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At least 919 records · Page 51

Dynamic self-assembly of compartmentalized DNA nanotubes

Abstract Bottom-up synthetic biology aims to engineer artificial cells capable of responsive behaviors by using a minimal set of molecular components. An important challenge toward this goal is the development of programmable biomaterials that can provide active spatial organization in cell-sized compartments. Here, we demonstrate the dynamic self-assembly of nucleic acid (NA) nanotubes inside water-in-oil droplets. We develop methods to encapsulate and assemble different types of DNA nanotubes from programmable DNA monomers, and demonstrate temporal control of assembly via designed pathways of RNA production and degradation. We examine the dynamic response of encapsulated nanotube assembly and disassembly with the support of statistical analysis of droplet images. Our study provides a toolkit of methods and components to build increasingly complex and functional NA materials to mimic life-like functions in synthetic cells.

59 BASIC BIOLOGICAL SCIENCES↗

Direct flue gas capture for algae cultivation and subsequent valorization: evaluating life cycle emissions and costs

Algae cultivation and processing is an important pathway under discussion within the broader CO 2 capture and utilization umbrella. Here, we discuss the results of a life-cycle analysis and techno-economic analysis of a pilot-scale photobioreactor that uses flue gas directly from natural gas or biogas combustion at 3–5% CO 2 concentration. The system requires minimal freshwater use as it has been successfully run with industrial wastewater and has a much smaller areal footprint compared with open pond cultivation. Introducing the flue gas directly to the photobioreactor avoids the need for CO 2 separation and pressurization, which is undertaken in many other algae cultivation systems. For the end-use of the biomass, the default case assumes conversion of algae to liquid fuels via hydrothermal liquefaction. The results indicate that the pilot-scale system has a higher cost, and comparable greenhouse gas emissions compared to pond-based systems, especially as the grid is anticipated to evolve to a lower carbon intensity. The costs of algae biofuel production range from $\$12–16$ per GGE at the current pilot scale. Depending on whether the source of the carbon is fossil or biogenic, the net emissions are 68 g CO 2 e per MJ and −4 g CO 2 e per MJ respectively. If the marine algae species is used instead of the freshwater species, it offers an additional 16 g CO 2 e per MJ carbon fixation in the form of calcium carbonate. The findings point to broadly desirable trends in GHG emissions and costs, while the discussion aims to shed light on areas that could further improve the scalability of the system.

20 FOSSIL-FUELED POWER PLANTS↗

Probing two-path electron quantum interference in strong-field ionization with time-correlation filtering

We report attosecond dynamics in strong-field tunnel ionization are encoded in intricate holographic patterns in the photoelectron momentum distributions. These patterns show the interference between two or more superposed quantum electron trajectories, which are defined by their ionization times and subsequent evolution in the laser field. We determine the ionization time separation between interfering pairs of electron orbits by performing a differential Fourier analysis on the measured momentum spectrum. We identify electron holograms formed by trajectory pairs whose ionization times are separated by less than a single quarter cycle, between a quarter cycle and half cycle, between a half cycle and three fourths of a cycle, and a full cycle apart. We compare our experimental results to the predictions of the Coulomb quantum orbit strong-field approximation (CQSFA) with significant success. We also time-filter the CQSFA trajectory calculations to demonstrate the validity of the technique on spectra with known time correlations. As a general analysis technique, the filter can be applied to all energy- and angularly resolved data sets to recover time correlations between interfering electron pathways, providing an important tool to analyze any strong-field ionization spectra. Moreover, it is independent of theory and can be applied directly to experiments, without the need of a direct comparison with orbit-based theoretical methods.

74 ATOMIC AND MOLECULAR PHYSICS↗

Spectrometer-free quantitative vapor sensing and classification via spatiotemporal imaging of porous silicon metasurfaces

Metasurfaces offer a compact platform for optical vapor sensing, but their practical deployment has been limited by weak evanescent light–matter interactions and reliance on spectrally resolved instrumentation. Here, we report porous silicon (pSi) metasurfaces for spectrometer-free quantitative detection of volatile organic compounds (VOCs) with strongly enhanced light–matter interaction. The engineered porosity increases sensitivity by >100× relative to non-porous dielectric metasurfaces, enabling limits of detection of 1.65 ppm for methanol and 9.1 ppm for ethanol across a broad dynamic range (<10 ppm to >103 ppm). Imaging-based readout provides a lightweight, spectrometer-free pathway for real-time quantitative sensing. Beyond quantitative detection, the mesoporous architecture introduces adsorption–desorption kinetics as an additional information channel. Analysis of the resulting spatiotemporal signatures enables kinetic fingerprinting without reliance on infrared spectral features or surface functionalization, and a lightweight machine-learning classifier differentiates acetone, methanol, ethanol, and isopropanol with 91.6% accuracy. These results establish porous metasurfaces as spatiotemporal sensing elements that couple quantitative vapor detection with kinetic fingerprinting through real-time dynamical responses, enabling low-cost, high-performance optical sensors.

Dash, Tomoshree [Clemson University]↗

GREET-Based Interactive Life-Cycle Assessment of Biofuel Pathways: User Manual

An interactive, web-based tool was developed to streamline the process design for biofuel pathways that the Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) is developing. The tool utilizes the latest life-cycle analysis (LCA) data in the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model developed by Argonne National Laboratory (Argonne National Laboratory, 2021). It provides techno-economic analysis (TEA) modelers with a interative interface that generates real-time LCA results based on life-cycle inventory (LCI) data and generates useful insights into key emissions drivers. Economic implications of the LCA results are also included in the tool. Overall, the tool aims to assist TEA researchers with the development of economically viable and environmentally beneficial biofuel technologies. This manual introduces the interface and analysis capabilities of the tool.

09 BIOMASS FUELS↗

Engineering Methanogenic Microbiomes to Redirect Flux to Biomass

In this study, we present a method for acquiring and characterizing novel microbial consortia that regulates methanogens and methanotrophs through selective cultivation and metagenomic analysis of indigenous microorganisms in the environment. In addition, we present the work performed as part of this project to model the pathways that act as limiting factors in microbial methane metabolism based on a carbon cycle model. In this report, we describe the methods for selective cultivation of methane-metabolism-related microorganisms from environmental samples, the method for monitoring their methane consumption performance, and the method and results for verifying their functions using quantitative PCR and metagenomics techniques. The microbial consortia containing methanotrophs were obtained through selective cultivation and molecular biological verification, and their methane consumption performance was evaluated. In addition, the potential of the existence of bacteriophages interacting with methane metabolism-related microorganisms was identified through metagenomic sequencing.

09 BIOMASS FUELS↗

Developing a Framework for Valuation of Grid Services

The electric system is rapidly evolving and growing, raising new questions about how to define and value grid services delivered by a diverse set of resources, including customer-owned assets. This report advances a service–parameter–value framework that links what a grid service does to why it matters, and how its benefits are evidenced. We build upon prior efforts (Bender et al. 2021) and extend them to include value categories (reliability, resilience, cost & access, and security) with primary and secondary tiers, service-specific value streams that explain how benefits materialize, and metrics that make valuation traceable and comparable. We apply the framework to the six core grid services defined in (Kolln et al. 2023): Frequency Response, Regulation, Reserves, Energy, Voltage Management, and Blackstart and demonstrate it on three use cases to highlight the adaptability of these value streams. Further, we outline how the framework integrates with existing tools such as asset optimization, hosting capacity and cost-benefit analysis, and propose a path to portable qualifications and consistent stacking rules for use in tariffs and filings. Finally, we identify future pathways for research and application research needs to support standardization and decision-ready comparisons across services, assets, and architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

Grid Interconnection and Renewables Deployment Related Air Quality and Human Health Benefits in Southeast Asia

The Association of Southeast Asian Nations (ASEAN) has increasingly focused on multilateral electricity trade, improved grid resiliency and modernization. These opportunities in the power sector have been studied through the ASEAN Interconnection Masterplan Studies, the most recent of which is the ASEAN Interconnection Masterplan Study III (AIMS III). AIMS III assessed four different scenarios of power system in the ASEAN countries that include a base scenario and three additional scenarios (called optimum RE, ASEAN RE, and High RE) considering different levels of deployment of renewable energy (RE) and cross-border generation and trade of electricity for three years (2025, 2030, 2040). In this work, we quantify the potential air quality and public health co-benefits of AIMS III scenarios. For a rapidly expanding, energy hungry region like SE Asia generation is power generation is expected to increase significantly. The AIMS III scenarios' capacity expansion modeling suggest that: 1) Generation nearly doubles from 2025 to 2040 in all four AIMS III scenarios; 2) Most of the increased generation is met by coal in all four AIMS III scenarios; 3) While renewables generation increases in all four AIMS III scenarios, the fraction of total generation (its share) generally decreases because of the much greater increase in non-renewable sources, mostly coal. Only in the High RE Target scenario do renewables represent a higher share in 2040 than in 2025, though even here it is at the expense of natural gas rather than coal; 4) As a result, emissions of gaseous and aerosol pollutants increase significantly in all scenarios. Because emissions increase in 2040 compared to 2025 for all four AIMS III scenarios, so do PM2.5 concentrations. Even for the High RE Target scenario (the scenario with highest share of renewable energy), compared to the Base scenario in 2025, in 2040 PM2.5 concentrations are higher. Compared to the Base scenario in the same years, the Optimum RE and ASEAN RE Target scenarios do not differ very much from the Base in terms of PM2.5 concentration. The High RE Target scenario, on the other hand, yields noticeably lower PM2.5 concentration. For example, in 2040 the population-weighted decrease in annual average PM2.5 concentration in the High RE Target scenario relative to the Base scenario is 0.5 ug m-3. Compared to the Base scenario in 2040, each of the alternative AIMS III scenarios is estimated to result in net reductions in power-sector air quality-related excess mortality in the ASEAN region. Yet there are a few countries for which the Optimum RE and ASEAN RE Target result in increases in PM2.5-related excess mortality (Thailand and Vietnam for the ASEAN RE Target scenario and Thailand for the Optimum RE scenario). However, for the High RE Target scenario, all countries benefit and find reductions in excess mortality resulting from the power sector scenarios modeled in AIMS III with regionwide mortality decreasing by 16,000 compared to the Base scenario in 2040. In summary, our analysis finds that changing power generation emissions is a crucial lever for improving public health in ASEAN member countries and provides a pathway for policymakers to make decision backed by a realistic power sector expansion and air quality analyses.

air quality↗

Novosphingobium aromaticivorans LigR coordinates transcription of genes involved in metabolism of multiple types of aromatics

Aromatic compounds are a ubiquitous and diverse family of chemicals with functions as biomolecules, natural products, industrial chemicals, and pollutants. Novosphingobium aromaticivorans DSM 12444 uses multiple inducible pathways to catabolize H-, G-, and S-type aromatics that contain zero, one, or two methoxy groups, respectively. Here, we obtain a systems-level view of the transcriptional control of its aromatic metabolic pathways. Several in vitro analyses found that a N. aromaticivorans homolog of the Sphingobium lignivorans SYK-6 transcription factor LigR bound genomic DNA upstream of genes involved in metabolism of multiple aromatic types. We found that a ΔLigR mutant had growth defects on all three types of aromatics as sole carbon sources. Transcriptomic analysis revealed that LigR was required to increase expression of gene products that function in metabolism of all three aromatic types. We also found that, in media containing both glucose and an aromatic carbon source, the ΔLigR mutant directed intermediates through alternative aromatic metabolic pathways. Protein-DNA binding assays showed that N. aromaticivorans LigR binds immediately upstream of promoters of genes involved in aromatic metabolism. We found that N. aromaticivorans LigR coordinates the expression of enzymes that function in the catabolism of H-, G-, and S-type aromatics, and that there are differences in the role of LigR in N. aromaticivorans and S. lignivorans. A comparative genomic analysis predicted that LigR homologs and the aromatic-metabolizing genes that it directly regulates are often co-localized in the genomes of Sphingomonadales, but often not found in this arrangement in many other known aromatic metabolizing bacteria.

Aromatic Compound Degradation↗

7-Deazaguanines in DNA: functional and structural elucidation of a DNA modification system

Abstract The modified nucleosides 2′-deoxy-7-cyano- and 2′-deoxy-7-amido-7-deazaguanosine (dPreQ0 and dADG, respectively) recently discovered in DNA are the products of the bacterial queuosine tRNA modification pathway and the dpd gene cluster, the latter of which encodes proteins that comprise the elaborate Dpd restriction–modification system present in diverse bacteria. Recent genetic studies implicated the dpdA, dpdB and dpdC genes as encoding proteins necessary for DNA modification, with dpdD–dpdK contributing to the restriction phenotype. Here we report the in vitro reconstitution of the Dpd modification machinery from Salmonella enterica serovar Montevideo, the elucidation of the roles of each protein and the X-ray crystal structure of DpdA supported by small-angle X-ray scattering analysis of DpdA and DpdB, the former bound to DNA. While the homology of DpdA with the tRNA-dependent tRNA-guanine transglycosylase enzymes (TGT) in the queuosine pathway suggested a similar transglycosylase activity responsible for the exchange of a guanine base in the DNA for 7-cyano-7-deazaguanine (preQ0), we demonstrate an unexpected ATPase activity in DpdB necessary for insertion of preQ0 into DNA, and identify several catalytically essential active site residues in DpdA involved in the transglycosylation reaction. Further, we identify a modification site for DpdA activity and demonstrate that DpdC functions independently of DpdA/B in converting preQ0-modified DNA to ADG-modified DNA.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-scale structural analysis of swift heavy ion-irradiated ZrO 2 and HfO 2

The radiation-induced monoclinic-to-tetragonal phase transition in ZrO 2 and HfO 2 has been the subject of many investigations, but the transformation pathways and underlying structural mechanisms are still not well understood. In this study, microcrystalline powder samples of ZrO 2 and HfO 2 were irradiated with 946 MeV and 1470 MeV Au ions to a wide fluence range up to 3 × 10 13 ions/cm 2 . To characterize beam-induced structural modifications across all spatial length scales, complementary experimental techniques such as synchrotron X-ray diffraction and spallation neutron total scattering were used. The phase evolution of the tetragonal polymorph with increasing ion fluence is accurately described by a heterogeneous track-overlap model that incorporates both direct- and double-impact processes. These damage accumulation processes are an expression of a core-shell ion track morphology that depends on irradiation conditions and target material. Neutron pair distribution function analysis revealed that ion-beam-induced tetragonal ZrO 2 is merely a configurational average of short-range orthorhombic (Pbcn) domains stabilized by a dense network of domain walls. Furthermore, this knowledge is critical for a better understanding of how crystalline-to-crystalline phase transformations proceed at the atomic scale under extreme conditions.

Monoclinic-to-tetragonal phase transformation↗

Metabolic flux, metabolite, and transcript analysis uncover reprogramming of metabolism toward higher seed oil

Overexpression of WRINKLED1 (WRI1), a master regulator of glycolysis and fatty acid biosynthesis, together with DIACYLGLYCEROL ACYLTRANSFERASE1 (DGAT1), which catalyzes the final step of triacylglycerol assembly, is a promising strategy for enhancing seed oil content. However, how these regulators coordinate system-wide metabolic reprogramming at the levels of gene expression, metabolite pools, and fluxes remains poorly understood. To address this, we performed 13 C-metabolic flux analysis, metabolomics, and transcriptomics on in vitro cultured pennycress (Thlaspi arvense L.) embryos overexpressing the native WRI1 and DGAT1 homologs. Here, in cultured embryos, WRI1/DGAT1 overexpression increased triacylglycerol accumulation by 28% while reducing protein content by 34%, relative to the wild type. Embryos showed ∼20-fold and 50-fold upregulation of WRI1 and DGAT1 along with induction of WRI1 target genes in glycolysis and fatty acid biosynthesis. Genes associated with photosynthesis and Calvin cycle functions were also upregulated, whereas genes encoding ribosomal proteins and seed storage proteins were strongly repressed, consistent with the observed lipid–protein tradeoff. Flux analysis revealed that enhanced triacylglycerol biosynthesis is supported by increased flux through the Rubisco shunt and cytosolic pyruvate kinase, while the oxidative pentose phosphate pathway and malic enzyme contributed little to NADPH or pyruvate supply. Metabolomic profiling revealed extensive perturbations in glycolytic intermediates, tricarboxylic acid cycle metabolites, and amino acids. In plant grown seeds, WRI1/DGAT1 lines also showed a modest but significant increase in total lipid content. Collectively, these findings reveal how WRI1 and DGAT1 reprogram central metabolism to enhance oil accumulation, with relevance to mature seeds.

59 BASIC BIOLOGICAL SCIENCES↗

Polyyne production is regulated by the transcriptional regulators PgnC and GacA in Pseudomonas protegens Pf-5

ABSTRACT Polyynes produced by bacteria have promising applications in agriculture and medicine due to their potent antimicrobial activities. Polyyne biosynthetic genes have been identified inPseudomonasandBurkholderia. However, the molecular mechanisms underlying the regulation of polyyne biosynthesis remain largely unknown. In this study, we used a soil bacteriumPseudomonas protegensPf-5, which was recently reported to produce polyyne called protegenin, as a model to investigate the regulation of bacterial polyyne production. Our results show that Pf-5 controls polyyne production at both the pathway-specific level and a higher global level. Mutation ofpgnC, a transcriptional regulatory gene located in the polyyne biosynthetic gene cluster, abolished polyyne production. Gene expression analysis revealed that PgnC directly activates the promoter of polyyne biosynthetic genes. The production of polyyne also requires a global regulator GacA. Mutation ofgacAdecreased the translation of PgnC, which is consistent with the result thatpgnCleader mRNA bound directly to RsmE, an RNA-binding protein negatively regulated by GacA. These results suggest that GacA induces the expression of the PgnC regulator, which in turn activates polyyne biosynthesis. Additionally, the polyyne-producing strain of Pf-5, but not the polyyne-nonproducing strain, could inhibit a broad spectrum of bacteria including both Gram-negative and Gram-positive bacteria. IMPORTANCE Antimicrobial metabolites produced by bacteria are widely used in agriculture and medicine to control plant, animal, and human pathogens. Although bacteria-derived polyynes have been identified as potent antimicrobials for decades, the molecular mechanisms by which bacteria regulate polyyne biosynthesis remain understudied. In this study, we found that polyyne biosynthesis is directly activated by a pathway-specific regulator PgnC, which is induced by a global regulator GacA through the RNA-binding protein RsmE inPseudomonas protegens. To our knowledge, this work is the first comprehensive study of the regulatory mechanisms of bacterial polyyne biosynthesis at both pathway-specific level and global level. The discovered molecular mechanisms can help us optimize polyyne production for agricultural or medical applications.

Biotechnology & Applied Microbiology↗

Thermodynamic analysis of heat transfer reduction in spark ignition using thermal barrier coatings

This work uses a 0D thermodynamic engine model coupled to a 1D surface temperature solver to study the potential of low thermal inertia thermal barrier coatings (TBCs) on combustion chamber surfaces to increase the efficiency of spark ignition engines. Under ideal conditions, coating the piston crown, head, and valve faces with a TBC with a thermal inertia of 640 J/m 2 K s 1/2 resulted in less than a 1% relative improvement in efficiency. Despite using a low thermal inertia coating to avoid open cycle charge heating, the reduction in closed cycle heat transfer, which is the pathway to increasing efficiency, increased knock propensity. Therefore, any efficiency gain through closed cycle heat transfer reduction in spark ignition is offset by the need to retard spark timing to counter knock. An exergy analysis of completely blocking heat transfer for a 10 crank-angle degree window showed that on a low compression engine, like those used for stoichiometric gasoline spark ignition, the maximum efficiency gain achievable was limited compared to a higher compression ratio engine. Furthermore, the high gas temperatures of stoichiometric operation mean that even state-of-the-art TBCs cannot elevate surface temperatures enough purely through temperature swing to achieve a significant reduction in heat transfer near top dead center, where work availability is highest. Overall, these results indicate that low thermal inertia TBCs are ill-suited for achieving an efficiency benefit in spark ignition through a heat transfer reduction pathway. Instead spark ignition TBC research should explore ways to use low thermal inertia TBCs to achieve open cycle charge cooling to reduce knock propensity.

Engineering↗

Physiological potential and evolutionary trajectories of syntrophic sulfate-reducing bacterial partners of anaerobic methanotrophic archaea

Sulfate-coupled anaerobic oxidation of methane (AOM) is performed by multicellular consortia of anaerobic methanotrophic archaea (ANME) in obligate syntrophic partnership with sulfate-reducing bacteria (SRB). Diverse ANME and SRB clades co-associate but the physiological basis for their adaptation and diversification is not well understood. In this work, we used comparative metagenomics and phylogenetics to investigate the metabolic adaptation among the 4 main syntrophic SRB clades (HotSeep-1, Seep-SRB2, Seep-SRB1a, and Seep-SRB1g) and identified features associated with their syntrophic lifestyle that distinguish them from their non-syntrophic evolutionary neighbors in the phylum Desulfobacterota. We show that the protein complexes involved in direct interspecies electron transfer (DIET) from ANME to the SRB outer membrane are conserved between the syntrophic lineages. In contrast, the proteins involved in electron transfer within the SRB inner membrane differ between clades, indicative of convergent evolution in the adaptation to a syntrophic lifestyle. Our analysis suggests that in most cases, this adaptation likely occurred after the acquisition of the DIET complexes in an ancestral clade and involve horizontal gene transfers within pathways for electron transfer (CbcBA) and biofilm formation (Pel). We also provide evidence for unique adaptations within syntrophic SRB clades, which vary depending on the archaeal partner. Among the most widespread syntrophic SRB, Seep-SRB1a, subclades that specifically partner ANME-2a are missing the cobalamin synthesis pathway, suggestive of nutritional dependency on its partner, while closely related Seep-SRB1a partners of ANME-2c lack nutritional auxotrophies. Our work provides insight into the features associated with DIET-based syntrophy and the adaptation of SRB towards it.

59 BASIC BIOLOGICAL SCIENCES↗

Data Collection and Analysis Challenges and Mitigation Strategies for Quantitative Human Factors Research Studies in Nuclear Power Plant Modernization

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program Plant Modernization Pathway is conducting targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. LWR fleet. In this effort, the application of human factors engineering (HFE) provides an important role in ensuring new digital plant technologies enable broad innovation and business improvement with continued operational safety. Evaluation is a key activity in HFE, which often occurs iteratively through the system design lifecycle. While qualitative methods are important in collecting information of how users perform tasks through observations, quantitative methods are equally important in assessing system design based on performance. In collecting and analyzing this quantitative data, there are notable challenges in the nuclear HFE domain that may threaten the validity and reliability of the inferences made in these studies. Notable challenges include small sample size and limited resources, large error variance and small effect size, an “adding test features to losing degrees of freedom” dilemma, non-normal distribution, and heterogeneity of variance. The results in control room usability studies are often statistically non-significant, which makes it hard to interpret. This work discusses these challenges across different scientific viewpoints and provides real-world examples of these challenges in practice. Collectively, the objective of this work is to position these challenges to the larger data science community as a means of identifying future opportunities to address these issues.

99 GENERAL AND MISCELLANEOUS↗