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UNLABELLED: Continuous tobacco use in patients with cancer is linked to substantial healthcare costs due to increased risks and complications, whereas quitting smoking leads to improved treatment outcomes and cost reductions. Addressing the need for empirical evidence on the economic impact of smoking cessation, this study examined the association between smoking cessation and healthcare cost utilization among a sample of 930 patients with cancer treated at The University of Texas MD Anderson Cancer Centers Tobacco Research and Treatment Program (TRTP). Applying conditional quantile regression and propensity scores to address confounding, our findings revealed that abstinence achieved through the TRTP significantly reduced the median cost during a 3-month period post-quitting by $1,095 [β = -$1,095, P = 0.007, 95% confidence interval (CI), = (-$1,886 to -$304)]. Sensitivity analysis corroborated these conclusions, showing a pronounced cost reduction when outlier data were excluded. The long-term accrued cost savings from smoking cessation could potentially offset the cost of participation in the TRTP program, underscoring its cost effectiveness. An important implication of this study is that by reducing smoking rates, healthcare systems can more efficiently allocate resources, enhance patient health outcomes, and lessen the overall cancer burden. PREVENTION RELEVANCE: This study emphasizes the dual impact of smoking cessation programs in patients with cancer: quitting smoking and reducing healthcare costs. It highlights the importance of integrating cessation programs into cancer prevention strategies, ensuring both individual health benefits and broader, system-wide economic efficiencies. See related Spotlight, p. 197.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR

Recycling olive waste, a major by-product of the olive oil industry, presents significant environmental and economic benefits. This study explores the potential of olive waste (OW) by-products, specifically their individual components such as olive stones (OS), olive oily pomace (OS) and olive oil-free pomace (OF), as sustainable alternatives to wood in eco-friendly composite materials, alongside other residues such as miscanthus, spent mushroom substrate and recycled textile waste. Composite panels were produced with densities ranging from 685 to 907 kg/m3 through thermocompression. The manuscript details the production methodology and assesses the panel’s thermal performance, water absorption, and mechanical strength. The aim is to assess the viability of these alternative materials in producing composites that could serve as environmentally friendly substitutes for traditional wood-based products. Oil-free pomace is a promising and effective alternative to wood, suitable for dry environments. Composite panels composed of miscanthus or spent mushroom substrate and oil-free pomace met the EN 312 standards for general-purpose products in dry conditions, highlighting their potential for use in sustainable applications.

Approximately 20% of primary energy consumed in the U.S. is attributed to HVAC use. Ideally, HVAC operation would be driven by actual building occupancy, but lack of reliable occupancy information often results in the use of conservative static schedules. This disparity is even more pronounced in a college campus, where the function of each space differs by building (classrooms, offices, libraries) and the class schedules change frequently -- every semester, day of week, and hour. While several research papers propose the use of counts of the Wi-Fi connections (e.g., phones, computers) as a proxy for occupancy, few real-world implementationsexist. This paper describes the development and deployment of an open-sourceWi-Fi-to-Occupancy software library in 65 buildings of a college campus, and the plannedintegration with the building energy management and control system at the building scale. Overa year of Wi-Fi data was gathered into distinct academic periods, including fall and springsemester, academic breaks, and summer sessions. Patterns such as students moving between classrooms, closing laptops before exams, etc., can be visualized from the data. Approximating occupancy from Wi-Fi data presents challenges which we address in this project -- for example, identifying static devices, or estimating the ratio of devices per person. Utilizing real-time occupancy data to inform optimal HVAC schedules and ventilation rates creates the potential to identify and reduce energy waste. Other potential applications include forecasting occupancy, and using Wi-Fi data to predict peak demands. Finally, the paper discusses how to easily scale these tools to other buildings.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Abstract Background Epicardial adipose tissue (EAT) surrounds the heart and is hypothesised to play a role in the development of heart failure (HF). In this study, we first investigated the differences in gene expression between epicardial adipose tissue (EAT) and subcutaneous adipose tissue (SAT) in patients undergoing elective coronary artery bypass graft (CABG) surgery (n = 21; 95% male). Secondly, we examined the association between EAT and SAT in patients at risk for HF stage A (n = 12) and in pre-HF patients, who show signs but not symptoms of HF, stage B (n = 9). Results The study confirmed a distinct separation between EAT and SAT. In EAT 17 clusters of genes were present, of which several novel gene modules are associated with characteristics of HF. Notably, seven gene modules showed significant correlation to measures of HF, such as end diastolic left ventricular posterior wall thickness, e’mean, deceleration time and BMI. One module was particularly distinct in EAT when compared to SAT, featuring key genes such as FLT4, SEMA3A, and PTX3, which are implicated in angiogenesis, inflammation regulation, and tissue repair, suggesting a unique role in EAT linked to left ventricular dysfunction. Genetic expression was compared in EAT across all pre-HF and normal phenotypes, revealing small genetic changes in the form of 18 differentially expressed genes in ACC/AHA Stage A vs. Stage B. Conclusions The roles of subcutaneous and epicardial fat are clearly different. We highlight the gene expression difference in search of potential modifiers of HF progress. The true implications of our findings should be corroborated in other studies since HF ACC/AHA stage B patients are common and carry a considerable risk for progression to symptomatic HF.

Abstract Aims The prevalence of iron deficiency (ID) in newly diagnosed heart failure (HF) and the progression of ID in patients after initiation of HF therapy are unknown. We aimed to describe the natural trajectory of ID in patients with new onset HF during the first year after HF diagnosis, assessing associations between ID, clinical factors, and quality of life (QoL). Methods and results A prospective cohort of patients with new onset HF in hospitals or outpatient clinics at five major hospitals in Stockholm, Sweden, during 2015–2018 were analysed with clinical assessment, electrocardiogram, blood samples including iron levels, Minnesota living with heart failure questionnaire (MLHFQ), and echocardiogram at baseline and after 12 months. Of 547 patients with new‐onset HF, 482 (88%) had complete iron data at baseline. Median age was 70 years (interquartile range 61–77) and 311 (65%) were men; 55% of patients had ejection fraction (EF) ≤ 40%, 19% had EF 41–49%, and 26% had HF with preserved EF (HFpEF) [Correction added on 26 June 2024, after first online publication: The ‘Mean age was 70 years’ has been corrected to ‘Median age was 70 years’ in this version.]. At baseline, 163 patients (34%) had ID defined as ferritin

Abstract Visceral leishmaniasis (VL) is an urgent public health concern in Brazil. We evaluated the spatiotemporal distribution of VL to better understand the effects of economic activities related to agriculture, livestock, and deforestation on its incidence in the Brazilian Legal Amazon (BLA). The data on newly confirmed cases of VL in Brazilian municipalities from 2007 to 2020 were extracted from the Brazilian Notifiable Diseases Information System (SINAN) and analyzed. The data on agricultural production (planted area in hectares) and livestock (total number of cattle) were obtained from the Brazilian Institute of Geography and Statistics (IBGE), whereas deforestation data (in hectares) were obtained from the Amazon Deforestation Estimation Project (PRODES). SatScan and the local indicators of spatial association (LISA) were used to identify the spatial and temporal patterns of VL and its relationships with economic and environmental variables. The cumulative incidence rate was found to be 4.5 cases per 100,000 inhabitants. Based on the LISA results, areas with a high incidence of VL and deforestation were identified in the states of Roraima, Pará, and Maranhão. Strengthening deforestation monitoring programs and environmental enforcement actions can help implement public policies to control illegal deforestation and mitigate the socio-environmental vulnerability in the BLA. Therefore, areas identified in this study should be prioritized for controlling VL.

The transfer of carbon from land to the near-coastal ocean is increasingly being recognized in global carbon budgets. However, a more direct transfer of terrestrial organic carbon to the deep sea is comparatively overlooked. Among systems that connect coastal to deep-sea environments, the submarine Congo Canyon is of particular interest since the canyon head starts 30 km into the Congo River estuary, which delivers ∼7 % of the dissolved and particulate organic carbon from the world's rivers. However, sediment and particulate organic carbon transport mechanisms that operate in the Congo Canyon and submarine canyons more globally are poorly constrained compared to rivers because monitoring of deep-sea canyons remains challenging. Using a novel array of acoustic instruments, sediment traps, and cores, this study seeks to understand the hydrodynamic processes that control delivery of particulate organic carbon via the submarine Congo Canyon to the deep sea. We show that particulate organic carbon transport in the canyon axis is modulated by two processes. First, we observe periods where the canyon dynamics are dominated by tides, which induce a background oscillatory flow (speeds of up to 0.15 m s−1) through the water column, keeping muds in suspension, with a net upslope transport direction. Second, fast-moving (up to 8 m s−1) turbidity currents occur for 35 % of the time during monitoring periods and transport particulate organic carbon with mud and sand at an estimated transit flux that is more than 3 to 6 times the flux induced by tides. Organic carbon transported and deposited in the submarine canyon has a similar isotopic composition to organic carbon in the Congo River and in the deep-sea fan at 5 km of water depth. Episodic turbidity currents thus promote efficient transfer of river-derived particulate organic carbon in the Congo submarine fan, leading to some of the highest terrestrial carbon preservation rates observed in marine sediments globally.

Abstract Major Depressive Disorder, or depression, has been extensively linked to dysregulated HPA axis function, chronic inflammation and cardiovascular diseases. While the former two have been studied in depth, the mechanistic connection between depression and cardiovascular disease is unclear. As major mediators of vascular homeostasis, vascular pathology and immune activity, endothelial cells represent an important player connecting the diseases. Exaggerated inflammation and glucocorticoid function are important topics to explore in the endothelial response to MDD. Glucocorticoid resistance in several cell types strongly promotes inflammatory signaling and results in worsened severity in many diseases. However, endothelial health and inflammation in chronic stress and depression are rarely considered from the perspective of glucocorticoid signaling and resistance. In this review, we aim to discuss (1) endothelial dysfunction in depression, (2) inflammation in depression, (3) general glucocorticoid resistance in depression and (4) endothelial glucocorticoid resistance in depression co-morbid inflammatory diseases. We will first describe vascular pathology, inflammation and glucocorticoid resistance separately in depression and then describe their potential interactions with one another in depression-relevant diseases. Lastly, we will hypothesize potential mechanisms by which glucocorticoid resistance in endothelial cells may contribute to vascular disease states in depressed people. Overall, endothelial-glucocorticoid signaling may play an important role in connecting depression and vascular pathology and warrants further study.

PURPOSE: To characterize the recovery of diagnostic cardiovascular procedure volumes in U.S. and non-U.S. facilities in the year following the initial COVID-19 outbreak. MATERIALS AND METHODS: The International Atomic Energy Agency (IAEA) coordinated a worldwide study called the IAEA Noninvasive Cardiology Protocols Study of COVID-19 2 (INCAPS COVID 2), collecting data from 669 facilities in 107 countries, including 93 facilities in 34 U.S. states, to determine the impact of the pandemic on diagnostic cardiovascular procedure volumes. Participants reported volumes for each diagnostic imaging modality used at their facility for March 2019 (baseline), April 2020, and April 2021. This secondary analysis of INCAPS COVID 2 evaluated differences in changes in procedure volume between U.S. and non-U.S. facilities and among U.S. regions. Factors associated with return to prepandemic volumes in the United States were also analyzed in a multivariable regression analysis. RESULTS: Reduction in procedure volumes in April 2020 compared with baseline was similar for U.S. and non-U.S. facilities (-66% vs -71%, P = .27). U.S. facilities reported greater return to baseline in April 2021 than did all non-U.S. facilities (4% vs -6%, P = .008), but there was no evidence of a difference when comparing U.S. facilities with non-U.S. high-income country (NUHIC) facilities (4% vs 0%, P = .18). U.S. regional differences in return to baseline were observed between the Midwest (11%), Northeast (9%), South (1%), and West (-7%, P = .03), but no studied factors were significant predictors of 2021 change from prepandemic baseline. CONCLUSION: The reductions in cardiac testing during the early pandemic have recovered within a year to prepandemic baselines in the United States and NUHICs, while procedure volumes remain depressed in lower-income countries.Keywords: SPECT, Cardiac, Epidemiology, Angiography, CT Angiography, CT, Echocardiography, SPECT/CT, MR Imaging, Radionuclide Studies, COVID-19, Cardiovascular Imaging, Diagnostic Cardiovascular Procedure, Cardiovascular Disease, Cardiac Testing Supplemental material is available for this article. © RSNA, 2023.