Enterprise Science and Computing (United States)

Context. The X-ray output of low-metallicity starburst galaxies is a key component of stellar feedback, tracing the processes responsible for gas ionization and chemical enrichment. The integrated X-ray luminosity ( L X ) from high-mass X-ray binaries in star-forming galaxies scales with the star formation rate (SFR) and the host galaxy metallicity Z . Due to the inverse correlation between L X /SFR and Z , the contribution of X-ray binaries to the ionizing photon budget is expected to be enhanced in metal-poor systems. Their radiation can potentially ionize He II in the surrounding interstellar medium, powering nebular He II λ 4686 Å emission. However, detailed studies of the X-ray emission in individual low- Z starburst galaxies are rare, and their X-ray properties are not well explored. Aims. The blue compact dwarf galaxy ESO 338-IG04 (ESO 338-4 hereafter) serves as a nearby template for studying stellar feedback and X-ray emission in low-metallicity starbursts. It combines vigorous recent star formation, a low metallicity (12 + log(O/H)≈7.9, or 12% solar), and a rich population of massive stellar clusters. Extensively observed in optical and UV wavelengths with HST and VLT MUSE, ESO 338-4 is ideally suited for multiwavelength feedback studies. We characterize the X-ray emission of ESO 338-4 and its galactic halo using new deep observations obtained with the Chandra X-ray Observatory ( Chandra ) and XMM-Newton . Methods. We analyzed X-ray spectra, light curves, and images of ESO 338-4 to constrain the nature of its X-ray sources. Additionally, we employed photoionization modeling to assess the significance of X-ray sources to the observed nebular He II λ 4686 Å emission. Results. We identified five ultraluminous X-ray sources (ULXs) and diffuse hot gas surrounding ESO 338-4. Two of the ULXs are spatially associated with stellar clusters. The total galactic X-ray luminosity exceeds 10 41 erg s −1 . The brightest point source, ULX1, is variable on timescales of days and is not associated with a stellar cluster. Last, our modeling demonstrates that X-ray sources significantly affect the ionizing photon budget of the galaxy. Photoionization modeling with ULX1 as the ionizing source predicts a high nebular He II λ 4686 Å line luminosity of approximately 10 39 erg s −1 .

MAXI J1957+032 is an accreting millisecond X-ray pulsar that shows brief, recurrent outbursts in an ultra-compact ~1 h orbit. We characterise the 2025 outburst using X-ray timing and spectroscopy from XMM-Newton and Swift (and a late-time NuSTAR observation), together with contemporaneous optical photometry from LCO, and compare the spin frequency with the 2022 outburst. Timing searches detect coherent pulsations at ~313.6 Hz with no measurable frequency derivative during the XMM-Newton exposure. Relative to its 2022 outburst, we measure a long-term spin-down of ~-2x10^-14 Hz s^-1, consistent with magnetic-dipole braking in quiescence. The pulse profile is nearly sinusoidal, with significant power at the fundamental, second, and fifth harmonics; the fractional amplitude decreases with increasing flux and shows soft lags up to a few keV. The 0.5-10 keV spectrum is well described by absorbed thermal Comptonisation (photon index ~2.4) plus a cool blackbody (kT ~0.23 keV) consistent with emission from a surface hotspot; no reflection or Fe-line features are detected. Requiring R_m \leq R_co implies B_s ~(0.5-3)x10^8 G for d=(5 \pm 2) kpc and ξ=0.3-0.5, below the upper limit from the secular spin-down (B_p \leq 10^9 G), possibly indicating a mildly leaky propeller. The optical emission lies on the neutron-star branch of the L_OIR-L_X relation, consistent with reprocessing in a compact disc. The optical SEDs are broadly flat, while an early red excess suggests a transient jet contribution during the initial hard X-ray phase; an optical peak delayed relative to the X-rays may trace an outward-propagating heating front and rapid disc evolution in these short-lived outbursts.

Yamamoto’s rate equation was applied to two-step age hardening of an Al-6%Zn-0.75%Mg alloy. All aging processes at 160–200°C were described as the sum of three precipitation reactions, that is, spherical, plate-like, and rod-like precipitation independent of the holding time at room temperature (RT). These results agreed with the observation of TEM microstructures. Based on the activation energy of diffusion calculated from the rate equation, it was suggested that the diffusion of zinc controlled the spherical precipitation reaction, and the diffusion of magnesium did the rod-like one. The plate-like precipitation reaction which depended on the holding time at RT is controlled by the diffusion of zinc for a short time and the one of magnesium for a long time. These precipitation reactions were related to the meta-stable and stable phase particles. The comparison between electrical resistivity (ER) and Vickers hardness (HV) changes at 160°C aging showed that the HV change was faster than ER one in the long holding time at RT. On the other hand, the ER change became faster than HV change in the short one at RT. This difference is related to the formation of clusters and GP zones that are formed by holding at room temperature.

Finding global and local minima on the potential energy surface is a key task for most studies in computational chemistry. Having a set of possible conformations for chemical structures and their corresponding energies, one can judge their chemical activity, understand the mechanisms of reactions, describe the formation of metal-ligand and ligand-protein complexes, and so forth. Despite the fact that the interest in various minima search algorithms in computational chemistry arose a while ago (during the formation of this science), new methods are still emerging. These methods allow to perform conformational analysis and geometry optimization faster, more accurately, or for more specific tasks. This article presents the application of a novel global geometry optimization approach based on the Tree Parzen Estimator method. For benchmarking, a database of small organic molecule geometries in the global minimum conformation was created, as well as a software package to perform the tests.

For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays. The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC–MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Researchers are applying a wide variety of assay methods to explore the complex and dynamic human immunology system. There are a number of initiatives to encourage sharing of results, the standardization of terminology, and the reanalysis of data to improve reproducibility and ensure scientific rigor. The ImmPort project is an example of a NIH resource to collect, curate, and share immunological research. We describe the ImmPort project resources available to encourage an exploration of the tools and skill sets needed for analyzing shared immunological data, including clinical and mechanistic studies, analysis tools, and example analysis code. There is an ongoing effort to annotate the shared data with standardized terms from ontologies, make these curated data sets available in formats amenable to bioinformatic tools, and provide examples of how to access and analyze the data sets.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC), under the auspices of the National Cancer Institute's Office of Cancer Clinical Proteomics Research, is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of proteomic technologies and workflows to clinical tumor samples with characterized genomic and transcript profiles. The consortium analyzes cancer biospecimens using mass spectrometry, identifying and quantifying the constituent proteins and characterizing each tumor sample's proteome. Mass spectrometry enables highly specific identification of proteins and their isoforms, accurate relative quantitation of protein abundance in contrasting biospecimens, and localization of post-translational protein modifications, such as phosphorylation, on a protein's sequence. The combination of proteomics, transcriptomics, and genomics data from the same clinical tumor samples provides an unprecedented opportunity for tumor proteogenomics. The CPTAC Data Portal is the centralized data repository for the dissemination of proteomic data collected by Proteome Characterization Centers (PCCs) in the consortium. The portal currently hosts 6.3 TB of data and includes proteomic investigations of breast, colorectal, and ovarian tumor tissues from The Cancer Genome Atlas (TCGA). The data collected by the consortium is made freely available to the public through the data portal.

The Education and Student Activities Committee (ESAC) is on a roll this fall with a lot of exciting activity. The committee, led my Mark Steffka, is supporting both the Santa Clara and Dresden symposia in addition to its other initiatives and efforts. As you will see, a lot of work has been done and there is still a lot of hard work ahead of us.