This editorial considers the value and nature of academic psychiatry by asking what defines the specialty and psychiatrists as academics. We frame academic psychiatry as a way of thinking that benefits clinical services and discuss how to inspire the next generation of academics.

Coastal wetlands are hotspots of carbon sequestration, and their conservation and restoration can help to mitigate climate change. However, there remains uncertainty on when and where coastal wetland restoration can most effectively act as natural climate solutions (NCS). Here, we synthesize current understanding to illustrate the requirements for coastal wetland restoration to benefit climate, and discuss potential paths forward that address key uncertainties impeding implementation. To be effective as NCS, coastal wetland restoration projects will accrue climate cooling benefits that would not occur without management action (additionality), will be implementable (feasibility) and will persist over management-relevant timeframes (permanence). Several issues add uncertainty to understanding if these minimum requirements are met. First, coastal wetlands serve as both a landscape source and sink of carbon for other habitats, increasing uncertainty in additionality. Second, coastal wetlands can potentially migrate outside of project footprints as they respond to sea-level rise, increasing uncertainty in permanence. To address these first two issues, a system-wide approach may be necessary, rather than basing cooling benefits only on changes that occur within project boundaries. Third, the need for NCS to function over management-relevant decadal timescales means methane responses may be necessary to include in coastal wetland restoration planning and monitoring. Finally, there is uncertainty on how much data are required to justify restoration action. We summarize the minimum data required to make a binary decision on whether there is a net cooling benefit from a management action, noting that these data are more readily available than the data required to quantify the magnitude of cooling benefits for carbon crediting purposes. By reducing uncertainty, coastal wetland restoration can be implemented at the scale required to significantly contribute to addressing the current climate crisis.

Tidal flooding occurs when coastal water levels exceed impact-based flood thresholds due to tides alone, under average weather conditions. Transitions to tidal flood regimes are already underway for nuisance flood severities in harbours and bays and expected for higher severities in coming decades. In the first such regional assessment, we show that the same transition to tidally forced floods can also be expected to occur in Australian estuaries with less than 0.1 m further sea-level rise. Flood thresholds that historically used to only be exceeded under the combined effects of riverine (freshwater) and coastal (salt water) influences will then occur due to high tides alone. Once this tidal flooding emerges, it is projected to become chronic within two decades. Locations most at-risk of the emergence of tidal flooding and subsequent establishment of chronic flood regimes are those just inside estuary entrances. These locations are exemplified by low freeboard, the vertical distance between a flood threshold and a typical high tide level. We use a freeboard-based analysis to estimate the sea-level rise required for impacts associated with official flood thresholds to occur due to tides alone. The resultant tide-only flood frequency estimates provide a lower bound for future flood rates.

The COVID-19 has had major direct (e.g., deaths) and indirect (e.g., social inequities) effects in the United States. While the public health response to the epidemic featured some important successes (e.g., universal masking ,and rapid development and approval of vaccines and therapeutics), there were systemic failures (e.g., inadequate public health infrastructure) that overshadowed these successes. Key deficiency in the U.S. response were shortages of personal protective equipment (PPE) and supply chain deficiencies. Recommendations are provided for mitigating supply shortages and supply chain failures in healthcare settings in future pandemics. Some key recommendations for preventing shortages of essential components of infection control and prevention include increasing the stockpile of PPE in the U.S. National Strategic Stockpile, increased transparency of the Stockpile, invoking the Defense Production Act at an early stage, and rapid review and authorization by FDA/EPA/OSHA of non-U.S. approved products. Recommendations are also provided for mitigating shortages of diagnostic testing, medications and medical equipment.

Throughout the COVID-19 pandemic, many areas in the United States experienced healthcare personnel (HCP) shortages tied to a variety of factors. Infection prevention programs, in particular, faced increasing workload demands with little opportunity to delegate tasks to others without specific infectious diseases or infection control expertise. Shortages of clinicians providing inpatient care to critically ill patients during the early phase of the pandemic were multifactorial, largely attributed to increasing demands on hospitals to provide care to patients hospitalized with COVID-19 and furloughs.1 HCP shortages and challenges during later surges, including the Omicron variant-associated surges, were largely attributed to HCP infections and associated work restrictions during isolation periods and the need to care for family members, particularly children, with COVID-19. Additionally, the detrimental physical and mental health impact of COVID-19 on HCP has led to attrition, which further exacerbates shortages.2 Demands increased in post-acute and long-term care (PALTC) settings, which already faced critical staffing challenges difficulty with recruitment, and high rates of turnover. Although individual healthcare organizations and state and federal governments have taken actions to mitigate recurring shortages, additional work and innovation are needed to develop longer-term solutions to improve healthcare workforce resiliency. The critical role of those with specialized training in infection prevention, including healthcare epidemiologists, was well-demonstrated in pandemic preparedness and response. The COVID-19 pandemic underscored the need to support growth in these fields.3 This commentary outlines the need to develop the US healthcare workforce in preparation for future pandemics.

Throughout history, pandemics and their aftereffects have spurred society to make substantial improvements in healthcare. After the Black Death in 14th century Europe, changes were made to elevate standards of care and nutrition that resulted in improved life expectancy.1 The 1918 influenza pandemic spurred a movement that emphasized public health surveillance and detection of future outbreaks and eventually led to the creation of the World Health Organization Global Influenza Surveillance Network.2 In the present, the COVID-19 pandemic exposed many of the pre-existing problems within the US healthcare system, which included (1) a lack of capacity to manage a large influx of contagious patients while simultaneously maintaining routine and emergency care to non-COVID patients; (2) a “just in time” supply network that led to shortages and competition among hospitals, nursing homes, and other care sites for essential supplies; and (3) longstanding inequities in the distribution of healthcare and the healthcare workforce. The decades-long shift from domestic manufacturing to a reliance on global supply chains has compounded ongoing gaps in preparedness for supplies such as personal protective equipment and ventilators. Inequities in racial and socioeconomic outcomes highlighted during the pandemic have accelerated the call to focus on diversity, equity, and inclusion (DEI) within our communities. The pandemic accelerated cooperation between government entities and the healthcare system, resulting in swift implementation of mitigation measures, new therapies and vaccinations at unprecedented speeds, despite our fragmented healthcare delivery system and political divisions. Still, widespread misinformation or disinformation and political divisions contributed to eroded trust in the public health system and prevented an even uptake of mitigation measures, vaccines and therapeutics, impeding our ability to contain the spread of the virus in this country.3 Ultimately, the lessons of COVID-19 illustrate the need to better prepare for the next pandemic. Rising microbial resistance, emerging and re-emerging pathogens, increased globalization, an aging population, and climate change are all factors that increase the likelihood of another pandemic.4

Recent theories suggest that for youth highly sensitive to incentives, perceiving more social threat may contribute to social anxiety (SA) symptoms. In 129 girls (ages 11–13) oversampled for shy/fearful temperament, we thus examined how interactions between neural responses to social reward (vs. neutral) cues (measured during anticipation of peer feedback) and perceived social threat in daily peer interactions (measured using ecological momentary assessment) predict SA symptoms two years later. No significant interactions emerged when neural reward function was modeled as a latent factor. Secondary analyses showed that higher perceived social threat was associated with more severe SA symptoms two years later only for girls with higher basolateral amygdala (BLA) activation to social reward cues at baseline. Interaction effects were specific to BLA activation to social reward (not threat) cues, though a main effect of BLA activation to social threat (vs. neutral) cues on SA emerged. Unexpectedly, interactions between social threat and BLA activation to social reward cues also predicted generalized anxiety and depression symptoms two years later, suggesting possible transdiagnostic risk pathways. Perceiving high social threat may be particularly detrimental for youth highly sensitive to reward incentives, potentially due to mediating reward learning processes, though this remains to be tested.

Background: Sedation in PICU masks physical exam findings, leading to diagnostic challenges. In adult models, electroencephalography can evaluate the brain’s response to sedation using feedforward connectivity and anteriorization of alpha hubs, proving useful for prognostication. Feasibility of model translation into pediatric population was assessed, with the hypothesis that the same markers of adaptive reconfiguration would correlate with a higher potential for recovering consciousness. Methods: Electroencephalograms from children undergoing sedation were analyzed for strength and direction of functional connectivity using the weighted and directed phase lag index. Target population was refined with an iterative inclusion criteria. We examined relationships between hub location reconfiguration, directed phase lag index, baseline Glasgow Coma Scale, and 3-month post-treatment Glasgow Outcome Scale-Extended. Results: Evaluation of 14 subjects showed promise in children aged 5-18 undergoing sedation with midazolam, dexmedetomidine, and propofol. Further analysis of five subjects revealed a correlation between adaptive reconfiguration during anesthesia and both higher baseline Glasgow Coma Scale and Glasgow Outcome Scale-Extended scores post-treatment. Conclusions: The findings indicate that the functional brain network connectivity model may have diagnostic and prognostic potential regarding children’s consciousness levels. While the initial data is promising, further analysis of six additional cases is pending and deemed essential to thoroughly evaluate the model’s efficacy.

Background: We performed a network meta-analysis of randomized controlled trials to assess the comparative effectiveness of available pharmacological prophylaxis for migraines. Methods: We searched MEDLINE, EMBASE, Web of Science, Scopus, PsycINFO and Cochrane CENTRAL up to October 2023 for trials that: (1) enrolled adults diagnosed with chronic migraine, and (2) randomized them to any prophylactic medication vs. another medication or placebo. We performed a random-effects frequentist network meta-analysis for patient-important outcomes. Results: We included 193 randomized trials. Compared to placebo, CGRP monoclonal antibodies (mean difference [MD] -1.7, 95%CI: -1.1 to -2.2), injection of botulinum toxin (MD -1.8, 95%CI: -0.7 to -2.9), calcium channel blockers (MD -1.8, 95%CI: -0.5 to -3.0), beta-blockers (MD -1.4, 95%CI: -0.2 to -2.6), and anticonvulsants (MD -1.1, 95%CI: -0.4 to -1.8) were among the most effective treatments in reducing average number of headache days per months. Anticonvulsants (Risk Ratio [RR] 2.3, 95%CI: 1.8 to 3.0), calcium channel blockers (RR 1.8, 95% CI: 1.1 to 3.1), and tricyclic antidepressants (RR 2.3, 95% CI: 1.3 to 3.8) showed the highest risk of discontinuation due to adverse events. Conclusions: Our findings suggest that CGRP inhibitors, botulinum toxin, and beta-blockers may provide the greatest benefit, and tolerability, for reducing the frequency of migraine headaches.

Invasive plants can gain a foothold in new environments by manipulating soil conditions through allelopathy or through the disruption of associations between native plants and their mycorrhizal associates. The resulting changes in soil conditions can affect the recovery of habitats long after the invasive plant has been removed. We conducted a series of greenhouse experiments to examine the effects of soil conditioned by pale swallow-wort [Vincetoxicum rossicum (Kleopow) Barbarich; Apocynaceae], on the growth of native plants. Additionally, we tested the effects of aqueous extracts of common milkweed (Asclepias syriaca L.; Apocynaceae), a related plant with known allelopathic effects, on the regrowth of V. rossicum from transplanted root crowns. Soil from a 15-yr-old V. rossicum infestation reduced seedling emergence in A. syriaca as well as in V. rossicum itself. Conversely, the same soil had no effect on the growth of mature A. syriaca plants. Soil conditioned by V. rossicum growth in the greenhouse had no effect on the biomass and percentage cover generated by two restoration seed mixes. Soil conditioned by A. syriaca, however, yielded lower biomass and percentage cover from both seed mixes. In contrast to the allelopathic effects of A. syriaca on seedlings, aqueous extracts of A. syriaca increased aboveground plant growth in V. rossicum. Our results suggest that the effects of V. rossicum–conditioned soil on native plants are concentrated at the seedling establishment phase. Additionally, the use of diverse native seed mixes shows great potential for restoring productivity to ecosystems affected by V. rossicum.

OBJECTIVES/GOALS: The correction of spinopelvic parameters is associated with better outcomes in patients with adult spinal deformity (ASD). This study presents a novel artificial intelligence (AI) tool that automatically predicts spinopelvic parameters from spine x-rays with high accuracy and without need for any manual entry. METHODS/STUDY POPULATION: The AI model was trained/validated on 761 sagittal whole-spine x-rays to predict the following parameters: Sagittal Vertical Axis (SVA), Pelvic Tilt (PT), Pelvic Incidence (PI), Sacral Slope (SS), Lumbar Lordosis (LL), T1-Pelvic Angle (T1PA), and L1-Pelvic Angle (L1PA). A separate test set of 40 x-rays was labeled by 4 reviewers including fellowship-trained spine surgeons and a neuroradiologist. Median errors relative to the most senior reviewer were calculated to determine model accuracy on test and cropped-test (i.e. lumbosacral) images. Intraclass correlation coefficients (ICC) were used to assess inter-rater reliability RESULTS/ANTICIPATED RESULTS: The AI model exhibited the following median (IQR) parameter errors: SVA[2.1mm (8.5mm), p=0.97], PT [1.5° (1.4°), p=0.52], PI[2.3° (2.4°), p=0.27], SS[1.7° (2.2°), p=0.64], LL [2.6° (4.0°), p=0.89], T1PA [1.3° (1.1°), p=0.41], and L1PA [1.3° (1.2°), p=0.51]. The parameter errors on cropped lumbosacral images were: LL[2.9° (2.6°), p=0.80] and SS[1.9° (2.2°), p=0.78]. The AI model exhibited excellent reliability at all parameters in both whole-spine (ICC: 0.92-1.0) and lumbosacral x-rays: (ICC: 0.92-0.93). DISCUSSION/SIGNIFICANCE: Our AI model accurately predicts spinopelvic parameters with excellent reliability comparable to fellowship-trained spine surgeons and neuroradiologists. Utilization of predictive AI tools in spine-imaging can substantially aid in patient selection and surgical planning.