Saint Louis University (SLU) is a private Jesuit research university with campuses in St. Louis, Missouri, United States, and Madrid, Spain. Founded in 1818 by Louis William Valentine DuBourg, it is the oldest university west of the Mississippi River and the second-oldest Jesuit university in the United States. It is one of 27 member institutions of the Association of Jesuit Colleges and Universities. The university is accredited by the North Central Association of Colleges and Secondary Schools.In the 2021-2022 academic year, SLU had an enrollment of 12,883 students. The student body included 8,138 undergraduate students and 4,745 graduate students that represents all 50 states and 82 countries. The University is classified as a Research II university by the Carnegie Classification of Institutions of Higher Education.For more than 50 years, the university has maintained a campus in Madrid, Spain. The Madrid campus was the first freestanding campus operated by an American university in Europe and the first American institution to be recognized by Spain's higher education authority as an official foreign university. The campus has 850 students, a faculty of 110, an average class size of 17 and a student-faculty ratio of 12:1. Of the 12,883 students, 788 study at the Madrid Campus which also represents students from 45 of the 82 total countries students are from.SLU's athletic teams compete in the National Collegiate Athletic Association's Division I and are a member of the Atlantic 10 Conference.
In photosynthetic proteins, pigments at a higher energy level funnel excitation energy to pigments at a lower energy level. Specifically, in Photosystem II (PSII), energy is transferred downhill to the reaction center (RC), where water splitting occurs. However, the lowest-energy state in PSII is not the RC, but the F695 state, which can be observed using low-temperature spectroscopy. This lowest-energy state is typically assigned to a monomeric pigment, Chl B16 (ligated by His114), but this assignment has been called into question based on theoretical fits to low-temperature spectra. In this study, we set out to test concretely whether the F695 state is localized on Chl B16 using site-directed mutagenesis and 77 K fluorescence spectroscopy. To reduce spectral congestion for whole-cell PSII studies, we developed a background strain (PSI-kd/ Δ PBS) that combines a Photosystem I (PSI) knockdown with a Phycobilisome (PBS) knockout. In this background strain, we made site-directed mutations at site Thr5 in the PsbH subunit, which forms a hydrogen bond with the 13^1 -keto group of Chl B16. All mutants were capable of heterotrophic growth (without noticeable differences from wild-type), indicating the PSII function remains intact. As expected for Chl B16-localized fluorescence, the Thr5 → Arg mutation red-shifted the F695 state due to the strengthening of the hydrogen bond, while the Thr5 → Ala mutation exhibits a blue shift as the hydrogen bond is eliminated. Taken together, these findings provide strong confirmation that Chl B16 is responsible for the lowest-energy state.
Human milk oligosaccharides (HMOs) are complex sugars in breast milk that protect babies by preventing harmful bacteria from colonizing the gut. Our team extended the study of HMOs beyond the neonatal gut and characterized their antimicrobial activity against group B Streptococcus (GBS), a diplococcus responsible for invasive perinatal infection. To date, the mechanism of action of this antimicrobial activity has remained obscure. To address this key gap, we employed untargeted proteomics, which revealed downregulation of PcsB, an essential murein hydrolase required for cell division. Following successful purification of the active domain of PcsB, we found that this protein domain restores GBS growth in the presence of HMOs, thereby validating PcsB as an HMO protein-interacting partner. In silico docking and molecular dynamics simulations predicted that two fucosylated HMOs, lacto-N-fucopentaose I (LNFPI) and lacto-N-fucopentaose III (LNFPIII), bind to PcsB. In silico predictions were validated using microscale thermophoresis assays, which reported dissociation constants of 5 ± 1 mM for LNFPI and 263 ± 72 μM for LNFPIII. Lastly, to test the hypothesis that HMOs may directly modulate the enzymatic activity of the CHAP domain, we employed a turbidimetric assay with commercial PG as the substrate. This assay provided further evidence that HMOs inhibit CHAP. Together, these data suggest that HMOs inhibit GBS growth by binding PcsB at its catalytic site, disturbing essential cell wall separation and division.
Through centuries and across continents, the singular condition which brings afflicted individuals in conflict with society is what might be broadly regarded as psychopathic disorder. Within the considerable body of knowledge amassed, the investigator who has indisputably made the most substantial contribution is Robert Hare, whose conceptualization of psychopathy is measurable as a superarching dimension and with subdimensions or factors and their facets. The instrument for identifying and measuring psychopathy, the Psychopathy Checklist-Revised (PCL-R), commonly regarded as the gold standard for psychopathy research (Westen Weinberger, 2004), is widely used internationally for psychopathy research. Authors from four international domains – Germanic, Italian, Nordic and English – briefly describe the development of concepts of the psychopathic disorder, the influence of psychopathy as defined by Hare, as well as research and practical applications of PCL-R psychopathy and/or specific contributions concerning psychopathy within each of the domains. From the richness and diversity of investigative productivity within each of these domains, one can readily appreciate the impact of Hare’s work both within and between these major domains.
Driving behaviour is the main contributor to road crashes. Increasing the road incidents on Malaysian highways raised the concern about traffic safety. The emergence of Autonomous Vehicles (AVs) has the potential to reshape traffic dynamics and safety outcomes on Malaysian roads. Yet, assessing how mixed traffic of Conventional Vehicles (CVs) and AVs influences driving behaviour during incident occurrence remains not investigated. This study assessing the incident driving behaviour impact under varying driving behaviour logics (Cautious, Normal, and Aggressive) by utilising a dynamic CoExist microsimulation model integrated with a unique optimisation method based on Genetic Algorithm (GA) and COM interface feature. First, the study analysed three years of incident data using PTV VISUM to identify incident hot spots. Secondly, the study implemented PTV VISSIM's CoExist framework to simulate three different segments of three selected highways (E2 AH2, E6 ELITE, and E23 Kerinchi Link) during peak periods. Third, a total of 23 different driving behaviours from four different driving models, which are following, car-following, lane change, and lateral movement, were calibrated to reflect a comprehensive behaviour of local conditions. Finally, an incident scenario was implemented utilising VISSIM’s event-based script to evaluate bottleneck impacts on driving behaviour. Simulation outcomes demonstrate that AVs significantly improves traffic safety compared to CVs. Specifically, AVs maintained superior operational condition awareness by dynamically expanding their forward scanning and proactively increasing their minimum look back distance. This expanded perception successfully overcomes limited situational awareness and cognitive tunnel vision exhibited by human drivers, allowing faster reactions to prevent secondary collisions.
Missing data are a pervasive challenge in data-intensive science and engineering, where imputation must recover incomplete observations while preserving downstream predictive performance. Ultra-data-oriented parallel fractional hot-deck imputation (UP-FHDI) is an assumption-free and scalable approach for large, high-dimensional incomplete data. However, its practical value and configuration sensitivity cannot be fully characterized by imputation accuracy alone. To address this gap, we propose an imputation-and-prediction integrated framework (IPIF) that jointly evaluates imputation methods from two complementary perspectives: imputation quality and impact on downstream predictive tasks. Unlike conventional approaches that treat imputation as an isolated preprocessing step, IPIF provides a unified and modular pipeline in which imputation methods and predictive models can be flexibly integrated. To further enhance scalability, we refine the parallel workflow of UP-FHDI through optimized file system and communication strategies, significantly reducing I/O overhead in large-scale settings. Extensive experiments on synthetic and real-world datasets demonstrate that UP-FHDI consistently outperforms state-of-the-art baselines in imputation accuracy and yields improved downstream predictive performance. Notably, the results reveal that lower imputation error does not necessarily translate into better predictive outcomes, underscoring the importance of task-oriented evaluation. Finally, sensitivity analyses of the UP-FHDI configurations within IPIF indicate that selecting 70–90 important variables achieves a favorable balance between imputation effectiveness and predictive performance.
