University of Oklahoma

Mechanisms driving aggressive meningiomas remain poorly understood. Given the pivotal role of the immune microenvironment in tumor progression, we developed a comprehensive atlas of the meningioma microenvironment, with a view toward identifying modifiable opportunities. The immune microenvironment of 2,727 meningiomas was profiled using orthogonal methodologies, including 24 with mass cytometry, 24 single-cell RNAseq, 1,437 bulk RNAseq, 1,125 DNA methylation, 117 multiplex immunofluorescence, as well as that of 5 paired peripheral blood samples and 10 human meninges. Patient-derived organotypic tumor spheroids (PDOTS) were established to assess the effect of STING stimulation combined with anti-PD-1 treatment. We revealed a rich immune infiltration in meningioma, among the highest across 34 human cancer types (n = 12,188). Macrophages predominated in meningioma microenvironment, in contrast to the lymphoid dominance of peripheral blood, with meninges exhibiting an intermediate immune profile between meningiomas and peripheral blood. Cellular states and phenotypes of both immune and tumor cells shifted during tumor progression, with aggressive meningiomas possessing earlier-stage, immunosuppressive immune cells and proliferative tumor cells. Using ex vivo meningioma PDOTS, we demonstrated inducible responses to STING activation, marked by elevated cytokine release, which were synergistic when combined with PD-1 blockade. These findings offer an extensive resource on the cellular heterogeneity of the meningioma microenvironment and provide a framework for rational therapeutic modeling and strategy development.

Incorporation of postconsumer recycled (PCR) plastics in asphalt mixes is reported to improve the mechanical performance of asphalt mixes when used at a lower dosage. However, overstiffening of asphalt mixes due to the addition of higher amounts of plastic has been a serious concern. To this end, this study aims at increasing the percentage of plastic in asphalt mixes by incorporating a biorejuvenator. For this purpose, a control mix was designed using the balanced mix design (BMD) approach and then modified with two different types of PCR plastics, namely low-density polyethylene (LDPE) and linear low-density polyethylene (LLDPE). The asphalt mixes were then further modified by adding a biorejuvenator. The volumetric properties were determined, and the mechanical performances (rutting, cracking, and moisture-induced damage resistance) of the asphalt mixes were evaluated using the Hamburg Wheel Tracking (HWT) and Indirect Asphalt Tensile Cracking Test (IDEAL-CT). The optimum dosage of plastics was determined using the BMD criteria. The optimum dose of LDPE was found to be 1.5% with 2% waste cooking oil (WCO)-modified binder. In addition, environmental impact analyses were performed on the plastic-modified mixes. A significant reduction in greenhouse gas emission was observed from the use of plastic in asphalt mixes. A minimum of 7.5% reduction in greenhouse gas generation was found by using optimum LDPE and WCO-modified asphalt mixes.

Abstract Coastal breeze circulations [bay breeze (BB) and sea breeze (SB)] modulate weather conditions by advecting a maritime air mass onshore, altering air quality, and often initiating deep convection. Coastal breeze interactions with the planetary boundary layer (PBL) are not well simulated due to small-scale interactions being parameterized by numerical weather models. As part of the Tracking Aerosol Convection Interactions Experiment (TRACER) in Houston, Texas, PBL observations from remote sensors and uncrewed aerial systems provide a unique benchmark for evaluating model performance and investigating underlying processes. The Warn-on-Forecast System (WoFS) is a convection-allowing, 18-member ensemble designed to predict high-impact weather by combining rapidly updating data assimilation cycles with varying PBL and radiation parameterizations. The TRACER datasets are used to evaluate WoFS’s simulation of the PBL, coastal breezes, and their interactions with high vertical and temporal resolution. There is broad variability across members in the depth, arrival time, and intensity of the simulated SB case. Moreover, only a subset of members simulate the preceding BB, but none do so accurately. The radiation scheme impacts the ability to simulate a BB and the onset time of the SB. The mixing scheme for PBL parameterization lends differences in depth, intensity, and evolution. Nonlocal mixing schemes allow baroclinic circulations to develop more readily, thus simulating coastal flows better, but overestimate PBL depth and temperature. The influence parameterization schemes have on meteorological biases offers potential solutions to improve simulations of coastal PBL processes.

Abstract This chapter investigates the coexistence of corporate social responsibility (CSR) and corporate social irresponsibility (CSI) within the same leadership teams, advancing a behavioural strategy lens on executive decision-making. Cases such as Enron, Volkswagen and Meta illustrate how leaders simultaneously cultivate legitimacy through prosocial initiatives while engaging in misconduct, showing CSR and CSI to be strategically intertwined rather than moral opposites. Scholarship has typically treated them in isolation – CSR as stakeholder engagement, CSI as opportunism – leaving little theorization of their joint occurrence. To address this gap, we integrate a bibliometric analysis of over 5,000 articles with a systematic review of 319 studies, yielding a multilevel configurational framework. Findings reveal how individual traits, team dynamics, organizational structures and institutional pressures interact through mechanisms such as impression management, moral disengagement and strategic ambiguity, under boundary conditions like governance design and cultural norms. By introducing concepts such as moral elasticity and ethical ambivalence, the chapter reframes CSR and CSI as complementary dimensions of executive agency under bounded rationality and institutional pluralism. This reconceptualization expands behavioural strategy’s explanatory reach and offers a forward-looking agenda for governance and responsibility research.

Satellite synthetic aperture radar (SAR) imagery enables all-weather observation of landslide hazards, yet isolating landslide signals from pervasive noise in SAR intensity imagery remains challenging, particularly across diverse terrains and spatial scales. We develop a spectral filtering approach for C-band dual-polarized multitemporal SAR intensity imagery to enhance the detection of widespread landslides in Hokkaido and Hiroshima, Japan, triggered by earthquakes and rainfall events in 2018, respectively. Fourier spectral analysis of SAR intensity change images, constructed from post-event stacking from days to months, reveals characteristic separation between lower-frequency landslide signals (wavelengths >80–125 m) and higher-frequency noise (<60–70 m). Through spatial low-pass filtering, landslide areas are enhanced and distinguished from non-landslide areas, using uniform or adaptive percentile thresholds that vary by land surface type. Detected landslides are validated against independent inventories via pixel-based receiver-operating-characteristic curves and classification metrics. From low- to high-stacking conditions, filtered cases increase overall accuracy (89–94% in Hokkaido and 95–98% in Hiroshima) and precision (34–81% and 8–26%) compared to unfiltered cases. Detection performance varies with slope attributes and land surface conditions, with optimal metrics for moderate slopes (~6–18°) and forested terrains. Spectral filtering of noisier low-stacking images retains larger landslides and reduces misdetections for smaller ones, preserving power-law frequency-area scaling over ~103–105 m2. Our approach facilitates near-real-time landslide characterization and continuous landscape monitoring.

The Ground Hydrological Observation Gear (GroundHOG) sites in the Susquehanna Shale Hills Critical Zone Observatory provide integrated observation of water, energy, and temperature at the Cole Farm field site within the greater Shavers Creek watershed. Soil moisture and soil temperature are measured at 4 depths at 4 sites. Each of these measurements is made using HydraProbe II sensors from Stevens Instruments. These datasets were collected at four locations: Ridge Top, East Mid-slope, West Mid-slope, and Valley Floor. All data have been quality controlled.