Objectives: Patients with mild cognitive impairment (MCI) employ compensatory cognitive processes to maintain independence in day-to-day functioning as compared to patients with Alzheimer’s dementia (AD). The dorsolateral prefrontal cortex (DLFPC) supports cognitive compensation in normal aging and MCI. Using Paired Associative Stimulation combined with Electroencephalography (PAS-EEG) we have previously shown that patients with AD have impaired DLPFC plasticity compared to healthy control (HC) individuals. The aim of this study is to examine whether DLPFC plasticity in individuals with MCI is preserved compared to those with AD and HC, serving as a potential mechanism underlying cognitive compensation in MCI.

Methods: We analyzed a combined cross-sectional data of 47 AD, 16 MCI, and 40 HC participants from three different studies that assessed their DLPFC plasticity using PAS-EEG. PAS-EEG assesses DLPFC plasticity via the induction of Long Term Potentiation (LTP)-like activity, thereby referred to as PAS-LTP. Using multiple regression, we compared PAS-LTP in MCI to PAS-LTP in AD and HCs, after adjusting for age andgender.

Results: Among the 47 participants with AD (mean [SD] age = 75.3 [7] years), 29 were women and 18 were men; among the 16 participants with MCI (mean [SD] age = 74.8 [6] years), 11 were women and 5 were men; and among the 40 HCs (mean [SD] age = 76.4 [5.1] years), 22 were women and 18 were men. After adjusting for age and gender, there was an impact of diagnostic group on PAS-LTP [F (2,95) = 4.19, p = 0.018, between-group comparison η2 = 0.81]. Post-hoc comparisons showed that participants with MCI had a higher PAS-LTP (mean [SD] = 1.31 [0.49]) than those with AD (mean [SD] = 1.09 [0.28]) (Bonferroni corrected p = 0.042) but not different from PAS-LTP in HCs (mean [SD] = 1.25 [0.33]) (Bonferroni corrected p = 1.0).

Conclusions: Our findings indicate that plasticity is preserved in the DLPFC among individuals with MCI, supporting the hypothesis that DLPFC plasticity contributes to cognitive compensation towards delaying progression to AD. Thus, further enhancement of longer preservation of DLPFC plasticity in individuals with MCI could further delay the onset of AD in this population.

Accelerating COVID-19 Treatment Interventions and Vaccines (ACTIV) was initiated by the US government to rapidly develop and test vaccines and therapeutics against COVID-19 in 2020. The ACTIV Therapeutics-Clinical Working Group selected ACTIV trial teams and clinical networks to expeditiously develop and launch master protocols based on therapeutic targets and patient populations. The suite of clinical trials was designed to collectively inform therapeutic care for COVID-19 outpatient, inpatient, and intensive care populations globally. In this report, we highlight challenges, strategies, and solutions around clinical protocol development and regulatory approval to document our experience and propose plans for future similar healthcare emergencies.

This manuscript addresses a critical topic: navigating complexities of conducting clinical trials during a pandemic. Central to this discussion is engaging communities to ensure diverse participation. The manuscript elucidates deliberate strategies employed to recruit minority communities with poor social drivers of health for participation in COVID-19 trials. The paper adopts a descriptive approach, eschewing analysis of data-driven efficacy of these efforts, and instead provides a comprehensive account of strategies utilized. The Accelerate COVID-19 Treatment Interventions and Vaccines (ACTIV) public–private partnership launched early in the COVID-19 pandemic to develop clinical trials to advance SARS-CoV-2 treatments. In this paper, ACTIV investigators share challenges in conducting research during an evolving pandemic and approaches selected to engage communities when traditional strategies were infeasible. Lessons from this experience include importance of community representatives’ involvement early in study design and implementation and integration of well-developed public outreach and communication strategies with trial launch. Centralization and coordination of outreach will allow for efficient use of resources and the sharing of best practices. Insights gleaned from the ACTIV program, as outlined in this paper, shed light on effective strategies for involving communities in treatment trials amidst rapidly evolving public health emergencies. This underscores critical importance of community engagement initiatives well in advance of the pandemic.

Preoperative nasopharyngeal viral screening may reduce clinical uncertainty of upper respiratory infections prior to pediatric cardiac surgery but with unclear benefit. From March 2018 to March 2020, patients aged <3 years were screened for respiratory viruses and had substantial rates of viral detection (40%) but no observed differences in outcomes.

Background: In September 2022, UNC Hospitals was awarded a Regional Emerging Special Pathogens Treatment Center (RESPTC) grant by the U.S. Department of Health and Human Services Administration for Strategic Preparedness and Response (ASPR) to care for up to two patients with viral hemorrhagic fever, or similar pathogen, and up to ten patients with novel respiratory pathogens. Intensive infection prevention efforts and timely multidisciplinary commitment was required to develop the Space, Strategy, Staff, and Stuff needed to care for patients with a special pathogen. Methods: Multiple space needs assessments were undertaken to acquire spaces for the care of patients, simulation training, and a dedicated laboratory. Strategies for developing the response plan required collaboration with hospital executives, nursing leadership, public health leaders, and regional partners. Staff were recruited across various disciplines to join the response team and were provided hands-on skills training which was assessed by post-training surveys. Specialized ‘stuff’ (i.e., PPE, training equipment, and waste management devices) were researched and procured for use by the team. Results: Patient care and dedicated laboratory space was identified within existing infrastructure, and renovation plans were developed to adapt the space for these specialized activities. A waste management plan that benefits the hospital for routine waste and allows for Category A waste management was approved. Fifty-three staff members were recruited from 3 main disciplines (RNs, MDs, Paramedics), and across numerous settings (Medicine Acute Care & ICU, Pediatric ICU & Stepdown, Air Care/Transport, Burn ICU, Surgery Stepdown, Emergency Medicine, Infection Prevention, Infectious Disease) were trained during five 4-hour training sessions, culminating in an exercise involving transporting a rule–out Ebola patient to the hospital’s special pathogens unit. Post-training evaluations demonstrated a very high level of confidence (‘strongly agree’) in staffs’ knowledge about the RESPTC site (92.3%), special pathogens (80.8%), collaboration needed for managing patient care (80.8%), and in their comfort with special PPE donning and doffing (73.1%). Conclusions: Using a systematic approach to develop Space, Strategy, Staff, and Stuff, a large academic hospital readied itself to become a new RESPTC site. Key lessons learned include the importance of a multidisciplinary response team; local, state, and regional coordination for care planning and delivery; and early community partnership development. Logistical infrastructure and waste management challenges continue to require partnership with hospital leadership to optimize workflows and patient care. Holistic decision-making around infrastructure has led to changes that benefit all hospital patients and offer efficiencies to

Disclosure: William Fischer: Consultant - Roche, Merck, Inhalon Biopharma; Speaker for ACGME - IMG. David J Weber: Consultant on vaccines: Pfizer; DSMB chair: GSK; Consultant on disinfection: BD, GAMA, PDI, Germitec

The U.S. Department of Veterans Affairs is actively transitioning away from a disease-centric model of healthcare to one that prioritizes disease prevention and the promotion of overall health and well-being. Described as Whole Health, this initiative aims to provide personalized, values-centered care that optimizes physical, behavioral, spiritual, and socioeconomic well-being. To inform this initiative, we analyzed cross-sectional data from a nationally representative sample of primarily older U.S. military veterans to estimate levels of well-being across these domains, and identify sociodemographic, military, and potentially modifiable health and psychosocial correlates of them. Results revealed that, overall, veterans reported high domain-specific well-being (average scores ranging from 6.7 to 8.3 out of 10), with the highest levels in the socioeconomic domain and lowest in the physical domain. Several modifiable factors, including purpose in life, resilience, and social support, were strongly associated with the examined well-being domains. Interventions targeting these constructs may help promote well-being among U.S. veterans.

Globally, forests are net carbon sinks that partly mitigates anthropogenic climate change. However, there is evidence of increasing weather-induced tree mortality, which needs to be better understood to improve forest management under future climate conditions. Disentangling drivers of tree mortality is challenging because of their interacting behavior over multiple temporal scales. In this study, we take a data-driven approach to the problem. We generate hourly temperate weather data using a stochastic weather generator to simulate 160,000 years of beech, pine, and spruce forest dynamics with a forest gap model. These data are used to train a generative deep learning model (a modified variational autoencoder) to learn representations of three-year-long monthly weather conditions (precipitation, temperature, and solar radiation) in an unsupervised way. We then associate these weather representations with years of high biomass loss in the forests and derive weather prototypes associated with such years. The identified prototype weather conditions are associated with 5–22% higher median biomass loss compared to the median of all samples, depending on the forest type and the prototype. When prototype weather conditions co-occur, these numbers increase to 10–25%. Our research illustrates how generative deep learning can discover compounding weather patterns associated with extreme impacts.

Trends in 2-1-1 calls reflect evolving community needs during public health emergencies (PHEs). The study examined how changes in 2-1-1 call volume after 2 PHEs (Hurricane Irma and the coronavirus disease 2019 [COVID-19] pandemic declaration) in Broward County, Florida, varied by PHE type and whether variations differed by gender and over time. Examining 2-1-1 calls during June to December 2016, June to December 2017, and March 2019 to April 2021, this study measured changes in call volume post-PHEs using interrupted time series analysis. Hurricane Irma and the COVID-19 pandemic were associated with increases in call volume (+81 calls/d and +84 calls/d, respectively). Stratified by gender, these PHEs were associated with larger absolute increases for women (+66 and +57 calls/d vs +15 and +27 calls/d for men) but larger percent increases above their baseline for men (+143% and +174% vs +119% and +138% for women). Calls by women remained elevated longer after Hurricane Irma (5 wk vs 1 wk), but the opposite pattern was observed after the pandemic declaration (8 vs 21 wk). PHEs reduce gender differences in help-seeking around health-related social needs. Findings demonstrate the utility of 2-1-1 call data for monitoring and responding to evolving community needs in the PHE context.

Background: Saccade and pupil responses are potential neurodegenerative disease biomarkers due to overlap between oculomotor circuitry and disease-affected areas. Instruction-based tasks have previously been examined as biomarker sources, but are arduous for patients with limited cognitive abilities; additionally, few studies have evaluated multiple neurodegenerative pathologies concurrently. Methods: The Ontario Neurodegenerative Disease Research Initiative recruited individuals with Alzheimer’s disease (AD), mild cognitive impairment (MCI), amyotrophic lateral sclerosis (ALS), frontotemporal dementia, progressive supranuclear palsy, or Parkinson’s disease (PD). Patients (n=274, age 40-86) and healthy controls (n=101, age 55-86) viewed 10 minutes of frequently changing video clips without instruction while their eyes were tracked. We evaluated differences in saccade and pupil parameters (e.g. saccade frequency and amplitude, pupil size, responses to clip changes) between groups. Results: Preliminary data indicates low-level behavioural alterations in multiple disease cohorts: increased centre bias, lower overall saccade rate and reduced saccade amplitude. After clip changes, patient groups generally demonstrated lower saccade rate but higher microsaccade rate following clip change to varying degrees. Additionally, pupil responses were blunted (AD, MCI, ALS) or exaggerated (PD). Conclusions: This task may generate behavioural biomarkers even in cognitively impaired populations. Future work should explore the possible effects of factors such as medication and disease stage.