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At least 1,153 records · Page 64

Amylases in the Human Vagina

ABSTRACT Dominance of Lactobacillus species in vaginal communities is a hallmark of healthy conditions in the female genital tract. Key nutrients for lactobacilli include sugars produced when glycogen is degraded by α-amylase in the vagina. While α-amylase activity has been demonstrated in vaginal fluids, it is unclear whether α-amylases are produced solely by the host, bacteria in the vagina, or both. We screened cervicovaginal mucus from 23 reproductive-age women, characterized the species composition of vaginal communities, measured vaginal pH, and determined levels of amylase activity, glycogen, and lactic acid. Based on differences in these measured variables, one sample from each of four individual donors was selected for metagenomic and proteomic analyses. Of eight putative bacterial amylases identified in the assembled bacterial metagenomes, we detected four in vaginal fluids. These amylases were produced by various bacteria in different vaginal communities. Moreover, no two communities were the same in terms of which bacteria were producing amylases. Although we detected bacterial amylases in vaginal fluids, there was no clear association between the bacterial species that was dominant in a community and the level of amylase activity. This association was likely masked by the presence of human α-amylase, which was also detected in vaginal fluids. Finally, the levels of amylase activity and glycogen were only weakly associated. Our findings show, for the first time, that multiple amylases from both bacterial and human origins can be present simultaneously in the vagina. This work also suggests that the link between glycogen, amylase, and Lactobacillus in the vagina is complex. IMPORTANCE In this study, we show that multiple bacteria in the vaginal community produce amylases that hydrolyze glycogen into simpler sugars (i.e., maltose and maltotriose). These sugars serve as “common goods” that sustain bacterial populations in vaginal communities. Given the temporal changes that are observed in the human vaginal microbiome, we expect the kinds of bacterial amylases produced will also vary over time. These differences influence the pool of resources that are broadly shared and shape the species composition of the vaginal bacterial community.

59 BASIC BIOLOGICAL SCIENCES↗

Combinatorial Biosynthesis of Sulfated Benzenediol Lactones with a Phenolic Sulfotransferase from Fusarium graminearum PH-1

Total biosynthesis or whole-cell biocatalytic production of sulfated small molecules relies on the discovery and implementation of appropriate sulfotransferase enzymes. Although fungi are prominent biocatalysts and have been used to sulfate drug-like phenolics, no gene encoding a sulfotransferase enzyme has been functionally characterized from these organisms. Here, we identify a phenolic sulfotransferase, FgSULT1, by genome mining from the plant-pathogenic fungus Fusarium graminearum PH-1. We expressed FgSULT1 in a Saccharomyces cerevisiae chassis to modify a broad range of benzenediol lactones and their nonmacrocyclic congeners, together with an anthraquinone, with the resulting unnatural natural product (uNP) sulfates displaying increased solubility. FgSULT1 shares low similarity with known animal and plant sulfotransferases. Instead, it forms a sulfotransferase family with putative bacterial and fungal enzymes for phase II detoxification of xenobiotics and allelochemicals. Among fungi, putative FgSULT1 homologues are encoded in the genomes of Fusarium spp. and a few other genera in nonsyntenic regions, some of which may be related to catabolic sulfur recycling. Computational structure modeling combined with site-directed mutagenesis revealed that FgSULT1 retains the key catalytic residues and the typical fold of characterized animal and plant sulfotransferases. Our work opens the way for the discovery of hitherto unknown fungal sulfotransferases and provides a synthetic biological and enzymatic platform that can be adapted to produce bioactive sulfates, together with sulfate ester standards and probes for masked mycotoxins, precarcinogenic toxins, and xenobiotics.

59 BASIC BIOLOGICAL SCIENCES↗

Elevated temperature alters microbial communities, but not decomposition rates, during 3 years of in situ peat decomposition

ABSTRACT Peatlands are large carbon sinks with primary production outpacing decomposition of organic matter. Results from the S pruce and P eatland R esponses U nder C hanging E nvironments (SPRUCE) study show net losses of organic matter and increased greenhouse gas production from peatlands in response to whole-ecosystem warming. Here, we investigated how warming and elevated CO 2 impact peat microbial communities and peat soil decomposition rates and characterized microbial communities through amplicon sequencing and compositional changes across four depth increments. Microbial diversity and community composition were significantly impacted by soil depth, temperature, and CO 2 treatment. Bacterial/archaeal α-diversity increased significantly with increasing temperature, and fungal α-diversity was lower under elevated CO 2 treatments. Trans domain microbial networks showed higher complexity of microbial communities in decomposition ladder depths from the warmed enclosures, and the number of highly connected hub taxa within the networks was positively correlated with temperature. Methanogenic hubs were identified in the networks constructed from the warmest enclosures, indicating increased importance of methanogenesis in response to warming. Microbial community responses were not however reflected in measures of peat soil decomposition, as warming and elevated CO 2 had no significant short-term effects on soil mass loss or composition. Regardless of treatment, on average only 4.5% of the original soil mass was lost after 3 years and variation between replicates was high, potentially masking treatment effects. Previous results at the SPRUCE experiment have shown warming is accelerating organic-matter decomposition and CO 2 and CH 4 production, and our results suggest these changes may be driven by warming-induced shifts in microbial communities. IMPORTANCE Microbial community changes in response to climate change drivers have the potential to alter the trajectory of important ecosystem functions. In this paper, we show that while microbial communities in peatland systems responded to manipulations of temperature and CO 2 concentrations, these changes were not associated with similar responses in peat decomposition rates over 3 years. It is unclear however from our current studies whether this functional resiliency over 3 years will continue over the longer time scales relevant to peatland ecosystem functions.

54 ENVIRONMENTAL SCIENCES↗

FCC-ee interaction region backgrounds

The FCC-ee machine induced backgrounds on the two proposed detectors (CLD and IDEA) have been studied in detail. Synchrotron Radiation (SR) considerations dictate the Interaction Region (IR) optimization. An asymmetric IR design limits the final bend critical energy to 100 keV. Masks placed before the final focus quadrupole protect the detector from direct hits, and a shield placed around the beam pipe from secondary particles, keeping the effect of SR on the detector to negligible levels. The most important source of background is expected to be the Incoherent Pair Creation (IPC). Its effect has been studied in full simulation and reconstruction, and it was shown that it will not pose a problem for the detector, even if conservative estimations for the time resolution of the detector sensors are assumed. Moreover, the γγ → hadrons, radiative Bhabhas and beam-gas interaction induced backgrounds were studied. All were found to have small to negligible effect on the detector. Finally overall, the FCC–ee interaction region backgrounds are not expected to compromise the detector performance.

47 OTHER INSTRUMENTATION↗

Emerging Flexible Designs for Geospatial Multimodal Foundation Models

Foundation models are rapidly transforming Earth observation by enabling scalable pretraining across diverse unlabeled geospatial modalities. However, their architectural diversity—ranging from encoder-only to encoder-decoder and masked autoencoding paradigms—makes it challenging to assess performance trade-offs in a consistent manner. In this work, we present an apples-to-apples comparison of leading FM architectures designed for geospatial multimodal reasoning, with a particular focus on flexibility across varied spectral band configurations. We standardize pretraining using identical self-supervised learning objectives and training datasets, and evaluate all models under consistent parameterization on the GEOBench benchmark across classification and segmentation tasks. Our results offer new insights into the design trade-offs between model flexibility, modality alignment, and downstream task performance. By highlighting architectural strengths and limitations under controlled conditions, this study provides practical guidance for building next-generation geospatial foundation models capable of robust multimodal reasoning.

Ambrozio Dias, Philipe [ORNL] (ORCID:0000000194277↗

Demystifying the Diffuse Vibrational Spectrum of Aqueous Protons Through Cold Cluster Spectroscopy

The ease with which the pH is routinely determined for aqueous solutions masks the fact that the cationic product of Arrhenius acid dissolution, the hydrated proton, or H + (aq), is a remarkably complex species. Here, we review how results obtained over the past 30 years in the study of H + ·(H 2 O) n cluster ions isolated in the gas phase shed light on the chemical nature of H + (aq). This effort has also revealed molecular-level aspects of the Grotthuss relay mechanism for positive-charge translocation in water. Recently developed methods involving cryogenic cooling in radiofrequency ion traps and the application of two-color, infrared–infrared (IR–IR) double-resonance spectroscopy have established a clear picture of how local hydrogen-bond topology drives the diverse spectral signatures of the excess proton. This information now enables a new generation of cluster studies designed to unravel the microscopic mechanics underlying the ultrafast relaxation dynamics displayed by H + (aq).

Chemistry↗

Observation of a single protein by ultrafast X-ray diffraction

* runs/ - The raw data from the pnCCD * histograms.h5 - Histogram of the values recorded by each pixel throughout the data acquisition. Used for pedestal and gain correction. * mask.h5 - Detector bad pixels mask. * 1SS8.pdb - PDB model of the assembled GroEL 14-mer, from the 1SS8 PDB entry. * 1SS8_H2O.pdb - Hydrated version of the assembled GroEL 14-mer, derived from the 1SS8 PDB entry. The various hydrated models are created by removing water from this initial model. * rotations.h5 - Quaternions of the rotations used for template matching

European XFEL↗

Panel-Segmentation [SWR-21-18]

Panel-Segmentation contains the scripts for automated metadata extraction of solar PV installations, using satellite imagery coupled with computer vision techniques. In this package, the user can perform the following actions: *Automatically generate a satellite image using a set of lat-long coordinates, and a Google Maps API key. Users would need to set up a Google Cloud account and get a Maps Static API key. Please refer to Setting Up Google Maps Static API Key section for this process. *Perform image segmentation on the satellite image, to locate the solar array(s) in the image on a pixel-by-pixel basis, using an image segmentation model (panel_detection_model.pth). Get classification of the installation (rooftop, ground mounted fixed-tilt or tracking, carport, etc). *Perform azimuth estimation on each solar array cluster in the masked image. *Detect solar panels and get its latitude, longitude, and address within a geographic bounding box through the SOL-Searcher Pipeline. *Detect and calculate hurricane damage on solar installations given pre-hurricane and post-hurricane satellite imagery through the Hurricane Detection Pipeline. *Detect and calculate hail damage on solar installations given satellite imagery through the Hail Detection pipeline. *Convert NOAA MESH (Maximum Estimated Size of Hail) grib2 files into kml or geojson files. *Estimate tilt and azimuth of a solar array by processing USGS LiDAR data for the array’s location.

Edun, Ayobami↗

RadTraQ (Radar Tracking and Quality Toolkit

RadTraQ is a python library housing routines related to assessing and monitoring the quality of a radar's quality and calibration. This library is a work in progress, currently housing scripts to plot radar CFADs, plot and analyze corner reflector scans, calculate noise floors, create cloud masks, and plot up average profiles for comparisons.

THEISEN, ADAMK↗

FINITE-ELEMENT DISTORED WAVE BORN APPROXIMATION FOR SURFACE SCATTERING

FE-DWBA is a software package that computes the x-ray scattering patterns of objects that locate on a surface or buried next to a surface, such as the nano-circuits and nano-patterns of the mask used in the extreme ultraviolet lithography. It can incorporate the dynamical scattering effect (photons scattered multiple times), which is predominant in surface scattering and yield high-fidelity scattering patterns. The application includes surface imaging using x-rays, and critical dimension determination for semiconductor manufacturing.

HU, MAIOQI↗

Cybersecurity-Tools/V2W-BERT

Software Vulnerabilities to Weakness Mapping. V2W-BERT optimizes the learnable parameters θ of Fθ in two steps. In the first step, the pre-trained BERT language model is further fine-tuned with CVE/CWE descriptions specific to cyber security. In the second step, the trained BERT model is employed in a Siamese network architecture to establish links between CVEs and CWEs. The architecture takes a specific CVE-CWE pair as input and predicts whether the CVE belongs to the CWE or not, with a confidence value. V2W-BERT includes a Mask Language Model (LM) based Reconstruction Decoder to ensure that the descriptions’ contexts are not changed too much during the training process.

Halappanavar,, Mahantesh↗

test-grid-buildouts [SWR-23-112]

Test-grid-buildouts is a set of notebooks for creating buildouts of synthetic transmission grids with various levels of renewable energy. Workflows can be used to augment various test grid with varying levels of wind/solar generation. Aggregated renewable energy time series (actuals and scenarios) at grid buses can then be used for various transmission grid operation problems. Highly customizable workflow consists of parsing of synthetic grid files, setting up SAM & reV simulations, application of exclusion masks, creating of custom renewable generators on the grid, aggregating of power time series, and writing of modified grid description files.

Satkauskas, Ignas↗

Disclosure of the XRD pipeline software

The XRD pipeline software is a program to reduce 2D X-ray diffraction data from area detectors with advanced algorithms on automatic masking and image segmentation, which help characterization of multiple phases recorded in the data and facilitate data analysis.SF-25-114

XU, WENQIAN [Argonne National Laboratory (ANL), Ar↗

Simulation-Based Inference for Neutrino Interaction Model Tuning

This project demonstrates, for the first time, the application of simulation-based inference (SBI) techniques to tune neutrino–nucleus interaction models. Using a mock dataset based on the MicroBooNE tuning of the GENIE event generator, our approach employs a Neural Posterior Estimator (NPE) with Masked Autoregressive Flows (MAF) to infer the posterior distributions of key GENIE parameters directly from simulated histograms. The workflow provides a scalable and amortized framework for performing likelihood-free inference in high-dimensional parameter spaces, offering a pathway to more efficient and uncertainty-aware model tuning for next-generation neutrino experiments such as DUNE and SBND.

Tame-Narvaez, KarlaMaria [Fermi National Accelerat↗

Machine Learning Atom Probe Tomography Tool For Automatic And Fast Clustering

The software uses a YOLO11 segmentation model trained on synthetic data to analyze APT datasets. The workflow operates as follows: 1. Data Slicing: The APT dataset is divided into multiple 2D cross-sections of a specified thickness. 2. Segmentation: The model identifies point-dense regions within each 2D slice. 3. 3D Reconstruction: Detected regions (masks) from all slices are combined and reconstructed back into the original 3D space, forming clusters. The integration with HPC resources enables the software to process large-scale APT datasets efficiently. This combination of automation and scalability reduces manual intervention, improves reproducibility, and accelerates the clustering workflow.

Tang, Yalei [Idaho National Laboratory (INL), Idah↗

areaDetector/ADTimePix3

ADTimePix3 is an open‑source EPICS areaDetector driver for TimePix3 pixel detectors from Advanced Scientific Instruments (ASI). It provides a complete control and data‑acquisition interface between EPICS and the Serval server, supporting both real detectors (single‑chip and 2×2 quad configurations) and the TimePix3 emulator. The driver configures measurements via an HTTP/JSON REST API and acquires data through high‑rate TCP streams for raw events, images, and histograms. It offers real‑time preview and accumulated images, Time‑of‑Flight histogram processing, pixel masking (including Binary Pixel Configuration files and hot‑pixel tools), extensive health and status monitoring, and integration with standard areaDetector plugins for file saving and downstream analysis. ADTimePix3 is designed for Linux 64‑bit systems (tested on Ubuntu and RHEL) and is distributed under an MIT license with additional institutional disclaimers, enabling reuse and extension in photon science beamlines and other TimePix3‑based experimental facilities.

Gofron, Kaz↗