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At least 415 records · Page 23

Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

59 BASIC BIOLOGICAL SCIENCES↗

On the feasibility of comprehensive high-resolution 3D remote dosimetry

Purpose: This study investigates the feasibility of remote high-resolution 3D dosimetry with the PRESAGE®/Optical-CT system. In remote dosimetry, dosimeters are shipped out from a central base institution to a remote institution for irradiation, then shipped back to the base institution for subsequent readout and analysis. Methods: Two nominally identical optical-CT scanners for 3D dosimetry were constructed and placed at the base (Duke University) and remote (Radiological Physics Center) institutions. Two formulations of PRESAGE® (SS1, SS2) radiochromic dosimeters were investigated. Higher sensitivity was expected in SS1, which had higher initiator content (0.25% bromotrichloromethane), while greater temporal stability was expected in SS2. Four unirradiated PRESAGE® dosimeters (two per formulation, cylindrical dimensions 11 cm diameter, 8.5–9.5 cm length) were imaged at the base institution, then shipped to the remote institution for planning and irradiation. Each dosimeter was irradiated with the same simple treatment plan: an isocentric 3-field “cross” arrangement of 4 × 4 cm open 6 MV beams configured as parallel opposed laterals with an anterior beam. This simple plan was amenable to accurate and repeatable setup, as well as accurate dose modeling by a commissioned treatment planning system (Pinnacle). After irradiation and subsequent (within 1 h) optical-CT readout at the remote institution, the dosimeters were shipped back to the base institution for remote dosimetry readout 3 days postirradiation. Measured on-site and remote relative 3D dose distributions were registered to the Pinnacle dose calculation, which served as the reference distribution for 3D gamma calculations with passing criteria of 5%/2 mm, 3%/3 mm, and 3%/2 mm with a 10% dose threshold. Gamma passing rates, dose profiles, and color-maps were all used to assess and compare the performance of both PRESAGE® formulations for remote dosimetry. Results: The best agreements between the Pinnacle plan and dosimeter readout were observed in PRESAGE® formulation SS2. Under 3%/3 mm 3D gamma passing criteria, passing rates were 91.5% ± 3.6% (SS1) and 97.4% ± 2.2% (SS2) for immediate on-site dosimetry, 96.7% ± 2.4% (SS1) and 97.6% ± 0.6% (SS2) for remote dosimetry. These passing rates are well within TG119 recommendations (88%–90% passing). Under the more stringent criteria of 3%/2 mm, there is a pronounced difference [8.0 percentage points (pp)] between SS1 formulation passing rates for immediate and remote dosimetry while the SS2 formulation maintains both higher passing rates and consistency between immediate and remote results (differences ≤ 1.2 pp) at all metrics. Both PRESAGE® formulations under study maintained high linearity of dose response (R{sup 2} > 0.996) for 1–8 Gy over 14 days with response slope consistency within 4.9% (SS1) and 6.6% (SS2), and a relative dose distribution that remained stable over time was demonstrated in the SS2 dosimeters. Conclusions: Remote 3D dosimetry was shown to be feasible with a PRESAGE® dosimeter formulation (SS2) that exhibited relative temporal stability and high accuracy when read off-site 3 days postirradiation. Characterization of the SS2 dose response demonstrated linearity (R{sup 2} > 0.998) over 14 days and suggests accurate readout over longer periods of time would be possible. This result provides a foundation for future investigations using remote dosimetry to study the accuracy of advanced radiation treatments. Further work is planned to characterize dosimeter reproducibility and dose response over longer periods of time.

60 APPLIED LIFE SCIENCES↗

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗

Computational study of inertial migration of prolate particles in a straight rectangular channel

Inertial migration of spherical particles has been investigated extensively using experiments, theory, and computational modeling. Yet, a systematic investigation of the effect of particle shape on inertial migration is still lacking. Herein, we numerically mapped the migration dynamics of a prolate particle in a straight rectangular microchannel using smoothed particle hydrodynamics at moderate Reynolds number flows. After validation, we applied our model to 2:1 and 3:1 shape aspect ratio particles at multiple confinement ratios. Their effects on the final focusing position, rotational behavior, and transitional dynamics were studied. In addition to the commonly reported tumbling motion, for the first time, we identified a new logrolling behavior of a prolate ellipsoidal particle in the confined channel. This new behavior occurs when the confinement ratio is above an approximate threshold value of K = 0.72. Our microfluidic experiments using cell aggregates with similar shape aspect ratio and confinement ratio confirmed this new predicted logrolling motion. In this study, we also found that the same particle can undergo different rotational modes, including kayaking behavior, depending on its initial cross-sectional position and orientation. Furthermore, we examined the migration speed, angular velocity, and rotation period as well as their dependence on both particle shape aspect ratio and confinement ratio. Our findings are especially relevant to the applications where particle shape and alignment are used for sorting and analysis, such as the use of barcoded particles for biochemical assays through optical reading, or the shape-based enrichment of microalgae, bacteria, and chromosomes.

42 ENGINEERING↗

Automated protein crystal growth facility

A customer for the protein crystal growth facility fills the specially designed chamber with the correct solutions, fills the syringes with their quenching solutions, and submits the data needed for the proper growth of their crystal. To make sure that the chambers and syringes are filled correctly, a NASA representative may assist the customer. The data needed is the approximate growth time, the growth temperature, and the desired crystal size, but this data can be changed anytime from the ground, if needed. The chambers are gathered and placed into numbered slots in special drawers. Then, data is entered into a computer for each of the chambers. Technicians map out when each chamber's growth should be activated so that all of the chambers have enough time to grow. All of this data is up-linked to the space station when the previous growth session is over. Anti-vibrational containers need to be constructed for the high forces encountered during the lift off and the landing of the space shuttle, and though our team has not designed these containers, we do not feel that there is any reason why a suitable one could not be made. When the shuttle reaches the space station, an astronaut removes a drawer of quenched chambers from the growth facility and inserts a drawer of new chambers. All twelve of the drawers can be replaced in this fashion. The optical disks can also be removed this way. The old drawers are stored for the trip back to earth. Once inside the growth facility, a chamber is removed by the robot and placed in one of 144 active sites at a time previously picked by a technician. Growth begins when the chamber is inserted into an active site. Then, the sensing system starts to determine the size of the protein crystal. All during the crystal's growth, the customer can view the crystal and read all of the crystal's data, such as growth rate and crystal size. When the sensing system determines that the crystal has reached the predetermined size, the robot is told to pick up a syringe filled with the correct quenchant solution and inject it into the chamber to stop the crystal growth. The chamber is then removed from the active site and placed into its original storage slot. Another chamber is then placed into the active site and the process is repeated in all of the active sites until all of the chambers have complted their growth. After ninety days (the scheduled time between shuttle visits), the crystal growth is completed, and the old drawers are replaced with new ones. Once the customer extracts the crystals, the chambers are retrieved for future customers.

Donald, Stacey↗

Early results from the Far Infrared Absolute Spectrophotometer (FIRAS)

The Far Infrared Absolute Spectrophotometer (FIRAS) on the Cosmic Background Explorer (COBE) mapped 98 percent of the sky, 60 percent of it twice, before the liquid helium coolant was exhausted. The FIRAS covers the frequency region from 1 to 100/cm with a 7 deg angular resolution. The spectral resolution is 0.2/cm for frequencies less than 20/cm and 0.8/cm for higher frequencies. Preliminary results include: a limit on the deviations from a Planck curve of 1 percent of the peak brightness from 1 to 20/cm, a temperature of 2.735 +/- 0.06 K, a limit on the Comptonization parameter y of 0.001, on the chemical potential parameter mu of 0.01, a strong limit on the existence of a hot smooth intergalactic medium, and a confirmation that the dipole anisotropy spectrum is that of a Doppler shifted blackbody.

Mather, J. C.↗

Mapping the body’s battle with Ebola and Zika

The viruses that cause Ebola and Zika, daunting diseases that inspire concern at every outbreak, share a strong similarity in how they first infiltrate a host’s cells. Through the computer modeling capabilities of Los Alamos National Laboratory, the molecular calisthenics involved in invading a cell are visually documented, an essential step toward vaccine and therapeutic medicine development. “The two very different viruses both use a surface protein to initiate a process called ‘membrane fusion,’ which allows the viral entry into the host cell,” said Chang-Shung Tung, the leading and corresponding author of the recent work in the journal Biomolecules. “Before the membrane fusion started, these two proteins went through large conformational changes that was not fully understood, as the proteins would take on the physical shape that would allow them to fuse with the cell and begin the infection. In this work, we modeled the structures of the two proteins in the fusion-initiation state. Then we used the structures to explain how four different antibodies in our bodies can fight the infection and block the viral entry, based on how they bind to these two proteins,” Tung said. The aim of the team’s work was to understand the specific structure-function relationship of the Ebola glycoprotein (EBOV GP) and Zika envelope (ZIKA E) proteins, the ones that are instrumental in the fusion with the host cell. “This computer modeling approach allowed us to generate atomic-level models of EBOV GP and ZIKV E proteins in the fusion state for the first time,” said Anna Lappala, a postdoctoral fellow at the Center for Nonlinear Studies and the Theoretical Biology & Biophysics Group at Los Alamos. “These models, together with the knowledge of the envelope proteins in the pre-fusion state, allowed us to study the function of neutralizing antibodies as they bind to the viral envelope proteins.” Read the published scientific paper here: http://www.mdpi.com/2218-273X/8/2/25/pdf

59 BASIC BIOLOGICAL SCIENCES↗

Landslides caused by the Mw7.8 Kaikōura earthquake and the immediate response

Tens of thousands of landslides were generated over 10,000 km 2 of North Canterbury and Marlborough as a consequence of the 14 November 2016, M w 7.8 Kaikōura Earthquake. The most intense landslide damage was concentrated in 3500 km 2 around the areas of fault rupture. Given the sparsely populated area affected by landslides, only a few homes were impacted and there were no recorded deaths due to landslides. Landslides caused major disruption with all road and rail links with Kaikōura being severed. The landslides affecting State Highway 1 (the main road link in the South Island of New Zealand) and the South Island main trunk railway extended from Ward in Marlborough all the way to the south of Oaro in North Canterbury. The majority of landslides occurred in two geological and geotechnically distinct materials reflective of the dominant rock types in the affected area. In the Neogene sedimentary rocks (sandstones, limestones and siltstones) of the Hurunui District, North Canterbury and around Cape Campbell in Marlborough, first-time and reactivated rock-slides and rock-block slides were the dominant landslide type. These rocks also tend to have rock material strength values in the range of 5-20 MPa. In the Torlesse ‘basement’ rocks (greywacke sandstones and argillite) of the Kaikōura Ranges, first-time rock and debris avalanches were the dominant landslide type. These rocks tend to have material strength values in the range of 20-50 MPa. A feature of this earthquake is the large number (more than 200) of valley blocking landslides it generated. This was partly due to the steep and confined slopes in the area and the widely distributed strong ground shaking. The largest landslide dam has an approximate volume of 12(±2) M m 3 and the debris from this travelled about 2.7 km 2 downslope where it formed a dam blocking the Hapuku River. The long-term stability of cracked slopes and landslide dams from future strong earthquakes and large rainstorms are an ongoing concern to central and local government agencies responsible for rebuilding homes and infrastructure. A particular concern is the potential for debris floods to affect downstream assets and infrastructure should some of the landslide dams breach catastrophically. At least twenty-one faults ruptured to the ground surface or sea floor, with these surface ruptures extending from the Emu Plain in North Canterbury to offshore of Cape Campbell in Marlborough. The mapped landslide distribution reflects the complexity of the earthquake rupture. Landslides are distributed across a broad area of intense ground shaking reflective of the elongate area affected by fault rupture, and are not clustered around the earthquake epicentre. The largest landslides triggered by the earthquake are located either on or adjacent to faults that ruptured to the ground surface. Surface faults may provide a plane of weakness or hydrological discontinuity and adversely oriented surface faults may be indicative of the location of future large landslides. Their location appears to have a strong structural geological control. Initial results from our landslide investigations suggest predictive models relying only on ground-shaking estimates underestimate the number and size of the largest landslides that occurred.

58 GEOSCIENCES↗

Far Ultraviolet Imaging from the Image Spacecraft: Wideband FUV Imaging - 2

The Far Ultraviolet Wideband Imaging Camera (WIC) complements the magnetospheric images taken by the IMAGE satellite instruments with simultaneous global maps of the terrestrial aurora. Thus, a primary requirement of WIC is to image the total intensity of the aurora in wavelength regions most representative of the aurora] source and least contaminated by dayglow, have sufficient field of view to cover the entire polar region from spacecraft apogee and have resolution that is Sufficient to resolve auroras on a scale of 1 to 2 latitude degrees, The instrument is sensitive in the spectral region from 140- 190 nm. The WIC is mounted on the rotating, IMAGE spacecraft viewing radially outward and has a field of view of 17 deg in the direction parallel to the spacecraft spin axis. Its field of view is 30 deg in the direction perpendicular to the spin axis, although only a 17 deg x 17 deg image of the Earth is recorded. The optics was an all-reflective, inverted Cassegrain Burch camera using concentric optics with a small convex primary and a large concave secondary mirror. The mirrors were coated by a special multi-layer coating, which has low reflectivity in the visible and near UV region, The detector consists of a MCP-Intensified CCD. The MCP is curved to accommodate the focal surface of the concentric optics. Tile phosphor of the image intensifier is deposited on a concave fiberoptic window, which is then Coupled to the CCD with a fiberoptic taper. The camera head operates in a fast frame transfer mode with the CCD being read approximately 30 full frames (512 by 256 pixel) per second with an exposure time of 0.033 s. The image motion (file to the satellite spin is minimal during such a short exposure. Each image is electronically distortion corrected using the look up table scheme. An offset is added to each memory address that is proportional to the image shift due to satellite rotation, and the charge signal is digitally summed in memory. On orbit, approximately 300 frames will be added to produce one WIC image in memory. The advantage of the electronic motion compensation and distortion correction is that it is extremely flexible, permitting several kinds of corrections including motions parallel and perpendicular to the predicted axis of rotation. File instrument was calibrated by applying ultraviolet light through a vacuum monochromator and measuring the absolute responsivity of the instrument. To obtain the data for the distortion look up table the camera was turned through various angles and the input angles corresponding to a pixel matrix were recorded. It was found that the spectral response peaked at 150 nm and fell off in either direction. The equivalent aperture of the camera, including mirror reflectivities and effective photocathode quantum efficiency, is about 0.04 sq cm. Thus, a 100 Rayleigh LBH aurora is expected to produce 23 equivalent counts per pixel per 10 s exposure at the peak of instrument response.

Mende, S. B.↗

The Solsticial Pause on Mars: A Planetary Wave Reanalysis - Part 1

Large-scale planetary waves are diagnosed from an analysis of profiles retrieved from the Thermal Emission Spectrometer aboard the Mars Global Surveyor spacecraft during its scientific mapping phase. The analysis is conducted by assimilating thermal profiles and total dust opacity retrievals into a Mars global circulation model. Transient waves are largest throughout the northern hemisphere autumn, winter and spring period and almost absent during the summer. The southern hemisphere exhibits generally weaker transient wave behavior. A striking feature of the low-altitude transient waves in the analysis is that they show a broad subsidiary minimum in amplitude centred on the winter solstice, a period when the thermal contrast between the summer hemisphere and the winter pole is strongest and baroclinic wave activity might be expected to be strong. This behavior, here called the 'solsticial pause,' is present in every year of the analysis. This strong pause is under-represented in many independent model experiments, which tend to produce relatively uniform baroclinic wave activity throughout the winter. This paper documents and diagnoses the transient wave solsticial pause found in the analysis; a companion paper investigates the origin of the phenomenon in a series of model experiments.

Lewis, Stephen R.↗

Accurate prediction of protein structures and interactions using a three-track neural network

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo–electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. Here, we make the method available to the scientific community to speed biological research.

59 BASIC BIOLOGICAL SCIENCES↗

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from 7 Perennial and 7 Intermittent Streams across San Antonio, Texas (v3)

This dataset supports a broader study examining the effects of intermittency on sediment respiration. The dataset provides sediment and surface water geochemistry and in situ sensor data from 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). Related data were collected and will be published separately in collaboration with A. Veach. The data package was originally published in April 2025. It was updated in June 2025 (v2; modified and new files) and September 2025 (v3; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) sediment grain size data; (4) sediment iron (II) data and averages; (5) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment percent carbon and nitrogen; (11) sediment X-ray diffraction (XRD) data; (12) gravimetric moisture and averages; (13) a subfolder with sediment incubation respiration data, scripts, and plots; (14) surface water and sediment FTICR methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: The data processing methods for FTICR described in “v3_WHONDRS_AV1_Methods_Codes.csv” mistakenly indicate that users should process the data in Formultitude. The corrected description should read: “Both unprocessed and processed data are provided to allow users flexibility in data processing. Instructions and scripts for processing the data using CoreMS are included.” CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package.

54 ENVIRONMENTAL SCIENCES↗

Data from: 'Abiotic influences on continuous conifer forest structure across a subalpine watershed'

This package archives the core data used for analysis and inference in 'Abiotic influences on continuous conifer forest structure across a subalpine watershed' (Worsham et al., 2025). All data were collected in the East River, Washington Gulch, Slate River, and Coal Creek watersheds of Colorado. In the paper, we quantified the relative influence of climate, topographic, edaphic, and geologic factors on conifer stand structure and composition, and their functional relationships, at the watershed scale. We used waveform LiDAR data to derive spatially continuous stand structure metrics. We fused these with a species-level classification map to estimate tree species abundance. We applied generalized additive and generalized boosted models to evaluate the covariability of structural and compositional metrics with abiotic variables. The package contains the essential products required for reproducing our analysis and the tables and figures reported in the publication. The products comprise four classes: (1) geospatial data, (2) tabular data used for inferential analysis, (3) tabular data describing analytical results and performance statistics, and (4) a data user guide. (1) includes discretized waveform LiDAR data, locations and attributes of individual tree crowns, sampling locations and domain boundaries, a canopy height model, and raster files of estimated forest structural and compositional metrics at 100 m grid scale. (2) includes all response and explanatory variable values applied in inferential models. Response variables include conifer forest stand density, basal area, 95th percentile height, quadratic mean diameter, and others. Explanatory variables include climatic water deficit, actual evapotranspiration, elevation, heat load, soil available water content, and others. (3) includes results of training and testing several individual tree detection (ITD) algorithms, as well as inferential modeling results. (4) is a PDF user guide for this data package, including detailed descriptions and data dictionaries for all files. The data package root contains 17 assets: 8 compressed tape archive (.tar.gz) files, 5 comma-separated values (.csv) files, 3 Geographic Tagged Image File Format (GeoTIFF) (.tif) files, and 1 Portable Document Format (.pdf) file. The compressed .tar.gz archives contain ESRI shapefiles (.shp) .tif, compressed LASer (.laz), and .csv files. The archives must first be decompressed using the widely distributed command-line software utility TAR. All other files, including constituent files within the .tar.gz archives, can be opened in the open-source R statistical computing environment. Alternatively, .csv files may also be read in any simple text editor software or Microsoft Excel. Geospatial files including .shp and .tif files can also be opened in GIS software, such as QGIS (open-source) or ESRI ArcGIS (proprietary). The .pdf Data User Guide can be read with Adobe Acrobat Reader or other compatible readers.

2018 NEON and 2025 CHESS Campaigns↗

Accelerating crystal structure determination with iterative AlphaFold prediction

Experimental structure determination can be accelerated with artificial intelligence (AI)-based structure-prediction methods such as AlphaFold . Here, an automatic procedure requiring only sequence information and crystallographic data is presented that uses AlphaFold predictions to produce an electron-density map and a structural model. Iterating through cycles of structure prediction is a key element of this procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. This procedure was applied to X-ray data for 215 structures released by the Protein Data Bank in a recent six-month period. In 87% of cases our procedure yielded a model with at least 50% of C α atoms matching those in the deposited models within 2 Å. Predictions from the iterative template-guided prediction procedure were more accurate than those obtained without templates. It is concluded that AlphaFold predictions obtained based on sequence information alone are usually accurate enough to solve the crystallographic phase problem with molecular replacement, and a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization is suggested.

59 BASIC BIOLOGICAL SCIENCES↗

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗

The Imaging X-ray Polarimetry Explorer (IXPE): Technical Overview

The Imaging X-ray Polarimetry Explorer (IXPE) will expand the information space for study of cosmic sources, by adding linear polarization to the properties (time, energy, and position) observed in x-ray astronomy. Selected in 2017 January as a NASA Astrophysics Small Explorer (SMEX) mission, IXPE will be launched into an equatorial orbit in 2021. The IXPE mission will provide scientifically meaningful measurements of the x-ray polarization of a few dozen sources in the 2-8 keV band, including polarization maps of several x-ray-bright extended sources and phase-resolved polarimetry of many bright pulsating x-ray sources.

O'Dell, Stephen L.↗

The E4 protein; structure, function and patterns of expression

The papillomavirus E4 open reading frame (ORF) is contained within the E2 ORF, with the primary E4 gene-product (E1{sup ∧}E4) being translated from a spliced mRNA that includes the E1 initiation codon and adjacent sequences. E4 is located centrally within the E2 gene, in a region that encodes the E2 protein′s flexible hinge domain. Although a number of minor E4 transcripts have been reported, it is the product of the abundant E1{sup ∧}E4 mRNA that has been most extensively analysed. During the papillomavirus life cycle, the E1{sup ∧}E4 gene products generally become detectable at the onset of vegetative viral genome amplification as the late stages of infection begin. E4 contributes to genome amplification success and virus synthesis, with its high level of expression suggesting additional roles in virus release and/or transmission. In general, E4 is easily visualised in biopsy material by immunostaining, and can be detected in lesions caused by diverse papillomavirus types, including those of dogs, rabbits and cattle as well as humans. The E4 protein can serve as a biomarker of active virus infection, and in the case of high-risk human types also disease severity. In some cutaneous lesions, E4 can be expressed at higher levels than the virion coat proteins, and can account for as much as 30% of total lesional protein content. The E4 proteins of the Beta, Gamma and Mu HPV types assemble into distinctive cytoplasmic, and sometimes nuclear, inclusion granules. In general, the E4 proteins are expressed before L2 and L1, with their structure and function being modified, first by kinases as the infected cell progresses through the S and G2 cell cycle phases, but also by proteases as the cell exits the cell cycle and undergoes true terminal differentiation. The kinases that regulate E4 also affect other viral proteins simultaneously, and include protein kinase A, Cyclin-dependent kinase, members of the MAP Kinase family and protein kinase C. For HPV16 E1{sup ∧}E4, these kinases regulate one of the E1{sup ∧}E4 proteins main functions, the association with the cellular keratin network, and eventually also its cleavage by the protease calpain which allows assembly into amyloid-like fibres and reorganisation of the keratin network. Although the E4 proteins of different HPV types appear divergent at the level of their primary amino acid sequence, they share a recognisable modular organisation and pattern of expression, which may underlie conserved functions and regulation. Assembly into higher-order multimers and suppression of cell proliferation are common to all E4 proteins examined. Although not yet formally demonstrated, a role in virus release and transmission remains a likely function for E4. - Highlights: • E4 gene products have a modular structure, and are expressed from the E1{sup ∧}E4 spliced mRNA. • E4 proteins are modified during epithelial differentiation by phosphorylation and proteolysis. • The E4 proteins contribute to genome amplification-efficiency and virus synthesis. • E4 proteins are abundantly expressed and may facilitate efficient virus release and transmission. • High-risk E4 proteins are deposited as amyloid fibres and can be used as infection biomarkers.

60 APPLIED LIFE SCIENCES↗

Epitaxial growth, magnetoresistance, and electronic band structure of GdSb magnetic semimetal films

Motivated by observations of extreme magnetoresistance (XMR) in bulk crystals of rare-earth monopnictide (RE-V) compounds and emerging applications in novel spintronic and plasmonic devices based on thin-film semimetals, we have investigated the electronic band structure and transport behavior of epitaxial GdSb thin films grown on III-V semiconductor surfaces. The Gd 3 + ion in GdSb has a high spin S=7/2 and no orbital angular momentum, serving as a model system for studying the effects of antiferromagnetic order and strong exchange coupling on the resulting Fermi surface and magnetotransport properties of RE-Vs. Here, we present a surface and structural characterization study mapping the optimal synthesis window of thin epitaxial GdSb films grown on III-V lattice-matched buffer layers via molecular-beam epitaxy. To determine the factors limiting XMR in RE-V thin films and provide a benchmark for band-structure predictions of topological phases of RE-Vs, the electronic band structure of GdSb thin films is studied, comparing carrier densities extracted from magnetotransport, angle-resolved photoemission spectroscopy (ARPES), and density-functional theory (DFT) calculations. ARPES shows a hole-carrier rich, topologically trivial, semimetallic band structure close to complete electron-hole compensation, with quantum confinement effects in the thin films observed through the presence of quantum-well states. DFT-predicted Fermi wave vectors are in excellent agreement with values obtained from quantum oscillations observed in magnetic field-dependent resistivity measurements. An electron-rich Hall coefficient is measured despite the higher hole-carrier density, attributed to the higher electron Hall mobility. The carrier mobilities are limited by surface and interface scattering, resulting in lower magnetoresistance than that measured for bulk crystals.

36 MATERIALS SCIENCE↗