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BackgroundWe proposed a Phase I dose escalation trial to assess the safety of allogeneic human amniotic epithelial cells (hAECs) in stroke patients with a view to informing the design for a Phase II trial.MethodsThe design is based on 3 + 3 dose escalation design with additional components for measuring MR signal of efficacy as well as the effect of hAECs (2–8 × 106/kg, i.v.) on preventing immunosuppression after stroke.ResultsEight patients (six males) were recruited within 24 h of ischemic stroke onset and were infused with hAECs. We were able to increase the dose of hAECs to 8 × 106 cells/kg (2 × 106/kg, n = 3; 4 × 106/kg, n = 3; 8 × 106/kg, n = 2). The mean age is 68.0 ± 10.9 (mean ± SD). The frequencies of hypertension and hyperlipidemia were 87.5%, diabetes was 37.5%, atrial fibrillation was 50%, ischemic heart disease was 37.5% and ever-smoker was 25%. Overall, baseline NIHSS was 7.5 ± 3.1, 7.8 ± 7.2 at 24 h, and 4.9 ± 5.4 at 1 week (n = 8). The modified Rankin scale at 90 days was 2.1 ± 1.2. Supplemental oxygen was given in five patients during hAEC infusion. Using pre-defined criteria, two serious adverse events occurred. One patient developed recurrent stroke and another developed pulmonary embolism whilst in rehabilitation. For the last four patients, infusion of hAECs was split across separate infusions on subsequent days to reduce the risk for fluid overload.ConclusionOur Phase I trial demonstrates that a maximal dose of 2 × 106/kg hAECs given intravenously each day over 2 days (a total of 4 × 106/kg) is safe and optimal for use in a Phase II trial.Clinical trial registrationClinicalTrials.gov, identifier ACTRN12618000076279P.

BackgroundPost-stroke pneumonia is a frequent complication of stroke and is associated with high mortality. Investigators have described its associations with beta-blocker. However, there has been no evaluation of the role of recombinant tissue plasminogen activator (RTPA). We postulate that RTPA may modify the effect of stroke on pneumonia by reducing stroke disability. We explore this using data from neuroprotection trials in Virtual International Stroke Trials Archive (VISTA)-Acute.MethodWe evaluated the impact of RTPA and other medications in random forest model. Random forest is a type of supervised ensemble tree-based machine learning method. We used the standard approach for performing random forest and partitioned the data into training (70%) and validation (30%) sets. This action enabled to the model developed on training data to be evaluated in the validation data. We borrowed idea from Coalition Game Theory on fair distribution of marginal profit (Shapley value) to determine proportional contribution of a covariate to the model. Consistent with other analysis using the VISTA-Acute data, the diagnosis of post-stroke pneumonia was based on reports of serious adverse events.ResultsThe overall frequency of pneumonia was 10.9% (614/5652). It was present in 11.5% of the RTPA (270/2358) and 10.4% (344/3295) of the no RTPA groups. There was significant (pConclusionIn this cohort pneumonia was strongly associated with stroke severity and age whereas RTPA had a much lower effect. An intriguing finding is a possible association between benzodiazepine and pneumonia but this requires further evaluation.

Abstract Background The aim of the study was to develop and test an artificial intelligence (AI)-based method to improve the quality of [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) images. Methods A convolutional neural network (CNN) was trained by using pairs of excellent (acquisition time of 6 min/bed position) and standard (acquisition time of 1.5 min/bed position) or sub-standard (acquisition time of 1 min/bed position) images from 72 patients. A test group of 25 patients was used to validate the CNN qualitatively and quantitatively with 5 different image sets per patient: 4 min/bed position, 1.5 min/bed position with and without CNN, and 1 min/bed position with and without CNN. Results Difference in hotspot maximum or peak standardized uptake value between the standard 1.5 min and 1.5 min CNN images fell short of significance. Coefficient of variation, the noise level, was lower in the CNN-enhanced images compared with standard 1 min and 1.5 min images. Physicians ranked the 1.5 min CNN and the 4 min images highest regarding image quality (noise and contrast) and the standard 1 min images lowest. Conclusions AI can enhance [18F]FDG-PET images to reduce noise and increase contrast compared with standard images whilst keeping SUVmax/peak stability. There were significant differences in scoring between the 1.5 min and 1.5 min CNN image sets in all comparisons, the latter had higher scores in noise and contrast. Furthermore, difference in SUVmax and SUVpeak fell short of significance for that pair. The improved image quality can potentially be used either to provide better images to the nuclear medicine physicians or to reduce acquisition time/administered activity.

Abstract Background [18F]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is a well-established modality in the work-up of patients with suspected or confirmed diagnosis of lung cancer. Recent research efforts have focused on extracting theragnostic and textural information from manually indicated lung lesions. Both semi-automatic and fully automatic use of artificial intelligence (AI) to localise and classify FDG-avid foci has been demonstrated. To fully harness AI’s usefulness, we have developed a method which both automatically detects abnormal lung lesions and calculates the total lesion glycolysis (TLG) on FDG PET-CT. Methods One hundred twelve patients (59 females and 53 males) who underwent FDG PET-CT due to suspected or for the management of known lung cancer were studied retrospectively. These patients were divided into a training group (59%; n = 66), a validation group (20.5%; n = 23) and a test group (20.5%; n = 23). A nuclear medicine physician manually segmented abnormal lung lesions with increased FDG-uptake in all PET-CT studies. The AI-based method was trained to segment the lesions based on the manual segmentations. TLG was then calculated from manual and AI-based measurements, respectively and analysed with Bland-Altman plots. Results The AI-tool’s performance in detecting lesions had a sensitivity of 90%. One small lesion was missed in two patients, respectively, where both had a larger lesion which was correctly detected. The positive and negative predictive values were 88% and 100%, respectively. The correlation between manual and AI TLG measurements was strong (R 2 = 0.74). Bias was 42 g and 95% limits of agreement ranged from − 736 to 819 g. Agreement was particularly high in smaller lesions. Conclusions The AI-based method is suitable for the detection of lung lesions and automatic calculation of TLG in small- to medium-sized tumours. In a clinical setting, it will have an added value due to its capability to sort out negative examinations resulting in prioritised and focused care on patients with potentially malignant lesions.

Abstract Background The Deauville score (DS) is a clinical tool, based on the comparison between lesion and reference organ uptake of 18F-fluorodeoxyglucose (FDG), used to stratify patients with lymphoma into categories reflecting their disease status. With a plethora of positron emission tomography with computed tomography (PET-CT) hard- and software algorithms, standard uptake value (SUV) in lesions and reference organs may differ which affects DS classification and therefore medical treatment. The EANM Research Ltd. (EARL) harmonization program from the European Association of Nuclear Medicine (EANM) partly mitigates this issue, but local preferences are common in clinical practice. We have investigated the discordance in DS calculated from patients with lymphoma referred for 18F-FDG PET-CT reconstructed with three different algorithms: the newly introduced block-sequential regularization expectation-maximization algorithm commercially sold as Q. Clear (QC, GE Healthcare, Milwaukee, WI, USA), compliant with the newly proposed updated EARL recommendations, and two settings compliant with the current EARL recommendations (EARLlower and EARLupper, representing the lower and upper limit of the EARL recommendations). Methods Fifty-two patients with non-Hodgkin and Hodgkin lymphoma were included (18 females and 34 males). Segmentation of mediastinal blood pool and liver were semi-automatically performed, whereas segmentation of lesions was done manually. From these segmentations, SUVmax and SUVpeak were obtained and DS calculated. Results There was a significant difference in DS between the QC algorithm and EARLlower/EARLupper (p

Background and Purpose: Post-stroke pneumonia is a feared complication of stroke as it is associated with greater mortality and disability than in those without pneumonia. Patients are often kept “Nil By Mouth” (NBM) after stroke until after receiving a screen for dysphagia and declared safe to resume oral intake. We aimed to assess the proportional contribution of stroke severity and dysphagia screen to pneumonia by borrowing idea from coalition game theory on fair distribution of marginal profit (Shapley value).Method: Retrospective study of admissions to the stroke unit at Monash Medical Center in 2015. Seventy-five percent of data were partitioned into training set and the remainder (25%) into validation set. Variables associated with pneumonia (p < 0.1) were entered into Shapley value regression and conditional decision tree analysis.Results: In 2015, there were 797 admissions and 617 patients with ischemic and hemorrhagic stroke (age 69.9 ± 16.2, male = 55.0%, National Institute of Health Stroke Scale/NIHSS 8.1 ± 7.9). The frequency of pneumonia was 6.6% (41/617). In univariable analyses NIHSS, time to dysphagia screen, Charlson comorbidity index (CCI), and age were significantly associated with pneumonia but not weekend admission. Shapley value regression showed that the largest contributor to the model was stroke severity (72.8%) followed by CCI (16.2%), dysphagia screen (3.8%), and age (7.2%). Decision tree analysis yielded an NIHSS threshold of 14 for classifying people with (27% of 75 patients) and without pneumonia (2.5% of 308 patients). The area under the ROC curve for training data was 0.83 (95% CI 0.75–0.91) with no detectable difference between the training and test data (p = 0.4). Results were similar when dysphagia was exchanged for the variable dysphagia screen.Conclusion: Stroke severity status, and not dysphagia or dysphagia screening contributed to the decision tree model of post stroke pneumonia. We cannot exclude the chance that using dysphagia screen in this cohort had minimized the impact of dysphagia on development of pneumonia.

BackgroundPrognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data.MethodThe inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003–2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82–1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86–1.00).ConclusionOur findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.

Background: Lacunar infarcts have been characterized as small subcortical infarcts, resulting from in situ microatheroma or lipohyalinosis in small vessels. Based on this hypothesis, such infarcts should not be associated with large areas of perfusion deficits extending beyond subcortical regions to involve cortical regions. By contrast, selected small subcortical infarcts, as defined by MR imaging in the subacute or chronic stage, may initially have large perfusion deficits or related large vessel occlusions. These infarcts with ‘lacunar’ phenotype may also be caused by disease in the parent vessel and may have very different stroke mechanisms from small vessel disease. Our aim was to describe differences in imaging characteristics between patients with small subcortical infarction with ‘lacunar phenotype’ from those with lacunar mechanism. Methods: Patients undergoing acute CT Perfusion/angiography (CTP/CTA) within 6 hours of symptom onset and follow-up magnetic resonance imaging (MRI) for ischaemic stroke were included (2009-2013). A lacunar infarct was defined as a single subcortical infarct (SSI) ≤20 mm on follow-up MRI. Presence of perfusion deficits, vessel occlusion and infarct dimensions were compared between lacunar infarcts and other topographical infarct types. Results: Overall, 182 patients (mean age 66.4±15.3 years, 66% male) were included. SSI occurred in 31 (17%) patients. Of these, 12 (39%) patients had a perfusion deficit compared with those with any cortical infarction (120/142, 67%), and the smallest SSI with a perfusion deficit had a diameter of

Background and Purpose: Cerebral microbleeds, cortical superficial siderosis, white matter lesions and cerebral atrophy may signify greater bleeding risk particularly in patients in whom anticoagulation is to be considered. We investigated their prevalence and associations with stroke type in patients with stroke and atrial fibrillation. Material and Methods: Cross-sectional sample, Monash Medical Centre (Melbourne, Australia) between 2010 and 2013, with brain MRI. MRI abnormalities were rated using standardized methods. Logistic regression was used to study associations adjusting for age and sex.Results: There were 170 patients, mean age 78 years (SD 9.8), 154 (90.6%) with ischemic stroke. Prevalence of MRI markers were: any microbleed 49%, multiple (≥2) microbleeds 30%, confluent white matter lesions 18.8%, siderosis 8.9%, severe cerebral atrophy 37.7%. Combinations of the severe manifestations of these markers were much less prevalent (2.9% to 12.4%). Compared with ischemic stroke, those with hemorrhagic stroke were more likely to have ≥10 microbleeds (OR 5.50 95% CI 1.46-20.77, p=0.012) and siderosis (OR 6.24, 95% CI 1.74-22.40, p=0.005). Siderosis was associated with multiple microbleeds (OR 8.14, 95% CI 2.38 - 27.86, p = 0.001). Patients admitted with hemorrhagic stroke and multiple microbleeds were more frequently anticoagulated prior to stroke (6/7, 85.7%) than in those with single (1/2, 50%) or no microbleeds (4/7, 57%). Conclusion: Multiple CMBs, severe WML, and severe cerebral atrophy were common individually in hospitalized patients with stroke and AF, but less so in combination. A higher burden of CMBs may be associated with ICH in stroke patients with AF.

BackgroundThe Ebola virus disease (EVD) epidemic has threatened access to basic health services through facility closures, resource diversion, and decreased demand due to community fear and distrust. While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data.Methods and findingsWe conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias.ConclusionsWe detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may under-approximate the effect seen in the most heavily affected areas. These are the first population-based survey data to show collateral disruptions to facility-based delivery caused by the West African EVD epidemic, and they reinforce the need to consider the full spectrum of implications caused by public health emergencies.

Abstract Background Ovine gammaherpesvirus 2 (OvHV-2) is the causative agent of sheep associated malignant catarrhal fever (MCF). As sheep are the adapted host for OvHV-2, it is generally presumed that infection is not associated with disease in this species. However, a recent case review combined in-situ hybridisation, PCR and histopathology and correlated the viral distribution with systemic necrotizing vasculitis and concluded OvHV-2 was the likely agent responsible for sporadic, MCF-like vascular disease in sheep. Case presentation Using similar methods this case study reports on the findings of the first reported cases in an Irish Flock of MCF- like systemic necrotizing vasculitis in sheep associated with OvHV-2. Sheep A, a 16-month-old Texel-cross hogget displayed signs of ill- thrift, Sheep B, a nine-month-old Belclare-cross lamb, was found dead having displayed no obvious symptoms. Both cases occurred on the same farm, however the animals were not related. Lymphohistiocytic vasculitis of various tissues was the predominant histopathological finding in both animals. Conclusion By combining histopathology, PCR and in-situ hybridisation results, MCF- like systemic necrotizing vasculitis associated with OvHV-2 has been diagnosed for the first time in an Irish flock.

Objective To illustrate how whole-population linked data can be used to understand a system perspective of client complexity, and build robust evidence of Family by Family program impact. Methods Family by Family program (the program) participant data were linked into the Better Evidence Better Outcomes Linked Data (BEBOLD) Platform. BEBOLD is a whole-of-population linked de-identified administrative data platform for all South Australian children born 1991 onwards (n~500,000), as well as their parents including data spanning health, education, and social services. We descriptively analysed parental child protection history, emergency department presentations, hospitalisations, homelessness and justice system contact in the 24 months prior to and post program commencement. We emulate a trial using the ‘target trial’ causal inference framework to evaluate the program effect on a range of child outcomes using targeted maximum likelihood with a set of over 20 confounders. Results There were 361 families and 841 children in the program included in analysis. Selected results follow: Prior to the program, 35.8% of children were in a family where at least one parent had their own child protection history and 8% had a parent who experienced out-of-home care. Nearly 40% of children had at least one parent with a mental health related emergency department and/or hospitalisation, while 22% of children were in a family with specialist homelessness service contact. Program impact results will be presented at the conference. Conclusion This research-practice partnership illustrates how bringing together program and linked-administrative data generates new evidence about client complexity and program impact.

Introduction To prevent abuse, neglect and poor outcomes for children and families, including child protection intervention, maltreatment, and removals, it is critical to understand the scale and timing of child protection system contacts to identify opportunities for early prevention. Objectives and Approach We quantified the cumulative incidence of child protection contacts during childhood, including initial reports, screened-in reports, investigations, substantiations and removal into out-of-home-care, among all children in two Australian states. We used child protection system data linked for the South Australian (SA) BEBOLD and NSW Child E-Cohort data platforms as the numerator, and census data for the denominator, for 571,497 SA children (birth-years 1991-2019) and 1,362,505 NSW children (birth-years 2005-2018). Results Of children born in 2005 (NSW SA): Two in five children were reported to child protection by age 14; one in ten children were the subject of a child protection investigation in NSW and SA; one in twelve children in NSW and one in 17 in SA, were substantiated at least once; and one in 35 children in NSW and one in 40 in SA were removed into out-of-home care at least once by age 14. Approximately half of all types of child protection contact first occurred by the child’s fourth birthday. Conclusions/implications The scale of lifecourse child protection contact underscores the opportunities for early health and social supports to prevent child maltreatment and escalating child protection intervention. Child protection reports also represent an asset to generate public health intelligence to inform early prevention.

Objective Quantify the scale and type of maternal substance use from conception to the child’s second birthday (First 1000 days) to inform screening and support services that may reduce associated harm or risk for children. Approach We used mother and child records from whole-population health, death, and child protection datasets to ascertain maternal substance use during the First 1000 days for children born in NSW, Australia, from 2008-2017. The primary outcome - maternal substance use - included use of illicit substances, alcohol, opioid-agonist treatment, organic compounds, solvents, and misuse of prescription medicines. ICD-10 and SNOMED-CT diagnosis codes were used. Results The birth cohort included 970,470 children and 625,856 mothers. 32,000 children (3.4%) had a record of maternal substance use during the First 1000 days of life, including 13,647 (1.4%) with alcohol and 23,485 (2.4%) other drug use. Ascertainment was highest from child protection records (26,045 children), followed by mother’s (12,956 children) then children’s hospital records (3,826 children). 18,672 (1.9%) children had a record of carer substance use only in child protection records. Combining data increased the prevalence estimates; adding child protection records increased the prevalence estimate to 3.4%, compared with 1.2% in health and death records alone. Conclusion More than 3 in every 100 Australian children had a record of maternal substance use in administrative data during the First 1000 days of life in this decade-long study. In addition to health and death data, child protection data offers public health insights into the scale of maternal substance use among whole-population cohorts of children.

Introduction Children who experience maltreatment have worse health and development outcomes than other children. Early prevention relies on opportunities to respond to system contacts that reliably indicate the population burden of children’s future developmental risk. Objectives and Approach We quantified the population burden of developmental vulnerability at age five by the type, timing, and frequency of child protection contacts before school, among children in two Australian states. We used linked whole-population births, child protection and Australian Early Development Census (AEDC) data (2009-2018 cycles) in New South Wales (NSW) and South Australia (SA). Results 56,650/398,702 (14%) NSW and 12,617/80,731 (16%) SA children had ≥1 child protection contacts before school. The risk of developmental vulnerability on ≥1 domains was lowest in the no child protection group (NSW, 17-18%; SA, 19%), with higher risks in the child protection report (NSW, 28-29%; SA, 32-35%) through to the OOHC (NSW, 35-38%; SA, 39-50%) groups, with a similar pattern for the risk of medically diagnosed conditions. Children with only one child protection report before school had a higher developmental risk than the no child protection group (NSW, 34% versus 21%; SA, 42% versus 24%). Conclusions/Implications Even a single child protection report in the first 2000 days of children’s lives was a robust indicator of developmental risk at age five, with higher developmental risks among children with more serious child protection contacts before school. Child protection reports represent an under-utilised asset to inform early universal and targeted support from health, human and early education services.

Abstract Background The optimal treatment approach for low‐risk prostate cancer (LRPC) remains controversial. While active surveillance is an increasingly popular option, definitive local treatments, including radical prostatectomy (RP), external beam radiotherapy (EBRT), and prostate seed implantation (PSI), are also commonly used. This study aimed to evaluate the survival outcomes of patients with LRPC using a large patient population from the National Cancer Database (NCDB). Methods We analyzed data from 195,452 patients diagnosed with LRPC between 2004 and 2015 using the NCDB. Patients were classified based on their treatment modalities, including RP, EBRT, PSI, or no local treatment (NLT). Only patients with Charlson–Deyo comorbidity scores of 0 or 1 were included to ensure comparability. Propensity score analysis was used to balance the treatment groups, and the accelerated failure time model was used to analyze the survival rates of the treatment groups. Results After a median follow‐up of 70.8 months, 24,545 deaths occurred, resulting in an all‐cause mortality rate of 13%. RP demonstrated a survival benefit compared with NLT, particularly in patients younger than 74 years of age. In contrast, radiation treatments (EBRT and PSI) did not improve survival in the younger age groups, except for patients older than 70 years for EBRT and older than 65 years for PSI. Notably, EBRT in patients younger than 65 years was associated with inferior outcomes. Conclusion This study highlights the differences in survival outcomes among LRPC treatment modalities. RP was associated with improved survival compared to NLT, especially in younger patients. In contrast, EBRT and PSI showed survival benefits primarily in the older age groups. NLT is a reasonable choice, particularly in younger patients when RP is not chosen. These findings emphasize the importance of individualized treatment decisions for LRPC management.

Background: The University of Washington (UW) Center for Stewardship in Medicine (CSiM) supports a tele-antimicrobial stewardship (AMS) program (TASP) using the ECHO approach (Extension for Community Healthcare Outcomes) in small, rural, and Critical Access Hospitals (primarily in the western U.S.) with education, mentoring, organizational capacity building, and a community of peers. To evaluate the continuing education (CE) component of UW-TASP ECHO, CSiM surveyed individuals receiving CE credits as part of the program. This survey was designed to track individuals’ satisfaction with the program and to assess the impact of UW-TASP ECHO on AMS in participating facilities. Methods: The CE participants’ survey was completed annually by individuals participating in UW TASP ECHO using online survey software. The survey included closed-ended and open-ended questions. Responses to open-ended questions were entered into Atlas.ti qualitative analysis software and coded iteratively according to themes that emerged. When a new code emerged partway through the coding process, earlier surveys were re-coded for the new code. Final codes were grouped into themes and sub-themes and quotes from each theme identified were summarized and attached to the theme and reported. Results: Data from three administrations of this survey were available: 2018-2019 (n=66); 2020-2021 (n=27); and 2021-2022 (n=30). These surveys were completed by a total of 95 individuals from 53 hospitals. Seven of these individuals completed a survey in each year, 14 completed a survey in two years, and 74 completed only one survey. Themes identified were COVID-19 support (including procedures and policies, being kept up-to-date, research summaries, and peer support), the antibiotic pocket guide developed by UW, strength in community, staff education, role of CSiM in developing/strengthening the AMS program at the facility, change in use of antibiotics, UW imprimatur, learning/growing as a healthcare provider, and importance for small, rural hospitals (see examples in Table 1). Conclusions: This qualitative analysis provides evidence from surveys of individuals participating in CE that UW TASP ECHO has had a meaningful impact in such domains as building a strong community among small, rural and critical access hospitals, educating staff, changing antibiotic use and providing peer support, among others.

Abstract Background Children less than five years of age comprised approximately 30% in 2020 of foster care entries in the United States, and they are consistently the largest foster care entry group. Very young children can respond differently to the same adverse life events. Detection of complex interpersonal traumas is core to providing appropriate interventions and prevention of reoccurring negative outcomes in these children. Methods Children who (1) were identified as having experienced complex interpersonal trauma, but (2) who did not have traumatic stress symptoms were identified using Child and Adolescent Needs and Strengths data in a large midwestern state from 2010 to 2021. A logistic model was fit to determine the effect of cumulative traumatic exposures (e.g., adverse childhood experiences such that increased events were hypothesized to predict an increased likelihood of symptomatic detection. We conducted a latent class analysis to understand the relationship between traumatic experiences, asset-based factors, and the detection of traumatic stress in children aged five years and under who had exposure to traumatic events but did not have detectable traumatic stress symptoms. Results We detected three classes within this population of very young children, who were described as “resilient” (demonstrating asset-based resilience when faced with traumatic experiences), “missed” (those who exhibit behavioral and mental health types like those with detected traumatic stress symptoms but who were not detected as such), and “unfolding”. Very young children do demonstrate asset-based resilience when faced with traumatic experiences. Conclusions Detection of traumatic stress may be more difficult in young children. It is important to assess both traumatic stress and strengths to ensure that children who are resilient after exposure to traumatic experiences (i.e., do not demonstrate traumatic stress symptoms) are not referred to unnecessary interventions. Additional educational approaches are needed to help caseworkers identify symptoms of traumatic stress that mirror symptoms of other behavioral and emotional challenges. Precision medicine approaches are required to best match the interventions to specific needs of young children. Recognition of resilience in very young children is critical for designing systems that customize approaches of trauma-informed care.

Abstract Background Cancer control initiatives are informed by quantifying the capacity to reduce cancer burden through effective interventions. Burden measures using health administrative data are a sustainable way to support monitoring and evaluating of outcomes among patients and populations. The Fraction of Life Years Lost After Diagnosis (FLYLAD) is one such burden measure. We use data on Aboriginal and non-Aboriginal South Australians from 1990 to 2010 to show how FLYLAD quantifies disparities in cancer burden: between populations; between sub-population cohorts where stage at diagnosis is available; and when follow-up is constrained to 24-months after diagnosis. Method FLYLADcancer is the fraction of years of life expectancy lost due to cancer (YLLcancer) to life expectancy years at risk at time of cancer diagnosis (LYAR) for each person. The Global Burden of Disease standard life table provides referent life expectancies. FLYLADcancer was estimated for the population of cancer cases diagnosed in South Australia from 1990 to 2010. Cancer stage at diagnosis was also available for cancers diagnosed in Aboriginal people and a cohort of non-Aboriginal people matched by sex, year of birth, primary cancer site and year of diagnosis. Results Cancers diagnoses (N = 144,891) included 777 among Aboriginal people. Cancer burden described by FLYLADcancer was higher among Aboriginal than non-Aboriginal (0.55, 95% CIs 0.52–0.59 versus 0.39, 95% CIs 0.39–0.40). Diagnoses at younger ages among Aboriginal people, 7 year higher LYAR (31.0, 95% CIs 30.0–32.0 versus 24.1, 95% CIs 24.1–24.2) and higher premature cancer mortality (YLLcancer = 16.3, 95% CIs 15.1–17.5 versus YLLcancer = 8.2, 95% CIs 8.2–8.3) influenced this. Disparities in cancer burden between the matched Aboriginal and non-Aboriginal cohorts manifested 24-months after diagnosis with FLYLADcancer 0.44, 95% CIs 0.40–0.47 and 0.28, 95% CIs 0.25–0.31 respectively. Conclusion FLYLAD described disproportionately higher cancer burden among Aboriginal people in comparisons involving: all people diagnosed with cancer; the matched cohorts; and, within groups diagnosed with same staged disease. The extent of disparities were evident 24-months after diagnosis. This is evidence of Aboriginal peoples’ substantial capacity to benefit from cancer control initiatives, particularly those leading to earlier detection and treatment of cancers. FLYLAD’s use of readily available, person-level administrative records can help evaluate health care initiatives addressing this need.

Abstract ABCG2 is a medically important ATP-binding cassette transporter with crucial roles in the absorption and distribution of chemically-diverse toxins and drugs, reducing the cellular accumulation of chemotherapeutic drugs to facilitate multidrug resistance in cancer. ABCG2’s capacity to transport both hydrophilic and hydrophobic compounds is not well understood. Here we assess the molecular basis for substrate discrimination by the binding pocket. Substitution of a phylogenetically-conserved polar residue, N436, to alanine in the binding pocket of human ABCG2 permits only hydrophobic substrate transport, revealing the unique role of N436 as a discriminator. Molecular dynamics simulations show that this alanine substitution alters the electrostatic potential of the binding pocket favoring hydration of the transport pore. This change affects the contact with substrates and inhibitors, abrogating hydrophilic compound transport while retaining the transport of hydrophobic compounds. The N436 residue is also required for optimal transport inhibition of ABCG2, as many inhibitors are functionally impaired by this ABCG2 mutation. Overall, these findings have biomedical implications, broadly extending our understanding of substrate and inhibitor interactions.

Background and Purpose: Distinguishing treatment-induced imaging changes from progressive disease has important implications for avoiding inappropriate discontinuation of a treatment. Our goal in this study is to evaluate the utility of dynamic contrast-enhanced (DCE) perfusion MRI as a biomarker for the early detection of progression. We hypothesize that DCE-MRI may have the potential as an early predictor for the progression of disease in GBM patients when compared to the current standard of conventional MRI. Methods: We identified 26 patients from 2011 to 2023 with newly diagnosed primary glioblastoma by histopathology and gross or subtotal resection of the tumor. Then, we classified them into two groups: patients with progression of disease (POD) confirmed by pathology or change in chemotherapy and patients with stable disease without evidence of progression or need for therapy change. Finally, at least three DCE-MRI scans were performed prior to POD for the progression cohort, and three consecutive DCE-MRI scans were performed for those with stable disease. The volume of interest (VOI) was delineated by a neuroradiologist to measure the maximum values for Ktrans and plasma volume (Vp). A Friedman test was conducted to evaluate the statistical significance of the parameter changes between scans. Results: The mean interval between subsequent scans was 57.94 days, with POD-1 representing the first scan prior to POD and POD-3 representing the third scan. The normalized maximum Vp values for POD-3, POD-2, and POD-1 are 1.40, 1.86, and 3.24, respectively (FS = 18.00, p = 0.0001). It demonstrates that Vp max values are progressively increasing in the three scans prior to POD when measured by routine MRI scans. The normalized maximum Ktrans values for POD-1, POD-2, and POD-3 are 0.51, 0.09, and 0.51, respectively (FS = 1.13, p < 0.57). Conclusions: Our analysis of the longitudinal scans leading up to POD significantly correlated with increasing plasma volume (Vp). A longitudinal study for tumor perfusion change demonstrated that DCE perfusion could be utilized as an early predictor of tumor progression.

Abstract While heme synthesis requires the formation of a potentially lethal intermediate, protoporphyrin IX (PPIX), surprisingly little is known about the mechanism of its toxicity, aside from its phototoxicity. The cellular protein interactions of PPIX might provide insight into modulators of PPIX-induced cell death. Here we report the development of PPB, a biotin-conjugated, PPIX-probe that captures proteins capable of interacting with PPIX. Quantitative proteomics in a diverse panel of mammalian cell lines reveal a high degree of concordance for PPB-interacting proteins identified for each cell line. Most differences are quantitative, despite marked differences in PPIX formation and sensitivity. Pathway and quantitative difference analysis indicate that iron and heme metabolism proteins are prominent among PPB-bound proteins in fibroblasts, which undergo PPIX-mediated death determined to occur through ferroptosis. PPB proteomic data (available at PRIDE ProteomeXchange # PXD042631) reveal that redox proteins from PRDX family of glutathione peroxidases interact with PPIX. Targeted gene knockdown of the mitochondrial PRDX3, but not PRDX1 or 2, enhance PPIX-induced death in fibroblasts, an effect blocked by the radical-trapping antioxidant, ferrostatin-1. Increased PPIX formation and death was also observed in a T-lymphoblastoid ferrochelatase-deficient leukemia cell line, suggesting that PPIX elevation might serve as a potential strategy for killing certain leukemias.

Abstract Urbanization and inequalities are two of the major policy themes of our time, intersecting in large cities where social and economic inequalities are particularly pronounced. Large scale street-level images are a source of city-wide visual information and allow for comparative analyses of multiple cities. Computer vision methods based on deep learning applied to street images have been shown to successfully measure inequalities in socioeconomic and environmental features, yet existing work has been within specific geographies and have not looked at how visual environments compare across different cities and countries. In this study, we aim to apply existing methods to understand whether, and to what extent, poor and wealthy groups live in visually similar neighborhoods across cities and countries. We present novel insights on similarity of neighborhoods using street-level images and deep learning methods. We analyzed 7.2 million images from 12 cities in five high-income countries, home to more than 85 million people: Auckland (New Zealand), Sydney (Australia), Toronto and Vancouver (Canada), Atlanta, Boston, Chicago, Los Angeles, New York, San Francisco, and Washington D.C. (United States of America), and London (United Kingdom). Visual features associated with neighborhood disadvantage are more distinct and unique to each city than those associated with affluence. For example, from what is visible from street images, high density poor neighborhoods located near the city center (e.g., in London) are visually distinct from poor suburban neighborhoods characterized by lower density and lower accessibility (e.g., in Atlanta). This suggests that differences between two cities is also driven by historical factors, policies, and local geography. Our results also have implications for image-based measures of inequality in cities especially when trained on data from cities that are visually distinct from target cities. We showed that these are more prone to errors for disadvantaged areas especially when transferring across cities, suggesting more attention needs to be paid to improving methods for capturing heterogeneity in poor environment across cities around the world.

Providing consumers with product-specific environmental impact information for food products (ecolabels) may promote more sustainable purchasing, needed to meet global environmental targets. This UK study (N = 1051 participants) investigated the effectiveness of different ecolabels using an experimental online supermarket platform, comparing three labels against control (no label). Significant reductions were found in the environmental impact score (EIS) for all labels compared to control (labels presented: values for four environmental indicators [-3.9 percentiles, 95%CIs: -5.3, -2.6]; a composite score [taking values from A to E; -3.9, 95%CIs: -5.2,-2.5]; or both together [-3.2, 95%CIs: -4.5, -1.9]). Providing ecolabels is a promising intervention to promote the selection of more sustainable products.

Abstract Background To assess the compound effects of BMI and sustained depressive symptoms on changes in knee structure, cartilage composition, and knee pain over 4 years using statistical interaction analyses. Methods One thousand eight hundred forty-four individuals from the Osteoarthritis Initiative Database were analyzed at baseline and 4-year follow-up. Individuals were categorized according to their BMI and presence of depressive symptoms (based on the Center for Epidemiological Studies Depression Scale (threshold≥16)) at baseline and 4-year follow-up. 3 T MRI was used to quantify knee cartilage T2 over 4 years, while radiographs were used to assess joint space narrowing (JSN). Mixed effects models examined the effect of BMI-depressive symptoms interactions on outcomes of cartilage T2, JSN, and knee pain over 4-years. Results The BMI-depressive symptoms interaction was significantly associated with knee pain (p

Background: Western State Hospital (WSH) is an 800-bed, state-owned psychiatric hospital in Washington State which services individuals in 20 counties. WSH provides services and inpatient treatment to patients referred via behavioral health providers and/or the civil court system. Because many patients are admitted with serious, long-term illness, WSH also provides primary care and addresses infectious syndromes encountered in admitted patients. In January 2016, WSH officially began their antimicrobial stewardship program (ASP). In 2017 WSH joined the UW Center for Stewardship in Medicine (UW-CSiM) to grow and optimize their ASP. Methods: The lead pharmacist at WSH participated in weekly hour-long education and tele-mentoring sessions through the UW-CSiM program. Educational materials were adapted from UW-CSiM didactics and delivered to providers during regular meetings and grand rounds. Daily pharmacist led prospective audit with feedback was conducted. Antibiotic use data were collected and measured by days of therapy (DOT) per 1000-patient days from pharmacy dispensing records from 2015 to 2022. Results: From 1/1/15 to 12/31/22, there was a consistent trend of decreasing antibiotic consumption annually. In particular, antibiotic use decreased by over 65% ranging from 35-43 DOT per 1000 patient-days in 2015 to 9-11 DOT per 1000 patient-days in 2022 (Figure 1). This translates to approximately 1000 antibiotic days of therapy in 2015 and 200 days of antibiotic therapy in 2022. As of 2022, the two most common antibiotics used were cephalexin and sulfamethoxazole/trimethoprim Conclusion: Although treating infections is not a principal focus of a psychiatric hospital, patients receiving care in inpatient psychiatric facilities do experience common infections and receive antibiotics during their stay. At WSH, initiation of an antimicrobial stewardship program was associated with sustained decrease in total antibiotic DOT over 7 years. These data highlight the impact of tele-education and tele-mentoring in infectious diseases and antimicrobial stewardship as a path to build a successful antimicrobial stewardship even without formal infectious diseases training. Our single center experience at a large psychiatric hospital demonstrates the use of antimicrobials in these facilities and the opportunity for a large impact of an antimicrobial stewardship program in inpatient psychiatric facilities.

The data is collected through laboratory experiments on a dynamic common pool resource game, where, in an infinitely repeated number of rounds (i.e., game ended randomly), individuals made decisions about whether to exert a high or a low effort level to extract resources. Experiments were conducted using the student sample (consent provided and ethics approved) at the University of Hawaiʻi at Mānoa. A total of 8 sessions, 2 for each of the 4 treatments, were run with exactly 20 participants within a session. Individuals made decisions in groups of 10. Communication between any participant was not allowed. A session is randomly assigned (1) to vary whether the inflow of resources at the beginning of each round is high or low, and (2) to allow participants to either financially punish or socially punish defectors. A financial punishment resulted to a loss in profit for the punished while a social punishment displayed the words “You have extracted too much! You're being greedy!” on the computer screen of the punished. Individuals were assigned subject ID numbers and interacted using their subject IDs. The data is useful in understanding how resource inflow and type of punishment affects individual resource extraction behavior. The data could also be combined with other publicly available common pool resource datasets for a meta-analysis on individual behavior in the commons.

Due to their thermal inertia, buildings equipped with electric heating and cooling systems can help to stabilize the electricity grid by shifting their load in time, and can thus facilitate energy flexible urban energy systems with the right control system in place. Because of minimum capacity requirements, they can often only participate in demand response schemes, such as secondary frequency reserves through aggregation. Such an aggregation could also take the form of entire district heating and cooling systems with connected buildings that are supplied by large-scale heat pumps and chillers. However, there is a lack of studies investigating the control of such configurations, both in simulation and in application. We present a two-level control scheme based on robust Model Predictive Control with affine policies to offer frequency reserves with a district system, where we exploit the thermal inertia of buffer storage tanks and a subset of the connected buildings. We leverage data-driven model generation methods to overcome the bottleneck of physics-based building modeling. In a numerical case study based on one-year historical data of a real system, we compare the approach to a situation where only the buffer storage is used for flexibility and demonstrate that the reserves offered increase substantially if the inertia of a subset of the connected buildings is also exploited. Furthermore, we validate the control approach in a first-of-its-kind experiment on the actual system, where we show that reserves can be offered by the district system without compromising the comfort in the connected buildings.