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At least 307 records · Page 17

Prevalence of human papillomavirus genotypes in high-grade cervical precancer and invasive cervical cancer from cancer registries before and after vaccine introduction in the United States

Background. US population-based cancer registries can be used for surveillance of human papillomavirus (HPV) types found in HPV-associated cancers. Using this framework, HPV prevalence among high-grade cervical precancers and invasive cervical cancers were compared before and after HPV vaccine availability. Methods. Archived tissue from 2 studies of cervical precancers and invasive cervical cancers diagnosed from 1993-2005 (prevaccine) were identified from 7 central cancer registries in Florida; Hawaii; Iowa; Kentucky; Louisiana; Los Angeles County, California; and Michigan; from 2014 through 2015 (postvaccine) cases were identified from 3 registries in Iowa, Kentucky, and Louisiana. HPV testing was performed using L1 consensus polymerase chain reaction analysis. HPV-type–specific prevalence was examined grouped by hierarchical attribution to vaccine types: HPV 16, 18, HPV 31, 33, 45, 52, 58, other oncogenic HPV types, and other types/HPV negative. Generalized logit models were used to compare HPV prevalence in the prevaccine study to the postvaccine study by patient age, adjusting for sampling factors. Results. A total of 676 precancers (328 prevaccine and 348 postvaccine) and 1140 invasive cervical cancers (777 prevaccine and 363 postvaccine) were typed. No differences were observed in HPV-type prevalence by patient age between the 2 studies among precancers or invasive cancers. Conclusions. The lack of reduction in vaccine-type prevalence between the 2 studies is likely explained by the low number of cases and low HPV vaccination coverage among women in the postvaccine study. Monitoring HPV-type prevalence through population-based strategies will continue to be important in evaluating the impact of the HPV vaccine.

59 BASIC BIOLOGICAL SCIENCES↗

Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus‐associated oropharyngeal squamous cell carcinoma

Background Understanding biological differences between different racial groups of human papillomavirus (HPV)‐associated oropharyngeal squamous cell carcinoma (OPSCC) patients, who have differences in terms of incidence, survival, and tumor morphology, can facilitate accurate prognostic biomarkers, which can help develop personalized treatment strategies. Methods This study evaluated whether there were morphologic differences between HPV‐associated tumors from Black and White patients in terms of multinucleation index (MuNI), an image analysis‐derived metric that measures density of multinucleated tumor cells within epithelial regions on hematoxylin–eosin images and previously has been prognostic in HPV‐associated OPSCC patients. In this study, the authors specifically evaluated whether the same MuNI cutoff that was prognostic of overall survival (OS) and disease‐free survival in their previous study, T TR , is valid for Black and White patients, separately. We also evaluated population‐specific cutoffs, T B for Blacks and T W for Whites, for risk stratification. Results MuNI was statistically significantly different between Black (mean, 3.88e–4; median, 3.67e–04) and White patients (mean, 3.36e–04; median, 2.99e–04), with p = .0078. Using T TR , MuNI was prognostic of OS in the entire population with hazard ratio (HR) of 1.71 ( p = .002; 95% confidence interval [CI], 1.21–2.43) and in White patients with HR of 1.72 ( p = .005; 95% CI, 1.18–2.51). Population‐specific cutoff, T W , yielded improved HR of 1.77 ( p = .003; 95% CI, 1.21–2.58) for White patients, whereas T B did not improve risk‐stratification in Black patients with HR of 0.6 ( p = .3; HR, 0.6; 95% CI, 0.2–1.80). Conclusions Histological difference between White and Black patient tumors in terms of multinucleated tumor cells suggests the need for considering population‐specific prognostic biomarkers for personalized risk stratification strategies for HPV‐associated OPSCC patients.

Koyuncu, Can F.↗

Response of Pseudomonas putida to Complex, Aromatic-Rich Fractions from Biomass

There is strong interest in the valorization of lignin to produce valuable products; however, its structural complexity has been a conversion bottleneck. Chemical pretreatment liberates lignin-derived soluble fractions that may be upgraded by bioconversion. Here, cholinium ionic liquid pretreatment of sorghum produced soluble, aromatic-rich fractions that were converted by Pseudomonas putida (P. putida), a promising host for aromatic bioconversion. Growth studies and mutational analysis demonstrated that P. putida growth on these fractions was dependent on aromatic monomers but unknown factors also contributed. Proteomic and metabolomic analyses indicated that these unknown factors were amino acids and residual ionic liquid; the oligomeric aromatic fraction derived from lignin was not converted. A cholinium catabolic pathway was identified, and the deletion of the pathway stopped the ability of P. putida to grow on cholinium ionic liquid. This work demonstrates that aromatic-rich fractions obtained through pretreatment contain multiple substrates; conversion strategies should account for this complexity.

09 BIOMASS FUELS↗

N and P constrain C in ecosystems under climate change: Role of nutrient redistribution, accumulation, and stoichiometry

Abstract We use the Multiple Element Limitation (MEL) model to examine responses of 12 ecosystems to elevated carbon dioxide (CO 2 ), warming, and 20% decreases or increases in precipitation. Ecosystems respond synergistically to elevated CO 2 , warming, and decreased precipitation combined because higher water‐use efficiency with elevated CO 2 and higher fertility with warming compensate for responses to drought. Response to elevated CO 2 , warming, and increased precipitation combined is additive. We analyze changes in ecosystem carbon (C) based on four nitrogen (N) and four phosphorus (P) attribution factors: (1) changes in total ecosystem N and P, (2) changes in N and P distribution between vegetation and soil, (3) changes in vegetation C:N and C:P ratios, and (4) changes in soil C:N and C:P ratios. In the combined CO 2 and climate change simulations, all ecosystems gain C. The contributions of these four attribution factors to changes in ecosystem C storage varies among ecosystems because of differences in the initial distributions of N and P between vegetation and soil and the openness of the ecosystem N and P cycles. The net transfer of N and P from soil to vegetation dominates the C response of forests. For tundra and grasslands, the C gain is also associated with increased soil C:N and C:P. In ecosystems with symbiotic N fixation, C gains resulted from N accumulation. Because of differences in N versus P cycle openness and the distribution of organic matter between vegetation and soil, changes in the N and P attribution factors do not always parallel one another. Differences among ecosystems in C‐nutrient interactions and the amount of woody biomass interact to shape ecosystem C sequestration under simulated global change. We suggest that future studies quantify the openness of the N and P cycles and changes in the distribution of C, N, and P among ecosystem components, which currently limit understanding of nutrient effects on C sequestration and responses to elevated CO 2 and climate change.

54 ENVIRONMENTAL SCIENCES↗

Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north-central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.

59 BASIC BIOLOGICAL SCIENCES↗

Carbon budget of the Harvard Forest Long-Term Ecological Research site: pattern, process, and response to global change

How, where, and why carbon (C) moves into and out of an ecosystem through time are long-standing questions in biogeochemistry. Here, we bring together hundreds of thousands of C-cycle observations at the Harvard Forest in central Massachusetts, USA, a mid-latitude landscape dominated by 80–120-yr-old closed-canopy forests. These data answered four questions: (1) where and how much C is presently stored in dominant forest types; (2) what are current rates of C accrual and loss; (3) what biotic and abiotic factors contribute to variability in these rates; and (4) how has climate change affected the forest’s C cycle? Harvard Forest is an active C sink resulting from forest regrowth following land abandonment. Soil and tree biomass comprise nearly equal portions of existing C stocks. Net primary production (NPP) averaged 680–750 g C·m –2 ·yr –1 ; belowground NPP contributed 38–47% of the total, but with large uncertainty. Mineral soil C measured in the same inventory plots in 1992 and 2013 was too heterogeneous to detect change in soil-C pools; however, radiocarbon data suggest a small but persistent sink of 10–30 g C·m –2 ·yr –1 . Net ecosystem production (NEP) in hardwood stands averaged ~300 g C·m –2 ·yr –1 . NEP in hemlock-dominated forests averaged ~450 g C·m –2 ·yr –1 until infestation by the hemlock woolly adelgid turned these stands into a net C source. Since 2000, NPP has increased by 26%. For the period 1992–2015, NEP increased 93%. The increase in mean annual temperature and growing season length alone accounted for ~30% of the increase in productivity. Interannual variations in GPP and NEP were also correlated with increases in red oak biomass, forest leaf area, and canopy-scale light-use efficiency. Compared to long-term global change experiments at the Harvard Forest, the C sink in regrowing biomass equaled or exceeded C cycle modifications imposed by soil warming, N saturation, and hemlock removal. Furthermore, the results of this synthesis and comparison to simulation models suggest that forests across the region are likely to accrue C for decades to come but may be disrupted if the frequency or severity of biotic and abiotic disturbances increases.

54 ENVIRONMENTAL SCIENCES↗

Large‐ and small‐seeded species have contrasting functional neighborhoods in a subtropical forest

Abstract Forest community composition is the outcome of multiple forces, including those that increase taxonomic and functional divergence and those that promote convergence in traits. The mechanisms underlying these forces may not operate homogenously within communities; individuals of different species are never perfectly mixed, and thus, species tend to be surrounded and interact with different subsets of species. In fact, taxonomic and functional composition of neighborhoods of different focal species can be highly variable. Here, we examine whether mechanisms driving species‐level neighborhoods relate to intrinsic characteristics of focal species such as differences in life‐history and resource‐uptake strategies and in turn relate to species survival. We focus on two key characteristics: (1) seed mass, which defines a dominant axis of life‐history strategies related to stress tolerance, and (2) understory light preferences that sort species from light‐demanding pioneers to shade‐tolerant. We monitored seedling communities over 10 yr in Puerto Rico and calculated neighborhood trait dispersion in species‐level neighborhoods using seven functional traits. We examined whether species‐level characteristics, seed mass and preferred light conditions, influence patterns of functional dispersion in seedling neighborhoods using linear models. Then, we examined how species‐level functional neighborhoods impact seedling survival. We found that small‐ and large‐seeded species diverge in the type of functional neighborhoods they associate with. Large‐seeded species associate with neighbors that are more similar than expected in leaf economic traits, but more different than expected in seed mass and leaf area traits, while the opposite was found for small‐seeded species. This variation in species functional neighborhood was important in determining seedling survival. In sum, our results suggest that divergent and convergent forces do not operate homogenously over entire communities. Their relative role changes in space, and on a species‐by‐species basis, probably with a deterministic foundation linked to traits such as seed mass.

Umaña, María Natalia↗

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗

Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Abstract Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain ( https://centilebrain.org/#/brainAGE2 ), an open‐science, web‐based platform for individualized neuroimaging metrics.

60 APPLIED LIFE SCIENCES↗

Integration of CO 2 capture and microalgae cultivation: demonstration assessment of outdoor Scenedesmus acutus cultivation using gaseous ammonia as a nitrogen source

Towards the goal of integrating CO 2 capture using aqueous ammonia with its utilization for algae cultivation, Scenedesmus acutus (UTEX B72) was grown in 1100 L open raceway ponds using CO 2 and NH 3 supplied from gas cylinders. CO 2 /NH 3 mole ratios of 7 and 10 were employed, the gas mixture acting as a surrogate for the output from a CO 2 scrubbing system using aqueous ammonia. Compared to Scenedesmus acutus grown in open ponds using gaseous CO 2 and NaNO 3 as the N-source, the ponds supplied with gaseous CO 2 and NH 3 displayed higher productivity at both CO 2 /NH 3 ratios, with the higher ratio providing the best growth. Depending on the culturing conditions and CO 2 /NH 3 ratio, CO 2 utilization ranged up to 15.8% and NH 3 utilization to 23.0%. These rather low values reflect the fact the high CO 2 /NH 3 feed rate used, resulting in a substantial release of NH 3 from the ORPs (~45%). Finally, these findings demonstrate the suitability of gaseous NH 3 as a N-source for microalgae cultivation, while highlighting the need for a control strategy that closely balances the CO 2 /NH 3 supply with the algae growth rate. The produced algae biomass possessed a high protein and low ash content, rendering it particularly suitable for use as a bioplastic feedstock.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Imitating the “breeder's eye”: Predicting grain yield from measurements of non‐yield traits

Abstract Plant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency of genetic improvement in future breeding cycles. However, generating the genetic marker data required to apply genomic prediction at the early stages of a breeding program remains costly for many public‐sector breeding programs as well as for many plant breeders operating in developing countries. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties requires plant breeders to make selection decisions without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, both lower cost and higher accuracy methods for prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the 21 st century. To address this challenge, we conducted linked yield trials of 752 public maize ( Zea mays ) genotypes in two distinct environments. We developed and trained a phenotypic prediction model to predict yield from manually scored plant traits. The phenotypic prediction approach we employed outperformed genomic prediction in predicting yields in a second environment, with 8.7%–63% higher R 2 and 4%–13% less root mean square error than the genomic prediction. The phenotypic prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.

60 APPLIED LIFE SCIENCES↗

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.

Schuhl, Haley [Donald Danforth Plant Science Cente↗

Coefficient of Thermal Expansion during Ratchet Growth of TATB Compactions

Triamino trinitrobenzene (TATB) is an insensitive high explosive, meaning that it is quite immune from accidental detonation and only performs in appropriately engineered configurations. While this is advantageous for applications, the TATB crystal is graphitic and possesses significant thermal and mechanical anisotropy. Compactions of TATB crystals, with or without binder, have been shown to have oriented TATB crystals that relate to the pressing geometry and process, and this TATB texture necessarily imparts microscale and macroscale anisotropy to the compaction. By a mechanism not fully understood, thermal cycling results in irreversible volume expansion (also called ratchet growth) of the compaction likely by creating stress points on the microscale. Changes in density caused by thermal cycling can certainly effect the explosive performance. Our past characterization of the ratchet growth phenomenon has focused on the magnitude of the irreversible strain as measured before and after a thermal cycle. Finally, in the work presented here, we analyze the evolving thermal expansion behavior during the ascending and descending temperature ramps, providing further insight into the material changes taking place during the ratchet growth phenomenon.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Identification of Blue Discoloration in PBX 9404 using Ultrahigh Pressure Liquid Chromatography with Quadrupole Time-of-Flight Mass Spectrometry

PBX 9404, composed of 94 wt% HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazoctane), 3 wt% NC (nitrocellulose), 2.9 wt% CEF (tris(beta-chloroethyl) phosphate) and 0.1 wt% DPA (diphenylamine), has often been observed with a slight to entire blue discoloration of the manufactured prills. This blue discoloration has been observed since the formulation development of PBX 9404 in the late 1950s. In order to determine the source of the blue discoloration in PBX 9404, ultraviolet/visible (UV/Vis) absorbance of PBX 9404 and two potential candidates for the discoloration, p-nitrosodiphenylamine (p-NDPA) and N-nitrosodiphenylamine (N-NDPA) were evaluated. An absorbance band at 590 nm in PBX 9404 sample was attributed to the blue discoloration while p-NDPA and N-NPDA had different absorbance bands. Using the knowledge gained from the UV/Vis analysis, a semi-targeted approach using ultrahigh pressure liquid chromatography coupled to UV/Vis detector and quadrupole time of flight mass spectrometry (UHPLC-UV/Vis-QTOF) was implemented. Investigating the UHPLC-UV/Vis-QTOF chromatograms at a wavelength of 590 nm, a single compound was tentatively identified as being the source of the blue discoloration. Targeted tandem mass spectrometry (MS/MS) on the compound and subsequent analysis indicated that 4,4 -{[4-(Phenylimino)-2,5-cyclohexadien-1-ylidene]methylene}bis(N-phenylaniline), also known as Spirit Blue Base, was the source of the blue discoloration, which was confirmed using a standard. Here, a theory on the formation of Spirit Blue Base in PBX 9404 involving DPA, nitric acid (HNO 3 ) / nitrogen oxide(s) NO x , and formaldehyde is proposed.

36 MATERIALS SCIENCE↗

Coefficient of Thermal Expansion Evolution during Ratchet Growth of PBX 9502 and Neat TATB

The Plastic-Bonded Explosive (PBX) 9502 is comprised of the insensitive high explosive TATB (triamino trinitrobenzine) crystals coated in FK-800 polymer binder and isostatically pressed. The TATB crystals have a graphitic, plate-like morphology and possess significant thermal and mechanical anisotropy. Compactions of neat TATB or TATB-based composites (like PBX 9502) have been shown to have TATB crystals that are oriented during the pressing process giving rise to TATB texture and resulting in micro- and macro-scale anisotropy of the compaction. Thermal cycling of the compactions results in irreversible volume expansion (or ratchet growth) likely by creating stress points on the microscale. However, the actual mechanism behind this expansion is not fully understood. Previous characterization of the ratchet growth phenomenon has focused on the magnitude of the irreversible strain as measured before and after a thermal cycle. In the work presented here, we analyze the evolving thermal expansion behavior during the ascending and descending temperature ramps and compare differences observed due to the presence/absence of binder in the compaction.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Strong degradation of polycarbonate and polystyrene by the CO 2 capture solvent diethyl sebacate

Here, we report on observations of strong degradation of a polycarbonate vessel by a solvent being considered for a CO 2 capture process, diethyl sebacate. This degradation led to failure of a polymeric hollow fiber membrane unit. Additional tests showed rapid degradation of polycarbonate safety glasses and polystyrene-based petri dishes by exposure to diethyl sebacate at ambient conditions. We also report on safe operations with diethyl sebacate in extensive experiments studying the corrosion of steel in CO 2 -pressurized reactors lined with PTFE and using PTFE gaskets. Used diethyl sebacate was also stored for long time periods in bottles made from low-density polyethylene bottles without physical deterioration. These observations indicate that care must be taken in development of new contactors and processes for CO 2 capture with diethyl sebacate and related solvents and in the choice of material for storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) peak intensity normalization for complex mixture analyses

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a preferred technique for analyzing complex organic mixtures. Currently, there is no consensus normalization approach, nor an objective method for selecting one, for quantitative analyses of FT-ICR-MS data. We investigate a method to evaluate and score the amount of bias various normalization approaches introduce into the data. We evaluate the ability of the Statistical Procedure for the Analysis of Normalization Strategies (SPANS) to guide selection of appropriate normalization approaches for two different FT-ICR-MS datasets. Further, we test the robustness of SPANS results to changes in SPANS parameter values and assess the impact of using various normalization approaches on downstream statistical analyses. The normalization approach identified by SPANS differed for the two datasets. Normalization methods impacted the statistical significance of peaks differently, underscoring the importance of carefully evaluating potential methods. More consistent SPANS scores resulted when at least 120 significant peaks are used, where larger sets of peaks were obtained by increasing the p-value threshold. Interestingly, we show that Total Sum Scaling and highest peak normalization, used in previous studies, underperformed relative to SPANS-recommended normalization approaches. While there is no single, best normalization method for all datasets, SPANS provides a mechanism to identify an appropriate normalization method for analyzing FT-ICR-MS data quantitatively. As a result, the number of peaks used in the background distributions of SPANS contributes more significantly to the reproducibility of results than the p-value thresholds used to obtain those peaks.

47 OTHER INSTRUMENTATION↗

1D to 2D Transition in Tellurium Observed by 4D Electron Microscopy

A new microwave-enhanced synthesis method for the production of tellurium nanostructures is reported here—with control over products from the 1D regime (sub-5 nm diameter nanowires), to nanoribbons, to the 2D tellurene regime—along with a new methodology for local statistical quantification of the crystallographic parameters of these materials at the nanometer scale. Using a direct electron detector and image-corrected microscope, large and robust 4D scanning transmission electron microscopy datasets for accurate structural analysis are obtained. These datasets allow the adaptation of quantitative techniques originally developed for X-ray diffraction (XRD) refinement analyses to transmission electron microscopy, enabling the first demonstration of sub-picometer accuracy lattice parameter extraction while also obtaining both the size of the coherent crystallite domains and the nanostrain, which is observed to decrease as nanowires transition to tellurene. This new local analysis is commensurate with global powder XRD results, indicating the robustness of both the new synthesis approach and new structural analysis methodology for future scalable production of 2D tellurene and characterization of nanomaterials.

2D materials↗