Maxime A. Visa

Background: Traumatic brain injury ( TBI ) carries significant mortality and morbidity in civilian and military populations. Current treatment guidelines for TBI are primarily supportive, and no pharmacological agent exists to attenuate the progression of brain injury. Valproic Acid ( VPA ) has long been used to treat neurological disorders; however, recent work has demonstrated its potential as a neuroprotective agent. We have already demonstrated that VPA administration in swine models of TBI (with or without associated hemorrhage and polytrauma) significantly improves survival and neurological recovery and decreases brain lesion size compared to controls. This paper introduces a phase 2/3 clinical trial that is designed to evaluate the efficacy and safety of VPA administration in patients with TBI. Methods: In this randomized, double‐blind, placebo‐controlled, multicenter trial, patients with moderate to severe TBI ( GCS 3–12) across nine level 1 trauma centers in the US will be randomized to receive either standard of care treatment and 250 mL of isotonic saline (control), or standard of care treatment and intravenous VPA at either 50 mg/kg (low‐dose VPA group), or 100 mg/kg (high‐dose VPA group). The primary endpoint of this clinical trial will be neurological status as measured by the Extended Glasgow Outcome Scale ( GOS ‐E) 3 months post‐TBI. Discussion: Our team has conducted multiple large animal studies that strongly support the cytoprotective effects of VPA treatment. The goal of this upcoming trial is to study the efficacy and safety of two doses of VPA in patients with moderate to severe TBI . Trial registration: ClinicalTrials.gov, https://clinicaltrials.gov/study/NCT07166393 , September 3, 2025.

Electric vehicle adoption strategies have the potential to reduce greenhouse gas and air pollutant emissions. However, the effectiveness of this transition may depend on which vehicles are electrified, and where. To assess the efficacy of different modes of transportation electrification, we apply a watts-to-wheel analysis framework that accounts for upstream emission increases from battery charging and downstream reductions in tailpipe emissions. Using the WRF-CMAQ chemical transport model at ∼1 km ² resolution, we compare the greenhouse gas, air quality, and public health impacts of electrifying 30% of light-duty vehicles (eLDVs) versus 30% of heavy-duty vehicles (eHDVs) across a U.S. Midwestern domain. Both electrification scenarios achieve net reductions in CO ₂ emissions despite increased emissions from electricity generation units, with greater total reductions from eLDVs (∼7 Mt CO ₂ /year, −4.5%) than eHDVs (∼1.6 Mt CO ₂ /year, −1.1%). However, air quality benefits are greater in the eHDV scenario, where cumulative reductions in health-harming air pollutants such as nitrogen dioxide (NO ₂ ) and elemental carbon (EC) exceed those in the eLDV scenario. Both scenarios show modest increases in daily 8 h average ozone (MDA8 O ₃ ), with disbenefits largest in the eHDV scenario. Estimated health benefits of the eHDV scenario exceed those of the eLDV scenario, with 70 (50) more avoided premature deaths annually from reduced NO ₂ (EC), offset by 50 additional deaths from MDA8 O ₃ increases. In both scenarios, the largest health benefits occur in communities with higher proportions of Black and Hispanic residents. However, long-standing relative exposure disparities persist. On a per-vehicle basis, we find that electrifying one HDV yields nearly 5× more CO ₂ reduction-based economic benefits and 23× more NO ₂ reduction-based economic health benefits than a single eLDV. Our results demonstrate that multi-modal and multi-pollutant assessments are critical for informing more effective and equitable decarbonization and air pollutant remediation strategies.

Background: Robot-assisted thymectomy (RAT) has been widely accepted due to its safety and feasibility. However, the optimal approach for large thymomas remains unclear. This study compares peri-operative and long-term oncological outcomes of RAT and open thymectomy (OT) for large thymomas. Methods: From the National Cancer Database (NCDB), 1,592 patients with thymomas >4 cm who underwent RAT (n=259, 16.3%) or OT (n=1,333, 83.7%) between 2010 and 2017 were identified. Tumor size was categorized as 4–5 cm, >5–6 cm, and >6 cm. A propensity-score-matched cohort analysis assessed tumor size, operative approach, and overall survival (OS) using Cox proportional hazards models and Kaplan-Meier survival curves. A single-institutional dataset of thymectomies for thymomas >5 cm (2008–2023) was similarly queried. Results: Both RAT and OT groups had similar R0 rates and peri-operative outcomes from the NCDB. The matched cohort (n=500, 50% RAT) demonstrated comparable OS between groups. A higher proportion of the African American and uninsured/Medicaid patients tended to receive OT, while insured or white patients received RAT. Institutional analysis of 43 thymectomy patients with >5 cm thymoma (RAT: n=21, OT: n=22) showed no significant differences in demographics, tumor stage, R0 rate, OS, and recurrence-free survival. RAT had fewer postoperative complications (4.8% vs. 31.8%, P=0.02) and shorter hospital stays (2.1±2.3 vs. 4.3±2.3 days, PConclusions: RAT is associated with fewer complications and shorter hospital stays while maintaining comparable OS to OT for large thymomas. Socioeconomic and racial disparity continues to exist in RAT access among those with limited insurance and the African American population.

Objective: To synthesize the methodologies of studies that evaluate the impacts of heat exposure on morbidity and mortality. Methods: Embase, MEDLINE, Web of Science, and Scopus were searched from date of inception until 1 March 2023 for English language literature on heat exposure and health outcomes. Records were collated, deduplicated and screened, and full texts were reviewed for inclusion and data abstraction. Eligibility for inclusion was determined as any article with climate‐related heat exposure and an associated morbidity/mortality outcome. Results: Of 13,136 records initially identified, 237 articles were selected for analysis. The scope of research represented 43 countries, with most studies conducted in China (62), the USA (44), and Australia (16). Across all studies, there were 141 unique climate data sources, no standard threshold for extreme heat, and 200 unique health outcome data sources. The distributed lag non‐linear model (DLNM) was the most common analytic method (48.1% of studies) and had high usage rates in China (68.9%) and the USA (31.8%); Australia frequently used conditional logistic regression (50%). Conditional logistic regression was most prevalent in case‐control studies (5 of 8 studies, 62.5%) and in case‐crossover studies (29 of 70, 41.4%). DLNMs were most common in time series studies (64 of 111, 57.7%) and ecological studies (13 of 20, 65.0%). Conclusions: This review underscores the heterogeneity of methods in heat impact studies across diverse settings and provides a resource for future researchers. Underrepresentation of certain countries, health outcomes, and limited data access were identified as potential barriers.

Treatment guidelines for non-small cell lung cancer (NSCLC) vary by several factors including pathological stage, patient candidacy, and goal of treatment. With many therapeutics and even more combinations available in the NSCLC clinician’s toolkit, a multitude of questions remain unanswered vis-a-vis treatment optimization. While some studies have begun exploring the interplay among the many pillars of NSCLC treatment—surgical resection, radiotherapy, chemotherapy, and immunotherapy—the vast number of combinations and permutations of different therapy modalities in addition to the modulation of each constituent therapy leaves much to be desired in a field that is otherwise rapidly evolving. Given NSCLC’s high incidence and lethality, the experimentation of synergistic benefits that combinatorial treatment may confer presents a ripe target for advancement and increased understanding without the cost and burden of novel drug development. This review introduces, synthesizes, and compares prominent NSCLC therapies, placing emphasis on the interplay among types of therapies and the synergistic benefits some combinatorial therapies have demonstrated over the past several years.

Heavy-duty vehicles (HDVs) disproportionately contribute to the creation of air pollutants and emission of greenhouse gases—with marginalized populations unequally burdened by the impacts of each. Shifting to non-emitting technologies, such as electric HDVs (eHDVs), is underway; however, the associated air quality and health implications have not been resolved at equity-relevant scales. Here we use a neighbourhood-scale (~1 km) air quality model to evaluate air pollution, public health and equity implications of a 30% transition of predominantly diesel HDVs to eHDVs over the region surrounding North America’s largest freight hub, Chicago, IL. We find decreases in nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) concentrations but ozone (O₃) increases, particularly in urban settings. Over our simulation domain NO₂ and PM_2.5 reductions translate to ~590 (95% confidence interval (CI) 150–900) and ~70 (95% CI 20–110) avoided premature deaths per year, respectively, while O₃ increases add ~50 (95% CI 30–110) deaths per year. The largest pollutant and health benefits simulated are within communities with higher proportions of Black and Hispanic/Latino residents, highlighting the potential for eHDVs to reduce disproportionate and unjust air pollution and associated air-pollution attributable health burdens within historically marginalized populations.

Electric vehicles (EVs) constitute just a fraction of the current U.S. transportation fleet; however, EV market share is surging. EV adoption reduces on-road transportation greenhouse gas emissions by decoupling transportation services from petroleum, but impacts on air quality and public health depend on the nature and location of vehicle usage and electricity generation. Here, we use a regulatory-grade chemical transport model and a vehicle-to-electricity generation unit electricity assignment algorithm to characterize neighborhood-scale (∼1 km) air quality and public health benefits and tradeoffs associated with a multi-modal EV transition. We focus on a Chicago-centric regional domain wherein 30% of the on-road transportation fleet is instantaneously electrified and changes in on-road, refueling, and power plant emissions are considered. We find decreases in annual population-weighted domain mean NO₂ (−11.83%) and PM_2.5 (−2.46%) with concentration reductions of up to −5.1 ppb and −0.98 µg m⁻³ in urban cores. Conversely, annual population-weighted domain mean maximum daily 8 h average ozone (MDA8O₃) concentrations increase +0.64%, with notable intra-urban changes of up to +2.3 ppb. Despite mixed pollutant concentration outcomes, we find overall positive public health outcomes, largely driven by NO₂ concentration reductions that result in outsized mortality rate reductions for people of color, particularly for the Black populations within our domain.

Electric vehicles (EVs) constitute just a fraction of the current U.S. transportation fleet; however, EV market-share is surging. EV adoption reduces on-road transportation greenhouse gas emissions by decoupling transportation services from petroleum, but impacts on air quality and public health depend on the nature and location of vehicle usage and electricity generation. Here, we use a regulatory-grade chemical transport model and an electricity dispatch algorithm to characterize neighborhood-scale (~1 km) air quality and public health benefits and tradeoffs associated with a multi-modal EV transition. We focus on a Chicago-centric regional domain wherein 30% of the on-road transportation fleet is instantaneously electrified and changes in on-road, refueling, and power plant emissions are considered. We find decreases in annual population-weighted domain mean NO2 (-11.84%) and PM2.5 (-2.56%) with concentration reductions of up to-5.1 ppb and-0.97 µg m-3 in urban cores. Conversely, annual population-weighted domain mean MDA8O3 concentrations increase +0.65%, with notable intra-urban changes of up to +2.3 ppb. Despite mixed pollutant concentration outcomes, we find overall positive public health outcomes, largely driven by NO2 decreases that produce mortality reductions that are ~5 times greater in census tracts with disproportionately large non-white populations.

A document by Maxime Visa. Click on the document to view its contents.

The U.S. and much of the world sit on the cusp of an electrification revolution – a moment driven largely by the need to reduce the emission of greenhouse gases to limit the impacts of anthropogenic climate change. The electrify everything movement aims to transition combustion-powered sectors into technologies powered solely by electricity, with the idea that the electric grid – currently comprised of a mix of combustion, renewable, and nuclear generation units – will become cleaner and greener over time. Studies indicate that electrifying high-efficiency devices, appliances, and vehicles will reduce greenhouse gas emissions regardless of the grid’s composition, however ancillary air quality benefits and tradeoffs remain poorly resolved, particularly at impact- and equity-relevant scales. Here, I use a fine-scale CONUS-wide climate and air quality co-benefit and tradeoff analysis framework (i.e., 4 km ² SMOKE-CMAQ-WRF simulations) to assess sustainable climate solutions. Analyses utilize emission scenarios that account for increased grid demand and uncertainties in grid evolution, simulate the interaction of meteorological and chemical processes, characterize changes in greenhouse gases and air pollutants, and assess economic, social, and public health consequences of sustainable transitions over two key, yet methodologically disparate, residential/commercial sectors: transportation: via the replacement of internal combustion vehicles with electric vehicles and lighting: via the replacement of low efficiency bulbs with high-efficiency LEDs.