifications such as N4‐acetylcytidine (ac4C) that are unstable under the basic and nucleophilic conditions used by standard RNA synthesis methods is described. The method uses the 4‐((t‐butyldimethylsilyl)oxy)‐2‐methoxybutanoyl (SoM) group for the protection of exo‐amino groups of nucleobases and the 4‐((t‐butyldimethylsilyl)oxy)‐2‐((aminophosphaneyl)oxy)butanoyl (SoA) group as the linker for solid phase synthesis. RNA cleavage and amino deprotection are achieved using fluoride under the same conditions used for the removal of the 2′‐OH silyl protecting groups. Using this method, a wide range of electrophilic and base‐sensitive groups including those that play structural and regulatory roles in biological systems and those that are artificially designed for various purposes are expected to be able to be incorporated into any position of any RNA sequences. As a proof of concept, several RNAs containing the highly sensitive ac4C epitranscriptomic modification was synthesized and purified with RP HPLC. MALDI MS analysis indicated that the ac4C modification is completely stable under the fluoride deprotection conditions. The sensitive RNA synthesis method is expected to be able to overcome the long‐lasting obstacle of accessing various modified sensitive RNAs to projects in areas such as epitranscriptomics, molecular biology and the development of nucleic acid therapeutics.

The extent and distribution of tropical peatlands, and their importance as a vulnerable carbon (C) store, remain poorly quantified. Although large peatland complexes in Peru, the Congo basin, and Southeast Asia have been mapped in detail, information on many other tropical areas is uncertain. In the Eastern Colombian lowlands, peatland area estimates range from 700 km² to nearly 60,000 km², leading to highly uncertain C stocks. Using new field data, high‐resolution Earth observation (EO), and a random forest approach, we mapped peatlands across Colombian territory East of the Andes below 400 m elevation. We estimated peatland extent using two approaches: a conservative method focused on medium‐to‐high peat probability areas and a more inclusive one accounting for large low‐probability areas. Multiplying these extents by below‐ground carbon density yields a conservative estimate of 0.95 (0.6–1.39 Pg C, 95% confidence interval) over 9,391 km² (7,369–11,549 km²) and up to 2.86 Pg C (1.76–4.22 Pg C) across 29,069 km² (22,429–36,238 km²). Among four potentially peat‐forming ecosystems identified, palm swamps and floodplain forests contributed most to the peat extent and C stock. We found that most peatland patches were relatively small, covering less than 100 ha. We compared our map to previously published global and pan‐tropical peat maps and found low spatial overlap among them, suggesting that peat maps uninformed by local field information may not precisely specify which landscape areas within a peatland‐rich region are actually peatlands. We further assessed the suitability of different EO and climate variables, highlighting the need for high‐resolution data to capture local heterogeneities in the landscape.

Aqueous two‐phase systems (ATPS) are a liquid–liquid extraction method that offers low‐cost, continuous‐adaptable virus purification. A two‐step ATPS using polyethylene glycol (PEG) and sodium citrate that recovered 66% of infectious porcine parvovirus with 2.0 logs of protein removal and 1.0 logs of DNA removal in batch has now been run continuously. The continuous system output of <10 ng/mL DNA regardless of starting DNA titer agreed with batch studies. However, the continuous system had a five‐fold higher contaminating protein titer than batch studies, likely because of incomplete mixing or settling. Turbidity was tested as a measure of mixing and settling efficiency. Monitoring in‐line absorbance at 880 nm directly after mixing and before collection in the settling reservoir could track both mixing and settling during operation. Settling time was reduced by changing the settling line material from PVC to PTFE, which is more hydrophobic. A flow‐through AEX filter tested to make impurity removal more robust recovered 90% of PPV and removed an additional 87% of host cell DNA. The filter did not add any additional protein removal. In the future, in‐line absorbance sensors could be implemented along with conductivity sensors to measure salt concentration, refractive index sensors to track the PEG‐citrate interface, and scales to track mixer and reservoir volumes to enable automated, continuous ATPS. Our vision is to integrate continuous ATPS into a fully continuous end‐to‐end production for viral vectors.

Biomaterials are increasingly used as implants in the body, but they often elicit tissue reactions due to the immune system recognizing them as foreign bodies. These reactions typically involve the activation of innate immunity and the initiation of an inflammatory response, which can persist as chronic inflammation, causing implant failure. To reduce these risks, various strategies have been developed to modify the material composition, surface characteristics, or mechanical properties of biomaterials. Moreover, bioactive materials have emerged as a new class of biomaterials that can induce desirable tissue responses and form a strong bond between the implant and the host tissue. In recent years, different immunomodulatory strategies have been incorporated into biomaterials as drug delivery systems. Furthermore, more advanced molecule and cell‐based immunomodulators have been developed and integrated with biomaterials. These emerging strategies will enable better control of the immune response to biomaterials and improve the function and longevity of implants and, ultimately, the outcome of biomaterial‐based therapies.

Objective. This study aimed to establish a link between the microstructure of simulated fibrotic liver tissues and the measured shear wave speed (SWS) variability using a machine-learning (ML)-based approach. Approach. Fibrotic liver tissues were simulated using biphasic random fields. The underlying microstructure of the simulated fibrotic liver pathology (sFLP) was characterized using spatial pattern distribution analysis. A ML technique was implemented to identify top-rated spatial characteristic (SC) features and provide context for SWS variability, ultimately enabling us to use the SWS variability to infer its underlying tissue microstructure. Different combinations of top three features were tested to understand the sensitivity of our parameter selection. Main results. Even though volume fraction and the SWS estimates were highly correlated, percent inclusion by itself as a single predictive factor was not an accurate indicator of the SWS estimates. For the sFLP tissue models developed for the current study, none of the individual SC features were able to predict the SWS estimates. Regardless of the top features identified, the model prediction correlation remained constant for each prediction iteration. However, even though the top three features across the five ML-based prediction iterations had different specific names, the features were all highly correlated. Significance. The findings from our current study suggest that while the percent inclusion rate was highly correlated to the mean SWS and SWS-STD, the percent inclusion rate alone cannot predict mean SWS or SWS-STD. mean SWS and SWS-STD provide unique information regarding the sFLP tissue microstructure, and both SWS estimates should be considered when analyzing fibrotic liver tissue. Consistent feature identification with previous published studies demonstrated that the sFLPs developed for this study may be representative of real-world patient data.

Rivers produce and decompose large amounts of carbon globally due, in part, to high rates of gross primary production (GPP) and ecosystem respiration (ER), collectively known as ecosystem metabolism. Water temperature is a major driver of ecosystem metabolism, and in‐stream temperatures are increasing globally, including extreme temperature events called heatwaves. This study used published estimates of daily GPP and ER from 48 stream and river locations in the United States to examine how ecosystem metabolism responds to riverine heatwaves. During low‐severity heatwaves, GPP and ER increase proportionally, resulting in no net difference. However, during severe and extreme heatwaves, GPP declined up to 82% while ER increased up to 47%, resulting in greater rates of heterotrophy (ER > GPP). While rivers were typically heterotrophic outside of heatwave conditions, these results suggest that during heatwaves, rivers become stronger sources of carbon dioxide.

Ecosystems are experiencing changing global patterns of mean annual precipitation (MAP) and enrichment with multiple nutrients that potentially colimit plant biomass production. In grasslands, mean aboveground plant biomass is closely related to MAP, but how this relationship changes after enrichment with multiple nutrients remains unclear. We hypothesized the global biomass–MAP relationship becomes steeper with an increasing number of added nutrients, with increases in steepness corresponding to the form of interaction among added nutrients and with increased mediation by changes in plant community diversity. We measured aboveground plant biomass production and species diversity in 71 grasslands on six continents representing the global span of grassland MAP, diversity, management, and soils. We fertilized all sites with nitrogen, phosphorus, and potassium with micronutrients in all combinations to identify which nutrients limited biomass at each site. As hypothesized, fertilizing with one, two, or three nutrients progressively steepened the global biomass–MAP relationship. The magnitude of the increase in steepness corresponded to whether sites were not limited by nitrogen or phosphorus, were limited by either one, or were colimited by both in additive, or synergistic forms. Unexpectedly, we found only weak evidence for mediation of biomass–MAP relationships by plant community diversity because relationships of species richness, evenness, and beta diversity to MAP and to biomass were weak or opposing. Site-level properties including baseline biomass production, soils, and management explained little variation in biomass–MAP relationships. These findings reveal multiple nutrient colimitation as a defining feature of the global grassland biomass–MAP relationship.

Lake heatwaves (extreme hot water events) can substantially disrupt aquatic ecosystems. Although surface heatwaves are well studied, their vertical structures within lakes remain largely unexplored. Here we analyse the characteristics of subsurface lake heatwaves (extreme hot events occurring below the surface) using a spatiotemporal modelling framework. Our findings reveal that subsurface heatwaves are frequent, often longer lasting but less intense than surface events. Deep-water heatwaves (bottom heatwaves) have increased in frequency (7.2 days decade⁻¹), duration (2.1 days decade⁻¹) and intensity (0.2 °C days decade⁻¹) over the past 40 years. Moreover, vertically compounding heatwaves, where extreme heat occurs simultaneously at the surface and bottom, have risen by 3.3 days decade⁻¹. By the end of the century, changes in heatwave patterns, particularly under high emissions, are projected to intensify. These findings highlight the need for subsurface monitoring to fully understand and predict the ecological impacts of lake heatwaves.

This review examines three aspects of hexagonal boron nitride (h-BN) nanomaterials: properties, synthesis methods, and biomedical applications. We focus the scope of review on three types of h-BN nanostructures: boron nitride nanosheets (BNNSs, few-layered h-BN, larger than ∼100 nm in lateral dimensions), boron nitride quantum dots (BN QDs, smaller than ∼10 nm in all dimensions, with inherent excitation-dependent fluorescence), and boron nitride dots (BN dots, smaller than ∼10 nm in all dimensions, wide bandgap without noise fluorescence). The synthesis methods of BNNSs, BN QDs, and BN dots are summarized in top-down and bottom-up approaches. Future synthesis research should focus on the scalability and the quality of the products, which are essential for reproducible applications. Regarding biomedical applications, BNNSs were used as nanocarriers for drug delivery, mechanical reinforcements (bone tissue engineering), and antibacterial applications. BN QDs are still limited for non-specific bioimaging applications. BN dots are used for the small dimension to construct high-brightness probes (HBPs) for gene sequence detections inside cells. To differentiate from other two-dimensional materials, future applications should focus on using the unique properties of BN nanostructures, such as piezoelectricity, boron neutron capture therapy (BNCT), and their electrically insulating and optically transparent nature. Examples would be combining BNCT and chemo drug delivery using BNNSs, and using BN dots to form HBPs with enhanced fluorescence by preventing fluorescence quenching using electrically insulating BN dots.

A chemical method suitable for the synthesis of RNAs containing modifications such as N4‐acetylcytidine (ac4C) that are unstable under the nucleophilic conditions used by standard RNA synthesis methods is described. The method uses the 4‐((t‐butyldimethylsilyl)oxy)‐2‐methoxybutanoyl (SoM) group for the protection of exo‐amino groups of nucleobases and the 4‐((t‐butyldimethylsilyl)oxy)‐2‐((aminophosphaneyl)oxy)butanoyl (SoA) group as the linker for solid phase synthesis. RNA cleavage and amino deprotection are achieved using fluoride under the same conditions used for the removal of the 2′‐OH silyl protecting groups. Using this method, a wide range of electrophilic and base‐sensitive groups including those that play structural and regulatory roles in biological systems and those that are artificially designed for various purposes are expected to be able to be incorporated into any position of any RNA sequences. As a proof of concept, several RNAs containing the highly sensitive ac4C epitranscriptomic modification was synthesized and purified with RP HPLC. MALDI MS analysis indicated that the ac4C modification is completely stable under the fluoride deprotection conditions. The sensitive RNA synthesis method is expected to be able to overcome the long‐lasting obstacle of accessing various modified sensitive RNAs to projects in areas such as epitranscriptomics, molecular biology and the development of nucleic acid therapeutics.

Wave surfing is a multi-billion dollar industry involving both maneuverability and speed, yet little research has been performed regarding the highest lift-to-drag-ratio fin shape for these competing qualities. Numerical modeling and laboratory experiments were performed here to identify a bio-inspired fin shape that maximized lateral stability and minimized drag forces, in order to increase surfing maneuverability. Nine fins based on dorsal fins of real fish were tested. Both the CFD and laboratory experiments confirmed that the fin of the same shape as that of the Short-Finned Pilot Whale at an angle of attack of 10° had the greatest lift-to-drag ratios. Flow patterns around fins at a low angle of attack were smooth with negligible flow separation, while at any angle of attack greater than 25°, flow-separation-induced drag forces became excessive.

Climate change may transform peatlands from net carbon (C) sinks to C sources, which could result in a positive feedback to global warming. Warmer temperatures might lower water tables, increase the abundance of shrubs, slow Sphagnum and sedge growth and further accelerate the decomposition of dissolved organic matter (DOM) with a concomitant release of C from the surface. Studies in which vascular plant functional groups (PFGs) in peatlands have been manipulated to mimic the potential effects of a warming climate on DOM are scarce. In the subject study, seasonal effects of PFGs on the molecular composition of DOM of peat porewater were investigated in manipulated plots of a poor fen in Nestoria, Michigan, United States. The organic molecular composition of the peat porewater exhibited strong interactions with PFG and season. Monomeric substances (e.g., monosaccharides and amino acids), which are found in root exudates and are also the products of decomposition of polymeric substances, were least abundant early in the growing season and increased in abundance late in the season. High levels of DOC and proteinaceous substances and an unlikely abundance of total phenolic substances in sedge plots with Sphagnum were attributed (1) to rapid decomposition of labile compounds in the oxygen-rich microenvironment surrounding sedge roots and preservation of more recalcitrant substances or (2) to contributions of lignin-like substances by Sphagnum. Tannin- and lignin-like compounds in the Ericaceae plots with Sphagnum were attributed to inputs of the woody biomass. The refractory organic substances apparently persisted due to a combination of rhizosphere anoxia and suppression of free-living saprotroph activity by the Ericoid mycorrhizal fungi. Through a novel analytic approach, which included organic compound class analysis, determination of spectral indices, and molecular analysis by ESI-UHR-MS, we observed indirect evidence of the complexation of proteinaceous substances by tannin-like substances and the apparent reaction of phenolic moieties of lignin-like substances with amino sugars. A synergistic effect between sedge and Ericaceae was likely responsible for rapid decomposition of DOM in plots with Sphagnum in which vascular PFGs were unmanipulated. Observing the effects of vascular PFGs on seasonal variations of the molecular composition of DOM will improve predictions of the short- and long-term storage of C in peatlands in a changing climate.